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\ No newline at end of file diff --git a/build/GUI应用/Analysis-00.toc b/build/GUI应用/Analysis-00.toc index 032e2fa..541fe46 100644 --- a/build/GUI应用/Analysis-00.toc +++ b/build/GUI应用/Analysis-00.toc @@ -1,5 +1,5 @@ -(['C:\\Users\\27942\\Desktop\\haha\\gui_app.py'], - ['C:\\Users\\27942\\Desktop\\haha'], +(['C:\\Users\\27942\\Desktop\\codes\\haha\\gui_app.py'], + ['C:\\Users\\27942\\Desktop\\codes\\haha'], ['PyQt5', 'PyQt5.QtCore', 'PyQt5.QtGui', @@ -53,7 +53,9 @@ ('pyi_rth_pythoncom', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\_pyinstaller_hooks_contrib\\rthooks\\pyi_rth_pythoncom.py', 'PYSOURCE'), - ('gui_app', 'C:\\Users\\27942\\Desktop\\haha\\gui_app.py', 'PYSOURCE')], + ('gui_app', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\gui_app.py', + 'PYSOURCE')], [('_pyi_rth_utils.qt', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyInstaller\\fake-modules\\_pyi_rth_utils\\qt.py', 'PYMODULE'), @@ -452,6 +454,9 @@ ('ctypes', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\ctypes\\__init__.py', 'PYMODULE'), + ('ctypes.wintypes', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\ctypes\\wintypes.py', + 'PYMODULE'), ('ctypes.util', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\ctypes\\util.py', 'PYMODULE'), @@ -743,6 +748,45 @@ ('setuptools._distutils.compilers.C.errors', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_distutils\\compilers\\C\\errors.py', 'PYMODULE'), + ('setuptools.compat.py310', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\compat\\py310.py', + 'PYMODULE'), + ('setuptools._vendor.tomli', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\tomli\\__init__.py', + 'PYMODULE'), + ('setuptools._vendor.tomli._parser', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\tomli\\_parser.py', + 'PYMODULE'), + ('setuptools._vendor.tomli._types', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\tomli\\_types.py', + 'PYMODULE'), + ('setuptools._vendor.tomli._re', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\tomli\\_re.py', + 'PYMODULE'), + ('tomllib', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\tomllib\\__init__.py', + 'PYMODULE'), + ('tomllib._parser', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\tomllib\\_parser.py', + 'PYMODULE'), + ('tomllib._types', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\tomllib\\_types.py', + 'PYMODULE'), + ('tomllib._re', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\tomllib\\_re.py', + 'PYMODULE'), + ('setuptools.compat', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\compat\\__init__.py', + 'PYMODULE'), + ('setuptools.compat.py311', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\compat\\py311.py', + 'PYMODULE'), + ('setuptools.compat.py39', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\compat\\py39.py', + 'PYMODULE'), + ('setuptools._path', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_path.py', + 'PYMODULE'), ('setuptools._vendor.more_itertools', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\more_itertools\\__init__.py', 'PYMODULE'), @@ -848,9 +892,6 @@ ('_pyrepl.windows_eventqueue', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\_pyrepl\\windows_eventqueue.py', 'PYMODULE'), - ('ctypes.wintypes', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\ctypes\\wintypes.py', - 'PYMODULE'), ('_pyrepl.readline', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\_pyrepl\\readline.py', 'PYMODULE'), @@ -940,12 +981,45 @@ ('setuptools._vendor.importlib_metadata', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\importlib_metadata\\__init__.py', 'PYMODULE'), + ('setuptools._vendor.zipp.compat.overlay', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\compat\\overlay.py', + 'PYMODULE'), + ('setuptools._vendor.zipp.compat', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\compat\\__init__.py', + 'PYMODULE'), + ('setuptools._vendor.zipp', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\__init__.py', + 'PYMODULE'), + ('setuptools._vendor.zipp.glob', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\glob.py', + 'PYMODULE'), + ('setuptools._vendor.zipp.compat.py313', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\compat\\py313.py', + 'PYMODULE'), + ('setuptools._vendor.zipp.compat.py310', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\compat\\py310.py', + 'PYMODULE'), + ('setuptools._vendor.zipp._functools', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\_functools.py', + 'PYMODULE'), ('setuptools._vendor.importlib_metadata._adapters', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\importlib_metadata\\_adapters.py', 'PYMODULE'), ('setuptools._vendor.importlib_metadata._text', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\importlib_metadata\\_text.py', 'PYMODULE'), + ('setuptools._vendor.importlib_metadata.compat.py311', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\importlib_metadata\\compat\\py311.py', + 'PYMODULE'), + ('setuptools._vendor.importlib_metadata.compat.py39', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\importlib_metadata\\compat\\py39.py', + 'PYMODULE'), + ('setuptools._vendor.importlib_metadata.compat', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\importlib_metadata\\compat\\__init__.py', + 'PYMODULE'), + ('setuptools._vendor.importlib_metadata._typing', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\importlib_metadata\\_typing.py', + 'PYMODULE'), ('setuptools._vendor.importlib_metadata._itertools', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\importlib_metadata\\_itertools.py', 'PYMODULE'), @@ -958,36 +1032,12 @@ ('setuptools._vendor.importlib_metadata._collections', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\importlib_metadata\\_collections.py', 'PYMODULE'), - ('setuptools._vendor.importlib_metadata.compat.py311', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\importlib_metadata\\compat\\py311.py', - 'PYMODULE'), - ('setuptools._vendor.importlib_metadata.compat.py39', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\importlib_metadata\\compat\\py39.py', - 'PYMODULE'), - ('setuptools._vendor.importlib_metadata.compat', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\importlib_metadata\\compat\\__init__.py', - 'PYMODULE'), ('setuptools._vendor.importlib_metadata._meta', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\importlib_metadata\\_meta.py', 'PYMODULE'), - ('setuptools._vendor.zipp', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\__init__.py', - 'PYMODULE'), - ('setuptools._vendor.zipp.glob', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\glob.py', - 'PYMODULE'), - ('setuptools._vendor.zipp.compat.py310', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\compat\\py310.py', - 'PYMODULE'), - ('setuptools._vendor.zipp.compat', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\compat\\__init__.py', - 'PYMODULE'), ('setuptools.extension', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\extension.py', 'PYMODULE'), - ('setuptools._path', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_path.py', - 'PYMODULE'), ('setuptools.dist', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\dist.py', 'PYMODULE'), @@ -1013,7 +1063,7 @@ 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\jaraco\\text\\__init__.py', 'PYMODULE'), ('setuptools._vendor.jaraco.context', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\jaraco\\context.py', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\jaraco\\context\\__init__.py', 'PYMODULE'), ('setuptools._vendor.backports.tarfile', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\backports\\tarfile\\__init__.py', @@ -1051,15 +1101,6 @@ ('setuptools.unicode_utils', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\unicode_utils.py', 'PYMODULE'), - ('setuptools.compat.py39', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\compat\\py39.py', - 'PYMODULE'), - ('setuptools.compat', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\compat\\__init__.py', - 'PYMODULE'), - ('setuptools.compat.py311', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\compat\\py311.py', - 'PYMODULE'), ('packaging.requirements', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\packaging\\requirements.py', 'PYMODULE'), @@ -1072,69 +1113,6 @@ ('wheel.wheelfile', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\wheelfile.py', 'PYMODULE'), - ('wheel.util', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\util.py', - 'PYMODULE'), - ('wheel.cli', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\cli\\__init__.py', - 'PYMODULE'), - ('wheel.cli.tags', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\cli\\tags.py', - 'PYMODULE'), - ('wheel.cli.convert', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\cli\\convert.py', - 'PYMODULE'), - ('wheel.vendored.packaging.tags', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\tags.py', - 'PYMODULE'), - ('wheel.vendored.packaging._musllinux', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\_musllinux.py', - 'PYMODULE'), - ('wheel.vendored.packaging._elffile', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\_elffile.py', - 'PYMODULE'), - ('wheel.vendored.packaging._manylinux', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\_manylinux.py', - 'PYMODULE'), - ('wheel.vendored.packaging', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\__init__.py', - 'PYMODULE'), - ('wheel.vendored', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\__init__.py', - 'PYMODULE'), - ('wheel.metadata', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\metadata.py', - 'PYMODULE'), - ('wheel.vendored.packaging.requirements', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\requirements.py', - 'PYMODULE'), - ('wheel.vendored.packaging.utils', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\utils.py', - 'PYMODULE'), - ('wheel.vendored.packaging.version', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\version.py', - 'PYMODULE'), - ('wheel.vendored.packaging._structures', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\_structures.py', - 'PYMODULE'), - ('wheel.vendored.packaging.specifiers', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\specifiers.py', - 'PYMODULE'), - ('wheel.vendored.packaging.markers', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\markers.py', - 'PYMODULE'), - ('wheel.vendored.packaging._tokenizer', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\_tokenizer.py', - 'PYMODULE'), - ('wheel.vendored.packaging._parser', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\_parser.py', - 'PYMODULE'), - ('wheel.cli.pack', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\cli\\pack.py', - 'PYMODULE'), - ('wheel.cli.unpack', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\cli\\unpack.py', - 'PYMODULE'), ('setuptools.installer', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\installer.py', 'PYMODULE'), @@ -1225,33 +1203,6 @@ ('setuptools._vendor.packaging', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\packaging\\__init__.py', 'PYMODULE'), - ('setuptools.compat.py310', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\compat\\py310.py', - 'PYMODULE'), - ('setuptools._vendor.tomli', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\tomli\\__init__.py', - 'PYMODULE'), - ('setuptools._vendor.tomli._parser', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\tomli\\_parser.py', - 'PYMODULE'), - ('setuptools._vendor.tomli._types', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\tomli\\_types.py', - 'PYMODULE'), - ('setuptools._vendor.tomli._re', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\tomli\\_re.py', - 'PYMODULE'), - ('tomllib', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\tomllib\\__init__.py', - 'PYMODULE'), - ('tomllib._parser', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\tomllib\\_parser.py', - 'PYMODULE'), - ('tomllib._types', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\tomllib\\_types.py', - 'PYMODULE'), - ('tomllib._re', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\tomllib\\_re.py', - 'PYMODULE'), ('setuptools.config._apply_pyprojecttoml', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\config\\_apply_pyprojecttoml.py', 'PYMODULE'), @@ -2999,19 +2950,23 @@ ('PyQt5', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\__init__.py', 'PYMODULE'), - ('tracemalloc', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\tracemalloc.py', - 'PYMODULE'), ('stringprep', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\stringprep.py', 'PYMODULE'), + ('tracemalloc', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\tracemalloc.py', + 'PYMODULE'), ('_py_abc', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\_py_abc.py', 'PYMODULE'), - ('gui_models', 'C:\\Users\\27942\\Desktop\\haha\\gui_models.py', 'PYMODULE'), - ('gui_worker', 'C:\\Users\\27942\\Desktop\\haha\\gui_worker.py', 'PYMODULE'), + ('gui_models', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\gui_models.py', + 'PYMODULE'), + ('gui_worker', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\gui_worker.py', + 'PYMODULE'), ('gui_constants', - 'C:\\Users\\27942\\Desktop\\haha\\gui_constants.py', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\gui_constants.py', 'PYMODULE'), ('loguru', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\loguru\\__init__.py', @@ -3094,7 +3049,7 @@ ('loguru._defaults', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\loguru\\_defaults.py', 'PYMODULE'), - ('main', 'C:\\Users\\27942\\Desktop\\haha\\main.py', 'PYMODULE'), + ('main', 'C:\\Users\\27942\\Desktop\\codes\\haha\\main.py', 'PYMODULE'), ('qfluentwidgets', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\qfluentwidgets\\__init__.py', 'PYMODULE'), @@ -3629,92 +3584,23 @@ ('pandas.core', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\__init__.py', 'PYMODULE'), - ('pandas.core.arraylike', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arraylike.py', + ('pandas.core.indexing', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexing.py', 'PYMODULE'), - ('pandas.core.ops.common', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\ops\\common.py', + ('pandas.core.indexers', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexers\\__init__.py', 'PYMODULE'), - ('pandas.core.ops', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\ops\\__init__.py', + ('pandas.core.indexers.utils', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexers\\utils.py', 'PYMODULE'), - ('pandas.core.ops.mask_ops', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\ops\\mask_ops.py', + ('pandas.core.construction', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\construction.py', 'PYMODULE'), - ('pandas.core.ops.invalid', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\ops\\invalid.py', + ('pandas.core.arrays.string_', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\string_.py', 'PYMODULE'), - ('pandas.core.ops.docstrings', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\ops\\docstrings.py', - 'PYMODULE'), - ('pandas.core.ops.array_ops', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\ops\\array_ops.py', - 'PYMODULE'), - ('pandas.core.ops.dispatch', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\ops\\dispatch.py', - 'PYMODULE'), - ('pandas.core.computation.expressions', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\computation\\expressions.py', - 'PYMODULE'), - ('pandas.core.computation.check', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\computation\\check.py', - 'PYMODULE'), - ('pandas.compat._optional', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\compat\\_optional.py', - 'PYMODULE'), - ('pandas.util.version', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\util\\version\\__init__.py', - 'PYMODULE'), - ('pandas.util', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\util\\__init__.py', - 'PYMODULE'), - ('pandas.core.util.hashing', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\util\\hashing.py', - 'PYMODULE'), - ('pandas.core.util', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\util\\__init__.py', - 'PYMODULE'), - ('pandas.core.computation', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\computation\\__init__.py', - 'PYMODULE'), - ('pandas.core.computation.expr', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\computation\\expr.py', - 'PYMODULE'), - ('pandas.core.computation.scope', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\computation\\scope.py', - 'PYMODULE'), - ('pandas.core.computation.parsing', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\computation\\parsing.py', - 'PYMODULE'), - ('pandas.core.computation.ops', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\computation\\ops.py', - 'PYMODULE'), - 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'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\timedeltas.py', - 'PYMODULE'), - ('pandas.core.arrays._ranges', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\_ranges.py', - 'PYMODULE'), - ('pandas.core.arrays.datetimelike', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\datetimelike.py', + ('pandas.core.arrays.masked', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\masked.py', 'PYMODULE'), ('pandas.core.groupby.ops', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\groupby\\ops.py', @@ -3731,11 +3617,17 @@ ('pandas.core.arrays.categorical', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\categorical.py', 'PYMODULE'), - ('pandas.core.dtypes.concat', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\dtypes\\concat.py', + ('pandas.core.reshape.concat', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\reshape\\concat.py', 'PYMODULE'), - ('pandas.core.dtypes.astype', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\dtypes\\astype.py', + ('pandas.core.reshape', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\reshape\\__init__.py', + 'PYMODULE'), + ('pandas.core.indexes.range', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexes\\range.py', + 'PYMODULE'), + ('pandas.core.indexes', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexes\\__init__.py', 'PYMODULE'), ('pandas.core.strings.object_array', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\strings\\object_array.py', @@ -3743,12 +3635,21 @@ ('pandas.core.strings', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\strings\\__init__.py', 'PYMODULE'), - ('pandas.core.strings.base', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\strings\\base.py', + ('pandas.core.ops.common', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\ops\\common.py', + 'PYMODULE'), + ('pandas.core.arrays._mixins', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\_mixins.py', 'PYMODULE'), ('pandas.core.accessor', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\accessor.py', 'PYMODULE'), + ('pandas.util._validators', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\util\\_validators.py', + 'PYMODULE'), + ('pandas.util', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\util\\__init__.py', + 'PYMODULE'), ('pandas.core.groupby', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\groupby\\__init__.py', 'PYMODULE'), @@ -3779,80 +3680,32 @@ ('pandas.core.window.expanding', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\window\\expanding.py', 'PYMODULE'), - ('pandas.core.window.doc', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\window\\doc.py', - 'PYMODULE'), - ('pandas.core.shared_docs', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\shared_docs.py', - 'PYMODULE'), - ('pandas.core.indexers.objects', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexers\\objects.py', - 'PYMODULE'), ('pandas.core.window.ewm', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\window\\ewm.py', 'PYMODULE'), ('pandas.core.window.online', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\window\\online.py', 'PYMODULE'), + ('pandas.compat._optional', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\compat\\_optional.py', + 'PYMODULE'), + ('pandas.util.version', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\util\\version\\__init__.py', + 'PYMODULE'), ('pandas.core.window.numba_', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\window\\numba_.py', 'PYMODULE'), ('pandas.core.window.common', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\window\\common.py', 'PYMODULE'), - ('pandas.core.util.numba_', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\util\\numba_.py', + ('pandas.core.arrays.datetimelike', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\datetimelike.py', 'PYMODULE'), - ('pandas.core.internals.blocks', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\internals\\blocks.py', + ('pandas.core.arrays.period', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\period.py', 'PYMODULE'), - ('pandas.core.array_algos.transforms', - 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'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\arrow\\accessors.py', 'PYMODULE'), + ('pickletools', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\pickletools.py', + 'PYMODULE'), + ('pandas.core.arrays.interval', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\interval.py', + 'PYMODULE'), + ('pandas.core.arrays.timedeltas', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\timedeltas.py', + 'PYMODULE'), + ('pandas.core.arrays._ranges', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\_ranges.py', + 'PYMODULE'), + ('pandas.core.arrays.datetimes', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\datetimes.py', + 'PYMODULE'), + ('pandas.tseries.frequencies', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\tseries\\frequencies.py', + 'PYMODULE'), + ('pandas.core.ops.invalid', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\ops\\invalid.py', + 'PYMODULE'), + ('pandas.core.arrays.arrow.array', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\arrow\\array.py', + 'PYMODULE'), + ('pandas.core.tools.numeric', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\tools\\numeric.py', + 'PYMODULE'), + ('pandas.core.tools', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\tools\\__init__.py', + 'PYMODULE'), + ('pandas.core.tools.times', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\tools\\times.py', + 'PYMODULE'), + ('pandas.core.tools.timedeltas', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\tools\\timedeltas.py', + 'PYMODULE'), + ('pandas.core.tools.datetimes', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\tools\\datetimes.py', + 'PYMODULE'), + ('pandas.io._util', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\_util.py', + 'PYMODULE'), ('pandas.core.arrays._arrow_string_mixins', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\_arrow_string_mixins.py', 'PYMODULE'), - ('pandas.core.apply', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\apply.py', + ('pandas.core.array_algos.datetimelike_accumulations', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\array_algos\\datetimelike_accumulations.py', 'PYMODULE'), - ('pandas.core._numba.extensions', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\_numba\\extensions.py', + ('pandas.core.indexers.objects', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexers\\objects.py', + 'PYMODULE'), + ('pandas.core.util.numba_', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\util\\numba_.py', + 'PYMODULE'), + 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'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\computation\\scope.py', + 'PYMODULE'), + ('pandas.core.computation.parsing', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\computation\\parsing.py', + 'PYMODULE'), + ('pandas.core.computation.ops', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\computation\\ops.py', + 'PYMODULE'), + ('pandas.core.computation.eval', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\computation\\eval.py', + 'PYMODULE'), + ('pandas.core.computation.engines', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\computation\\engines.py', + 'PYMODULE'), + ('pandas.core.computation.align', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\computation\\align.py', + 'PYMODULE'), + ('pandas.core.computation.common', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\computation\\common.py', + 'PYMODULE'), + ('pandas.core.array_algos.replace', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\array_algos\\replace.py', + 'PYMODULE'), + ('pandas.core.array_algos.putmask', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\array_algos\\putmask.py', + 'PYMODULE'), + ('pandas.core.dtypes.inference', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\dtypes\\inference.py', + 'PYMODULE'), + ('pandas.core.groupby.indexing', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\groupby\\indexing.py', 'PYMODULE'), ('pandas.core._numba.executor', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\_numba\\executor.py', @@ -3881,77 +3830,104 @@ ('pandas.core.groupby.base', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\groupby\\base.py', 'PYMODULE'), - ('pandas.core.arrays.period', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\period.py', + ('pandas.core.util.hashing', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\util\\hashing.py', 'PYMODULE'), - ('pandas.core.arrays.arrow.extension_types', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\arrow\\extension_types.py', + ('pandas.core.arrays._utils', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\_utils.py', 'PYMODULE'), - ('pickletools', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\pickletools.py', + ('pandas.core.array_algos.transforms', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\array_algos\\transforms.py', 'PYMODULE'), - ('pandas.core.arrays.interval', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\interval.py', + ('pandas.core.array_algos.quantile', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\array_algos\\quantile.py', 'PYMODULE'), - ('pandas.tseries.frequencies', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\tseries\\frequencies.py', + ('pandas.core.array_algos.masked_accumulations', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\array_algos\\masked_accumulations.py', 'PYMODULE'), - ('pandas.core.indexers', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexers\\__init__.py', + ('pandas.core.dtypes.astype', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\dtypes\\astype.py', 'PYMODULE'), - ('pandas.core.indexers.utils', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexers\\utils.py', + ('pandas.core.arrays.string_arrow', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\string_arrow.py', 'PYMODULE'), - ('pandas.core.arrays._mixins', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\_mixins.py', + ('pandas.core.arrays.numeric', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\numeric.py', 'PYMODULE'), - ('pandas.core.array_algos.datetimelike_accumulations', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\array_algos\\datetimelike_accumulations.py', + ('pandas.core.arrays.arrow._arrow_utils', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\arrow\\_arrow_utils.py', + 'PYMODULE'), + ('pandas.core.arrays.boolean', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\boolean.py', + 'PYMODULE'), + ('pandas.core.arrays.numpy_', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\numpy_.py', + 'PYMODULE'), + ('pandas.core.arrays.integer', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\integer.py', + 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'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\ops\\array_ops.py', + 'PYMODULE'), + ('pandas.core.ops.dispatch', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\ops\\dispatch.py', + 'PYMODULE'), + ('pandas.core.ops.missing', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\ops\\missing.py', + 'PYMODULE'), + ('pandas.util._exceptions', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\util\\_exceptions.py', + 'PYMODULE'), ('pandas.compat.numpy.function', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\compat\\numpy\\function.py', 'PYMODULE'), ('pandas.compat.numpy', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\compat\\numpy\\__init__.py', 'PYMODULE'), - ('pandas.core.arrays.datetimes', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\datetimes.py', + ('pandas.core.dtypes.base', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\dtypes\\base.py', 'PYMODULE'), - ('pandas.core.arrays.arrow.array', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\arrow\\array.py', + ('pandas.core.dtypes.concat', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\dtypes\\concat.py', 'PYMODULE'), - ('pandas.core.tools.times', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\tools\\times.py', + ('pandas.core.dtypes.cast', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\dtypes\\cast.py', 'PYMODULE'), - ('pandas.core.tools.timedeltas', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\tools\\timedeltas.py', + ('pandas.errors.cow', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\errors\\cow.py', 'PYMODULE'), - ('pandas.core.tools.datetimes', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\tools\\datetimes.py', + ('pandas.compat._constants', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\compat\\_constants.py', 'PYMODULE'), - ('pandas.core.arrays.floating', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\floating.py', + ('pandas.core.sample', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\sample.py', 'PYMODULE'), - ('pandas.core.arrays.integer', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\integer.py', + ('pandas.core.arraylike', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arraylike.py', 'PYMODULE'), - ('pandas.io._util', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\_util.py', + ('pandas.core.nanops', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\nanops.py', 'PYMODULE'), - ('pandas.core.dtypes.inference', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\dtypes\\inference.py', - 'PYMODULE'), - ('pandas.util._exceptions', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\util\\_exceptions.py', - 'PYMODULE'), - ('pandas.core.ops.missing', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\ops\\missing.py', - 'PYMODULE'), - ('pandas.core.construction', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\construction.py', + ('pandas.core.roperator', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\roperator.py', 'PYMODULE'), ('pandas.core.algorithms', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\algorithms.py', @@ -3968,42 +3944,15 @@ ('pandas.core.internals.ops', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\internals\\ops.py', 'PYMODULE'), - ('pandas.core.internals.base', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\internals\\base.py', - 'PYMODULE'), - ('pandas.core.internals.array_manager', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\internals\\array_manager.py', - 'PYMODULE'), ('pandas.core.reshape.tile', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\reshape\\tile.py', 'PYMODULE'), - ('pandas.core.reshape', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\reshape\\__init__.py', - 'PYMODULE'), ('pandas.core.array_algos.take', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\array_algos\\take.py', 'PYMODULE'), - ('pandas.core.sample', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\sample.py', - 'PYMODULE'), - ('pandas.core.indexing', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexing.py', - 'PYMODULE'), - ('pandas.compat._constants', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\compat\\_constants.py', - 'PYMODULE'), - ('pandas.core.nanops', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\nanops.py', - 'PYMODULE'), ('pandas.core.missing', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\missing.py', 'PYMODULE'), - ('pandas.core.roperator', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\roperator.py', - 'PYMODULE'), - ('pandas.util._decorators', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\util\\_decorators.py', - 'PYMODULE'), ('pandas.io.formats.string', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\formats\\string.py', 'PYMODULE'), @@ -4013,12 +3962,6 @@ ('pandas.core.indexes.multi', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexes\\multi.py', 'PYMODULE'), - ('pandas.core.indexes', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexes\\__init__.py', - 'PYMODULE'), - ('pandas.core.reshape.util', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\reshape\\util.py', - 'PYMODULE'), ('pandas.core.indexes.frozen', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexes\\frozen.py', 'PYMODULE'), @@ -4028,6 +3971,21 @@ ('pandas.io.formats.printing', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\formats\\printing.py', 'PYMODULE'), + ('pandas.io.common', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\common.py', + 'PYMODULE'), + ('pandas.core.indexes.timedeltas', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexes\\timedeltas.py', + 'PYMODULE'), + ('pandas.core.indexes.extension', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexes\\extension.py', + 'PYMODULE'), + ('pandas.core.indexes.datetimelike', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexes\\datetimelike.py', + 'PYMODULE'), + ('pandas.core.indexes.datetimes', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexes\\datetimes.py', + 'PYMODULE'), ('pandas.io.formats', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\formats\\__init__.py', 'PYMODULE'), @@ -4049,6 +4007,9 @@ ('pandas.io.excel._openpyxl', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\excel\\_openpyxl.py', 'PYMODULE'), + ('pandas.core.shared_docs', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\shared_docs.py', + 'PYMODULE'), ('pandas.io.excel._odswriter', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\excel\\_odswriter.py', 'PYMODULE'), @@ -4100,42 +4061,6 @@ ('pandas.core.dtypes.api', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\dtypes\\api.py', 'PYMODULE'), - ('pandas.io.common', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\common.py', - 'PYMODULE'), - ('pandas.core.reshape.concat', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\reshape\\concat.py', - 'PYMODULE'), - ('pandas.core.indexes.timedeltas', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexes\\timedeltas.py', - 'PYMODULE'), - ('pandas.core.indexes.extension', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexes\\extension.py', - 'PYMODULE'), - ('pandas.core.indexes.datetimelike', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexes\\datetimelike.py', - 'PYMODULE'), - ('pandas.core.indexes.range', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexes\\range.py', - 'PYMODULE'), - ('pandas.core.indexes.datetimes', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexes\\datetimes.py', - 'PYMODULE'), - ('pytz', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pytz\\__init__.py', - 'PYMODULE'), - ('pytz.tzfile', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pytz\\tzfile.py', - 'PYMODULE'), - ('pytz.tzinfo', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pytz\\tzinfo.py', - 'PYMODULE'), - ('pytz.lazy', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pytz\\lazy.py', - 'PYMODULE'), - ('pytz.exceptions', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pytz\\exceptions.py', - 'PYMODULE'), ('pandas.core.indexes.api', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\indexes\\api.py', 'PYMODULE'), @@ -4154,12 +4079,6 @@ ('pandas.core.base', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\base.py', 'PYMODULE'), - ('pandas.core.arrays.string_', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\string_.py', - 'PYMODULE'), - ('pandas.core.arrays.numpy_', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\numpy_.py', - 'PYMODULE'), ('pandas.core.arrays', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\arrays\\__init__.py', 'PYMODULE'), @@ -4181,12 +4100,21 @@ ('pandas.core.dtypes.common', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\dtypes\\common.py', 'PYMODULE'), + ('pandas.util._decorators', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\util\\_decorators.py', + 'PYMODULE'), ('pandas._config.config', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\_config\\config.py', 'PYMODULE'), ('pandas.core.window.rolling', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\window\\rolling.py', 'PYMODULE'), + ('pandas.core.apply', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\apply.py', + 'PYMODULE'), + ('pandas.core._numba.extensions', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\_numba\\extensions.py', + 'PYMODULE'), ('pandas.core.series', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\series.py', 'PYMODULE'), @@ -4274,6 +4202,9 @@ ('pandas.core.reshape.pivot', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\reshape\\pivot.py', 'PYMODULE'), + ('pandas.io.iceberg', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\iceberg.py', + 'PYMODULE'), ('pandas.io.formats.xml', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\formats\\xml.py', 'PYMODULE'), @@ -4316,9 +4247,6 @@ ('pandas.io.stata', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\stata.py', 'PYMODULE'), - ('pandas.io.gbq', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\gbq.py', - 'PYMODULE'), ('pandas.core.methods.to_dict', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\methods\\to_dict.py', 'PYMODULE'), @@ -4451,6 +4379,9 @@ ('pandas.api.indexers', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\api\\indexers\\__init__.py', 'PYMODULE'), + ('pandas.api.executors', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\api\\executors\\__init__.py', + 'PYMODULE'), ('pandas.core.reshape.api', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\reshape\\api.py', 'PYMODULE'), @@ -4472,6 +4403,87 @@ ('pandas.core.dtypes.dtypes', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\dtypes\\dtypes.py', 'PYMODULE'), + ('zoneinfo', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\zoneinfo\\__init__.py', + 'PYMODULE'), + ('tzdata', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.US', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\US\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Pacific', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Pacific\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Mexico', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Mexico\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Indian', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Indian\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Europe', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Europe\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Etc', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Etc\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Chile', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Chile\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Canada', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Canada\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Brazil', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Brazil\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Australia', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Australia\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Atlantic', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Atlantic\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Asia', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Asia\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Arctic', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Arctic\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Antarctica', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Antarctica\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.America.North_Dakota', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\America\\North_Dakota\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.America.Kentucky', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\America\\Kentucky\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.America.Indiana', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\America\\Indiana\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.America.Argentina', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\America\\Argentina\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.America', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\America\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Africa', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Africa\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\__init__.py', + 'PYMODULE'), + ('zoneinfo._zoneinfo', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\zoneinfo\\_zoneinfo.py', + 'PYMODULE'), + ('zoneinfo._common', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\zoneinfo\\_common.py', + 'PYMODULE'), + ('zoneinfo._tzpath', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\zoneinfo\\_tzpath.py', + 'PYMODULE'), + ('pandas.core.col', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\col.py', + 'PYMODULE'), ('pandas.core.api', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\api.py', 'PYMODULE'), @@ -4493,9 +4505,6 @@ ('pandas.compat.pyarrow', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\compat\\pyarrow.py', 'PYMODULE'), - ('pandas.compat.compressors', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\compat\\compressors.py', - 'PYMODULE'), ('typing', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\typing.py', 'PYMODULE'), @@ -4538,29 +4547,41 @@ ('numpy.libs\\msvcp140-a4c2229bdc2a2a630acdc095b4d86008.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\numpy.libs\\msvcp140-a4c2229bdc2a2a630acdc095b4d86008.dll', 'BINARY'), - ('PyQt5\\Qt5\\bin\\libEGL.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\libEGL.dll', - 'BINARY'), ('PyQt5\\Qt5\\bin\\libGLESv2.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\libGLESv2.dll', 'BINARY'), - ('PyQt5\\Qt5\\bin\\d3dcompiler_47.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\d3dcompiler_47.dll', + ('PyQt5\\Qt5\\bin\\libEGL.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\libEGL.dll', 'BINARY'), ('PyQt5\\Qt5\\bin\\opengl32sw.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\opengl32sw.dll', 'BINARY'), + ('PyQt5\\Qt5\\bin\\d3dcompiler_47.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\d3dcompiler_47.dll', + 'BINARY'), ('pywin32_system32\\pywintypes313.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pywin32_system32\\pywintypes313.dll', 'BINARY'), ('pywin32_system32\\pythoncom313.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pywin32_system32\\pythoncom313.dll', 'BINARY'), + ('PyQt5\\Qt5\\plugins\\platforms\\qoffscreen.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\platforms\\qoffscreen.dll', + 'BINARY'), + ('PyQt5\\Qt5\\plugins\\imageformats\\qwebp.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qwebp.dll', + 'BINARY'), + ('PyQt5\\Qt5\\plugins\\platformthemes\\qxdgdesktopportal.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\platformthemes\\qxdgdesktopportal.dll', + 'BINARY'), ('PyQt5\\Qt5\\plugins\\imageformats\\qtga.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qtga.dll', 'BINARY'), - ('PyQt5\\Qt5\\plugins\\imageformats\\qtiff.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qtiff.dll', + ('PyQt5\\Qt5\\plugins\\generic\\qtuiotouchplugin.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\generic\\qtuiotouchplugin.dll', + 'BINARY'), + ('PyQt5\\Qt5\\plugins\\imageformats\\qgif.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qgif.dll', 'BINARY'), ('PyQt5\\Qt5\\plugins\\imageformats\\qsvg.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qsvg.dll', @@ -4568,41 +4589,29 @@ 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'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qwebp.dll', + ('PyQt5\\Qt5\\plugins\\imageformats\\qtiff.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qtiff.dll', 'BINARY'), - ('PyQt5\\Qt5\\plugins\\imageformats\\qico.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qico.dll', + ('PyQt5\\Qt5\\plugins\\imageformats\\qwbmp.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qwbmp.dll', 'BINARY'), - ('PyQt5\\Qt5\\plugins\\generic\\qtuiotouchplugin.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\generic\\qtuiotouchplugin.dll', - 'BINARY'), - ('PyQt5\\Qt5\\plugins\\platformthemes\\qxdgdesktopportal.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\platformthemes\\qxdgdesktopportal.dll', + ('PyQt5\\Qt5\\plugins\\platforms\\qwebgl.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\platforms\\qwebgl.dll', 'BINARY'), ('PyQt5\\Qt5\\plugins\\styles\\qwindowsvistastyle.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\styles\\qwindowsvistastyle.dll', @@ -4913,49 +4922,55 @@ ('pandas\\_libs\\algos.cp313-win_amd64.pyd', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\_libs\\algos.cp313-win_amd64.pyd', 'EXTENSION'), - ('api-ms-win-crt-conio-l1-1-0.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-conio-l1-1-0.dll', - 'BINARY'), - ('api-ms-win-crt-environment-l1-1-0.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-environment-l1-1-0.dll', - 'BINARY'), - ('api-ms-win-crt-convert-l1-1-0.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-convert-l1-1-0.dll', - 'BINARY'), - ('api-ms-win-crt-process-l1-1-0.dll', - 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'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-filesystem-l1-1-0.dll', 'BINARY'), - ('api-ms-win-crt-runtime-l1-1-0.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-runtime-l1-1-0.dll', + ('VCRUNTIME140.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\VCRUNTIME140.dll', 'BINARY'), - ('api-ms-win-crt-locale-l1-1-0.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-locale-l1-1-0.dll', - 'BINARY'), - ('zlib.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\zlib.dll', 'BINARY'), ('api-ms-win-crt-time-l1-1-0.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-time-l1-1-0.dll', 'BINARY'), + ('api-ms-win-crt-math-l1-1-0.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-math-l1-1-0.dll', + 'BINARY'), + ('api-ms-win-crt-process-l1-1-0.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-process-l1-1-0.dll', + 'BINARY'), + ('api-ms-win-crt-heap-l1-1-0.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-heap-l1-1-0.dll', + 'BINARY'), 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'PYMODULE'), + ('_collections_abc', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\_collections_abc.py', + 'PYMODULE'), + ('types', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\types.py', 'PYMODULE'), + ('genericpath', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\genericpath.py', + 'PYMODULE'), + ('operator', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\operator.py', + 'PYMODULE'), ('keyword', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\keyword.py', 'PYMODULE'), - ('ntpath', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\ntpath.py', + ('locale', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\locale.py', + 'PYMODULE'), + ('weakref', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\weakref.py', + 'PYMODULE'), + ('sre_parse', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\sre_parse.py', + 'PYMODULE'), + ('abc', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\abc.py', 'PYMODULE'), + ('sre_compile', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\sre_compile.py', 'PYMODULE'), ('functools', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\functools.py', diff --git a/build/GUI应用/EXE-00.toc b/build/GUI应用/EXE-00.toc index 6157b86..0cfe2f1 100644 --- a/build/GUI应用/EXE-00.toc +++ b/build/GUI应用/EXE-00.toc @@ -1,4 +1,4 @@ -('C:\\Users\\27942\\Desktop\\haha\\dist\\GUI应用.exe', +('C:\\Users\\27942\\Desktop\\codes\\haha\\dist\\GUI应用.exe', False, False, False, @@ -29,25 +29,25 @@ None, None, None, - 'C:\\Users\\27942\\Desktop\\haha\\build\\GUI应用\\GUI应用.pkg', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\build\\GUI应用\\GUI应用.pkg', [('pyi-contents-directory _internal', '', 'OPTION'), ('PYZ-00.pyz', - 'C:\\Users\\27942\\Desktop\\haha\\build\\GUI应用\\PYZ-00.pyz', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\build\\GUI应用\\PYZ-00.pyz', 'PYZ'), ('struct', - 'C:\\Users\\27942\\Desktop\\haha\\build\\GUI应用\\localpycs\\struct.pyc', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\build\\GUI应用\\localpycs\\struct.pyc', 'PYMODULE'), ('pyimod01_archive', - 'C:\\Users\\27942\\Desktop\\haha\\build\\GUI应用\\localpycs\\pyimod01_archive.pyc', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\build\\GUI应用\\localpycs\\pyimod01_archive.pyc', 'PYMODULE'), ('pyimod02_importers', - 'C:\\Users\\27942\\Desktop\\haha\\build\\GUI应用\\localpycs\\pyimod02_importers.pyc', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\build\\GUI应用\\localpycs\\pyimod02_importers.pyc', 'PYMODULE'), ('pyimod03_ctypes', - 'C:\\Users\\27942\\Desktop\\haha\\build\\GUI应用\\localpycs\\pyimod03_ctypes.pyc', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\build\\GUI应用\\localpycs\\pyimod03_ctypes.pyc', 'PYMODULE'), ('pyimod04_pywin32', - 'C:\\Users\\27942\\Desktop\\haha\\build\\GUI应用\\localpycs\\pyimod04_pywin32.pyc', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\build\\GUI应用\\localpycs\\pyimod04_pywin32.pyc', 'PYMODULE'), ('pyiboot01_bootstrap', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyInstaller\\loader\\pyiboot01_bootstrap.py', @@ -73,7 +73,7 @@ ('pyi_rth_pythoncom', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\_pyinstaller_hooks_contrib\\rthooks\\pyi_rth_pythoncom.py', 'PYSOURCE'), - ('gui_app', 'C:\\Users\\27942\\Desktop\\haha\\gui_app.py', 'PYSOURCE'), + ('gui_app', 'C:\\Users\\27942\\Desktop\\codes\\haha\\gui_app.py', 'PYSOURCE'), ('python313.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\python313.dll', 'BINARY'), @@ -83,29 +83,41 @@ ('numpy.libs\\msvcp140-a4c2229bdc2a2a630acdc095b4d86008.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\numpy.libs\\msvcp140-a4c2229bdc2a2a630acdc095b4d86008.dll', 'BINARY'), - ('PyQt5\\Qt5\\bin\\libEGL.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\libEGL.dll', - 'BINARY'), ('PyQt5\\Qt5\\bin\\libGLESv2.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\libGLESv2.dll', 'BINARY'), - ('PyQt5\\Qt5\\bin\\d3dcompiler_47.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\d3dcompiler_47.dll', + ('PyQt5\\Qt5\\bin\\libEGL.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\libEGL.dll', 'BINARY'), ('PyQt5\\Qt5\\bin\\opengl32sw.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\opengl32sw.dll', 'BINARY'), + ('PyQt5\\Qt5\\bin\\d3dcompiler_47.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\d3dcompiler_47.dll', + 'BINARY'), ('pywin32_system32\\pywintypes313.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pywin32_system32\\pywintypes313.dll', 'BINARY'), ('pywin32_system32\\pythoncom313.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pywin32_system32\\pythoncom313.dll', 'BINARY'), + ('PyQt5\\Qt5\\plugins\\platforms\\qoffscreen.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\platforms\\qoffscreen.dll', + 'BINARY'), + ('PyQt5\\Qt5\\plugins\\imageformats\\qwebp.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qwebp.dll', + 'BINARY'), + ('PyQt5\\Qt5\\plugins\\platformthemes\\qxdgdesktopportal.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\platformthemes\\qxdgdesktopportal.dll', + 'BINARY'), ('PyQt5\\Qt5\\plugins\\imageformats\\qtga.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qtga.dll', 'BINARY'), - ('PyQt5\\Qt5\\plugins\\imageformats\\qtiff.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qtiff.dll', + ('PyQt5\\Qt5\\plugins\\generic\\qtuiotouchplugin.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\generic\\qtuiotouchplugin.dll', + 'BINARY'), + ('PyQt5\\Qt5\\plugins\\imageformats\\qgif.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qgif.dll', 'BINARY'), ('PyQt5\\Qt5\\plugins\\imageformats\\qsvg.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qsvg.dll', @@ -113,41 +125,29 @@ ('PyQt5\\Qt5\\plugins\\iconengines\\qsvgicon.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\iconengines\\qsvgicon.dll', 'BINARY'), - ('PyQt5\\Qt5\\plugins\\platforms\\qwindows.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\platforms\\qwindows.dll', - 'BINARY'), ('PyQt5\\Qt5\\plugins\\imageformats\\qicns.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qicns.dll', 'BINARY'), - ('PyQt5\\Qt5\\plugins\\imageformats\\qwbmp.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qwbmp.dll', + ('PyQt5\\Qt5\\plugins\\platforms\\qwindows.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\platforms\\qwindows.dll', 'BINARY'), ('PyQt5\\Qt5\\plugins\\platforms\\qminimal.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\platforms\\qminimal.dll', 'BINARY'), - ('PyQt5\\Qt5\\plugins\\platforms\\qwebgl.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\platforms\\qwebgl.dll', - 'BINARY'), - ('PyQt5\\Qt5\\plugins\\imageformats\\qgif.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qgif.dll', - 'BINARY'), - ('PyQt5\\Qt5\\plugins\\platforms\\qoffscreen.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\platforms\\qoffscreen.dll', + ('PyQt5\\Qt5\\plugins\\imageformats\\qico.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qico.dll', 'BINARY'), ('PyQt5\\Qt5\\plugins\\imageformats\\qjpeg.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qjpeg.dll', 'BINARY'), - ('PyQt5\\Qt5\\plugins\\imageformats\\qwebp.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qwebp.dll', + ('PyQt5\\Qt5\\plugins\\imageformats\\qtiff.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qtiff.dll', 'BINARY'), - ('PyQt5\\Qt5\\plugins\\imageformats\\qico.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qico.dll', + ('PyQt5\\Qt5\\plugins\\imageformats\\qwbmp.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\imageformats\\qwbmp.dll', 'BINARY'), - ('PyQt5\\Qt5\\plugins\\generic\\qtuiotouchplugin.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\generic\\qtuiotouchplugin.dll', - 'BINARY'), - ('PyQt5\\Qt5\\plugins\\platformthemes\\qxdgdesktopportal.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\platformthemes\\qxdgdesktopportal.dll', + ('PyQt5\\Qt5\\plugins\\platforms\\qwebgl.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\platforms\\qwebgl.dll', 'BINARY'), ('PyQt5\\Qt5\\plugins\\styles\\qwindowsvistastyle.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\plugins\\styles\\qwindowsvistastyle.dll', @@ -458,49 +458,55 @@ ('pandas\\_libs\\algos.cp313-win_amd64.pyd', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\_libs\\algos.cp313-win_amd64.pyd', 'EXTENSION'), - ('api-ms-win-crt-conio-l1-1-0.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-conio-l1-1-0.dll', - 'BINARY'), - ('api-ms-win-crt-environment-l1-1-0.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-environment-l1-1-0.dll', - 'BINARY'), - ('api-ms-win-crt-convert-l1-1-0.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-convert-l1-1-0.dll', - 'BINARY'), - ('api-ms-win-crt-process-l1-1-0.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-process-l1-1-0.dll', - 'BINARY'), - ('VCRUNTIME140.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\VCRUNTIME140.dll', - 'BINARY'), - ('api-ms-win-crt-math-l1-1-0.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-math-l1-1-0.dll', - 'BINARY'), + ('pandas\\_libs\\_cyutility.cp313-win_amd64.pyd', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\_libs\\_cyutility.cp313-win_amd64.pyd', + 'EXTENSION'), + ('_zoneinfo.pyd', + 'C:\\Users\\27942\\.conda\\envs\\haha\\DLLs\\_zoneinfo.pyd', + 'EXTENSION'), ('api-ms-win-crt-string-l1-1-0.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-string-l1-1-0.dll', 'BINARY'), - ('api-ms-win-crt-stdio-l1-1-0.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-stdio-l1-1-0.dll', - 'BINARY'), ('api-ms-win-core-path-l1-1-0.dll', 'C:\\Windows\\system32\\api-ms-win-core-path-l1-1-0.dll', 'BINARY'), - ('api-ms-win-crt-heap-l1-1-0.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-heap-l1-1-0.dll', + ('api-ms-win-crt-locale-l1-1-0.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-locale-l1-1-0.dll', + 'BINARY'), + ('api-ms-win-crt-stdio-l1-1-0.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-stdio-l1-1-0.dll', + 'BINARY'), + ('api-ms-win-crt-conio-l1-1-0.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-conio-l1-1-0.dll', + 'BINARY'), + ('api-ms-win-crt-convert-l1-1-0.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-convert-l1-1-0.dll', + 'BINARY'), + ('api-ms-win-crt-environment-l1-1-0.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-environment-l1-1-0.dll', + 'BINARY'), + ('zlib.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\zlib.dll', 'BINARY'), + ('api-ms-win-crt-runtime-l1-1-0.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-runtime-l1-1-0.dll', 'BINARY'), ('api-ms-win-crt-filesystem-l1-1-0.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-filesystem-l1-1-0.dll', 'BINARY'), - ('api-ms-win-crt-runtime-l1-1-0.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-runtime-l1-1-0.dll', + ('VCRUNTIME140.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\VCRUNTIME140.dll', 'BINARY'), - ('api-ms-win-crt-locale-l1-1-0.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-locale-l1-1-0.dll', - 'BINARY'), - ('zlib.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\zlib.dll', 'BINARY'), ('api-ms-win-crt-time-l1-1-0.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-time-l1-1-0.dll', 'BINARY'), + ('api-ms-win-crt-math-l1-1-0.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-math-l1-1-0.dll', + 'BINARY'), + ('api-ms-win-crt-process-l1-1-0.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-process-l1-1-0.dll', + 'BINARY'), + ('api-ms-win-crt-heap-l1-1-0.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-heap-l1-1-0.dll', + 'BINARY'), ('api-ms-win-crt-utility-l1-1-0.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\api-ms-win-crt-utility-l1-1-0.dll', 'BINARY'), @@ -510,38 +516,38 @@ ('VCRUNTIME140_1.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\VCRUNTIME140_1.dll', 'BINARY'), - ('PyQt5\\Qt5\\bin\\VCRUNTIME140.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\VCRUNTIME140.dll', - 'BINARY'), ('PyQt5\\Qt5\\bin\\VCRUNTIME140_1.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\VCRUNTIME140_1.dll', 'BINARY'), ('PyQt5\\Qt5\\bin\\MSVCP140.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\MSVCP140.dll', 'BINARY'), - ('PyQt5\\Qt5\\bin\\Qt5Core.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\Qt5Core.dll', + ('PyQt5\\Qt5\\bin\\VCRUNTIME140.dll', + 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'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\numpy-2.4.1.dist-info\\licenses\\numpy\\random\\LICENSE.md', + 'DATA'), + ('curl_cffi-0.14.0.dist-info\\REQUESTED', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\curl_cffi-0.14.0.dist-info\\REQUESTED', 'DATA'), ('base_library.zip', - 'C:\\Users\\27942\\Desktop\\haha\\build\\GUI应用\\base_library.zip', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\build\\GUI应用\\base_library.zip', 'DATA')], [], False, False, - 1769784815, + 1769879942, [('runw.exe', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyInstaller\\bootloader\\Windows-64bit-intel\\runw.exe', 'EXECUTABLE')], diff --git a/build/GUI应用/GUI应用.pkg b/build/GUI应用/GUI应用.pkg index fb7d0cd..573e9cf 100644 Binary files a/build/GUI应用/GUI应用.pkg and b/build/GUI应用/GUI应用.pkg differ diff --git a/build/GUI应用/PKG-00.toc b/build/GUI应用/PKG-00.toc index 6253af7..e47ae89 100644 --- a/build/GUI应用/PKG-00.toc +++ b/build/GUI应用/PKG-00.toc @@ -1,4 +1,4 @@ -('C:\\Users\\27942\\Desktop\\haha\\build\\GUI应用\\GUI应用.pkg', +('C:\\Users\\27942\\Desktop\\codes\\haha\\build\\GUI应用\\GUI应用.pkg', {'BINARY': True, 'DATA': True, 'EXECUTABLE': True, @@ -10,22 +10,22 @@ 'SYMLINK': False}, [('pyi-contents-directory _internal', '', 'OPTION'), ('PYZ-00.pyz', - 'C:\\Users\\27942\\Desktop\\haha\\build\\GUI应用\\PYZ-00.pyz', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\build\\GUI应用\\PYZ-00.pyz', 'PYZ'), ('struct', - 'C:\\Users\\27942\\Desktop\\haha\\build\\GUI应用\\localpycs\\struct.pyc', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\build\\GUI应用\\localpycs\\struct.pyc', 'PYMODULE'), ('pyimod01_archive', - 'C:\\Users\\27942\\Desktop\\haha\\build\\GUI应用\\localpycs\\pyimod01_archive.pyc', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\build\\GUI应用\\localpycs\\pyimod01_archive.pyc', 'PYMODULE'), ('pyimod02_importers', - 'C:\\Users\\27942\\Desktop\\haha\\build\\GUI应用\\localpycs\\pyimod02_importers.pyc', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\build\\GUI应用\\localpycs\\pyimod02_importers.pyc', 'PYMODULE'), ('pyimod03_ctypes', - 'C:\\Users\\27942\\Desktop\\haha\\build\\GUI应用\\localpycs\\pyimod03_ctypes.pyc', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\build\\GUI应用\\localpycs\\pyimod03_ctypes.pyc', 'PYMODULE'), ('pyimod04_pywin32', - 'C:\\Users\\27942\\Desktop\\haha\\build\\GUI应用\\localpycs\\pyimod04_pywin32.pyc', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\build\\GUI应用\\localpycs\\pyimod04_pywin32.pyc', 'PYMODULE'), ('pyiboot01_bootstrap', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyInstaller\\loader\\pyiboot01_bootstrap.py', @@ -51,7 +51,7 @@ ('pyi_rth_pythoncom', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\_pyinstaller_hooks_contrib\\rthooks\\pyi_rth_pythoncom.py', 'PYSOURCE'), - ('gui_app', 'C:\\Users\\27942\\Desktop\\haha\\gui_app.py', 'PYSOURCE'), + ('gui_app', 'C:\\Users\\27942\\Desktop\\codes\\haha\\gui_app.py', 'PYSOURCE'), ('python313.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\python313.dll', 'BINARY'), @@ -61,29 +61,41 @@ ('numpy.libs\\msvcp140-a4c2229bdc2a2a630acdc095b4d86008.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\numpy.libs\\msvcp140-a4c2229bdc2a2a630acdc095b4d86008.dll', 'BINARY'), - ('PyQt5\\Qt5\\bin\\libEGL.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\libEGL.dll', - 'BINARY'), ('PyQt5\\Qt5\\bin\\libGLESv2.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\libGLESv2.dll', 'BINARY'), - ('PyQt5\\Qt5\\bin\\d3dcompiler_47.dll', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\d3dcompiler_47.dll', + ('PyQt5\\Qt5\\bin\\libEGL.dll', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\libEGL.dll', 'BINARY'), ('PyQt5\\Qt5\\bin\\opengl32sw.dll', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\PyQt5\\Qt5\\bin\\opengl32sw.dll', 'BINARY'), + 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'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\numpy-2.4.1.dist-info\\licenses\\numpy\\random\\LICENSE.md', + 'DATA'), + ('curl_cffi-0.14.0.dist-info\\REQUESTED', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\curl_cffi-0.14.0.dist-info\\REQUESTED', 'DATA'), ('base_library.zip', - 'C:\\Users\\27942\\Desktop\\haha\\build\\GUI应用\\base_library.zip', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\build\\GUI应用\\base_library.zip', 'DATA')], 'python313.dll', False, diff --git a/build/GUI应用/PYZ-00.pyz b/build/GUI应用/PYZ-00.pyz index 353a535..63829b9 100644 Binary files a/build/GUI应用/PYZ-00.pyz and b/build/GUI应用/PYZ-00.pyz differ diff --git a/build/GUI应用/PYZ-00.toc b/build/GUI应用/PYZ-00.toc index ec455b5..262f5c9 100644 --- a/build/GUI应用/PYZ-00.toc +++ b/build/GUI应用/PYZ-00.toc @@ -1,4 +1,4 @@ -('C:\\Users\\27942\\Desktop\\haha\\build\\GUI应用\\PYZ-00.pyz', +('C:\\Users\\27942\\Desktop\\codes\\haha\\build\\GUI应用\\PYZ-00.pyz', [('DataRecorder', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\DataRecorder\\__init__.py', 'PYMODULE'), @@ -828,10 +828,14 @@ 'PYMODULE'), ('glob', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\glob.py', 'PYMODULE'), ('gui_constants', - 'C:\\Users\\27942\\Desktop\\haha\\gui_constants.py', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\gui_constants.py', + 'PYMODULE'), + ('gui_models', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\gui_models.py', + 'PYMODULE'), + ('gui_worker', + 'C:\\Users\\27942\\Desktop\\codes\\haha\\gui_worker.py', 'PYMODULE'), - ('gui_models', 'C:\\Users\\27942\\Desktop\\haha\\gui_models.py', 'PYMODULE'), - ('gui_worker', 'C:\\Users\\27942\\Desktop\\haha\\gui_worker.py', 'PYMODULE'), ('gzip', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\gzip.py', 'PYMODULE'), ('hashlib', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\hashlib.py', @@ -1096,7 +1100,7 @@ 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\lxml\\usedoctest.py', 'PYMODULE'), ('lzma', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\lzma.py', 'PYMODULE'), - ('main', 'C:\\Users\\27942\\Desktop\\haha\\main.py', 'PYMODULE'), + ('main', 'C:\\Users\\27942\\Desktop\\codes\\haha\\main.py', 'PYMODULE'), ('mimetypes', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\mimetypes.py', 'PYMODULE'), @@ -2226,6 +2230,9 @@ ('pandas.api', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\api\\__init__.py', 'PYMODULE'), + ('pandas.api.executors', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\api\\executors\\__init__.py', + 'PYMODULE'), ('pandas.api.extensions', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\api\\extensions\\__init__.py', 'PYMODULE'), @@ -2253,9 +2260,6 @@ ('pandas.compat._optional', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\compat\\_optional.py', 'PYMODULE'), - ('pandas.compat.compressors', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\compat\\compressors.py', - 'PYMODULE'), ('pandas.compat.numpy', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\compat\\numpy\\__init__.py', 'PYMODULE'), @@ -2430,6 +2434,9 @@ ('pandas.core.base', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\base.py', 'PYMODULE'), + ('pandas.core.col', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\col.py', + 'PYMODULE'), ('pandas.core.common', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\common.py', 'PYMODULE'), @@ -2628,12 +2635,6 @@ ('pandas.core.internals.api', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\internals\\api.py', 'PYMODULE'), - ('pandas.core.internals.array_manager', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\internals\\array_manager.py', - 'PYMODULE'), - ('pandas.core.internals.base', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\internals\\base.py', - 'PYMODULE'), ('pandas.core.internals.blocks', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\internals\\blocks.py', 'PYMODULE'), @@ -2721,9 +2722,6 @@ ('pandas.core.reshape.tile', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\reshape\\tile.py', 'PYMODULE'), - ('pandas.core.reshape.util', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\reshape\\util.py', - 'PYMODULE'), ('pandas.core.roperator', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\roperator.py', 'PYMODULE'), @@ -2745,9 +2743,6 @@ ('pandas.core.strings.accessor', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\strings\\accessor.py', 'PYMODULE'), - ('pandas.core.strings.base', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\strings\\base.py', - 'PYMODULE'), ('pandas.core.strings.object_array', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\strings\\object_array.py', 'PYMODULE'), @@ -2781,9 +2776,6 @@ ('pandas.core.window.common', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\window\\common.py', 'PYMODULE'), - ('pandas.core.window.doc', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\window\\doc.py', - 'PYMODULE'), ('pandas.core.window.ewm', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\core\\window\\ewm.py', 'PYMODULE'), @@ -2802,6 +2794,9 @@ ('pandas.errors', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\errors\\__init__.py', 'PYMODULE'), + ('pandas.errors.cow', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\errors\\cow.py', + 'PYMODULE'), ('pandas.io', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\__init__.py', 'PYMODULE'), @@ -2895,12 +2890,12 @@ ('pandas.io.formats.xml', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\formats\\xml.py', 'PYMODULE'), - ('pandas.io.gbq', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\gbq.py', - 'PYMODULE'), ('pandas.io.html', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\html.py', 'PYMODULE'), + ('pandas.io.iceberg', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\iceberg.py', + 'PYMODULE'), ('pandas.io.json', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pandas\\io\\json\\__init__.py', 'PYMODULE'), @@ -3068,21 +3063,6 @@ ('pythoncom', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pythoncom.py', 'PYMODULE'), - ('pytz', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pytz\\__init__.py', - 'PYMODULE'), - ('pytz.exceptions', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pytz\\exceptions.py', - 'PYMODULE'), - ('pytz.lazy', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pytz\\lazy.py', - 'PYMODULE'), - ('pytz.tzfile', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pytz\\tzfile.py', - 'PYMODULE'), - ('pytz.tzinfo', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\pytz\\tzinfo.py', - 'PYMODULE'), ('pywin', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\Pythonwin\\pywin\\__init__.py', 'PYMODULE'), @@ -3707,6 +3687,9 @@ ('setuptools._vendor.importlib_metadata._text', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\importlib_metadata\\_text.py', 'PYMODULE'), + ('setuptools._vendor.importlib_metadata._typing', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\importlib_metadata\\_typing.py', + 'PYMODULE'), ('setuptools._vendor.importlib_metadata.compat', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\importlib_metadata\\compat\\__init__.py', 'PYMODULE'), @@ -3718,7 +3701,7 @@ 'PYMODULE'), ('setuptools._vendor.jaraco', '-', 'PYMODULE'), ('setuptools._vendor.jaraco.context', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\jaraco\\context.py', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\jaraco\\context\\__init__.py', 'PYMODULE'), ('setuptools._vendor.jaraco.functools', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\jaraco\\functools\\__init__.py', @@ -3789,12 +3772,21 @@ ('setuptools._vendor.zipp', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\__init__.py', 'PYMODULE'), + ('setuptools._vendor.zipp._functools', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\_functools.py', + 'PYMODULE'), ('setuptools._vendor.zipp.compat', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\compat\\__init__.py', 'PYMODULE'), + ('setuptools._vendor.zipp.compat.overlay', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\compat\\overlay.py', + 'PYMODULE'), ('setuptools._vendor.zipp.compat.py310', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\compat\\py310.py', 'PYMODULE'), + ('setuptools._vendor.zipp.compat.py313', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\compat\\py313.py', + 'PYMODULE'), ('setuptools._vendor.zipp.glob', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\setuptools\\_vendor\\zipp\\glob.py', 'PYMODULE'), @@ -4037,6 +4029,72 @@ ('typing_extensions', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\typing_extensions.py', 'PYMODULE'), + ('tzdata', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Africa', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Africa\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.America', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\America\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.America.Argentina', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\America\\Argentina\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.America.Indiana', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\America\\Indiana\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.America.Kentucky', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\America\\Kentucky\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.America.North_Dakota', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\America\\North_Dakota\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Antarctica', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Antarctica\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Arctic', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Arctic\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Asia', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Asia\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Atlantic', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Atlantic\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Australia', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Australia\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Brazil', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Brazil\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Canada', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Canada\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Chile', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Chile\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Etc', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Etc\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Europe', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Europe\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Indian', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Indian\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Mexico', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Mexico\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.Pacific', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\Pacific\\__init__.py', + 'PYMODULE'), + ('tzdata.zoneinfo.US', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\tzdata\\zoneinfo\\US\\__init__.py', + 'PYMODULE'), ('unittest', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\unittest\\__init__.py', 'PYMODULE'), @@ -4245,72 +4303,9 @@ ('wheel', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\__init__.py', 'PYMODULE'), - ('wheel.cli', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\cli\\__init__.py', - 'PYMODULE'), - ('wheel.cli.convert', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\cli\\convert.py', - 'PYMODULE'), - ('wheel.cli.pack', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\cli\\pack.py', - 'PYMODULE'), - ('wheel.cli.tags', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\cli\\tags.py', - 'PYMODULE'), - ('wheel.cli.unpack', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\cli\\unpack.py', - 'PYMODULE'), ('wheel.macosx_libfile', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\macosx_libfile.py', 'PYMODULE'), - ('wheel.metadata', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\metadata.py', - 'PYMODULE'), - ('wheel.util', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\util.py', - 'PYMODULE'), - ('wheel.vendored', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\__init__.py', - 'PYMODULE'), - ('wheel.vendored.packaging', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\__init__.py', - 'PYMODULE'), - ('wheel.vendored.packaging._elffile', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\_elffile.py', - 'PYMODULE'), - ('wheel.vendored.packaging._manylinux', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\_manylinux.py', - 'PYMODULE'), - ('wheel.vendored.packaging._musllinux', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\_musllinux.py', - 'PYMODULE'), - ('wheel.vendored.packaging._parser', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\_parser.py', - 'PYMODULE'), - ('wheel.vendored.packaging._structures', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\_structures.py', - 'PYMODULE'), - ('wheel.vendored.packaging._tokenizer', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\_tokenizer.py', - 'PYMODULE'), - ('wheel.vendored.packaging.markers', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\markers.py', - 'PYMODULE'), - ('wheel.vendored.packaging.requirements', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\requirements.py', - 'PYMODULE'), - ('wheel.vendored.packaging.specifiers', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\specifiers.py', - 'PYMODULE'), - ('wheel.vendored.packaging.tags', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\tags.py', - 'PYMODULE'), - ('wheel.vendored.packaging.utils', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\utils.py', - 'PYMODULE'), - ('wheel.vendored.packaging.version', - 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\vendored\\packaging\\version.py', - 'PYMODULE'), ('wheel.wheelfile', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\site-packages\\wheel\\wheelfile.py', 'PYMODULE'), @@ -4470,4 +4465,16 @@ 'PYMODULE'), ('zipimport', 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\zipimport.py', + 'PYMODULE'), + ('zoneinfo', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\zoneinfo\\__init__.py', + 'PYMODULE'), + ('zoneinfo._common', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\zoneinfo\\_common.py', + 'PYMODULE'), + ('zoneinfo._tzpath', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\zoneinfo\\_tzpath.py', + 'PYMODULE'), + ('zoneinfo._zoneinfo', + 'C:\\Users\\27942\\.conda\\envs\\haha\\Lib\\zoneinfo\\_zoneinfo.py', 'PYMODULE')]) diff --git a/build/GUI应用/base_library.zip b/build/GUI应用/base_library.zip index a5ec5dd..0afd556 100644 Binary files a/build/GUI应用/base_library.zip and b/build/GUI应用/base_library.zip differ diff --git a/build/GUI应用/warn-GUI应用.txt b/build/GUI应用/warn-GUI应用.txt index 9b691b1..d03d5e6 100644 --- a/build/GUI应用/warn-GUI应用.txt +++ b/build/GUI应用/warn-GUI应用.txt @@ -18,7 +18,7 @@ missing module named urllib.urlopen - imported by urllib (delayed, optional), lx missing module named urllib.urlencode - imported by urllib (delayed, optional), lxml.html (delayed, optional) missing module named pwd - imported by posixpath (delayed, conditional, optional), shutil (delayed, optional), tarfile (optional), pathlib._local (optional), subprocess (delayed, conditional, optional), http.server (delayed, optional), psutil (optional), netrc (delayed, optional), getpass (delayed, optional), setuptools._distutils.util (delayed, conditional, optional), setuptools._vendor.backports.tarfile (optional), setuptools._distutils.archive_util (optional) missing module named grp - imported by shutil (delayed, optional), tarfile (optional), pathlib._local (optional), subprocess (delayed, conditional, optional), setuptools._vendor.backports.tarfile (optional), setuptools._distutils.archive_util (optional) -missing module named 'collections.abc' - imported by traceback (top-level), typing (top-level), inspect (top-level), logging (top-level), importlib.resources.readers (top-level), selectors (top-level), tracemalloc (top-level), numpy._typing._array_like (top-level), numpy._typing._nested_sequence (conditional), numpy._typing._shape (top-level), numpy._typing._dtype_like (top-level), asyncio.base_events (top-level), http.client (top-level), asyncio.coroutines (top-level), numpy.lib._function_base_impl (top-level), numpy.lib._npyio_impl (top-level), numpy.random._common (top-level), numpy.random._generator (top-level), numpy.random.bit_generator (top-level), typing_extensions (top-level), numpy.random.mtrand (top-level), numpy.polynomial._polybase (top-level), pandas._typing (top-level), pytz.lazy (optional), pandas.util._exceptions (conditional), pandas._config.config (conditional), pandas.util.version (top-level), pandas.core.dtypes.inference (conditional), pandas.util._validators (top-level), pandas.core.construction (top-level), pandas.core.common (top-level), pandas.util._decorators (conditional), pandas.core.frame (top-level), pandas.core.dtypes.concat (conditional), pandas.core.sorting (conditional), pandas.core.indexes.category (conditional), pandas.core.arrays._arrow_string_mixins (conditional), pandas.core.arrays.masked (conditional), pandas.core.apply (conditional), pandas.core.base (conditional), pandas.core.indexing (conditional), pandas.core.internals.blocks (conditional), pandas.core.arrays.numeric (conditional), pandas.core.arrays.timedeltas (conditional), pandas.io.formats.format (top-level), pandas.core.indexes.range (top-level), pandas.core.tools.timedeltas (conditional), pandas.core.indexes.datetimelike (conditional), pandas.core.reshape.concat (conditional), pandas.io.common (top-level), pandas.io.formats.printing (top-level), pandas.core.indexes.multi (top-level), pandas.io.formats.html (conditional), pandas.io.formats.string (conditional), pandas.io.formats.csvs (top-level), pandas.io.formats.style_render (top-level), pandas.core.interchange.dataframe_protocol (conditional), pandas.core.window.rolling (conditional), pandas.core.series (top-level), pandas.core.arrays.sparse.array (conditional), pandas.core.arrays.sparse.scipy_sparse (conditional), pandas.core.methods.selectn (top-level), pandas.core.strings.accessor (conditional), pandas.core.tools.datetimes (conditional), pandas.io.formats.info (conditional), pandas.plotting._core (conditional), pandas.plotting._misc (conditional), pandas.core.groupby.grouper (conditional), pandas.core.groupby.ops (conditional), pandas.io._util (conditional), pandas.io.json._normalize (conditional), pandas.io.parsers.base_parser (conditional), pandas.io.parsers.c_parser_wrapper (conditional), pandas.io.parsers.python_parser (top-level), pandas.io.parsers.readers (conditional), pandas.io.json._json (conditional), pandas.io.stata (conditional), pandas.io.formats.style (conditional), pandas.io.formats.excel (top-level), pandas.io.formats.css (conditional), pandas.io.excel._base (top-level), pandas.io.excel._util (top-level), xml.etree.ElementTree (top-level), pandas.core.arrays.interval (conditional), pandas.core.indexes.interval (conditional), pandas.core.arrays.period (conditional), pandas.core.indexes.period (conditional), pandas.core.internals.managers (top-level), pandas.core.internals.ops (conditional), pandas.core.internals.array_manager (conditional), pandas.core.internals.construction (conditional), pandas.core.methods.describe (conditional), pandas.core.generic (conditional), pandas.core.computation.parsing (conditional), pandas.compat.pickle_compat (conditional), pandas.core.computation.ops (conditional), pandas.core.computation.align (conditional), pandas.io.pytables (conditional), pandas.io.sql (conditional), sqlite3.dbapi2 (top-level), pandas.core.groupby.groupby (top-level), pandas.core.strings.base (conditional), pandas.core.strings.object_array (conditional), pandas.core.arrays.string_arrow (conditional), pandas.core.groupby.base (conditional), pandas.core.groupby.indexing (top-level), pandas.core.resample (conditional), pandas.core.groupby.generic (conditional), pandas.core.reshape.merge (top-level), pandas.core.arrays.arrow.array (conditional), pandas.core.arrays.datetimelike (conditional), pandas.core.arrays.datetimes (conditional), pandas.core.indexes.datetimes (conditional), pandas.core.arrays._mixins (conditional), pandas.core.arrays.categorical (conditional), pandas.core.reshape.melt (conditional), pandas.core.interchange.dataframe (conditional), pandas.io.feather_format (conditional), pandas.io.xml (conditional), pandas.core.reshape.pivot (top-level), pandas.core.arrays.base (conditional), pandas.core.internals.concat (conditional), pandas.core.indexes.base (conditional), pandas.core.arrays.numpy_ (conditional), pandas.core.dtypes.cast (conditional), pandas.core.arrays.string_ (conditional), pandas.core.arrays.arrow.accessors (conditional), pandas.core.dtypes.dtypes (conditional), pandas.core.util.hashing (conditional), pandas.core.reshape.encoding (top-level), pandas._config.localization (conditional), pandas._testing.contexts (conditional), pandas._testing._warnings (conditional), pandas.io.html (conditional), lxml.html (top-level), lxml.html._setmixin (optional), cssselect.parser (conditional), cssselect.xpath (top-level), pandas.io.sas.sasreader (conditional), pandas.io.spss (conditional), curl_cffi._asyncio_selector (top-level), curl_cffi.requests.cookies (top-level), curl_cffi.requests.headers (top-level), curl_cffi.requests.models (top-level), curl_cffi.requests.session (top-level), curl_cffi.requests.utils (top-level), curl_cffi.requests.websockets (top-level), setuptools (top-level), setuptools._distutils.filelist (top-level), setuptools._distutils.util (top-level), setuptools._vendor.jaraco.functools (top-level), setuptools._vendor.more_itertools.more (top-level), setuptools._vendor.more_itertools.recipes (top-level), setuptools._distutils._modified (top-level), setuptools._distutils.compat (top-level), setuptools._distutils.spawn (top-level), setuptools._distutils.compilers.C.base (top-level), setuptools._distutils.fancy_getopt (top-level), setuptools._reqs (top-level), setuptools.discovery (top-level), setuptools.dist (top-level), setuptools._distutils.command.bdist (top-level), setuptools._distutils.core (top-level), setuptools._distutils.cmd (top-level), setuptools._distutils.dist (top-level), configparser (top-level), setuptools._distutils.extension (top-level), setuptools.config.setupcfg (top-level), setuptools.config.expand (top-level), setuptools.config.pyprojecttoml (top-level), setuptools.config._apply_pyprojecttoml (top-level), tomllib._parser (top-level), setuptools._vendor.tomli._parser (top-level), setuptools.command.egg_info (top-level), setuptools._distutils.command.build (top-level), setuptools._distutils.command.sdist (top-level), setuptools.glob (top-level), setuptools.command._requirestxt (top-level), setuptools.command.bdist_wheel (top-level), wheel.cli.convert (top-level), wheel.cli.tags (top-level), requests.compat (top-level), tldextract.tldextract (top-level), tldextract.cache (top-level), filelock.asyncio (conditional), tldextract.suffix_list (top-level), setuptools._distutils.command.build_ext (top-level), _pyrepl.types (top-level), _pyrepl.readline (top-level), setuptools._distutils.compilers.C.msvc (top-level) +missing module named 'collections.abc' - imported by traceback (top-level), typing (top-level), inspect (top-level), logging (top-level), importlib.resources.readers (top-level), selectors (top-level), tracemalloc (top-level), numpy._typing._array_like (top-level), numpy._typing._nested_sequence (conditional), numpy._typing._shape (top-level), numpy._typing._dtype_like (top-level), asyncio.base_events (top-level), http.client (top-level), asyncio.coroutines (top-level), numpy.lib._function_base_impl (top-level), numpy.lib._npyio_impl (top-level), numpy.random._common (top-level), numpy.random._generator (top-level), numpy.random.bit_generator (top-level), typing_extensions (top-level), numpy.random.mtrand (top-level), numpy.polynomial._polybase (top-level), pandas._typing (top-level), pandas._libs.tslibs.offsets (top-level), pandas._libs.tslibs.timezones (top-level), pandas._libs.tslibs.tzconversion (top-level), pandas.util._exceptions (conditional), pandas._config.config (conditional), pandas._libs.lib (top-level), pandas._libs.properties (top-level), pandas.util.version (top-level), pandas.util._decorators (conditional), pandas._libs.hashtable (top-level), pandas.core.dtypes.inference (conditional), pandas.core.dtypes.common (conditional), pandas._libs.arrays (top-level), pandas.util._validators (top-level), pandas._libs.internals (top-level), pandas.core.common (top-level), pandas.core.col (top-level), pandas.core.construction (conditional), pandas.core.dtypes.concat (conditional), pandas._libs.ops (top-level), pandas.core.ops.invalid (conditional), pandas.core.ops.common (conditional), pandas.core.frame (top-level), pandas.core.nanops (conditional), pandas.core.accessor (conditional), pandas.core.indexes.extension (conditional), pandas.core.sorting (conditional), pandas.core.arrays.base (conditional), pandas.io.formats.format (top-level), pandas.core.base (conditional), pandas.core.array_algos.datetimelike_accumulations (conditional), pandas.core.arrays._arrow_string_mixins (conditional), pandas.core.array_algos.masked_accumulations (conditional), pandas.core.array_algos.masked_reductions (conditional), pandas.core.arrays.masked (conditional), pandas.core.groupby.generic (top-level), pandas.core.apply (top-level), pandas.core._numba.executor (conditional), pandas.core.util.numba_ (conditional), pandas.core.groupby.groupby (top-level), pandas.core.arrays.numeric (conditional), pandas.core.arrays.floating (conditional), pandas.core.arrays.integer (conditional), pandas.core.strings.object_array (conditional), pandas.core.arrays.string_arrow (conditional), pandas.core.groupby.base (conditional), pandas.core.groupby.numba_ (conditional), pandas.core.series (top-level), pandas.io.formats.printing (top-level), pandas.core.arrays.sparse.array (conditional), pandas.core.arrays.sparse.scipy_sparse (conditional), pandas.core.arrays.timedeltas (conditional), pandas.core.indexes.range (top-level), pandas.core.tools.timedeltas (conditional), pandas.core.indexes.datetimelike (conditional), pandas.core.indexes.multi (top-level), pandas.core.methods.selectn (top-level), pandas.core.reshape.concat (conditional), pandas.core.strings.accessor (conditional), pandas.core.tools.datetimes (conditional), pandas.io.formats.info (conditional), pandas.plotting._core (conditional), pandas.plotting._misc (conditional), pandas.core.groupby.grouper (conditional), pandas.core.groupby.ops (conditional), pandas.core.groupby.indexing (top-level), pandas.core.arrays.interval (conditional), pandas.core.indexes.interval (conditional), pandas.core.arrays.period (conditional), pandas.core.indexes.period (conditional), pandas._libs.window.aggregations (top-level), pandas.core.window.numba_ (conditional), pandas.core.window.rolling (conditional), pandas.core.window.expanding (conditional), pandas.core.resample (conditional), pandas.core.reshape.merge (top-level), pandas.core.reshape.tile (conditional), pandas.io._util (conditional), pandas.core.arrays.arrow.array (conditional), pandas.core.arrays.datetimelike (conditional), pandas.core.arrays.datetimes (conditional), pandas.core.indexes.datetimes (conditional), pandas.io.common (top-level), pandas.io.formats.html (conditional), pandas.io.formats.string (conditional), pandas.io.formats.csvs (top-level), pandas.io.formats.style_render (top-level), pandas.core.interchange.dataframe_protocol (conditional), pandas._libs.json (top-level), pandas.io.json._normalize (conditional), pandas._libs.parsers (top-level), pandas.io.parsers.base_parser (conditional), pandas.io.parsers.c_parser_wrapper (conditional), pandas.io.parsers.python_parser (conditional), pandas.io.parsers.readers (conditional), pandas.io.json._json (conditional), pandas.io.sas.sasreader (top-level), pandas.io.stata (conditional), pandas.io.formats.style (conditional), pandas.io.formats.excel (top-level), pandas.io.formats.css (conditional), pandas.io.excel._base (top-level), pandas.io.excel._util (top-level), xml.etree.ElementTree (top-level), pandas.core.arrays._mixins (conditional), pandas.core.indexes.category (conditional), pandas.core.indexing (conditional), pandas.core.methods.describe (conditional), pandas.core.generic (conditional), pandas.core.computation.parsing (conditional), pandas.compat.pickle_compat (conditional), pandas.core.computation.ops (conditional), pandas.core.computation.align (conditional), pandas.core.computation.expr (conditional), pandas.io.pytables (conditional), pandas.core.internals.managers (top-level), pandas.core.internals.ops (conditional), pandas.core.internals.construction (conditional), pandas.io.sql (conditional), sqlite3.dbapi2 (top-level), pandas.core.reshape.melt (conditional), pandas.core.interchange.dataframe (conditional), pandas.core.methods.to_dict (conditional), pandas.io.feather_format (conditional), pandas.io.xml (conditional), pandas.core.reshape.pivot (conditional), pandas.core.arrays.categorical (conditional), pandas.core.internals.blocks (conditional), pandas.core.internals.concat (conditional), pandas.core.indexes.base (conditional), pandas.core.arrays.numpy_ (conditional), pandas.core.dtypes.cast (conditional), pandas.core.missing (conditional), pandas.core.arrays.string_ (conditional), pandas.core.arrays.arrow.accessors (conditional), pandas.core.dtypes.dtypes (conditional), pandas.tseries.holiday (conditional), pandas.core.util.hashing (conditional), pandas.core.config_init (top-level), pandas.core.reshape.encoding (top-level), pandas._config.localization (conditional), pandas._testing._io (conditional), pandas._testing._warnings (conditional), pandas._libs.testing (top-level), pandas._testing.contexts (conditional), pandas._testing (conditional), pandas._version (top-level), pandas.io.html (conditional), lxml.html (top-level), lxml.html._setmixin (optional), cssselect.parser (conditional), cssselect.xpath (conditional), pandas.io.spss (conditional), curl_cffi._asyncio_selector (top-level), curl_cffi.requests.cookies (top-level), curl_cffi.requests.headers (top-level), curl_cffi.requests.models (top-level), curl_cffi.requests.session (top-level), curl_cffi.requests.utils (top-level), curl_cffi.requests.websockets (top-level), setuptools (top-level), setuptools._distutils.filelist (top-level), setuptools._distutils.util (top-level), setuptools._vendor.jaraco.functools (top-level), setuptools._vendor.more_itertools.more (top-level), setuptools._distutils._modified (top-level), setuptools._distutils.compat (top-level), setuptools._distutils.spawn (top-level), setuptools._distutils.compilers.C.base (top-level), setuptools._distutils.fancy_getopt (top-level), setuptools._reqs (top-level), setuptools._vendor.jaraco.context (top-level), setuptools.discovery (top-level), setuptools.dist (top-level), setuptools._vendor.importlib_metadata (top-level), setuptools._vendor.importlib_metadata._meta (top-level), setuptools._distutils.command.bdist (top-level), setuptools._distutils.core (top-level), setuptools._distutils.cmd (top-level), setuptools._distutils.dist (top-level), configparser (top-level), setuptools._distutils.extension (top-level), setuptools.config.setupcfg (top-level), setuptools.config.expand (top-level), setuptools.config.pyprojecttoml (top-level), setuptools.config._apply_pyprojecttoml (top-level), setuptools.extension (top-level), tomllib._parser (top-level), setuptools._vendor.tomli._parser (conditional), setuptools.wheel (top-level), setuptools.command.egg_info (top-level), setuptools.command.bdist_egg (top-level), setuptools.command.sdist (top-level), setuptools._distutils.command.build (top-level), setuptools._distutils.command.sdist (top-level), setuptools.glob (top-level), setuptools.command._requirestxt (top-level), setuptools.command.bdist_wheel (top-level), requests.compat (top-level), tldextract.tldextract (top-level), tldextract.cache (top-level), filelock.asyncio (conditional), tldextract.suffix_list (top-level), setuptools._distutils.command.build_ext (top-level), _pyrepl.types (top-level), _pyrepl.readline (top-level), setuptools._distutils.compilers.C.msvc (top-level) missing module named posix - imported by os (conditional, optional), posixpath (optional), shutil (conditional), importlib._bootstrap_external (conditional), _pyrepl.unix_console (delayed, optional) missing module named resource - imported by posix (top-level) missing module named _frozen_importlib_external - imported by importlib._bootstrap (delayed), importlib (optional), importlib.abc (optional), zipimport (top-level) @@ -37,6 +37,7 @@ missing module named multiprocessing.AuthenticationError - imported by multiproc missing module named multiprocessing.current_process - imported by multiprocessing (top-level), loguru._logger (top-level) missing module named asyncio.DefaultEventLoopPolicy - imported by asyncio (delayed, conditional), asyncio.events (delayed, conditional) missing module named annotationlib - imported by typing_extensions (conditional) +missing module named _typeshed - imported by numpy.random.bit_generator (top-level), setuptools._distutils.dist (conditional), setuptools.command.bdist_egg (conditional), setuptools.glob (conditional), wheel.wheelfile (conditional), setuptools.compat.py311 (conditional) missing module named vms_lib - imported by platform (delayed, optional) missing module named 'java.lang' - imported by platform (delayed, optional) missing module named java - imported by platform (delayed) @@ -44,8 +45,7 @@ missing module named usercustomize - imported by site (delayed, optional) missing module named sitecustomize - imported by site (delayed, optional) missing module named _curses - imported by curses (top-level), curses.has_key (top-level), _pyrepl.curses (optional) missing module named readline - imported by cmd (delayed, conditional, optional), code (delayed, conditional, optional), pdb (delayed, conditional, optional), rlcompleter (optional), site (delayed, optional), sqlite3.__main__ (delayed, conditional, optional) -missing module named _typeshed - imported by numpy.random.bit_generator (top-level), setuptools._distutils.dist (conditional), setuptools.glob (conditional), setuptools.compat.py311 (conditional) -missing module named _manylinux - imported by packaging._manylinux (delayed, optional), setuptools._vendor.packaging._manylinux (delayed, optional), wheel.vendored.packaging._manylinux (delayed, optional) +missing module named _manylinux - imported by packaging._manylinux (delayed, optional), setuptools._vendor.packaging._manylinux (delayed, optional) missing module named setuptools._vendor.backports.zstd - imported by setuptools._vendor.backports (top-level), urllib3.util.request (conditional, optional), urllib3.response (conditional, optional) missing module named importlib_resources - imported by setuptools._vendor.jaraco.text (optional) missing module named trove_classifiers - imported by setuptools.config._validate_pyproject.formats (optional) @@ -273,6 +273,7 @@ missing module named yaml - imported by numpy.__config__ (delayed) missing module named numpy._distributor_init_local - imported by numpy (optional), numpy._distributor_init (optional) missing module named PIL - imported by openpyxl.drawing.image (optional), qfluentwidgets.common.image_utils (top-level) missing module named sqlite3.connect - imported by sqlite3 (top-level), DataRecorder.db_recorder (top-level) +missing module named sqlite3.Error - imported by sqlite3 (delayed), pandas.io.sql (delayed) missing module named openpyxl.tests - imported by openpyxl.reader.excel (optional) missing module named cv2 - imported by DrissionPage._units.screencast (delayed, optional) missing module named wsaccel - imported by websocket._utils (optional) @@ -285,7 +286,6 @@ missing module named eventlet - imported by curl_cffi.requests.session (delayed, missing module named readability - imported by curl_cffi.requests.models (top-level) missing module named markdownify - imported by curl_cffi.requests.models (top-level) missing module named orjson - imported by curl_cffi.requests.models (optional) -missing module named collections.Mapping - imported by collections (optional), pytz.lazy (optional) missing module named aiocontextvars - imported by loguru._contextvars (delayed, conditional) missing module named exceptiongroup - imported by loguru._better_exceptions (conditional, optional) excluded module named IPython - imported by pandas.io.formats.printing (delayed), loguru._colorama (delayed, conditional, optional) @@ -305,23 +305,22 @@ missing module named six.moves.range - imported by six.moves (top-level), dateut runtime module named six.moves - imported by dateutil.tz.tz (top-level), dateutil.tz._factories (top-level), dateutil.tz.win (top-level), dateutil.rrule (top-level) missing module named dateutil.tz.tzfile - imported by dateutil.tz (top-level), dateutil.zoneinfo (top-level) missing module named StringIO - imported by six (conditional) -missing module named numexpr - imported by pandas.core.computation.expressions (conditional), pandas.core.computation.engines (delayed) -missing module named numba - imported by pandas.core._numba.executor (delayed, conditional), pandas.core.util.numba_ (delayed, conditional), pandas.core.window.numba_ (delayed, conditional), pandas.core.window.online (delayed, conditional), pandas.core._numba.kernels.mean_ (top-level), pandas.core._numba.kernels.shared (top-level), pandas.core._numba.kernels.sum_ (top-level), pandas.core._numba.kernels.min_max_ (top-level), pandas.core._numba.kernels.var_ (top-level), pandas.core.groupby.numba_ (delayed, conditional), pandas.core._numba.extensions (top-level) +missing module named numba - imported by pandas.core.util.numba_ (delayed, conditional), pandas.core._numba.executor (delayed, conditional), pandas.core.groupby.numba_ (delayed, conditional), pandas.core.window.numba_ (delayed, conditional), pandas.core.window.online (delayed, conditional), pandas.core._numba.kernels.mean_ (top-level), pandas.core._numba.kernels.shared (top-level), pandas.core._numba.kernels.sum_ (top-level), pandas.core._numba.kernels.min_max_ (top-level), pandas.core._numba.kernels.var_ (top-level), pandas.core._numba.extensions (top-level) missing module named 'numba.extending' - imported by pandas.core._numba.kernels.sum_ (top-level) -missing module named 'pyarrow.compute' - imported by pandas.core.arrays._arrow_string_mixins (conditional), pandas.core.arrays.string_arrow (conditional), pandas.core.reshape.merge (delayed, conditional), pandas.core.arrays.arrow.array (conditional), pandas.core.arrays.arrow.accessors (conditional) -missing module named 'numba.typed' - imported by pandas.core._numba.extensions (delayed) -missing module named 'numba.core' - imported by pandas.core._numba.extensions (top-level) -missing module named pyarrow - imported by pandas.core.arrays._arrow_string_mixins (conditional), pandas.core.arrays.masked (delayed), pandas.core.arrays.boolean (delayed, conditional), pandas.core.arrays.numeric (delayed, conditional), pandas.core.arrays.arrow._arrow_utils (top-level), pandas.core.interchange.utils (delayed, conditional), pandas.core.strings.accessor (delayed, conditional), pandas.io._util (conditional), pandas.io.parsers.base_parser (delayed, conditional), pandas.core.arrays.interval (delayed), pandas.core.arrays.arrow.extension_types (top-level), pandas.core.arrays.period (delayed), pandas.core.methods.describe (delayed, conditional), pandas.io.sql (delayed, conditional), pandas.core.arrays.string_arrow (conditional), pandas.core.reshape.merge (delayed, conditional), pandas.core.arrays.arrow.array (conditional), pandas.core.interchange.buffer (conditional), pandas.io.feather_format (delayed), pandas.core.indexes.base (delayed, conditional), pandas.core.dtypes.cast (delayed, conditional), pandas.core.arrays.string_ (delayed, conditional), pandas.core.arrays.arrow.accessors (conditional), pandas.core.dtypes.dtypes (delayed, conditional), pandas.compat.pyarrow (optional), pandas.core.reshape.encoding (delayed, conditional), pandas._testing (conditional) +missing module named numexpr - imported by pandas.core.computation.expressions (conditional), pandas.core.computation.engines (delayed) +missing module named 'pyarrow.compute' - imported by pandas.core.arrays._arrow_string_mixins (conditional), pandas.core.arrays.string_arrow (conditional), pandas.core.reshape.merge (delayed, conditional), pandas.core.arrays.arrow.array (conditional), pandas.core.missing (delayed, conditional), pandas.core.arrays.string_ (conditional), pandas.core.arrays.arrow.accessors (conditional) +missing module named pyarrow - imported by pandas.core.arrays._arrow_string_mixins (conditional), pandas.core.arrays.masked (delayed), pandas.core.arrays.boolean (delayed, conditional), pandas.core.arrays.numeric (delayed, conditional), pandas.core.arrays.arrow._arrow_utils (top-level), pandas.core.arrays.string_arrow (conditional), pandas.core.strings.accessor (delayed, conditional), pandas.core.arrays.interval (delayed), pandas.core.arrays.arrow.extension_types (top-level), pandas.core.arrays.period (delayed), pandas.tseries.frequencies (delayed, conditional), pandas.core.reshape.merge (delayed, conditional), pandas.io._util (conditional), pandas.core.arrays.arrow.array (conditional), pandas.core.interchange.utils (delayed, conditional), pandas.io.parsers.arrow_parser_wrapper (conditional), pandas.core.methods.describe (delayed, conditional), pandas.io.sql (delayed, conditional), pandas.core.interchange.buffer (conditional), pandas.io.feather_format (delayed), pandas.core.indexes.base (delayed, conditional), pandas.core.dtypes.cast (delayed, conditional), pandas.core.arrays.string_ (delayed, conditional), pandas.core.arrays.arrow.accessors (conditional), pandas.core.dtypes.dtypes (delayed, conditional), pandas.compat.pyarrow (optional), pandas.core.reshape.encoding (delayed, conditional), pandas._testing (conditional) missing module named 'scipy.stats' - imported by pandas.core.nanops (delayed, conditional) excluded module named scipy - imported by pandas.core.missing (delayed) missing module named traitlets - imported by pandas.io.formats.printing (delayed, conditional) missing module named 'IPython.core' - imported by pandas.io.formats.printing (delayed, conditional) +missing module named botocore - imported by pandas.io.common (delayed, conditional, optional) missing module named xlsxwriter - imported by pandas.io.excel._xlsxwriter (delayed) missing module named 'odf.config' - imported by pandas.io.excel._odswriter (delayed) missing module named 'odf.style' - imported by pandas.io.excel._odswriter (delayed) missing module named 'odf.text' - imported by pandas.io.excel._odfreader (delayed), pandas.io.excel._odswriter (delayed) missing module named 'odf.table' - imported by pandas.io.excel._odfreader (delayed), pandas.io.excel._odswriter (delayed) -missing module named 'odf.opendocument' - imported by pandas.io.excel._odfreader (delayed), pandas.io.excel._odswriter (delayed) +missing module named 'odf.opendocument' - imported by pandas.io.excel._odfreader (delayed), pandas.io.excel._odswriter (delayed, conditional) missing module named xlrd - imported by pandas.io.excel._xlrd (delayed, conditional), pandas.io.excel._base (delayed, conditional) missing module named pyxlsb - imported by pandas.io.excel._pyxlsb (delayed, conditional) missing module named 'odf.office' - imported by pandas.io.excel._odfreader (delayed) @@ -329,18 +328,17 @@ missing module named 'odf.element' - imported by pandas.io.excel._odfreader (del missing module named 'odf.namespaces' - imported by pandas.io.excel._odfreader (delayed) missing module named odf - imported by pandas.io.excel._odfreader (conditional) missing module named python_calamine - imported by pandas.io.excel._calamine (delayed, conditional) -missing module named 'matplotlib.pyplot' - imported by pandas.io.formats.style (optional) -excluded module named matplotlib - imported by pandas.io.formats.style (optional) missing module named 'matplotlib.colors' - imported by pandas.plotting._misc (conditional), pandas.io.formats.style (conditional) missing module named markupsafe - imported by pandas.io.formats.style_render (top-level) -missing module named botocore - imported by pandas.io.common (delayed, conditional, optional) -missing module named sets - imported by pytz.tzinfo (optional) -missing module named UserDict - imported by pytz.lazy (optional) -missing module named 'scipy.sparse' - imported by pandas.core.dtypes.common (delayed, conditional, optional), pandas.core.arrays.sparse.array (conditional), pandas.core.arrays.sparse.scipy_sparse (delayed, conditional), pandas.core.arrays.sparse.accessor (delayed) +missing module named 'scipy.sparse' - imported by pandas.core.dtypes.common (delayed, conditional, optional), pandas.core.arrays.sparse.array (conditional), pandas.core.arrays.sparse.accessor (delayed, conditional), pandas.core.arrays.sparse.scipy_sparse (delayed, conditional) +missing module named 'numba.typed' - imported by pandas.core._numba.extensions (delayed) +missing module named 'numba.core' - imported by pandas.core._numba.extensions (top-level) missing module named pandas.core.internals.Block - imported by pandas.core.internals (conditional), pandas.io.pytables (conditional) missing module named AppKit - imported by pandas.io.clipboard (delayed, conditional, optional) missing module named PyQt4 - imported by pandas.io.clipboard (delayed, conditional, optional) missing module named qtpy - imported by pandas.io.clipboard (delayed, conditional, optional) +missing module named adbc_driver_manager - imported by pandas.io.sql (delayed) +missing module named 'sqlalchemy.exc' - imported by pandas.io.sql (delayed) missing module named 'sqlalchemy.engine' - imported by pandas.io.sql (delayed) missing module named 'sqlalchemy.types' - imported by pandas.io.sql (delayed, conditional) missing module named 'sqlalchemy.schema' - imported by pandas.io.sql (delayed) @@ -350,9 +348,7 @@ missing module named tables - imported by pandas.io.pytables (delayed, condition missing module named 'pyarrow.fs' - imported by pandas.io.orc (conditional) missing module named fsspec - imported by pandas.io.orc (conditional) missing module named 'pyarrow.parquet' - imported by pandas.io.parquet (delayed) -missing module named google - imported by pandas.io.gbq (conditional) -missing module named pytest - imported by pandas._testing._io (delayed), pandas._testing (delayed) -missing module named 'matplotlib.axes' - imported by pandas.plotting._core (conditional), pandas.plotting._misc (conditional), pandas._testing.asserters (delayed) -missing module named 'matplotlib.artist' - imported by pandas._testing.asserters (delayed) +missing module named pytest - imported by pandas._testing (delayed) missing module named 'matplotlib.table' - imported by pandas.plotting._misc (conditional) missing module named 'matplotlib.figure' - imported by pandas.plotting._misc (conditional) +missing module named 'matplotlib.axes' - imported by pandas.plotting._core (conditional), pandas.plotting._misc (conditional) diff --git a/build/GUI应用/xref-GUI应用.html b/build/GUI应用/xref-GUI应用.html index 3461e93..a7cfec5 100644 --- a/build/GUI应用/xref-GUI应用.html +++ b/build/GUI应用/xref-GUI应用.html @@ -15,7 +15,7 @@
- gui_app.py + gui_app.py Script
imports: DrissionPage @@ -403,11 +403,32 @@ imported by: • numpy.random.mtrand • pandas._config.config • pandas._config.localization + • pandas._libs.arrays + • pandas._libs.hashtable + • pandas._libs.internals + • pandas._libs.json + • pandas._libs.lib + • pandas._libs.ops + • pandas._libs.parsers + • pandas._libs.properties + • pandas._libs.testing + • pandas._libs.tslibs.offsets + • pandas._libs.tslibs.timezones + • pandas._libs.tslibs.tzconversion + • pandas._libs.window.aggregations + • pandas._testing + • pandas._testing._io • pandas._testing._warnings • pandas._testing.contexts • pandas._typing + • pandas._version • pandas.compat.pickle_compat + • pandas.core._numba.executor + • pandas.core.accessor • pandas.core.apply + • pandas.core.array_algos.datetimelike_accumulations + • pandas.core.array_algos.masked_accumulations + • pandas.core.array_algos.masked_reductions • pandas.core.arrays._arrow_string_mixins • pandas.core.arrays._mixins • pandas.core.arrays.arrow.accessors @@ -416,6 +437,8 @@ imported by: • pandas.core.arrays.categorical • pandas.core.arrays.datetimelike • pandas.core.arrays.datetimes + • pandas.core.arrays.floating + • pandas.core.arrays.integer • pandas.core.arrays.interval • pandas.core.arrays.masked • pandas.core.arrays.numeric @@ -427,12 +450,16 @@ imported by: • pandas.core.arrays.string_arrow • pandas.core.arrays.timedeltas • pandas.core.base + • pandas.core.col • pandas.core.common • pandas.core.computation.align + • pandas.core.computation.expr • pandas.core.computation.ops • pandas.core.computation.parsing + • pandas.core.config_init • pandas.core.construction • pandas.core.dtypes.cast + • pandas.core.dtypes.common • pandas.core.dtypes.concat • pandas.core.dtypes.dtypes • pandas.core.dtypes.inference @@ -443,11 +470,13 @@ imported by: • pandas.core.groupby.groupby • pandas.core.groupby.grouper • pandas.core.groupby.indexing + • pandas.core.groupby.numba_ • pandas.core.groupby.ops • pandas.core.indexes.base • pandas.core.indexes.category • pandas.core.indexes.datetimelike • pandas.core.indexes.datetimes + • pandas.core.indexes.extension • pandas.core.indexes.interval • pandas.core.indexes.multi • pandas.core.indexes.period @@ -455,7 +484,6 @@ imported by: • pandas.core.indexing • pandas.core.interchange.dataframe • pandas.core.interchange.dataframe_protocol - • pandas.core.internals.array_manager • pandas.core.internals.blocks • pandas.core.internals.concat • pandas.core.internals.construction @@ -463,20 +491,28 @@ imported by: • pandas.core.internals.ops • pandas.core.methods.describe • pandas.core.methods.selectn + • pandas.core.methods.to_dict + • pandas.core.missing + • pandas.core.nanops + • pandas.core.ops.common + • pandas.core.ops.invalid • pandas.core.resample • pandas.core.reshape.concat • pandas.core.reshape.encoding • pandas.core.reshape.melt • pandas.core.reshape.merge • pandas.core.reshape.pivot + • pandas.core.reshape.tile • pandas.core.series • pandas.core.sorting • pandas.core.strings.accessor - • pandas.core.strings.base • pandas.core.strings.object_array • pandas.core.tools.datetimes • pandas.core.tools.timedeltas • pandas.core.util.hashing + • pandas.core.util.numba_ + • pandas.core.window.expanding + • pandas.core.window.numba_ • pandas.core.window.rolling • pandas.io._util • pandas.io.common @@ -508,11 +544,11 @@ imported by: • pandas.io.xml • pandas.plotting._core • pandas.plotting._misc + • pandas.tseries.holiday • pandas.util._decorators • pandas.util._exceptions • pandas.util._validators • pandas.util.version - • pytz.lazy • requests.compat • selectors • setuptools @@ -533,20 +569,26 @@ imported by: • setuptools._distutils.spawn • setuptools._distutils.util • setuptools._reqs + • setuptools._vendor.importlib_metadata + • setuptools._vendor.importlib_metadata._meta + • setuptools._vendor.jaraco.context • setuptools._vendor.jaraco.functools • setuptools._vendor.more_itertools.more - • setuptools._vendor.more_itertools.recipes • setuptools._vendor.tomli._parser • setuptools.command._requirestxt + • setuptools.command.bdist_egg • setuptools.command.bdist_wheel • setuptools.command.egg_info + • setuptools.command.sdist • setuptools.config._apply_pyprojecttoml • setuptools.config.expand • setuptools.config.pyprojecttoml • setuptools.config.setupcfg • setuptools.discovery • setuptools.dist + • setuptools.extension • setuptools.glob + • setuptools.wheel • sqlite3.dbapi2 • tldextract.cache • tldextract.suffix_list @@ -556,8 +598,6 @@ imported by: • tracemalloc • typing • typing_extensions - • wheel.cli.convert - • wheel.cli.tags • xml.etree.ElementTree
@@ -654,24 +694,12 @@ imported by:
-
- - 'matplotlib.artist' -MissingModule
-imported by: - pandas._testing.asserters - -
- -
-
'matplotlib.axes' MissingModule
imported by: - pandas._testing.asserters - • pandas.plotting._core + pandas.plotting._core • pandas.plotting._misc
@@ -701,17 +729,6 @@ imported by:
-
- - 'matplotlib.pyplot' -MissingModule
-imported by: - pandas.io.formats.style - -
- -
-
'matplotlib.table' @@ -888,7 +905,9 @@ imported by: pandas.core.arrays._arrow_string_mixins • pandas.core.arrays.arrow.accessors • pandas.core.arrays.arrow.array + • pandas.core.arrays.string_ • pandas.core.arrays.string_arrow + • pandas.core.missing • pandas.core.reshape.merge
@@ -997,6 +1016,17 @@ imported by: +
+ + 'sqlalchemy.exc' +MissingModule
+imported by: + pandas.io.sql + +
+ +
+
'sqlalchemy.schema' @@ -3235,17 +3265,6 @@ imported by:
-
- - UserDict -MissingModule
-imported by: - pytz.lazy - -
- -
-
__future__ @@ -3330,7 +3349,6 @@ imported by: • pandas.compat • pandas.compat._constants • pandas.compat._optional - • pandas.compat.compressors • pandas.compat.numpy.function • pandas.compat.pickle_compat • pandas.compat.pyarrow @@ -3380,6 +3398,7 @@ imported by: • pandas.core.arrays.string_arrow • pandas.core.arrays.timedeltas • pandas.core.base + • pandas.core.col • pandas.core.common • pandas.core.computation.align • pandas.core.computation.check @@ -3437,8 +3456,6 @@ imported by: • pandas.core.interchange.from_dataframe • pandas.core.interchange.utils • pandas.core.internals.api - • pandas.core.internals.array_manager - • pandas.core.internals.base • pandas.core.internals.blocks • pandas.core.internals.concat • pandas.core.internals.construction @@ -3465,14 +3482,12 @@ imported by: • pandas.core.reshape.pivot • pandas.core.reshape.reshape • pandas.core.reshape.tile - • pandas.core.reshape.util • pandas.core.roperator • pandas.core.sample • pandas.core.series • pandas.core.shared_docs • pandas.core.sorting • pandas.core.strings.accessor - • pandas.core.strings.base • pandas.core.strings.object_array • pandas.core.tools.datetimes • pandas.core.tools.numeric @@ -3481,7 +3496,6 @@ imported by: • pandas.core.util.hashing • pandas.core.util.numba_ • pandas.core.window.common - • pandas.core.window.doc • pandas.core.window.ewm • pandas.core.window.expanding • pandas.core.window.numba_ @@ -3514,7 +3528,6 @@ imported by: • pandas.io.formats.style • pandas.io.formats.style_render • pandas.io.formats.xml - • pandas.io.gbq • pandas.io.html • pandas.io.json._json • pandas.io.json._normalize @@ -3572,7 +3585,9 @@ imported by: • setuptools._reqs • setuptools._vendor.importlib_metadata • setuptools._vendor.importlib_metadata._meta + • setuptools._vendor.importlib_metadata.compat.py39 • setuptools._vendor.jaraco.context + • setuptools._vendor.jaraco.functools • setuptools._vendor.packaging._elffile • setuptools._vendor.packaging._manylinux • setuptools._vendor.packaging._musllinux @@ -3590,6 +3605,7 @@ imported by: • setuptools.command.bdist_egg • setuptools.command.bdist_wheel • setuptools.command.build + • setuptools.command.egg_info • setuptools.command.sdist • setuptools.compat.py311 • setuptools.config._apply_pyprojecttoml @@ -3652,14 +3668,7 @@ imported by: • urllib3.util.util • urllib3.util.wait • wheel - • wheel.cli - • wheel.cli.convert - • wheel.cli.pack - • wheel.cli.tags - • wheel.cli.unpack • wheel.macosx_libfile - • wheel.metadata - • wheel.util • wheel.wheelfile • win32com • win32com.client @@ -4236,7 +4245,6 @@ imported by: imported by: packaging._manylinux • setuptools._vendor.packaging._manylinux - • wheel.vendored.packaging._manylinux
@@ -5409,8 +5417,10 @@ imported by: imported by: numpy.random.bit_generator • setuptools._distutils.dist + • setuptools.command.bdist_egg • setuptools.compat.py311 • setuptools.glob + • wheel.wheelfile @@ -5525,6 +5535,16 @@ imported by: +
+ + _zoneinfo C:\Users\27942\.conda\envs\haha\DLLs\_zoneinfo.pyd
+imported by: + zoneinfo + +
+ +
+
abc @@ -5566,7 +5586,7 @@ imported by: • pandas.core.indexes.datetimelike • pandas.core.interchange.dataframe_protocol • pandas.core.methods.describe - • pandas.core.strings.base + • pandas.errors • pandas.io.common • pandas.io.formats.info • pandas.io.json._json @@ -5577,10 +5597,20 @@ imported by: • setuptools._distutils.cmd • setuptools._vendor.importlib_metadata • setuptools._vendor.packaging.specifiers + • setuptools.config.setupcfg • typing • typing_extensions - • wheel.cli.convert - • wheel.vendored.packaging.specifiers + +
+ + + +
+ + adbc_driver_manager +MissingModule
+imported by: + pandas.io.sql
@@ -5645,7 +5675,6 @@ imported by: • unittest.main • uuid • webbrowser - • wheel.cli • zipfile
@@ -5698,7 +5727,6 @@ imported by: • setuptools._vendor.packaging._parser • setuptools.config.expand • traceback - • wheel.vendored.packaging._parser @@ -6748,7 +6776,7 @@ imported by: • urllib3.util.request • websocket._handshake • websocket._http - • wheel.util + • wheel.wheelfile • xmlrpc.client @@ -6813,10 +6841,11 @@ imported by: • idna.core • idna.intranges • multiprocessing.heap - • pytz.tzinfo • random + • setuptools._vendor.more_itertools.recipes • statistics • urllib.request + • zoneinfo._zoneinfo @@ -7269,6 +7298,7 @@ imported by: • numpy.ma.core • numpy.random.mtrand • operator + • pandas._typing • pandas.core.common • pydoc • reprlib @@ -7306,7 +7336,8 @@ imported by: • fileinput • loguru._file_sink • numpy.lib._datasource - • pandas.compat.compressors + • pandas._testing._io + • pandas.io.common • setuptools._vendor.backports.tarfile • shutil • tarfile @@ -7342,6 +7373,7 @@ imported by: • loguru._datetime • requests.cookies • ssl + • zoneinfo._zoneinfo @@ -7898,7 +7930,6 @@ imports: _collections • _collections_abc • _weakref - • collections.Mapping • copy • heapq • itertools @@ -7975,7 +8006,6 @@ imported by: • pandas.core.internals.construction • pandas.core.reshape.concat • pandas.core.reshape.encoding - • pandas.core.sorting • pandas.core.tools.datetimes • pandas.core.window.common • pandas.io.common @@ -7988,10 +8018,7 @@ imported by: • pandas.io.parsers.c_parser_wrapper • pandas.io.parsers.python_parser • pandas.io.parsers.readers - • pandas.io.sas.sas7bdat - • pandas.io.sas.sas_xport • pandas.io.stata - • pandas.util.version • pkgutil • platform • pprint @@ -7999,7 +8026,6 @@ imported by: • psutil._common • psutil._ntuples • pydoc - • pytz.lazy • qfluentwidgets.common.smooth_scroll • qfluentwidgets.components.date_time.calendar_view • qfluentwidgets.components.date_time.fast_calendar_view @@ -8012,9 +8038,11 @@ imported by: • selectors • setuptools._vendor.importlib_metadata • setuptools._vendor.importlib_metadata._collections + • setuptools._vendor.importlib_metadata._itertools • setuptools._vendor.more_itertools.more • setuptools._vendor.more_itertools.recipes • setuptools._vendor.packaging._manylinux + • setuptools._vendor.zipp._functools • setuptools.command._requirestxt • setuptools.config.setupcfg • shlex @@ -8033,21 +8061,8 @@ imported by: • urllib.parse • urllib3._collections • urllib3.response - • wheel.cli.convert - • wheel.vendored.packaging._manylinux • xml.etree.ElementTree - - - - - -
- - collections.Mapping -MissingModule
-imported by: - collections - • pytz.lazy + • zoneinfo._zoneinfo
@@ -8426,7 +8441,6 @@ imported by: • pandas.core.indexing • pandas.io.clipboard • pandas.io.formats.format - • pandas.io.formats.style • pandas.io.pytables • pandas.io.sql • pandas.plotting._misc @@ -8443,9 +8457,10 @@ imported by: • setuptools._path • setuptools._vendor.importlib_metadata • setuptools._vendor.jaraco.context + • setuptools._vendor.more_itertools.more + • setuptools._vendor.more_itertools.recipes • setuptools._vendor.packaging._manylinux • setuptools._vendor.packaging._tokenizer - • setuptools._vendor.zipp • setuptools.archive_util • setuptools.command.sdist • setuptools.config._validate_pyproject.error_reporting @@ -8463,8 +8478,6 @@ imported by: • urllib.request • urllib3.contrib.emscripten.response • urllib3.response - • wheel.vendored.packaging._manylinux - • wheel.vendored.packaging._tokenizer • win32com.client.gencache • xml.etree.ElementTree • zipfile._path @@ -8543,7 +8556,6 @@ imported by: • openpyxl.worksheet.copier • openpyxl.worksheet.dimensions • openpyxl.worksheet.merge - • pandas.compat.pickle_compat • pandas.core.generic • pandas.core.indexes.base • pandas.core.indexes.multi @@ -8710,6 +8722,7 @@ imports: _ctypes • ctypes._endian • ctypes.util + • ctypes.wintypes • nt • os • struct @@ -8753,7 +8766,6 @@ imported by: • setuptools.windows_support • webbrowser • wheel.macosx_libfile - • wheel.vendored.packaging._manylinux • win32_setctime._setctime
@@ -8912,6 +8924,7 @@ imports: imported by: _pyrepl.windows_console • colorama.win32 + • ctypes • darkdetect._windows_detect • dateutil.tz.win • filelock._windows @@ -9656,6 +9669,7 @@ imported by: • packaging._tokenizer • pandas.core.dtypes.inference • pandas.core.groupby.base + • pandas.core.groupby.generic • pandas.core.internals.construction • pandas.io.common • pprint @@ -9663,7 +9677,6 @@ imported by: • tldextract.tldextract • urllib3.contrib.emscripten.request • urllib3.contrib.emscripten.response - • wheel.vendored.packaging._tokenizer @@ -9728,6 +9741,7 @@ imported by: • pandas._libs.tslibs.tzconversion • pandas._libs.tslibs.vectorized • pandas._typing + • pandas.core.arrays.arrow.array • pandas.core.arrays.datetimelike • pandas.core.arrays.datetimes • pandas.core.arrays.period @@ -9756,7 +9770,6 @@ imported by: • pandas.io.excel._calamine • pandas.io.excel._odswriter • pandas.io.excel._xlrd - • pandas.io.parsers.base_parser • pandas.io.pytables • pandas.io.sas.sas7bdat • pandas.io.sas.sas_xport @@ -9764,9 +9777,6 @@ imported by: • pandas.io.stata • pandas.tseries.holiday • psutil - • pytz - • pytz.tzfile - • pytz.tzinfo • requests.models • requests.sessions • setuptools._vendor.tomli._re @@ -9777,6 +9787,7 @@ imported by: • urllib3.connection • win32com.client.build • xmlrpc.client + • zoneinfo._zoneinfo @@ -10191,6 +10202,7 @@ imported by: • pandas.core.computation.pytables • pandas.core.dtypes.dtypes • pandas.core.dtypes.missing + • pandas.io.excel._base • pandas.io.formats.format • setuptools.config._validate_pyproject.fastjsonschema_validations • statistics @@ -10333,7 +10345,6 @@ imported by: lxml.doctestcompare • numpy.testing._private.utils • pickletools - • pytz @@ -10638,7 +10649,6 @@ imports: imported by: email.message • setuptools.command.bdist_wheel - • wheel.cli.pack @@ -10738,8 +10748,6 @@ imported by: • setuptools._vendor.importlib_metadata._adapters • setuptools.command.bdist_wheel • setuptools.config._validate_pyproject.formats - • wheel.cli.convert - • wheel.metadata @@ -10761,10 +10769,6 @@ imported by: email • http.client • urllib3.contrib.emscripten.fetch - • wheel.cli.convert - • wheel.cli.pack - • wheel.cli.tags - • wheel.metadata @@ -10788,9 +10792,7 @@ imports:
imported by: email.message - • wheel.cli.convert - • wheel.cli.pack - • wheel.cli.tags + • setuptools._vendor.importlib_metadata._adapters
@@ -13392,7 +13394,7 @@ imported by: • packaging._elffile • pandas._libs.lib • pandas._libs.tslibs.dtypes - • pandas.core.arrays.sparse.array + • pandas.core.computation.parsing • pandas.core.interchange.dataframe_protocol • pandas.io.parsers.base_parser • psutil._common @@ -13432,7 +13434,6 @@ imported by: • urllib3.util.request • urllib3.util.timeout • uuid - • wheel.vendored.packaging._elffile @@ -13462,10 +13463,12 @@ imported by: • multiprocessing.shared_memory • numpy.f2py._backends._meson • pandas._version + • pandas.io.html • pathlib._abc • posixpath • requests_file • setuptools._distutils.file_util + • setuptools._vendor.jaraco.context • shutil • site • socket @@ -14037,6 +14040,7 @@ imported by: • packaging.utils • pandas._version • pandas.core._numba.executor + • pandas.core.accessor • pandas.core.apply • pandas.core.array_algos.take • pandas.core.arrays._arrow_string_mixins @@ -14052,7 +14056,6 @@ imported by: • pandas.core.computation.ops • pandas.core.computation.pytables • pandas.core.dtypes.cast - • pandas.core.dtypes.missing • pandas.core.frame • pandas.core.generic • pandas.core.groupby.generic @@ -14061,12 +14064,12 @@ imported by: • pandas.core.groupby.ops • pandas.core.indexes.base • pandas.core.indexes.multi - • pandas.core.internals.blocks • pandas.core.missing • pandas.core.nanops • pandas.core.ops.array_ops • pandas.core.ops.common • pandas.core.reshape.merge + • pandas.core.series • pandas.core.strings.accessor • pandas.core.strings.object_array • pandas.core.tools.datetimes @@ -14104,6 +14107,7 @@ imported by: • setuptools._static • setuptools._vendor.importlib_metadata • setuptools._vendor.importlib_metadata._functools + • setuptools._vendor.importlib_metadata._typing • setuptools._vendor.jaraco.context • setuptools._vendor.jaraco.functools • setuptools._vendor.jaraco.text @@ -14113,6 +14117,9 @@ imported by: • setuptools._vendor.packaging._musllinux • setuptools._vendor.packaging.utils • setuptools._vendor.tomli._re + • setuptools._vendor.zipp + • setuptools._vendor.zipp._functools + • setuptools._vendor.zipp.compat.py313 • setuptools.command.egg_info • setuptools.config • setuptools.config._apply_pyprojecttoml @@ -14143,9 +14150,7 @@ imported by: • urllib3.poolmanager • urllib3.util.wait • warnings - • wheel.metadata - • wheel.vendored.packaging._manylinux - • wheel.vendored.packaging._musllinux + • zoneinfo._zoneinfo @@ -14162,7 +14167,6 @@ imports: imported by: _posixsubprocess • numpy.testing._private.utils - • pandas.core.generic • weakref @@ -14303,24 +14307,12 @@ imported by: • setuptools.discovery • setuptools.dist • setuptools.installer - • wheel.cli.convert • win32com.client.gencache -
- - google -MissingModule
-imported by: - pandas.io.gbq - -
- -
-
grp @@ -14339,7 +14331,7 @@ imported by:
- gui_constants + gui_constants SourceModule
imports: os @@ -14357,7 +14349,7 @@ imported by:
- gui_models + gui_models SourceModule
imports: PyQt5.QtCore @@ -14375,7 +14367,7 @@ imported by:
- gui_worker + gui_worker SourceModule
imports: PyQt5.QtCore @@ -14493,6 +14485,7 @@ imported by: • lxml.html._difflib • queue • setuptools._vendor.more_itertools.more + • setuptools._vendor.more_itertools.recipes
@@ -14918,9 +14911,12 @@ imported by: • requests.compat • setuptools._distutils • setuptools._vendor.importlib_metadata + • setuptools._vendor.zipp.compat.overlay • setuptools.config.expand • win32com.client.gencache • win32com.client.makepy + • zoneinfo._common + • zoneinfo._tzpath
@@ -15050,7 +15046,6 @@ imported by: • setuptools._vendor.packaging.tags • setuptools.config.expand • sysconfig - • wheel.vendored.packaging.tags
@@ -15268,6 +15263,8 @@ imported by: • setuptools._importlib • setuptools._vendor.jaraco.text • urllib3.contrib.emscripten.fetch + • zoneinfo._common + • zoneinfo._tzpath
@@ -15532,10 +15529,10 @@ imported by: • pandas.core.common • pandas.core.computation.scope • pandas.core.dtypes.astype - • pandas.core.frame - • pandas.core.groupby.groupby • pandas.core.groupby.numba_ + • pandas.core.indexes.extension • pandas.core.internals.blocks + • pandas.core.util.numba_ • pandas.core.window.rolling • pandas.util._decorators • pandas.util._exceptions @@ -15632,10 +15629,8 @@ imported by: • pandas.core.frame • pandas.io.clipboards • pandas.io.common - • pandas.io.excel._base • pandas.io.formats.format • pandas.io.formats.xml - • pandas.io.json._json • pandas.io.orc • pandas.io.parquet • pandas.io.parsers.python_parser @@ -15778,15 +15773,18 @@ imported by: • openpyxl.worksheet.worksheet • packaging.specifiers • packaging.version - • pandas._config.config + • pandas.core.arrays.categorical • pandas.core.computation.scope • pandas.core.frame • pandas.core.indexes.base - • pandas.core.internals.array_manager + • pandas.core.indexes.multi • pandas.core.internals.managers • pandas.core.nanops + • pandas.core.reshape.concat • pandas.core.reshape.encoding + • pandas.core.reshape.pivot • pandas.core.reshape.reshape + • pandas.core.sorting • pandas.core.tools.datetimes • pandas.core.util.hashing • pandas.io.formats.excel @@ -15832,10 +15830,6 @@ imported by: • traceback • urllib3.util.retry • weakref - • wheel.cli.tags - • wheel.metadata - • wheel.vendored.packaging.specifiers - • wheel.vendored.packaging.version • win32com.client • win32com.client.build • win32com.client.dynamic @@ -16152,8 +16146,7 @@ imported by: • urllib3.response • urllib3.util.retry • websocket._logging - • wheel.util - • wheel.vendored.packaging.tags + • wheel.wheelfile
@@ -17333,7 +17326,8 @@ imports: imported by: loguru._file_sink • numpy.lib._datasource - • pandas.compat.compressors + • pandas._testing._io + • pandas.io.common • setuptools._vendor.backports.tarfile • shutil • tarfile @@ -17345,7 +17339,7 @@ imported by:
- main + main SourceModule
imports: DrissionPage @@ -17453,17 +17447,6 @@ imported by:
-
- - matplotlib -ExcludedModule
-imported by: - pandas.io.formats.style - -
- -
-
mimetypes @@ -18957,8 +18940,6 @@ imported by: • pandas.core.interchange.from_dataframe • pandas.core.interchange.utils • pandas.core.internals.api - • pandas.core.internals.array_manager - • pandas.core.internals.base • pandas.core.internals.blocks • pandas.core.internals.concat • pandas.core.internals.construction @@ -18980,7 +18961,6 @@ imported by: • pandas.core.reshape.pivot • pandas.core.reshape.reshape • pandas.core.reshape.tile - • pandas.core.reshape.util • pandas.core.sample • pandas.core.series • pandas.core.sorting @@ -30234,7 +30214,6 @@ imported by: • statistics • typing • typing_extensions - • wheel.vendored.packaging.markers
@@ -30440,6 +30419,7 @@ imported by: • pandas.io.common • pandas.io.excel._base • pandas.io.formats.csvs + • pandas.io.html • pandas.io.parquet • pandas.io.pytables • pandas.io.stata @@ -30547,12 +30527,7 @@ imported by: • websocket._handshake • websocket._http • websocket._url - • wheel.cli - • wheel.cli.tags • wheel.macosx_libfile - • wheel.vendored.packaging._elffile - • wheel.vendored.packaging._manylinux - • wheel.vendored.packaging.markers • win32_setctime._setctime • win32com • win32com.client.gencache @@ -30563,6 +30538,7 @@ imported by: • xml.sax.saxutils • zipfile • zipfile._path.glob + • zoneinfo._tzpath
@@ -30594,8 +30570,6 @@ imported by: • os • pkgutil • py_compile - • pytz - • pytz.tzfile • requests.adapters • setuptools._distutils._modified • setuptools._distutils.file_util @@ -30603,9 +30577,6 @@ imported by: • sysconfig • tracemalloc • unittest.util - • wheel.cli.convert - • wheel.cli.pack - • wheel.metadata • wheel.wheelfile
@@ -31009,6 +30980,7 @@ imports: • pandas • pandas._config • pandas._libs + • pandas._libs._cyutility • pandas._libs.algos • pandas._libs.arrays • pandas._libs.byteswap @@ -31061,6 +31033,7 @@ imports: • pandas.arrays • pandas.compat • pandas.core.api + • pandas.core.col • pandas.core.computation.api • pandas.core.config_init • pandas.core.dtypes.dtypes @@ -31076,7 +31049,6 @@ imports: • pandas.tseries.offsets • pandas.util._print_versions • pandas.util._tester - • warnings
@@ -31091,14 +31063,12 @@ imported by: • pandas._testing._io • pandas._testing.asserters • pandas._testing.compat - • pandas._testing.contexts • pandas._typing • pandas._version • pandas._version_meson • pandas.api • pandas.arrays • pandas.compat - • pandas.compat.pickle_compat • pandas.core • pandas.core.accessor • pandas.core.algorithms @@ -31122,6 +31092,7 @@ imported by: • pandas.core.arrays.string_arrow • pandas.core.arrays.timedeltas • pandas.core.base + • pandas.core.col • pandas.core.common • pandas.core.computation.align • pandas.core.computation.expr @@ -31140,6 +31111,7 @@ imported by: • pandas.core.indexes.base • pandas.core.indexes.datetimelike • pandas.core.indexes.multi + • pandas.core.indexes.range • pandas.core.indexing • pandas.core.interchange.column • pandas.core.interchange.dataframe @@ -31158,7 +31130,6 @@ imported by: • pandas.core.reshape.tile • pandas.core.sorting • pandas.core.strings.accessor - • pandas.core.strings.base • pandas.core.strings.object_array • pandas.core.tools.datetimes • pandas.core.tools.numeric @@ -31173,7 +31144,6 @@ imported by: • pandas.io._util • pandas.io.clipboards • pandas.io.common - • pandas.io.excel._calamine • pandas.io.excel._odfreader • pandas.io.formats.console • pandas.io.formats.excel @@ -31184,8 +31154,8 @@ imported by: • pandas.io.formats.style • pandas.io.formats.style_render • pandas.io.formats.xml - • pandas.io.gbq • pandas.io.html + • pandas.io.iceberg • pandas.io.json._json • pandas.io.json._normalize • pandas.io.json._table_schema @@ -31239,37 +31209,29 @@ imported by: • pandas._config.display • pandas._config.localization • pandas._testing - • pandas._testing.contexts - • pandas.core.apply + • pandas.core.arrays._utils + • pandas.core.arrays.arrow.array • pandas.core.arrays.categorical • pandas.core.arrays.datetimelike • pandas.core.arrays.datetimes + • pandas.core.arrays.masked + • pandas.core.arrays.numeric • pandas.core.arrays.string_ - • pandas.core.base • pandas.core.computation.common • pandas.core.computation.expressions • pandas.core.construction • pandas.core.dtypes.cast • pandas.core.dtypes.common - • pandas.core.dtypes.missing • pandas.core.frame • pandas.core.generic - • pandas.core.groupby.groupby - • pandas.core.groupby.grouper • pandas.core.indexes.base - • pandas.core.indexes.datetimelike • pandas.core.indexes.multi - • pandas.core.indexing + • pandas.core.interchange.column • pandas.core.interchange.from_dataframe - • pandas.core.internals.base - • pandas.core.internals.blocks • pandas.core.internals.construction - • pandas.core.internals.managers + • pandas.core.missing • pandas.core.nanops - • pandas.core.reshape.concat - • pandas.core.series • pandas.core.strings.accessor - • pandas.core.tools.datetimes • pandas.io._util • pandas.io.excel._base • pandas.io.feather_format @@ -31278,7 +31240,8 @@ imported by: • pandas.io.formats.printing • pandas.io.formats.style • pandas.io.formats.style_render - • pandas.io.parsers.readers + • pandas.io.json._json + • pandas.io.json._table_schema • pandas.io.pytables • pandas.io.sas.sas7bdat • pandas.io.sql @@ -31296,13 +31259,11 @@ imports: 'collections.abc' • __future__ • contextlib - • itertools • keyword • pandas._config • pandas._typing • pandas.util._exceptions • re - • textwrap • tokenize • typing • warnings @@ -31314,16 +31275,19 @@ imported by: • pandas._config.dates • pandas._config.display • pandas._config.localization + • pandas.core.arrays.datetimelike + • pandas.core.arrays.datetimes + • pandas.core.arrays.sparse.array + • pandas.core.computation.align • pandas.core.config_init - • pandas.core.frame + • pandas.core.dtypes.dtypes • pandas.core.generic - • pandas.core.groupby.groupby - • pandas.core.series + • pandas.core.internals.managers + • pandas.core.reshape.reshape • pandas.errors • pandas.io.excel._base • pandas.io.formats.console • pandas.io.formats.format - • pandas.io.parquet • pandas.io.pytables
@@ -31417,6 +31381,7 @@ imports:
imported by: pandas + • pandas._libs._cyutility • pandas._libs.algos • pandas._libs.arrays • pandas._libs.byteswap @@ -31451,7 +31416,6 @@ imported by: • pandas.core._numba.extensions • pandas.core.algorithms • pandas.core.api - • pandas.core.apply • pandas.core.array_algos.datetimelike_accumulations • pandas.core.array_algos.masked_reductions • pandas.core.array_algos.putmask @@ -31478,6 +31442,7 @@ imported by: • pandas.core.arrays.timedeltas • pandas.core.base • pandas.core.common + • pandas.core.computation.pytables • pandas.core.construction • pandas.core.dtypes.astype • pandas.core.dtypes.base @@ -31506,8 +31471,6 @@ imported by: • pandas.core.indexes.range • pandas.core.indexes.timedeltas • pandas.core.interchange.utils - • pandas.core.internals.array_manager - • pandas.core.internals.base • pandas.core.internals.blocks • pandas.core.internals.concat • pandas.core.internals.construction @@ -31519,6 +31482,7 @@ imported by: • pandas.core.ops.array_ops • pandas.core.ops.mask_ops • pandas.core.resample + • pandas.core.reshape.concat • pandas.core.reshape.encoding • pandas.core.reshape.merge • pandas.core.reshape.pivot @@ -31527,7 +31491,6 @@ imported by: • pandas.core.series • pandas.core.sorting • pandas.core.strings.accessor - • pandas.core.strings.base • pandas.core.strings.object_array • pandas.core.tools.datetimes • pandas.core.tools.numeric @@ -31562,6 +31525,21 @@ imported by:
+
+ + pandas._libs._cyutility C:\Users\27942\.conda\envs\haha\Lib\site-packages\pandas\_libs\_cyutility.cp313-win_amd64.pyd
+imports: + pandas._libs + +
+
+imported by: + pandas + +
+ +
+
pandas._libs.algos C:\Users\27942\.conda\envs\haha\Lib\site-packages\pandas\_libs\algos.cp313-win_amd64.pyd
@@ -31581,15 +31559,16 @@ imported by: • pandas.core.arrays.base • pandas.core.arrays.categorical • pandas.core.arrays.datetimelike + • pandas.core.arrays.masked • pandas.core.arrays.period • pandas.core.dtypes.common • pandas.core.frame • pandas.core.groupby.groupby + • pandas.core.groupby.grouper • pandas.core.indexes.base • pandas.core.indexes.multi - • pandas.core.indexes.range - • pandas.core.internals.base • pandas.core.internals.concat + • pandas.core.internals.managers • pandas.core.methods.selectn • pandas.core.missing • pandas.core.sorting @@ -31603,7 +31582,8 @@ imported by: pandas._libs.arrays C:\Users\27942\.conda\envs\haha\Lib\site-packages\pandas\_libs\arrays.cp313-win_amd64.pyd
imports: - numpy + 'collections.abc' + • numpy • pandas._libs • pandas._typing • typing @@ -31615,7 +31595,6 @@ imported by: • pandas.compat.pickle_compat • pandas.core.arrays._mixins • pandas.core.arrays.categorical - • pandas.core.arrays.datetimelike • pandas.core.arrays.period • pandas.core.arrays.string_ @@ -31681,7 +31660,8 @@ imported by: pandas._libs.hashtable C:\Users\27942\.conda\envs\haha\Lib\site-packages\pandas\_libs\hashtable.cp313-win_amd64.pyd
imports: - numpy + 'collections.abc' + • numpy • pandas._libs • pandas._typing • typing @@ -31751,7 +31731,8 @@ imported by: pandas._libs.internals C:\Users\27942\.conda\envs\haha\Lib\site-packages\pandas\_libs\internals.cp313-win_amd64.pyd
imports: - numpy + 'collections.abc' + • numpy • pandas • pandas._libs • pandas._typing @@ -31792,7 +31773,6 @@ imports: imported by: pandas • pandas._libs - • pandas._libs.lib • pandas.core.arrays.interval • pandas.core.dtypes.dtypes • pandas.core.indexes.interval @@ -31825,7 +31805,8 @@ imported by: pandas._libs.json C:\Users\27942\.conda\envs\haha\Lib\site-packages\pandas\_libs\json.cp313-win_amd64.pyd
imports: - pandas._libs + 'collections.abc' + • pandas._libs • typing
@@ -31843,12 +31824,11 @@ imported by: pandas._libs.lib C:\Users\27942\.conda\envs\haha\Lib\site-packages\pandas\_libs\lib.cp313-win_amd64.pyd
imports: - decimal + 'collections.abc' + • decimal • enum • numpy • pandas._libs - • pandas._libs.interval - • pandas._libs.tslibs • pandas._typing • typing @@ -31860,10 +31840,10 @@ imported by: • pandas._testing.asserters • pandas.api.extensions • pandas.api.types + • pandas.api.typing • pandas.compat.numpy.function • pandas.core._numba.extensions • pandas.core.algorithms - • pandas.core.apply • pandas.core.array_algos.putmask • pandas.core.array_algos.take • pandas.core.arraylike @@ -31889,6 +31869,7 @@ imported by: • pandas.core.arrays.timedeltas • pandas.core.base • pandas.core.common + • pandas.core.computation.pytables • pandas.core.construction • pandas.core.dtypes.astype • pandas.core.dtypes.cast @@ -31899,9 +31880,7 @@ imported by: • pandas.core.dtypes.missing • pandas.core.frame • pandas.core.generic - • pandas.core.groupby.generic • pandas.core.groupby.groupby - • pandas.core.groupby.grouper • pandas.core.groupby.ops • pandas.core.indexers.utils • pandas.core.indexes.accessors @@ -31916,8 +31895,6 @@ imported by: • pandas.core.indexing • pandas.core.interchange.column • pandas.core.interchange.utils - • pandas.core.internals.array_manager - • pandas.core.internals.base • pandas.core.internals.blocks • pandas.core.internals.concat • pandas.core.internals.construction @@ -31929,6 +31906,7 @@ imported by: • pandas.core.ops.common • pandas.core.ops.mask_ops • pandas.core.resample + • pandas.core.reshape.concat • pandas.core.reshape.merge • pandas.core.reshape.pivot • pandas.core.reshape.tile @@ -31936,7 +31914,6 @@ imported by: • pandas.core.series • pandas.core.sorting • pandas.core.strings.accessor - • pandas.core.strings.base • pandas.core.strings.object_array • pandas.core.tools.datetimes • pandas.core.tools.numeric @@ -31987,8 +31964,12 @@ imported by: • pandas._libs • pandas._testing.asserters • pandas.api.typing + • pandas.core.algorithms • pandas.core.api • pandas.core.array_algos.masked_reductions + • pandas.core.arrays._utils + • pandas.core.arrays.arrow.array + • pandas.core.arrays.base • pandas.core.arrays.boolean • pandas.core.arrays.interval • pandas.core.arrays.masked @@ -32009,6 +31990,7 @@ imported by: • pandas.core.strings.object_array • pandas.core.tools.numeric • pandas.io.formats.format + • pandas.util._validators
@@ -32018,7 +32000,8 @@ imported by: pandas._libs.ops C:\Users\27942\.conda\envs\haha\Lib\site-packages\pandas\_libs\ops.cp313-win_amd64.pyd
imports: - numpy + 'collections.abc' + • numpy • pandas._libs • pandas._typing • typing @@ -32089,7 +32072,8 @@ imported by: pandas._libs.parsers C:\Users\27942\.conda\envs\haha\Lib\site-packages\pandas\_libs\parsers.cp313-win_amd64.pyd
imports: - numpy + 'collections.abc' + • numpy • pandas._libs • pandas._typing • typing @@ -32098,7 +32082,6 @@ imports:
imported by: pandas - • pandas.io.excel._base • pandas.io.parsers.base_parser • pandas.io.parsers.c_parser_wrapper • pandas.io.parsers.readers @@ -32111,7 +32094,8 @@ imported by: pandas._libs.properties C:\Users\27942\.conda\envs\haha\Lib\site-packages\pandas\_libs\properties.cp313-win_amd64.pyd
imports: - pandas._libs + 'collections.abc' + • pandas._libs • pandas._typing • typing @@ -32192,7 +32176,8 @@ imported by: pandas._libs.testing C:\Users\27942\.conda\envs\haha\Lib\site-packages\pandas\_libs\testing.cp313-win_amd64.pyd
imports: - pandas._libs + 'collections.abc' + • pandas._libs
@@ -32251,7 +32236,6 @@ imports: imported by: pandas • pandas._libs - • pandas._libs.lib • pandas._libs.tslibs • pandas._libs.tslibs.base • pandas._libs.tslibs.ccalendar @@ -32290,6 +32274,7 @@ imported by: • pandas.core.dtypes.dtypes • pandas.core.dtypes.missing • pandas.core.generic + • pandas.core.groupby.groupby • pandas.core.groupby.grouper • pandas.core.indexers.objects • pandas.core.indexes.base @@ -32300,10 +32285,10 @@ imported by: • pandas.core.indexes.timedeltas • pandas.core.interchange.column • pandas.core.internals.managers - • pandas.core.methods.describe • pandas.core.ops.array_ops • pandas.core.resample • pandas.core.tools.datetimes + • pandas.core.tools.numeric • pandas.core.tools.timedeltas • pandas.core.window.ewm • pandas.core.window.rolling @@ -32311,7 +32296,6 @@ imported by: • pandas.io.formats.format • pandas.io.json._json • pandas.io.json._table_schema - • pandas.io.parsers.base_parser • pandas.io.pytables • pandas.tseries.frequencies @@ -32378,6 +32362,7 @@ imported by: imports: enum • pandas._libs.tslibs + • typing
@@ -32389,12 +32374,10 @@ imported by: • pandas.core.arrays.datetimes • pandas.core.arrays.period • pandas.core.dtypes.dtypes - • pandas.core.generic • pandas.core.indexes.datetimelike • pandas.core.indexes.datetimes • pandas.core.indexes.period - • pandas.core.resample - • pandas.io.json._table_schema + • pandas.core.indexes.timedeltas • pandas.tseries.frequencies
@@ -32474,11 +32457,11 @@ imported by: pandas._libs.tslibs.offsets C:\Users\27942\.conda\envs\haha\Lib\site-packages\pandas\_libs\tslibs\offsets.cp313-win_amd64.pyd
imports: - datetime + 'collections.abc' + • datetime • numpy • pandas._libs.tslibs • pandas._libs.tslibs.nattype - • pandas._libs.tslibs.timedeltas • pandas._typing • typing @@ -32492,6 +32475,7 @@ imported by: • pandas.core.dtypes.dtypes • pandas.core.indexes.datetimes • pandas.tseries.frequencies + • pandas.tseries.holiday • pandas.tseries.offsets
@@ -32515,7 +32499,6 @@ imported by: • pandas.core.arrays.period • pandas.core.indexes.datetimelike • pandas.core.tools.datetimes - • pandas.io.parsers.base_parser • pandas.tseries.api • pandas.tseries.frequencies @@ -32582,12 +32565,11 @@ imports: imported by: pandas • pandas._libs.tslibs - • pandas._libs.tslibs.offsets • pandas.core.arrays.datetimelike • pandas.core.arrays.timedeltas • pandas.core.dtypes.astype • pandas.core.dtypes.cast - • pandas.core.indexes.timedeltas + • pandas.core.groupby.groupby • pandas.core.tools.datetimes • pandas.core.tools.timedeltas @@ -32622,10 +32604,10 @@ imported by: pandas._libs.tslibs.timezones C:\Users\27942\.conda\envs\haha\Lib\site-packages\pandas\_libs\tslibs\timezones.cp313-win_amd64.pyd
imports: - datetime + 'collections.abc' + • datetime • numpy • pandas._libs.tslibs - • typing
@@ -32633,6 +32615,7 @@ imported by: pandas • pandas._libs.tslibs • pandas.core.arrays.arrow.array + • pandas.core.arrays.datetimelike • pandas.core.arrays.datetimes • pandas.core.dtypes.dtypes • pandas.core.indexes.datetimes @@ -32648,11 +32631,11 @@ imported by: pandas._libs.tslibs.tzconversion C:\Users\27942\.conda\envs\haha\Lib\site-packages\pandas\_libs\tslibs\tzconversion.cp313-win_amd64.pyd
imports: - datetime + 'collections.abc' + • datetime • numpy • pandas._libs.tslibs • pandas._typing - • typing
@@ -32707,7 +32690,8 @@ imported by: pandas._libs.window.aggregations C:\Users\27942\.conda\envs\haha\Lib\site-packages\pandas\_libs\window\aggregations.cp313-win_amd64.pyd
imports: - numpy + 'collections.abc' + • numpy • pandas._libs.window • pandas._typing • typing @@ -32769,7 +32753,8 @@ imported by: pandas._testing Package
imports: - __future__ + 'collections.abc' + • __future__ • decimal • numpy • operator @@ -32791,7 +32776,6 @@ imports: • pytest • sys • typing - • warnings
@@ -32812,20 +32796,18 @@ imported by: pandas._testing._io SourceModule
imports: - __future__ + 'collections.abc' + • __future__ + • bz2 • gzip • io + • lzma • pandas • pandas._testing - • pandas._testing.contexts - • pandas._typing - • pandas.compat • pandas.compat._optional • pathlib - • pytest • tarfile • typing - • uuid • zipfile
@@ -32847,7 +32829,6 @@ imports: • contextlib • inspect • pandas._testing - • pandas.compat • re • sys • typing @@ -32867,9 +32848,7 @@ imported by: pandas._testing.asserters SourceModule
imports: - 'matplotlib.artist' - • 'matplotlib.axes' - • __future__ + __future__ • numpy • operator • pandas @@ -32888,8 +32867,11 @@ imports: • pandas.core.dtypes.dtypes • pandas.core.dtypes.missing • pandas.core.indexes.api + • pandas.errors • pandas.io.formats.printing + • pandas.util._decorators • typing + • warnings
@@ -32930,26 +32912,19 @@ imports: • contextlib • csv • os - • pandas - • pandas._config • pandas._testing • pandas._typing • pandas.compat - • pandas.core.computation - • pandas.core.computation.expressions • pandas.errors • pandas.io.common - • pathlib - • tempfile + • sys • time • typing - • uuid
imported by: pandas._testing - • pandas._testing._io
@@ -32962,6 +32937,7 @@ imported by: imports: 'collections.abc' • __future__ + • builtins • datetime • numpy • numpy.typing @@ -32982,9 +32958,7 @@ imports: • pandas.core.window.rolling • pandas.io.formats.format • pandas.tseries.holiday - • sys • typing - • typing_extensions
@@ -33021,7 +32995,6 @@ imported by: • pandas._libs.window.indexers • pandas._libs.writers • pandas._testing - • pandas._testing._io • pandas._testing.asserters • pandas._testing.compat • pandas._testing.contexts @@ -33032,6 +33005,7 @@ imported by: • pandas.core._numba.kernels.min_max_ • pandas.core._numba.kernels.sum_ • pandas.core._numba.kernels.var_ + • pandas.core.accessor • pandas.core.algorithms • pandas.core.apply • pandas.core.array_algos.masked_accumulations @@ -33074,7 +33048,6 @@ imported by: • pandas.core.dtypes.common • pandas.core.dtypes.concat • pandas.core.dtypes.dtypes - • pandas.core.dtypes.inference • pandas.core.dtypes.missing • pandas.core.frame • pandas.core.generic @@ -33091,7 +33064,6 @@ imported by: • pandas.core.indexes.datetimelike • pandas.core.indexes.datetimes • pandas.core.indexes.extension - • pandas.core.indexes.frozen • pandas.core.indexes.interval • pandas.core.indexes.multi • pandas.core.indexes.period @@ -33100,8 +33072,6 @@ imported by: • pandas.core.indexing • pandas.core.interchange.utils • pandas.core.internals.api - • pandas.core.internals.array_manager - • pandas.core.internals.base • pandas.core.internals.blocks • pandas.core.internals.concat • pandas.core.internals.construction @@ -33116,6 +33086,7 @@ imported by: • pandas.core.ops.common • pandas.core.ops.dispatch • pandas.core.ops.invalid + • pandas.core.ops.mask_ops • pandas.core.resample • pandas.core.reshape.concat • pandas.core.reshape.encoding @@ -33124,12 +33095,10 @@ imported by: • pandas.core.reshape.pivot • pandas.core.reshape.reshape • pandas.core.reshape.tile - • pandas.core.reshape.util • pandas.core.sample • pandas.core.series • pandas.core.sorting • pandas.core.strings.accessor - • pandas.core.strings.base • pandas.core.strings.object_array • pandas.core.tools.datetimes • pandas.core.tools.numeric @@ -33156,6 +33125,7 @@ imported by: • pandas.io.formats.excel • pandas.io.formats.format • pandas.io.formats.info + • pandas.io.formats.printing • pandas.io.formats.style • pandas.io.formats.style_render • pandas.io.formats.xml @@ -33193,14 +33163,14 @@ imported by: pandas._version SourceModule
imports: - errno + 'collections.abc' + • errno • functools • os • pandas • re • subprocess • sys - • typing
@@ -33236,6 +33206,7 @@ imported by: imports: pandas • pandas.api + • pandas.api.executors • pandas.api.extensions • pandas.api.indexers • pandas.api.interchange @@ -33247,6 +33218,7 @@ imports: imported by: pandas • pandas.api + • pandas.api.executors • pandas.api.extensions • pandas.api.indexers • pandas.api.interchange @@ -33257,6 +33229,23 @@ imported by:
+
+ + pandas.api.executors +Package
+imports: + pandas.api + • pandas.core.apply + +
+
+imported by: + pandas.api + +
+ +
+
pandas.api.extensions @@ -33343,12 +33332,16 @@ imported by: Package
imports: pandas._libs + • pandas._libs.lib • pandas._libs.missing • pandas.api + • pandas.core.col • pandas.core.groupby + • pandas.core.indexes.frozen • pandas.core.resample • pandas.core.window • pandas.io.json._json + • pandas.io.sas.sasreader • pandas.io.stata
@@ -33367,8 +33360,6 @@ imported by: imports: pandas • pandas.core.arrays - • pandas.util._exceptions - • warnings
@@ -33376,6 +33367,7 @@ imported by: pandas • pandas._typing • pandas.core.arrays.masked + • pandas.core.arrays.numpy_ • pandas.core.arrays.string_ • pandas.core.tools.datetimes @@ -33393,7 +33385,6 @@ imports: • pandas • pandas._typing • pandas.compat._constants - • pandas.compat.compressors • pandas.compat.numpy • pandas.compat.pyarrow • platform @@ -33405,12 +33396,9 @@ imports: imported by: pandas • pandas._testing - • pandas._testing._io - • pandas._testing._warnings • pandas._testing.contexts • pandas.compat._constants • pandas.compat._optional - • pandas.compat.compressors • pandas.compat.numpy • pandas.compat.pickle_compat • pandas.compat.pyarrow @@ -33428,9 +33416,7 @@ imported by: • pandas.core.generic • pandas.core.indexing • pandas.core.series - • pandas.core.strings.accessor • pandas.io._util - • pandas.io.common • pandas.io.pickle • pandas.io.pytables @@ -33453,7 +33439,6 @@ imports:
imported by: pandas.compat - • pandas.compat.compressors • pandas.core.frame • pandas.core.generic • pandas.core.indexing @@ -33509,8 +33494,8 @@ imported by: • pandas.io.feather_format • pandas.io.formats.style • pandas.io.formats.style_render - • pandas.io.gbq • pandas.io.html + • pandas.io.iceberg • pandas.io.json._json • pandas.io.orc • pandas.io.parquet @@ -33528,27 +33513,6 @@ imported by:
-
- - pandas.compat.compressors -SourceModule
-imports: - __future__ - • bz2 - • lzma - • pandas.compat - • pandas.compat._constants - • pickle - -
-
-imported by: - pandas.compat - -
- -
-
pandas.compat.numpy @@ -33575,7 +33539,6 @@ imported by: • pandas.core.arrays.string_ • pandas.core.arrays.timedeltas • pandas.core.base - • pandas.core.common • pandas.core.frame • pandas.core.generic • pandas.core.groupby.groupby @@ -33583,7 +33546,6 @@ imported by: • pandas.core.indexes.datetimelike • pandas.core.indexes.multi • pandas.core.indexes.range - • pandas.core.resample • pandas.core.series
@@ -33625,7 +33587,6 @@ imported by: • pandas.core.indexes.datetimelike • pandas.core.indexes.multi • pandas.core.indexes.range - • pandas.core.resample • pandas.core.series
@@ -33640,10 +33601,8 @@ imports: 'collections.abc' • __future__ • contextlib - • copy • io • numpy - • pandas • pandas._libs.arrays • pandas._libs.tslibs • pandas.compat @@ -33718,6 +33677,7 @@ imported by: • pandas.core.arrays.string_ • pandas.core.arrays.timedeltas • pandas.core.base + • pandas.core.col • pandas.core.common • pandas.core.computation • pandas.core.computation.expressions @@ -33761,6 +33721,7 @@ imported by: • pandas.core.window • pandas.core.window.ewm • pandas.io.parsers.base_parser + • pandas.io.parsers.python_parser
@@ -33791,13 +33752,15 @@ imported by: pandas.core._numba.executor SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • functools • numba • numpy • pandas._typing • pandas.compat._optional • pandas.core._numba + • pandas.core.util.numba_ • typing
@@ -33830,6 +33793,7 @@ imports: • pandas.core.indexing • pandas.core.internals • pandas.core.series + • typing
@@ -33983,9 +33947,13 @@ imported by: pandas.core.accessor SourceModule
imports: - __future__ + 'collections.abc' + • __future__ + • functools • pandas + • pandas._typing • pandas.core + • pandas.core.generic • pandas.util._decorators • pandas.util._exceptions • typing @@ -34021,6 +33989,7 @@ imports: • pandas._libs.algos • pandas._libs.hashtable • pandas._libs.lib + • pandas._libs.missing • pandas._typing • pandas.core • pandas.core.array_algos.take @@ -34038,7 +34007,6 @@ imports: • pandas.core.sorting • pandas.util._decorators • pandas.util._exceptions - • textwrap • typing • warnings @@ -34072,7 +34040,6 @@ imported by: • pandas.core.indexes.interval • pandas.core.indexes.multi • pandas.core.indexing - • pandas.core.internals.array_manager • pandas.core.internals.blocks • pandas.core.internals.construction • pandas.core.internals.managers @@ -34085,6 +34052,7 @@ imported by: • pandas.core.tools.datetimes • pandas.core.window.rolling • pandas.io.parsers.base_parser + • pandas.io.parsers.python_parser • pandas.tseries.frequencies
@@ -34130,7 +34098,6 @@ imported by: pandas • pandas.core.indexes.datetimes • pandas.core.internals.blocks - • pandas.core.methods.selectn • pandas.io.feather_format • pandas.io.sql • pandas.tseries.frequencies @@ -34152,10 +34119,7 @@ imports: • inspect • numpy • pandas - • pandas._config - • pandas._libs • pandas._libs.internals - • pandas._libs.lib • pandas._typing • pandas.compat._optional • pandas.core @@ -34172,19 +34136,18 @@ imports: • pandas.core.indexes.base • pandas.core.resample • pandas.core.reshape.concat + • pandas.core.util.numba_ • pandas.core.window.rolling • pandas.errors • pandas.util._decorators - • pandas.util._exceptions • typing - • warnings
imported by: - pandas.core.frame + pandas.api.executors + • pandas.core.frame • pandas.core.groupby.generic - • pandas.core.groupby.groupby • pandas.core.resample • pandas.core.series • pandas.core.window.rolling @@ -34229,7 +34192,8 @@ imported by: pandas.core.array_algos.datetimelike_accumulations SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • numpy • pandas._libs • pandas.core.array_algos @@ -34252,7 +34216,8 @@ imported by: pandas.core.array_algos.masked_accumulations SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • numpy • pandas._typing • pandas.core.array_algos @@ -34274,7 +34239,8 @@ imported by: pandas.core.array_algos.masked_reductions SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • numpy • pandas._libs • pandas._libs.missing @@ -34341,7 +34307,6 @@ imported by: pandas.core.arrays._mixins • pandas.core.arrays.base • pandas.core.arrays.masked - • pandas.core.internals.array_manager • pandas.core.internals.blocks
@@ -34399,7 +34364,6 @@ imports: imported by: pandas.core.algorithms • pandas.core.frame - • pandas.core.internals.array_manager
@@ -34420,6 +34384,7 @@ imports:
imported by: pandas.core.arrays._mixins + • pandas.core.arrays.masked • pandas.core.internals.blocks
@@ -34439,6 +34404,7 @@ imports: • pandas._libs.ops_dispatch • pandas.core • pandas.core.construction + • pandas.core.dtypes.cast • pandas.core.dtypes.generic • pandas.core.frame • pandas.core.generic @@ -34536,13 +34502,13 @@ imported by: • pandas.core.generic • pandas.core.groupby.groupby • pandas.core.groupby.grouper + • pandas.core.groupby.ops • pandas.core.indexes.accessors • pandas.core.indexes.base • pandas.core.indexes.datetimelike • pandas.core.indexes.extension • pandas.core.indexes.multi • pandas.core.internals.api - • pandas.core.internals.array_manager • pandas.core.internals.blocks • pandas.core.internals.construction • pandas.core.internals.managers @@ -34559,6 +34525,7 @@ imported by: • pandas.core.window.rolling • pandas.io.formats.format • pandas.io.parsers.base_parser + • pandas.io.parsers.python_parser • pandas.io.pytables • pandas.io.sql @@ -34584,6 +34551,7 @@ imports: • pandas.core.arrays • pyarrow • re + • re._parser • typing
@@ -34641,6 +34609,7 @@ imported by: • pandas.core.indexes.extension • pandas.core.internals.blocks • pandas.core.internals.managers + • pandas.core.reshape.reshape
@@ -34657,6 +34626,7 @@ imports: • pandas._libs.tslibs • pandas._typing • pandas.core.arrays + • pandas.core.construction • typing
@@ -34676,10 +34646,13 @@ imported by: imports: __future__ • numpy + • pandas._config • pandas._libs • pandas._libs.lib + • pandas._libs.missing • pandas._typing • pandas.core.arrays + • pandas.core.arrays.base • pandas.core.dtypes.cast • pandas.core.dtypes.common • pandas.errors @@ -34774,12 +34747,15 @@ imports: 'collections.abc' • 'pyarrow.compute' • __future__ + • datetime • functools • numpy • operator • pandas + • pandas._config • pandas._libs • pandas._libs.lib + • pandas._libs.missing • pandas._libs.tslibs • pandas._libs.tslibs.timezones • pandas._typing @@ -34796,6 +34772,7 @@ imports: • pandas.core.arrays.string_ • pandas.core.arrays.timedeltas • pandas.core.common + • pandas.core.construction • pandas.core.dtypes.cast • pandas.core.dtypes.common • pandas.core.dtypes.dtypes @@ -34805,16 +34782,15 @@ imports: • pandas.core.nanops • pandas.core.ops • pandas.core.roperator - • pandas.core.strings.base • pandas.core.tools.datetimes • pandas.core.tools.numeric • pandas.core.tools.timedeltas • pandas.core.tools.times + • pandas.errors • pandas.io._util • pandas.tseries.frequencies • pandas.util._decorators • pandas.util._exceptions - • pandas.util._validators • pathlib • pyarrow • re @@ -34879,6 +34855,7 @@ imports: • pandas._libs • pandas._libs.algos • pandas._libs.lib + • pandas._libs.missing • pandas._typing • pandas.compat • pandas.compat.numpy @@ -34889,7 +34866,7 @@ imports: • pandas.core.arraylike • pandas.core.arrays • pandas.core.arrays.string_ - • pandas.core.dtypes.cast + • pandas.core.dtypes.astype • pandas.core.dtypes.common • pandas.core.dtypes.dtypes • pandas.core.dtypes.generic @@ -34914,13 +34891,13 @@ imported by: • pandas.core.array_algos.take • pandas.core.arrays • pandas.core.arrays._mixins + • pandas.core.arrays._utils • pandas.core.arrays.arrow.array • pandas.core.arrays.datetimelike • pandas.core.arrays.interval • pandas.core.arrays.masked • pandas.core.arrays.period • pandas.core.arrays.string_ - • pandas.core.construction • pandas.core.tools.datetimes
@@ -34948,6 +34925,7 @@ imports: • pandas.core.dtypes.dtypes • pandas.core.dtypes.missing • pandas.core.ops + • pandas.util._decorators • pyarrow • typing @@ -34958,7 +34936,7 @@ imported by: • pandas.core.arrays • pandas.core.arrays.string_arrow • pandas.core.dtypes.dtypes - • pandas.io.parsers.base_parser + • pandas.io.parsers.python_parser
@@ -34973,6 +34951,7 @@ imports: • __future__ • csv • functools + • itertools • numpy • operator • pandas @@ -35000,15 +34979,18 @@ imports: • pandas.core.dtypes.generic • pandas.core.dtypes.missing • pandas.core.groupby.ops + • pandas.core.indexes.range • pandas.core.ops • pandas.core.ops.common • pandas.core.reshape.concat • pandas.core.sorting • pandas.core.strings.object_array • pandas.core.util.hashing + • pandas.errors • pandas.io.formats • pandas.io.formats.console • pandas.io.formats.format + • pandas.util._decorators • pandas.util._exceptions • pandas.util._validators • shutil @@ -35045,15 +35027,16 @@ imports: • operator • pandas • pandas._config + • pandas._config.config • pandas._libs • pandas._libs.algos - • pandas._libs.arrays • pandas._libs.lib • pandas._libs.tslibs • pandas._libs.tslibs.fields • pandas._libs.tslibs.np_datetime • pandas._libs.tslibs.timedeltas • pandas._libs.tslibs.timestamps + • pandas._libs.tslibs.timezones • pandas._typing • pandas.compat.numpy • pandas.compat.numpy.function @@ -35099,7 +35082,6 @@ imported by: • pandas.core.arrays.datetimes • pandas.core.arrays.period • pandas.core.arrays.timedeltas - • pandas.core.indexes.datetimelike • pandas.core.indexes.interval • pandas.core.reshape.tile • pandas.core.window.ewm @@ -35121,6 +35103,7 @@ imports: • numpy • pandas • pandas._config + • pandas._config.config • pandas._libs • pandas._libs.lib • pandas._libs.tslib @@ -35140,6 +35123,7 @@ imports: • pandas.errors • pandas.tseries.frequencies • pandas.tseries.offsets + • pandas.util._decorators • pandas.util._exceptions • pandas.util._validators • typing @@ -35155,6 +35139,7 @@ imported by: • pandas.core.dtypes.cast • pandas.core.indexes.datetimes • pandas.core.tools.datetimes + • pandas.io.pytables
@@ -35165,12 +35150,14 @@ imported by: pandas.core.arrays.floating SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • numpy • pandas.core.arrays • pandas.core.arrays.numeric • pandas.core.dtypes.base • pandas.core.dtypes.common + • pandas.util._decorators • typing
@@ -35182,6 +35169,7 @@ imported by: • pandas.core.arrays.string_arrow • pandas.core.dtypes.cast • pandas.core.dtypes.dtypes + • pandas.core.indexes.base • pandas.core.methods.describe
@@ -35193,12 +35181,14 @@ imported by: pandas.core.arrays.integer SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • numpy • pandas.core.arrays • pandas.core.arrays.numeric • pandas.core.dtypes.base • pandas.core.dtypes.common + • pandas.util._decorators • typing
@@ -35251,11 +35241,9 @@ imports: • pandas.core.ops • pandas.errors • pandas.util._decorators - • pandas.util._exceptions • pyarrow • textwrap • typing - • warnings
@@ -35277,7 +35265,9 @@ imports: • __future__ • numpy • pandas + • pandas._config • pandas._libs + • pandas._libs.algos • pandas._libs.lib • pandas._libs.missing • pandas._libs.tslibs @@ -35292,12 +35282,15 @@ imports: • pandas.core.array_algos.masked_accumulations • pandas.core.array_algos.masked_reductions • pandas.core.array_algos.quantile + • pandas.core.array_algos.transforms • pandas.core.arraylike • pandas.core.arrays • pandas.core.arrays._utils • pandas.core.arrays.base • pandas.core.construction + • pandas.core.dtypes.astype • pandas.core.dtypes.base + • pandas.core.dtypes.cast • pandas.core.dtypes.common • pandas.core.dtypes.dtypes • pandas.core.dtypes.missing @@ -35308,9 +35301,6 @@ imports: • pandas.core.ops • pandas.core.util.hashing • pandas.errors - • pandas.util._decorators - • pandas.util._exceptions - • pandas.util._validators • pyarrow • typing • warnings @@ -35339,6 +35329,7 @@ imports: • __future__ • numbers • numpy + • pandas._config • pandas._libs • pandas._libs.lib • pandas._libs.missing @@ -35347,6 +35338,7 @@ imports: • pandas.core.arrays.arrow._arrow_utils • pandas.core.arrays.masked • pandas.core.dtypes.common + • pandas.core.dtypes.dtypes • pandas.core.tools.numeric • pandas.errors • pandas.util._decorators @@ -35377,6 +35369,7 @@ imports: • pandas._libs.lib • pandas._libs.tslibs • pandas._typing + • pandas.arrays • pandas.compat.numpy • pandas.compat.numpy.function • pandas.core @@ -35393,6 +35386,7 @@ imports: • pandas.core.nanops • pandas.core.ops • pandas.core.strings.object_array + • pandas.util._decorators • typing
@@ -35437,7 +35431,6 @@ imports: • pandas.core.dtypes.generic • pandas.core.dtypes.missing • pandas.util._decorators - • pandas.util._exceptions • pyarrow • typing • warnings @@ -35514,11 +35507,11 @@ imports: • 'scipy.sparse' • __future__ • collections - • enum • numbers • numpy • operator • pandas + • pandas._config.config • pandas._libs • pandas._libs.lib • pandas._libs.sparse @@ -35548,6 +35541,7 @@ imports: • pandas.util._decorators • pandas.util._exceptions • pandas.util._validators + • types • typing • warnings @@ -35597,6 +35591,7 @@ imported by: SourceModule
imports: 'collections.abc' + • 'pyarrow.compute' • __future__ • functools • numpy @@ -35631,6 +35626,7 @@ imports: • pandas.core.nanops • pandas.core.ops • pandas.core.roperator + • pandas.errors • pandas.io.formats • pandas.io.formats.printing • pandas.util._decorators @@ -35659,11 +35655,9 @@ imported by: • pandas.core.internals.construction • pandas.core.reshape.encoding • pandas.core.reshape.merge - • pandas.core.series • pandas.core.strings.accessor • pandas.core.strings.object_array • pandas.core.tools.numeric - • pandas.io.formats.format • pandas.io.pytables • pandas.io.sql @@ -35697,13 +35691,14 @@ imports: • pandas.core.arrays.numeric • pandas.core.arrays.string_ • pandas.core.dtypes.common + • pandas.core.dtypes.dtypes • pandas.core.dtypes.missing • pandas.core.strings.object_array - • pandas.util._exceptions + • pandas.util._decorators + • pandas.util._validators • pyarrow • re • typing - • warnings
@@ -35750,6 +35745,7 @@ imports: • pandas.core.ops.common • pandas.core.roperator • pandas.io.formats.format + • pandas.util._decorators • pandas.util._validators • textwrap • typing @@ -35777,7 +35773,6 @@ imports: • __future__ • numpy • pandas - • pandas._config • pandas._libs • pandas._libs.lib • pandas._typing @@ -35799,10 +35794,7 @@ imports: • pandas.core.ops • pandas.errors • pandas.util._decorators - • pandas.util._exceptions - • textwrap • typing - • warnings
@@ -35815,8 +35807,8 @@ imported by: • pandas.core.indexes.accessors • pandas.core.indexes.base • pandas.core.indexes.frozen - • pandas.core.internals.base • pandas.core.internals.blocks + • pandas.core.internals.managers • pandas.core.resample • pandas.core.series • pandas.core.strings.accessor @@ -35829,6 +35821,30 @@ imported by:
+
+ + pandas.core.col +SourceModule
+imports: + 'collections.abc' + • __future__ + • pandas + • pandas.core + • pandas.util._decorators + • typing + +
+
+imported by: + pandas + • pandas.api.typing + • pandas.core.common + • pandas.core.reshape.tile + +
+ +
+
pandas.core.common @@ -35846,14 +35862,14 @@ imports: • pandas._libs • pandas._libs.lib • pandas._typing - • pandas.compat.numpy • pandas.core + • pandas.core.col • pandas.core.dtypes.cast • pandas.core.dtypes.common • pandas.core.dtypes.generic • pandas.core.dtypes.inference + • sys • typing - • warnings
@@ -35889,7 +35905,6 @@ imported by: • pandas.core.internals.blocks • pandas.core.internals.construction • pandas.core.methods.to_dict - • pandas.core.resample • pandas.core.reshape.concat • pandas.core.reshape.merge • pandas.core.reshape.pivot @@ -35920,8 +35935,7 @@ imports:
imported by: - pandas._testing.contexts - • pandas.core.computation.align + pandas.core.computation.align • pandas.core.computation.api • pandas.core.computation.check • pandas.core.computation.common @@ -35934,7 +35948,6 @@ imported by: • pandas.core.computation.pytables • pandas.core.computation.scope • pandas.core.config_init - • pandas.core.frame • pandas.core.internals.blocks • pandas.core.ops.array_ops @@ -35952,6 +35965,7 @@ imports: • functools • numpy • pandas + • pandas._config.config • pandas._typing • pandas.core.base • pandas.core.common @@ -36077,6 +36091,7 @@ imports: • pandas.core.dtypes.common • pandas.core.generic • pandas.io.formats.printing + • pandas.util._decorators • pandas.util._exceptions • pandas.util._validators • tokenize @@ -36099,7 +36114,8 @@ imported by: pandas.core.computation.expr SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • ast • functools • keyword @@ -36151,11 +36167,9 @@ imports:
imported by: - pandas._testing.contexts - • pandas.core.computation + pandas.core.computation • pandas.core.computation.eval • pandas.core.config_init - • pandas.core.frame • pandas.core.internals.blocks • pandas.core.ops.array_ops @@ -36203,6 +36217,7 @@ imported by: imports: 'collections.abc' • __future__ + • enum • io • keyword • pandas.core.computation @@ -36231,6 +36246,8 @@ imports: • decimal • functools • numpy + • pandas._libs + • pandas._libs.lib • pandas._libs.tslibs • pandas._typing • pandas.core.common @@ -36292,16 +36309,17 @@ imported by: pandas.core.config_init SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • os • pandas._config.config • pandas.core • pandas.core.computation • pandas.core.computation.expressions - • pandas.core.dtypes.missing • pandas.core.nanops • pandas.core.util • pandas.core.util.numba_ + • pandas.errors • pandas.io.formats.printing • pandas.plotting • pandas.plotting._core @@ -36333,7 +36351,6 @@ imports: • pandas._typing • pandas.core • pandas.core.arrays - • pandas.core.arrays.base • pandas.core.arrays.string_ • pandas.core.common • pandas.core.dtypes.base @@ -36342,9 +36359,8 @@ imports: • pandas.core.dtypes.dtypes • pandas.core.dtypes.generic • pandas.core.dtypes.missing - • pandas.util._exceptions + • pandas.util._decorators • typing - • warnings
@@ -36356,6 +36372,8 @@ imported by: • pandas.core.array_algos.take • pandas.core.arraylike • pandas.core.arrays._mixins + • pandas.core.arrays._ranges + • pandas.core.arrays.arrow.array • pandas.core.arrays.categorical • pandas.core.arrays.datetimelike • pandas.core.arrays.interval @@ -36377,13 +36395,12 @@ imported by: • pandas.core.indexes.range • pandas.core.indexing • pandas.core.internals.api - • pandas.core.internals.array_manager - • pandas.core.internals.base • pandas.core.internals.blocks • pandas.core.internals.concat • pandas.core.internals.construction • pandas.core.internals.managers • pandas.core.ops.array_ops + • pandas.core.ops.common • pandas.core.reshape.merge • pandas.core.reshape.reshape • pandas.core.series @@ -36463,17 +36480,18 @@ imports:
imported by: - pandas.core.arrays.numpy_ + pandas.core.arrays.base + • pandas.core.arrays.masked + • pandas.core.arrays.numpy_ • pandas.core.arrays.sparse.array • pandas.core.dtypes.concat • pandas.core.dtypes.dtypes • pandas.core.generic • pandas.core.indexes.base - • pandas.core.internals.array_manager • pandas.core.internals.blocks • pandas.core.internals.construction • pandas.core.series - • pandas.io.parsers.base_parser + • pandas.io.parsers.python_parser
@@ -36496,6 +36514,7 @@ imports: • pandas.core.dtypes • pandas.core.dtypes.generic • pandas.errors + • pandas.util._decorators • typing
@@ -36509,6 +36528,7 @@ imported by: • pandas.core.construction • pandas.core.dtypes.common • pandas.core.dtypes.dtypes + • pandas.core.indexes.range • pandas.core.reshape.merge • pandas.io.json._table_schema • pandas.io.stata @@ -36561,12 +36581,13 @@ imported by: • pandas.core.apply • pandas.core.array_algos.putmask • pandas.core.array_algos.take + • pandas.core.arraylike • pandas.core.arrays._utils • pandas.core.arrays.arrow.array - • pandas.core.arrays.base • pandas.core.arrays.categorical • pandas.core.arrays.datetimelike • pandas.core.arrays.interval + • pandas.core.arrays.masked • pandas.core.arrays.numpy_ • pandas.core.arrays.sparse.accessor • pandas.core.arrays.sparse.array @@ -36577,6 +36598,7 @@ imported by: • pandas.core.dtypes.concat • pandas.core.dtypes.dtypes • pandas.core.frame + • pandas.core.generic • pandas.core.groupby.groupby • pandas.core.groupby.ops • pandas.core.indexes.api @@ -36584,8 +36606,6 @@ imported by: • pandas.core.indexes.interval • pandas.core.indexes.multi • pandas.core.indexing - • pandas.core.internals.array_manager - • pandas.core.internals.base • pandas.core.internals.blocks • pandas.core.internals.concat • pandas.core.internals.construction @@ -36608,7 +36628,8 @@ imported by: pandas.core.dtypes.common SourceModule
imports: - 'scipy.sparse' + 'collections.abc' + • 'scipy.sparse' • __future__ • numpy • pandas._config @@ -36624,6 +36645,8 @@ imports: • pandas.core.dtypes.dtypes • pandas.core.dtypes.generic • pandas.core.dtypes.inference + • pandas.errors + • pandas.util._decorators • pandas.util._exceptions • typing • warnings @@ -36691,7 +36714,6 @@ imported by: • pandas.core.indexes.timedeltas • pandas.core.indexing • pandas.core.internals.api - • pandas.core.internals.array_manager • pandas.core.internals.blocks • pandas.core.internals.concat • pandas.core.internals.construction @@ -36709,16 +36731,17 @@ imported by: • pandas.core.reshape.pivot • pandas.core.reshape.reshape • pandas.core.reshape.tile - • pandas.core.reshape.util • pandas.core.series • pandas.core.sorting • pandas.core.strings.accessor + • pandas.core.strings.object_array • pandas.core.tools.datetimes • pandas.core.tools.numeric • pandas.core.tools.timedeltas • pandas.core.util.hashing • pandas.core.window.ewm • pandas.core.window.rolling + • pandas.io._util • pandas.io.common • pandas.io.excel._base • pandas.io.excel._util @@ -36766,9 +36789,8 @@ imports: • pandas.core.dtypes.cast • pandas.core.dtypes.dtypes • pandas.core.dtypes.generic - • pandas.util._exceptions + • pandas.util._decorators • typing - • warnings
@@ -36778,7 +36800,6 @@ imported by: • pandas.core.arrays.categorical • pandas.core.frame • pandas.core.indexes.base - • pandas.core.indexes.category • pandas.core.indexes.datetimelike • pandas.core.indexing • pandas.core.internals.concat @@ -36801,6 +36822,7 @@ imports: • decimal • numpy • pandas + • pandas._config.config • pandas._libs • pandas._libs.interval • pandas._libs.lib @@ -36831,13 +36853,13 @@ imports: • pandas.core.indexes.base • pandas.core.util.hashing • pandas.errors - • pandas.util + • pandas.util._decorators • pandas.util._exceptions • pyarrow - • pytz • re • typing • warnings + • zoneinfo
@@ -36860,10 +36882,12 @@ imported by: • pandas.core.arrays.datetimes • pandas.core.arrays.interval • pandas.core.arrays.masked + • pandas.core.arrays.numeric • pandas.core.arrays.numpy_ • pandas.core.arrays.period • pandas.core.arrays.sparse.accessor • pandas.core.arrays.sparse.array + • pandas.core.arrays.string_arrow • pandas.core.arrays.timedeltas • pandas.core.base • pandas.core.construction @@ -36885,12 +36909,11 @@ imported by: • pandas.core.indexes.interval • pandas.core.indexes.multi • pandas.core.indexes.period + • pandas.core.indexes.timedeltas • pandas.core.indexing • pandas.core.interchange.column • pandas.core.interchange.utils • pandas.core.internals.api - • pandas.core.internals.array_manager - • pandas.core.internals.base • pandas.core.internals.blocks • pandas.core.internals.concat • pandas.core.internals.construction @@ -36916,8 +36939,8 @@ imported by: • pandas.io.formats.format • pandas.io.json._json • pandas.io.json._table_schema - • pandas.io.parsers.base_parser • pandas.io.parsers.c_parser_wrapper + • pandas.io.parsers.python_parser • pandas.io.pytables • pandas.io.sql • pandas.io.stata @@ -36961,6 +36984,7 @@ imported by: • pandas.core.dtypes.concat • pandas.core.dtypes.dtypes • pandas.core.dtypes.missing + • pandas.core.frame • pandas.core.generic • pandas.core.indexers.utils • pandas.core.indexes.accessors @@ -36972,7 +36996,6 @@ imported by: • pandas.core.indexes.range • pandas.core.indexes.timedeltas • pandas.core.indexing - • pandas.core.internals.array_manager • pandas.core.internals.blocks • pandas.core.internals.construction • pandas.core.internals.managers @@ -37020,8 +37043,8 @@ imports: • numpy • pandas._libs • pandas._libs.lib - • pandas._typing • pandas.core.dtypes + • pandas.util._decorators • re • typing @@ -37055,10 +37078,8 @@ imported by: imports: __future__ • decimal - • functools • numpy • pandas - • pandas._config • pandas._libs • pandas._libs.lib • pandas._libs.missing @@ -37072,6 +37093,7 @@ imports: • pandas.core.dtypes.generic • pandas.core.dtypes.inference • pandas.core.indexes.base + • pandas.util._decorators • re • typing • warnings @@ -37102,7 +37124,6 @@ imported by: • pandas.core.arrays.string_arrow • pandas.core.arrays.timedeltas • pandas.core.base - • pandas.core.config_init • pandas.core.construction • pandas.core.dtypes.cast • pandas.core.dtypes.dtypes @@ -37118,9 +37139,9 @@ imported by: • pandas.core.indexes.multi • pandas.core.indexes.period • pandas.core.indexing - • pandas.core.internals.array_manager • pandas.core.internals.blocks • pandas.core.internals.concat + • pandas.core.internals.construction • pandas.core.internals.managers • pandas.core.missing • pandas.core.nanops @@ -37157,6 +37178,7 @@ imports: __future__ • pandas.core • pandas.core.generic + • pandas.util._decorators • typing • weakref @@ -37180,7 +37202,6 @@ imports: • collections • datetime • functools - • inspect • io • itertools • numpy @@ -37189,7 +37210,6 @@ imports: • operator • pandas • pandas._config - • pandas._config.config • pandas._libs • pandas._libs.algos • pandas._libs.hashtable @@ -37214,14 +37234,13 @@ imports: • pandas.core.arrays.sparse • pandas.core.arrays.string_ • pandas.core.common - • pandas.core.computation • pandas.core.computation.eval - • pandas.core.computation.expressions • pandas.core.construction • pandas.core.dtypes.cast • pandas.core.dtypes.common • pandas.core.dtypes.concat • pandas.core.dtypes.dtypes + • pandas.core.dtypes.generic • pandas.core.dtypes.missing • pandas.core.generic • pandas.core.groupby.generic @@ -37233,6 +37252,7 @@ imports: • pandas.core.interchange.dataframe_protocol • pandas.core.internals • pandas.core.internals.construction + • pandas.core.internals.managers • pandas.core.methods • pandas.core.methods.selectn • pandas.core.methods.to_dict @@ -37248,7 +37268,7 @@ imports: • pandas.core.shared_docs • pandas.core.sorting • pandas.errors - • pandas.io + • pandas.errors.cow • pandas.io.common • pandas.io.feather_format • pandas.io.formats @@ -37257,7 +37277,7 @@ imports: • pandas.io.formats.info • pandas.io.formats.style • pandas.io.formats.xml - • pandas.io.gbq + • pandas.io.iceberg • pandas.io.orc • pandas.io.parquet • pandas.io.stata @@ -37282,10 +37302,9 @@ imported by: • pandas.core.groupby.ops • pandas.core.indexers.utils • pandas.core.reshape.encoding - • pandas.core.reshape.merge - • pandas.core.reshape.pivot • pandas.core.reshape.reshape • pandas.core.series + • pandas.core.strings.accessor • pandas.io.excel._base • pandas.io.formats.info • pandas.io.formats.style @@ -37308,7 +37327,6 @@ imports: • copy • datetime • functools - • gc • json • numpy • operator @@ -37318,7 +37336,6 @@ imports: • pandas._libs • pandas._libs.lib • pandas._libs.tslibs - • pandas._libs.tslibs.dtypes • pandas._typing • pandas.compat • pandas.compat._constants @@ -37335,6 +37352,7 @@ imports: • pandas.core.computation.parsing • pandas.core.construction • pandas.core.dtypes.astype + • pandas.core.dtypes.cast • pandas.core.dtypes.common • pandas.core.dtypes.dtypes • pandas.core.dtypes.generic @@ -37345,7 +37363,6 @@ imports: • pandas.core.indexes.api • pandas.core.indexing • pandas.core.internals - • pandas.core.internals.construction • pandas.core.methods.describe • pandas.core.missing • pandas.core.nanops @@ -37358,6 +37375,7 @@ imports: • pandas.core.tools.datetimes • pandas.core.window • pandas.errors + • pandas.errors.cow • pandas.io • pandas.io.clipboards • pandas.io.formats.excel @@ -37376,12 +37394,12 @@ imports: • sys • typing • warnings - • weakref
imported by: pandas._typing + • pandas.core.accessor • pandas.core.arraylike • pandas.core.computation.align • pandas.core.computation.eval @@ -37489,12 +37507,12 @@ imports: 'collections.abc' • __future__ • collections + • dataclasses • functools • numpy • pandas • pandas._libs • pandas._libs.hashtable - • pandas._libs.lib • pandas._typing • pandas.core • pandas.core.algorithms @@ -37509,7 +37527,6 @@ imports: • pandas.core.groupby • pandas.core.groupby.base • pandas.core.groupby.groupby - • pandas.core.groupby.ops • pandas.core.indexes.api • pandas.core.reshape.concat • pandas.core.reshape.merge @@ -37533,7 +37550,6 @@ imported by: • pandas.core.frame • pandas.core.groupby • pandas.core.groupby.groupby - • pandas.core.resample • pandas.core.series • pandas.plotting._core @@ -37550,15 +37566,14 @@ imports: • __future__ • datetime • functools - • inspect • numpy - • pandas._config - • pandas._config.config • pandas._libs • pandas._libs.algos • pandas._libs.groupby • pandas._libs.lib • pandas._libs.missing + • pandas._libs.tslibs + • pandas._libs.tslibs.timedeltas • pandas._typing • pandas.compat.numpy • pandas.compat.numpy.function @@ -37567,7 +37582,6 @@ imports: • pandas.core._numba.executor • pandas.core._numba.kernels • pandas.core.algorithms - • pandas.core.apply • pandas.core.arrays • pandas.core.arrays.string_ • pandas.core.arrays.string_arrow @@ -37585,6 +37599,7 @@ imports: • pandas.core.groupby.indexing • pandas.core.groupby.numba_ • pandas.core.groupby.ops + • pandas.core.indexers.objects • pandas.core.indexes.api • pandas.core.internals.blocks • pandas.core.resample @@ -37597,7 +37612,6 @@ imports: • pandas.errors • pandas.util._decorators • pandas.util._exceptions - • textwrap • typing • warnings @@ -37621,9 +37635,8 @@ imports: 'collections.abc' • __future__ • numpy - • pandas._config • pandas._libs - • pandas._libs.lib + • pandas._libs.algos • pandas._libs.tslibs • pandas._typing • pandas.core @@ -37643,9 +37656,7 @@ imports: • pandas.errors • pandas.io.formats.printing • pandas.util._decorators - • pandas.util._exceptions • typing - • warnings
@@ -37689,7 +37700,8 @@ imported by: pandas.core.groupby.numba_ SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • functools • inspect • numba @@ -37724,6 +37736,7 @@ imports: • pandas._libs.groupby • pandas._libs.lib • pandas._typing + • pandas.core.arrays • pandas.core.dtypes.cast • pandas.core.dtypes.common • pandas.core.dtypes.missing @@ -37746,7 +37759,6 @@ imported by: • pandas.core.arrays.datetimelike • pandas.core.arrays.masked • pandas.core.groupby - • pandas.core.groupby.generic • pandas.core.groupby.groupby • pandas.core.groupby.grouper • pandas.core.resample @@ -37781,8 +37793,8 @@ imported by: • pandas.core.indexers.utils • pandas.core.indexes.base • pandas.core.indexes.interval + • pandas.core.indexes.range • pandas.core.indexing - • pandas.core.internals.array_manager • pandas.core.internals.blocks • pandas.core.internals.managers • pandas.core.series @@ -37812,6 +37824,7 @@ imports: imported by: pandas.api.indexers • pandas.core.generic + • pandas.core.groupby.groupby • pandas.core.window.ewm • pandas.core.window.expanding • pandas.core.window.rolling @@ -37837,6 +37850,7 @@ imports: • pandas.core.frame • pandas.core.indexers • pandas.core.indexes.base + • pandas.util._decorators • typing
@@ -37896,6 +37910,7 @@ imports: • pandas.core.indexes • pandas.core.indexes.datetimes • pandas.core.indexes.timedeltas + • pandas.errors • pandas.util._exceptions • typing • warnings @@ -37931,7 +37946,6 @@ imports: • pandas.core.indexes.range • pandas.core.indexes.timedeltas • pandas.errors - • textwrap • typing
@@ -37948,12 +37962,12 @@ imported by: • pandas.core.groupby.groupby • pandas.core.groupby.grouper • pandas.core.groupby.ops + • pandas.core.indexes.base • pandas.core.indexes.datetimes • pandas.core.indexing - • pandas.core.internals.array_manager - • pandas.core.internals.base • pandas.core.internals.construction • pandas.core.internals.managers + • pandas.core.methods.selectn • pandas.core.resample • pandas.core.reshape.concat • pandas.core.reshape.encoding @@ -37970,6 +37984,7 @@ imported by: • pandas.io.orc • pandas.io.parsers.base_parser • pandas.io.parsers.c_parser_wrapper + • pandas.io.parsers.python_parser • pandas.io.parsers.readers • pandas.io.pytables @@ -38010,6 +38025,7 @@ imports: • pandas.core.array_algos.putmask • pandas.core.arraylike • pandas.core.arrays + • pandas.core.arrays.floating • pandas.core.arrays.numpy_ • pandas.core.arrays.string_ • pandas.core.base @@ -38025,6 +38041,7 @@ imports: • pandas.core.dtypes.missing • pandas.core.indexers • pandas.core.indexes + • pandas.core.indexes.api • pandas.core.indexes.frozen • pandas.core.indexes.multi • pandas.core.indexes.period @@ -38032,7 +38049,6 @@ imports: • pandas.core.missing • pandas.core.nanops • pandas.core.ops - • pandas.core.ops.invalid • pandas.core.reshape.merge • pandas.core.sorting • pandas.core.strings.accessor @@ -38066,7 +38082,6 @@ imported by: • pandas.core.indexes.period • pandas.core.indexes.range • pandas.core.indexes.timedeltas - • pandas.core.internals.array_manager • pandas.core.internals.blocks • pandas.core.resample • pandas.core.series @@ -38093,7 +38108,6 @@ imports: • pandas.core.arrays.categorical • pandas.core.construction • pandas.core.dtypes.common - • pandas.core.dtypes.concat • pandas.core.dtypes.dtypes • pandas.core.dtypes.missing • pandas.core.indexes @@ -38122,7 +38136,6 @@ imports: • datetime • numpy • pandas - • pandas._config • pandas._libs • pandas._libs.lib • pandas._libs.tslibs @@ -38132,7 +38145,6 @@ imports: • pandas.compat.numpy • pandas.compat.numpy.function • pandas.core.arrays - • pandas.core.arrays.datetimelike • pandas.core.common • pandas.core.dtypes.common • pandas.core.dtypes.concat @@ -38144,9 +38156,7 @@ imports: • pandas.core.tools.timedeltas • pandas.errors • pandas.util._decorators - • pandas.util._exceptions • typing - • warnings
@@ -38191,10 +38201,10 @@ imports: • pandas.core.indexes.datetimelike • pandas.core.indexes.extension • pandas.core.tools.times + • pandas.errors • pandas.io.formats.format • pandas.util._decorators • pandas.util._exceptions - • pytz • typing • warnings @@ -38208,6 +38218,7 @@ imported by: • pandas.core.indexes.interval • pandas.core.indexes.period • pandas.core.resample + • pandas.core.reshape.concat • pandas.core.tools.datetimes • pandas.io.formats.format @@ -38220,7 +38231,9 @@ imported by: pandas.core.indexes.extension SourceModule
imports: - __future__ + 'collections.abc' + • __future__ + • inspect • numpy • pandas._typing • pandas.core.arrays @@ -38251,16 +38264,17 @@ imported by: SourceModule
imports: __future__ - • pandas._typing • pandas.core.base • pandas.core.indexes • pandas.io.formats.printing + • pandas.util._decorators • typing
imported by: - pandas.core.indexes.base + pandas.api.typing + • pandas.core.indexes.base • pandas.core.indexes.multi • pandas.core.reshape.merge • pandas.core.reshape.reshape @@ -38301,7 +38315,6 @@ imports: • pandas.errors • pandas.util._decorators • pandas.util._exceptions - • textwrap • typing
@@ -38323,6 +38336,7 @@ imports: • __future__ • copy • functools + • itertools • numpy • pandas • pandas._config @@ -38350,7 +38364,6 @@ imports: • pandas.core.indexes.base • pandas.core.indexes.frozen • pandas.core.ops.invalid - • pandas.core.reshape.util • pandas.core.sorting • pandas.errors • pandas.io.formats.printing @@ -38402,9 +38415,7 @@ imports: • pandas.core.indexes.datetimes • pandas.core.indexes.extension • pandas.util._decorators - • pandas.util._exceptions • typing - • warnings
@@ -38428,8 +38439,8 @@ imports: • datetime • numpy • operator + • pandas • pandas._libs - • pandas._libs.algos • pandas._libs.index • pandas._libs.lib • pandas._typing @@ -38438,8 +38449,10 @@ imports: • pandas.core • pandas.core.common • pandas.core.construction + • pandas.core.dtypes.base • pandas.core.dtypes.common • pandas.core.dtypes.generic + • pandas.core.indexers • pandas.core.indexes • pandas.core.indexes.base • pandas.core.ops @@ -38451,7 +38464,8 @@ imports:
imported by: - pandas.core.indexes.api + pandas.core.arrays.categorical + • pandas.core.indexes.api • pandas.core.indexes.base • pandas.core.indexes.datetimelike • pandas.io.stata @@ -38470,19 +38484,19 @@ imports: • pandas._libs.index • pandas._libs.lib • pandas._libs.tslibs - • pandas._libs.tslibs.timedeltas + • pandas._libs.tslibs.dtypes • pandas._typing • pandas.core.arrays.timedeltas • pandas.core.common • pandas.core.dtypes.common + • pandas.core.dtypes.dtypes • pandas.core.dtypes.generic • pandas.core.indexes • pandas.core.indexes.base • pandas.core.indexes.datetimelike • pandas.core.indexes.extension - • pandas.util._exceptions + • pandas.util._decorators • typing - • warnings
@@ -38508,7 +38522,6 @@ imports: • contextlib • numpy • pandas - • pandas._config • pandas._libs.indexing • pandas._libs.lib • pandas._typing @@ -38527,8 +38540,8 @@ imports: • pandas.core.indexers • pandas.core.indexes.api • pandas.errors + • pandas.errors.cow • pandas.util._decorators - • pandas.util._exceptions • sys • typing • warnings @@ -38598,6 +38611,7 @@ imports: __future__ • numpy • pandas + • pandas._config • pandas._libs.lib • pandas._libs.tslibs • pandas.api.types @@ -38653,6 +38667,7 @@ imports: • abc • enum • pandas.core.interchange + • pandas.util._decorators • typing
@@ -38684,8 +38699,11 @@ imports: • pandas.core.interchange.dataframe_protocol • pandas.core.interchange.utils • pandas.errors + • pandas.util._decorators + • pandas.util._exceptions • re • typing + • warnings
@@ -38731,11 +38749,10 @@ imports: pandas.core • pandas.core.internals.Block • pandas.core.internals.api - • pandas.core.internals.array_manager - • pandas.core.internals.base • pandas.core.internals.blocks • pandas.core.internals.concat • pandas.core.internals.managers + • pandas.errors • warnings
@@ -38748,8 +38765,6 @@ imported by: • pandas.core.frame • pandas.core.generic • pandas.core.internals.api - • pandas.core.internals.array_manager - • pandas.core.internals.base • pandas.core.internals.blocks • pandas.core.internals.concat • pandas.core.internals.construction @@ -38790,7 +38805,7 @@ imports: • pandas.core.dtypes.dtypes • pandas.core.internals • pandas.core.internals.blocks - • pandas.core.internals.managers + • pandas.errors • typing • warnings @@ -38803,82 +38818,6 @@ imported by:
-
- - pandas.core.internals.array_manager -SourceModule
-imports: - 'collections.abc' - • __future__ - • itertools - • numpy - • pandas._libs - • pandas._libs.lib - • pandas._typing - • pandas.core.algorithms - • pandas.core.array_algos.quantile - • pandas.core.array_algos.take - • pandas.core.arrays - • pandas.core.construction - • pandas.core.dtypes.astype - • pandas.core.dtypes.cast - • pandas.core.dtypes.common - • pandas.core.dtypes.dtypes - • pandas.core.dtypes.generic - • pandas.core.dtypes.missing - • pandas.core.indexers - • pandas.core.indexes.api - • pandas.core.indexes.base - • pandas.core.internals - • pandas.core.internals.base - • pandas.core.internals.blocks - • pandas.core.internals.managers - • typing - -
-
-imported by: - pandas.core.internals - • pandas.core.internals.concat - • pandas.core.internals.construction - -
- -
- -
- - pandas.core.internals.base -SourceModule
-imports: - __future__ - • numpy - • pandas._config - • pandas._libs - • pandas._libs.algos - • pandas._libs.lib - • pandas._typing - • pandas.core.base - • pandas.core.construction - • pandas.core.dtypes.cast - • pandas.core.dtypes.dtypes - • pandas.core.indexes.api - • pandas.core.internals - • pandas.errors - • pandas.util._validators - • typing - -
-
-imported by: - pandas.core.internals - • pandas.core.internals.array_manager - • pandas.core.internals.managers - -
- -
-
pandas.core.internals.blocks @@ -38886,10 +38825,8 @@ imported by: imports: 'collections.abc' • __future__ - • functools • inspect • numpy - • pandas._config • pandas._libs • pandas._libs.internals • pandas._libs.lib @@ -38928,7 +38865,6 @@ imports: • re • typing • warnings - • weakref
@@ -38937,7 +38873,6 @@ imported by: • pandas.core.groupby.groupby • pandas.core.internals • pandas.core.internals.api - • pandas.core.internals.array_manager • pandas.core.internals.concat • pandas.core.internals.construction • pandas.core.internals.managers @@ -38969,13 +38904,10 @@ imports: • pandas.core.dtypes.dtypes • pandas.core.dtypes.missing • pandas.core.internals - • pandas.core.internals.array_manager • pandas.core.internals.blocks • pandas.core.internals.managers • pandas.util._decorators - • pandas.util._exceptions • typing - • warnings
@@ -39012,12 +38944,11 @@ imports: • pandas.core.dtypes.common • pandas.core.dtypes.dtypes • pandas.core.dtypes.generic + • pandas.core.dtypes.missing • pandas.core.indexes.api • pandas.core.internals - • pandas.core.internals.array_manager • pandas.core.internals.blocks • pandas.core.internals.managers - • pandas.core.series • typing
@@ -39025,7 +38956,6 @@ imports: imported by: pandas.core.algorithms • pandas.core.frame - • pandas.core.generic • pandas.io.sql
@@ -39041,8 +38971,9 @@ imports: • __future__ • itertools • numpy - • pandas._config + • pandas._config.config • pandas._libs + • pandas._libs.algos • pandas._libs.internals • pandas._libs.lib • pandas._libs.tslibs @@ -39051,6 +38982,7 @@ imports: • pandas.core.algorithms • pandas.core.arrays • pandas.core.arrays._mixins + • pandas.core.base • pandas.core.construction • pandas.core.dtypes.cast • pandas.core.dtypes.common @@ -39060,21 +38992,20 @@ imports: • pandas.core.indexers • pandas.core.indexes.api • pandas.core.internals - • pandas.core.internals.base • pandas.core.internals.blocks • pandas.core.internals.ops • pandas.errors • pandas.util._decorators • pandas.util._exceptions + • pandas.util._validators • typing • warnings
imported by: - pandas.core.internals - • pandas.core.internals.api - • pandas.core.internals.array_manager + pandas.core.frame + • pandas.core.internals • pandas.core.internals.concat • pandas.core.internals.construction • pandas.core.internals.ops @@ -39138,7 +39069,6 @@ imports: • abc • numpy • pandas - • pandas._libs.tslibs • pandas._typing • pandas.core.arrays.floating • pandas.core.dtypes.common @@ -39171,9 +39101,9 @@ imports: • pandas._libs • pandas._libs.algos • pandas._typing - • pandas.core.api • pandas.core.dtypes.common • pandas.core.dtypes.dtypes + • pandas.core.indexes.api • pandas.core.methods • pandas.core.reshape.concat • typing @@ -39194,7 +39124,8 @@ imported by: pandas.core.methods.to_dict SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • numpy • pandas • pandas._libs @@ -39224,10 +39155,13 @@ imported by: pandas.core.missing SourceModule
imports: - __future__ + 'collections.abc' + • 'pyarrow.compute' + • __future__ • functools • numpy • pandas + • pandas._config • pandas._libs • pandas._libs.algos • pandas._libs.lib @@ -39255,7 +39189,6 @@ imported by: • pandas.core.generic • pandas.core.indexes.base • pandas.core.internals.blocks - • pandas.core.series • pandas.util._validators
@@ -39267,7 +39200,8 @@ imported by: pandas.core.nanops SourceModule
imports: - 'scipy.stats' + 'collections.abc' + • 'scipy.stats' • __future__ • functools • itertools @@ -39280,7 +39214,6 @@ imports: • pandas.core • pandas.core.dtypes.common • pandas.core.dtypes.missing - • pandas.util._exceptions • typing • warnings @@ -39379,9 +39312,7 @@ imports: • pandas.core.ops.invalid • pandas.core.ops.missing • pandas.core.roperator - • pandas.util._exceptions • typing - • warnings
@@ -39397,11 +39328,13 @@ imported by: pandas.core.ops.common SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • functools • pandas._libs.lib • pandas._libs.missing • pandas._typing + • pandas.core.construction • pandas.core.dtypes.generic • pandas.core.ops • typing @@ -39462,7 +39395,8 @@ imported by: pandas.core.ops.invalid SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • numpy • operator • pandas._typing @@ -39473,7 +39407,6 @@ imports:
imported by: pandas.core.arrays.datetimelike - • pandas.core.indexes.base • pandas.core.indexes.multi • pandas.core.ops • pandas.core.ops.array_ops @@ -39492,7 +39425,9 @@ imports: • pandas._libs • pandas._libs.lib • pandas._libs.missing + • pandas._typing • pandas.core.ops + • typing
@@ -39538,20 +39473,15 @@ imports: • pandas._libs • pandas._libs.lib • pandas._libs.tslibs - • pandas._libs.tslibs.dtypes • pandas._typing - • pandas.compat.numpy - • pandas.compat.numpy.function • pandas.core • pandas.core.algorithms • pandas.core.apply • pandas.core.arrays • pandas.core.base - • pandas.core.common • pandas.core.dtypes.dtypes • pandas.core.dtypes.generic • pandas.core.generic - • pandas.core.groupby.generic • pandas.core.groupby.groupby • pandas.core.groupby.grouper • pandas.core.groupby.ops @@ -39560,12 +39490,12 @@ imports: • pandas.core.indexes.datetimes • pandas.core.indexes.period • pandas.core.indexes.timedeltas + • pandas.core.reshape.concat • pandas.errors • pandas.tseries.frequencies • pandas.tseries.offsets • pandas.util._decorators • pandas.util._exceptions - • textwrap • typing • warnings @@ -39601,7 +39531,6 @@ imported by: • pandas.core.reshape.pivot • pandas.core.reshape.reshape • pandas.core.reshape.tile - • pandas.core.reshape.util
@@ -39637,9 +39566,11 @@ imports: 'collections.abc' • __future__ • collections + • itertools • numpy • pandas - • pandas._config + • pandas._libs + • pandas._libs.lib • pandas._typing • pandas.core.arrays.categorical • pandas.core.common @@ -39648,10 +39579,13 @@ imports: • pandas.core.dtypes.generic • pandas.core.dtypes.missing • pandas.core.indexes.api + • pandas.core.indexes.datetimes • pandas.core.internals • pandas.core.reshape + • pandas.errors • pandas.util._decorators • pandas.util._exceptions + • types • typing • warnings @@ -39666,6 +39600,7 @@ imported by: • pandas.core.groupby.groupby • pandas.core.methods.describe • pandas.core.methods.selectn + • pandas.core.resample • pandas.core.reshape.api • pandas.core.reshape.encoding • pandas.core.reshape.melt @@ -39674,7 +39609,6 @@ imported by: • pandas.core.reshape.reshape • pandas.core.series • pandas.core.window.rolling - • pandas.io.formats.format • pandas.io.json._json
@@ -39705,6 +39639,7 @@ imports: • pandas.core.reshape • pandas.core.reshape.concat • pandas.core.series + • pandas.util._decorators • pyarrow • typing @@ -39734,8 +39669,6 @@ imports: • pandas.core.indexes.api • pandas.core.reshape • pandas.core.reshape.concat - • pandas.core.reshape.util - • pandas.core.shared_docs • pandas.core.tools.numeric • pandas.util._decorators • re @@ -39780,7 +39713,6 @@ imports: • pandas.core.dtypes.dtypes • pandas.core.dtypes.generic • pandas.core.dtypes.missing - • pandas.core.frame • pandas.core.groupby • pandas.core.indexes.api • pandas.core.indexes.frozen @@ -39791,6 +39723,7 @@ imports: • pandas.util._decorators • pandas.util._exceptions • pyarrow + • types • typing • uuid • warnings @@ -39814,6 +39747,7 @@ imported by: imports: 'collections.abc' • __future__ + • itertools • numpy • pandas • pandas._libs @@ -39824,17 +39758,13 @@ imports: • pandas.core.dtypes.common • pandas.core.dtypes.dtypes • pandas.core.dtypes.generic - • pandas.core.frame • pandas.core.groupby • pandas.core.indexes.api • pandas.core.reshape • pandas.core.reshape.concat - • pandas.core.reshape.util • pandas.core.series • pandas.util._decorators - • pandas.util._exceptions • typing - • warnings
@@ -39854,10 +39784,12 @@ imports: __future__ • itertools • numpy + • pandas._config.config • pandas._libs.reshape • pandas._typing • pandas.core.algorithms • pandas.core.arrays + • pandas.core.arrays._mixins • pandas.core.arrays.categorical • pandas.core.construction • pandas.core.dtypes.cast @@ -39892,7 +39824,8 @@ imported by: pandas.core.reshape.tile SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • numpy • pandas • pandas._libs @@ -39900,11 +39833,13 @@ imports: • pandas._typing • pandas.core.algorithms • pandas.core.arrays.datetimelike + • pandas.core.col • pandas.core.dtypes.common • pandas.core.dtypes.dtypes • pandas.core.dtypes.generic • pandas.core.dtypes.missing • pandas.core.reshape + • pandas.util._decorators • typing
@@ -39918,29 +39853,6 @@ imported by:
-
- - pandas.core.reshape.util -SourceModule
-imports: - __future__ - • numpy - • pandas._typing - • pandas.core.dtypes.common - • pandas.core.reshape - • typing - -
-
-imported by: - pandas.core.indexes.multi - • pandas.core.reshape.melt - • pandas.core.reshape.pivot - -
- -
-
pandas.core.roperator @@ -40003,10 +39915,9 @@ imported by: imports: 'collections.abc' • __future__ + • functools • numpy • operator - • pandas._config - • pandas._config.config • pandas._libs • pandas._libs.internals • pandas._libs.lib @@ -40026,7 +39937,6 @@ imports: • pandas.core.arrays.arrow • pandas.core.arrays.categorical • pandas.core.arrays.sparse - • pandas.core.arrays.string_ • pandas.core.base • pandas.core.common • pandas.core.construction @@ -40049,7 +39959,6 @@ imports: • pandas.core.internals • pandas.core.methods • pandas.core.methods.selectn - • pandas.core.missing • pandas.core.nanops • pandas.core.ops • pandas.core.reshape.concat @@ -40060,6 +39969,7 @@ imports: • pandas.core.strings.accessor • pandas.core.tools.datetimes • pandas.errors + • pandas.errors.cow • pandas.io.formats.format • pandas.io.formats.info • pandas.plotting @@ -40070,7 +39980,6 @@ imports: • textwrap • typing • warnings - • weakref
@@ -40085,7 +39994,6 @@ imported by: • pandas.core.groupby.groupby • pandas.core.groupby.grouper • pandas.core.groupby.ops - • pandas.core.internals.construction • pandas.core.reshape.encoding • pandas.core.reshape.pivot • pandas.core.reshape.reshape @@ -40110,28 +40018,10 @@ imports: imported by: pandas.core.frame • pandas.core.generic - • pandas.core.reshape.melt • pandas.core.series - • pandas.core.window.doc - • pandas.io.common - • pandas.io.excel._base - • pandas.io.excel._calamine • pandas.io.excel._odfreader • pandas.io.excel._openpyxl - • pandas.io.excel._pyxlsb - • pandas.io.excel._xlrd - • pandas.io.feather_format - • pandas.io.formats.excel - • pandas.io.formats.style - • pandas.io.formats.xml - • pandas.io.html - • pandas.io.json._json - • pandas.io.parquet - • pandas.io.parsers.readers - • pandas.io.pickle - • pandas.io.sas.sasreader • pandas.io.stata - • pandas.io.xml
@@ -40144,7 +40034,7 @@ imported by: imports: 'collections.abc' • __future__ - • collections + • itertools • numpy • pandas • pandas._libs @@ -40195,7 +40085,6 @@ imports:
imported by: pandas.core.strings.accessor - • pandas.core.strings.base • pandas.core.strings.object_array
@@ -40217,7 +40106,6 @@ imports: • pandas._libs • pandas._libs.lib • pandas._typing - • pandas.compat • pandas.core.arrays • pandas.core.arrays.arrow.array • pandas.core.arrays.string_ @@ -40227,8 +40115,8 @@ imports: • pandas.core.dtypes.dtypes • pandas.core.dtypes.generic • pandas.core.dtypes.missing + • pandas.core.frame • pandas.core.strings - • pandas.util._decorators • pandas.util._exceptions • pyarrow • re @@ -40245,32 +40133,6 @@ imported by:
-
- - pandas.core.strings.base -SourceModule
-imports: - 'collections.abc' - • __future__ - • abc - • pandas - • pandas._libs - • pandas._libs.lib - • pandas._typing - • pandas.core.strings - • re - • typing - -
-
-imported by: - pandas.core.arrays.arrow.array - • pandas.core.strings.object_array - -
- -
-
pandas.core.strings.object_array @@ -40287,15 +40149,14 @@ imports: • pandas._libs.ops • pandas._typing • pandas.core.arrays.string_ + • pandas.core.dtypes.common • pandas.core.dtypes.missing • pandas.core.strings - • pandas.core.strings.base - • pandas.util._exceptions + • pandas.util._validators • re • textwrap • typing • unicodedata - • warnings
@@ -40341,7 +40202,6 @@ imports: • itertools • numpy • pandas - • pandas._config • pandas._libs • pandas._libs.lib • pandas._libs.tslib @@ -40365,6 +40225,7 @@ imports: • pandas.core.indexes.base • pandas.core.indexes.datetimes • pandas.core.tools + • pandas.util._decorators • pandas.util._exceptions • typing • warnings @@ -40394,6 +40255,7 @@ imports: • pandas._libs • pandas._libs.lib • pandas._libs.missing + • pandas._libs.tslibs • pandas._typing • pandas.core.arrays • pandas.core.arrays.string_ @@ -40402,10 +40264,9 @@ imports: • pandas.core.dtypes.dtypes • pandas.core.dtypes.generic • pandas.core.tools - • pandas.util._exceptions + • pandas.util._decorators • pandas.util._validators • typing - • warnings
@@ -40439,9 +40300,8 @@ imports: • pandas.core.dtypes.dtypes • pandas.core.dtypes.generic • pandas.core.tools - • pandas.util._exceptions + • pandas.util._decorators • typing - • warnings
@@ -40467,9 +40327,7 @@ imports: • pandas.core.dtypes.generic • pandas.core.dtypes.missing • pandas.core.tools - • pandas.util._exceptions • typing - • warnings
@@ -40536,7 +40394,9 @@ imported by: pandas.core.util.numba_ SourceModule
imports: - __future__ + 'collections.abc' + • __future__ + • inspect • numba • numpy • pandas.compat._optional @@ -40548,7 +40408,9 @@ imports:
imported by: - pandas.core.config_init + pandas.core._numba.executor + • pandas.core.apply + • pandas.core.config_init • pandas.core.groupby.generic • pandas.core.groupby.groupby • pandas.core.groupby.numba_ @@ -40577,7 +40439,6 @@ imported by: • pandas.core.generic • pandas.core.groupby.groupby • pandas.core.window.common - • pandas.core.window.doc • pandas.core.window.ewm • pandas.core.window.expanding • pandas.core.window.numba_ @@ -40612,27 +40473,6 @@ imported by:
-
- - pandas.core.window.doc -SourceModule
-imports: - __future__ - • pandas.core.shared_docs - • pandas.core.window - • textwrap - -
-
-imported by: - pandas.core.window.ewm - • pandas.core.window.expanding - • pandas.core.window.rolling - -
- -
-
pandas.core.window.ewm @@ -40658,12 +40498,10 @@ imports: • pandas.core.util.numba_ • pandas.core.window • pandas.core.window.common - • pandas.core.window.doc • pandas.core.window.numba_ • pandas.core.window.online • pandas.core.window.rolling • pandas.util._decorators - • textwrap • typing
@@ -40680,16 +40518,15 @@ imported by: pandas.core.window.expanding SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • pandas • pandas._typing • pandas.core.generic • pandas.core.indexers.objects • pandas.core.window - • pandas.core.window.doc • pandas.core.window.rolling • pandas.util._decorators - • textwrap • typing
@@ -40706,7 +40543,8 @@ imported by: pandas.core.window.numba_ SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • functools • numba • numpy @@ -40785,11 +40623,9 @@ imports: • pandas.core.util.numba_ • pandas.core.window • pandas.core.window.common - • pandas.core.window.doc • pandas.core.window.numba_ • pandas.errors • pandas.util._decorators - • textwrap • typing
@@ -40811,6 +40647,7 @@ imported by: Package
imports: __future__ + • abc • ctypes • pandas • pandas._config.config @@ -40821,27 +40658,33 @@ imports:
imported by: pandas + • pandas._testing.asserters • pandas._testing.contexts • pandas.compat.numpy.function • pandas.core.apply • pandas.core.arrays._mixins • pandas.core.arrays._utils + • pandas.core.arrays.arrow.array • pandas.core.arrays.base + • pandas.core.arrays.categorical • pandas.core.arrays.datetimelike • pandas.core.arrays.datetimes • pandas.core.arrays.interval • pandas.core.arrays.masked • pandas.core.arrays.numeric • pandas.core.arrays.sparse.array + • pandas.core.arrays.string_ • pandas.core.base • pandas.core.computation.align • pandas.core.computation.engines • pandas.core.computation.expr • pandas.core.computation.pytables • pandas.core.computation.scope + • pandas.core.config_init • pandas.core.dtypes.astype • pandas.core.dtypes.base • pandas.core.dtypes.cast + • pandas.core.dtypes.common • pandas.core.dtypes.dtypes • pandas.core.frame • pandas.core.generic @@ -40849,25 +40692,31 @@ imported by: • pandas.core.groupby.groupby • pandas.core.groupby.grouper • pandas.core.groupby.ops + • pandas.core.indexes.accessors • pandas.core.indexes.api • pandas.core.indexes.base • pandas.core.indexes.datetimelike + • pandas.core.indexes.datetimes • pandas.core.indexes.interval • pandas.core.indexes.multi • pandas.core.indexing • pandas.core.interchange.column • pandas.core.interchange.from_dataframe - • pandas.core.internals.base + • pandas.core.internals + • pandas.core.internals.api • pandas.core.internals.blocks • pandas.core.internals.managers • pandas.core.resample + • pandas.core.reshape.concat • pandas.core.reshape.merge • pandas.core.reshape.reshape • pandas.core.series • pandas.core.util.numba_ • pandas.core.window.rolling + • pandas.errors.cow • pandas.io.clipboard • pandas.io.excel._base + • pandas.io.feather_format • pandas.io.formats.css • pandas.io.formats.xml • pandas.io.html @@ -40884,6 +40733,26 @@ imported by: • pandas.io.stata • pandas.io.xml • pandas.tseries.holiday + • pandas.util._decorators + +
+ +
+ +
+ + pandas.errors.cow +SourceModule
+imports: + pandas.errors + +
+
+imported by: + pandas.core.frame + • pandas.core.generic + • pandas.core.indexing + • pandas.core.series
@@ -40898,7 +40767,6 @@ imports: • pandas.io • pandas.io.clipboards • pandas.io.formats - • pandas.io.gbq • pandas.io.json • pandas.io.pytables • pandas.io.sql @@ -40909,7 +40777,6 @@ imports:
imported by: pandas - • pandas.core.frame • pandas.core.generic • pandas.io • pandas.io._util @@ -40920,8 +40787,8 @@ imported by: • pandas.io.excel • pandas.io.feather_format • pandas.io.formats - • pandas.io.gbq • pandas.io.html + • pandas.io.iceberg • pandas.io.json • pandas.io.orc • pandas.io.parquet @@ -40953,6 +40820,7 @@ imports: • pandas._typing • pandas.compat • pandas.compat._optional + • pandas.core.dtypes.common • pandas.io • pyarrow • typing @@ -40982,8 +40850,8 @@ imports: • pandas.io.clipboards • pandas.io.excel • pandas.io.feather_format - • pandas.io.gbq • pandas.io.html + • pandas.io.iceberg • pandas.io.json • pandas.io.orc • pandas.io.parquet @@ -41051,6 +40919,7 @@ imports: • pandas.io • pandas.io.clipboard • pandas.io.parsers + • pandas.util._decorators • pandas.util._exceptions • pandas.util._validators • typing @@ -41076,23 +40945,22 @@ imports: • __future__ • abc • botocore + • bz2 • codecs • collections • dataclasses • functools • gzip • io + • lzma • mmap • os • pandas • pandas._typing - • pandas.compat • pandas.compat._optional • pandas.core.dtypes.common • pandas.core.dtypes.generic - • pandas.core.shared_docs • pandas.io - • pandas.util._decorators • pandas.util._exceptions • pathlib • re @@ -41175,19 +41043,17 @@ imports: 'collections.abc' • __future__ • datetime + • decimal • functools - • io • os • pandas._config • pandas._config.config • pandas._libs • pandas._libs.lib - • pandas._libs.parsers • pandas._typing • pandas.compat._optional • pandas.core.dtypes.common • pandas.core.frame - • pandas.core.shared_docs • pandas.errors • pandas.io.common • pandas.io.excel @@ -41203,7 +41069,6 @@ imports: • pandas.util._exceptions • pandas.util._validators • pandas.util.version - • textwrap • types • typing • warnings @@ -41234,13 +41099,10 @@ imported by: imports: __future__ • datetime - • pandas • pandas._typing • pandas.compat._optional - • pandas.core.shared_docs • pandas.io.excel • pandas.io.excel._base - • pandas.util._decorators • python_calamine • typing @@ -41356,10 +41218,8 @@ imports: __future__ • pandas._typing • pandas.compat._optional - • pandas.core.shared_docs • pandas.io.excel • pandas.io.excel._base - • pandas.util._decorators • pyxlsb • typing @@ -41409,10 +41269,8 @@ imports: • numpy • pandas._typing • pandas.compat._optional - • pandas.core.shared_docs • pandas.io.excel • pandas.io.excel._base - • pandas.util._decorators • typing • xlrd @@ -41462,7 +41320,7 @@ imports: • pandas.compat._optional • pandas.core.api • pandas.core.arrays.arrow.extension_types - • pandas.core.shared_docs + • pandas.errors • pandas.io • pandas.io._util • pandas.io.common @@ -41470,6 +41328,7 @@ imports: • pandas.util._validators • pyarrow • typing + • warnings
@@ -41632,14 +41491,11 @@ imports: • pandas.core.dtypes • pandas.core.dtypes.common • pandas.core.dtypes.missing - • pandas.core.shared_docs • pandas.io.excel • pandas.io.formats • pandas.io.formats._color_data • pandas.io.formats.css • pandas.io.formats.format - • pandas.io.formats.printing - • pandas.util._decorators • pandas.util._exceptions • re • typing @@ -41679,7 +41535,6 @@ imports: • pandas._libs.tslibs.nattype • pandas._typing • pandas.core.arrays - • pandas.core.arrays.string_ • pandas.core.base • pandas.core.common • pandas.core.dtypes.common @@ -41689,7 +41544,6 @@ imports: • pandas.core.indexes.datetimes • pandas.core.indexes.multi • pandas.core.indexes.timedeltas - • pandas.core.reshape.concat • pandas.io.common • pandas.io.formats • pandas.io.formats.console @@ -41697,6 +41551,7 @@ imports: • pandas.io.formats.html • pandas.io.formats.printing • pandas.io.formats.string + • pandas.util._decorators • re • shutil • typing @@ -41791,6 +41646,7 @@ imports: • IPython • __future__ • pandas._config + • pandas._typing • pandas.core.dtypes.inference • pandas.io.formats • pandas.io.formats.console @@ -41818,7 +41674,6 @@ imported by: • pandas.core.indexes.frozen • pandas.core.indexes.multi • pandas.io.formats - • pandas.io.formats.excel • pandas.io.formats.format • pandas.io.formats.html • pandas.io.formats.info @@ -41861,12 +41716,9 @@ imported by: imports: 'collections.abc' • 'matplotlib.colors' - • 'matplotlib.pyplot' • __future__ - • contextlib • copy • functools - • matplotlib • numpy • operator • pandas @@ -41876,15 +41728,11 @@ imports: • pandas.core.common • pandas.core.frame • pandas.core.generic - • pandas.core.shared_docs • pandas.io.formats • pandas.io.formats.excel • pandas.io.formats.format • pandas.io.formats.style_render - • pandas.util._decorators - • pandas.util._exceptions • typing - • warnings
@@ -41919,6 +41767,7 @@ imports: • pandas.core.dtypes.common • pandas.core.dtypes.generic • pandas.io.formats + • pathlib • re • typing • uuid @@ -41945,14 +41794,12 @@ imports: • pandas._typing • pandas.core.dtypes.common • pandas.core.dtypes.missing - • pandas.core.shared_docs • pandas.errors • pandas.io.common • pandas.io.formats • pandas.io.xml • pandas.util._decorators • typing - • warnings • xml.dom.minidom • xml.etree.ElementTree @@ -41965,31 +41812,6 @@ imported by:
-
- - pandas.io.gbq -SourceModule
-imports: - __future__ - • google - • pandas - • pandas.compat._optional - • pandas.io - • pandas.util._exceptions - • typing - • warnings - -
-
-imported by: - pandas.core.frame - • pandas.io - • pandas.io.api - -
- -
-
pandas.io.html @@ -41999,9 +41821,11 @@ imports: • __future__ • bs4 • collections + • errno • lxml.etree • lxml.html • numbers + • os • pandas • pandas._libs • pandas._libs.lib @@ -42011,18 +41835,15 @@ imports: • pandas.core.indexes.base • pandas.core.indexes.multi • pandas.core.series - • pandas.core.shared_docs • pandas.errors • pandas.io • pandas.io.common • pandas.io.formats.printing • pandas.io.parsers • pandas.util._decorators - • pandas.util._exceptions • pandas.util._validators • re • typing - • warnings
@@ -42033,6 +41854,27 @@ imported by:
+
+ + pandas.io.iceberg +SourceModule
+imports: + pandas + • pandas.compat._optional + • pandas.io + • pandas.util._decorators + • typing + +
+
+imported by: + pandas.core.frame + • pandas.io.api + +
+ +
+
pandas.io.json @@ -42065,10 +41907,10 @@ imports: • __future__ • abc • collections - • io • itertools • numpy • pandas + • pandas._config • pandas._libs • pandas._libs.json • pandas._libs.lib @@ -42079,7 +41921,6 @@ imports: • pandas.core.dtypes.dtypes • pandas.core.generic • pandas.core.reshape.concat - • pandas.core.shared_docs • pandas.errors • pandas.io._util • pandas.io.common @@ -42088,7 +41929,6 @@ imports: • pandas.io.json._table_schema • pandas.io.parsers.readers • pandas.util._decorators - • pandas.util._exceptions • pandas.util._validators • types • typing @@ -42118,6 +41958,7 @@ imports: • pandas._libs.writers • pandas._typing • pandas.io.json + • pandas.util._decorators • typing
@@ -42137,11 +41978,11 @@ imported by: imports: __future__ • pandas + • pandas._config • pandas._libs • pandas._libs.json • pandas._libs.lib • pandas._libs.tslibs - • pandas._libs.tslibs.dtypes • pandas._libs.tslibs.timezones • pandas._typing • pandas.core.common @@ -42183,8 +42024,8 @@ imports: • pandas.io • pandas.io._util • pandas.io.common + • pandas.util._decorators • pandas.util._validators - • types • typing
@@ -42208,19 +42049,16 @@ imports: • json • os • pandas - • pandas._config.config • pandas._libs • pandas._libs.lib • pandas._typing • pandas.compat._optional • pandas.core.arrays.arrow.extension_types - • pandas.core.shared_docs • pandas.errors • pandas.io • pandas.io._util • pandas.io.common • pandas.util._decorators - • pandas.util._exceptions • pandas.util._validators • typing • warnings @@ -42279,6 +42117,7 @@ imports: • pandas.io.parsers • pandas.io.parsers.base_parser • pandas.util._exceptions + • pyarrow • typing • warnings @@ -42301,7 +42140,6 @@ imports: • collections • copy • csv - • datetime • enum • itertools • numpy @@ -42310,17 +42148,12 @@ imports: • pandas._libs.lib • pandas._libs.ops • pandas._libs.parsers - • pandas._libs.tslibs - • pandas._libs.tslibs.parsing • pandas._typing • pandas.compat._optional • pandas.core • pandas.core.algorithms • pandas.core.arrays - • pandas.core.arrays.boolean - • pandas.core.dtypes.astype • pandas.core.dtypes.common - • pandas.core.dtypes.dtypes • pandas.core.dtypes.missing • pandas.core.indexes.api • pandas.core.series @@ -42330,7 +42163,6 @@ imports: • pandas.io.common • pandas.io.parsers • pandas.util._exceptions - • pyarrow • typing • warnings @@ -42397,8 +42229,15 @@ imports: • pandas._libs • pandas._libs.lib • pandas._typing + • pandas.core + • pandas.core.algorithms + • pandas.core.arrays + • pandas.core.arrays.boolean + • pandas.core.dtypes.astype • pandas.core.dtypes.common + • pandas.core.dtypes.dtypes • pandas.core.dtypes.inference + • pandas.core.indexes.api • pandas.errors • pandas.io.common • pandas.io.parsers @@ -42429,7 +42268,6 @@ imports: • csv • numpy • pandas - • pandas._config • pandas._libs • pandas._libs.lib • pandas._libs.parsers @@ -42437,7 +42275,6 @@ imports: • pandas.core.dtypes.common • pandas.core.frame • pandas.core.indexes.api - • pandas.core.shared_docs • pandas.errors • pandas.io.common • pandas.io.parsers @@ -42449,7 +42286,6 @@ imports: • pandas.util._exceptions • pandas.util._validators • sys - • textwrap • types • typing • warnings @@ -42475,7 +42311,6 @@ imports: • pandas._typing • pandas.compat • pandas.compat.pickle_compat - • pandas.core.shared_docs • pandas.io • pandas.io.common • pandas.util._decorators @@ -42519,6 +42354,7 @@ imports: • pandas.compat._optional • pandas.compat.pickle_compat • pandas.core.arrays + • pandas.core.arrays.datetimes • pandas.core.arrays.string_ • pandas.core.common • pandas.core.computation.pytables @@ -42580,7 +42416,6 @@ imported by: SourceModule
imports: __future__ - • collections • datetime • numpy • pandas @@ -42631,7 +42466,6 @@ imported by: SourceModule
imports: __future__ - • collections • datetime • numpy • pandas @@ -42639,7 +42473,6 @@ imports: • pandas.io.common • pandas.io.sas • pandas.io.sas.sasreader - • pandas.util._decorators • pandas.util._exceptions • struct • typing @@ -42664,7 +42497,6 @@ imports: • abc • pandas • pandas._typing - • pandas.core.shared_docs • pandas.io.common • pandas.io.sas • pandas.io.sas.sas7bdat @@ -42676,7 +42508,8 @@ imports:
imported by: - pandas.io.sas + pandas.api.typing + • pandas.io.sas • pandas.io.sas.sas7bdat • pandas.io.sas.sas_xport @@ -42699,6 +42532,7 @@ imports: • pandas.core.dtypes.inference • pandas.io • pandas.io.common + • pandas.util._decorators • pandas.util._validators • pathlib • typing @@ -42719,11 +42553,13 @@ imported by: imports: 'collections.abc' • 'sqlalchemy.engine' + • 'sqlalchemy.exc' • 'sqlalchemy.schema' • 'sqlalchemy.sql' • 'sqlalchemy.types' • __future__ • abc + • adbc_driver_manager • contextlib • datetime • functools @@ -42747,12 +42583,14 @@ imports: • pandas.errors • pandas.io • pandas.io._util + • pandas.util._decorators • pandas.util._exceptions • pandas.util._validators • pyarrow • re • sqlalchemy • sqlite3 + • sqlite3.Error • typing • warnings @@ -42832,16 +42670,13 @@ imports: • pandas._typing • pandas.compat._optional • pandas.core.dtypes.common - • pandas.core.shared_docs • pandas.errors • pandas.io • pandas.io.common • pandas.io.parsers • pandas.util._decorators - • pandas.util._exceptions • pandas.util._validators • typing - • warnings • xml.etree.ElementTree
@@ -42928,6 +42763,7 @@ imports: • pandas • pandas.plotting • pandas.plotting._core + • pandas.util._decorators • typing
@@ -43027,6 +42863,7 @@ imports: • pandas.core.dtypes.generic • pandas.tseries • pandas.util._decorators + • pyarrow • typing
@@ -43049,14 +42886,17 @@ imported by: pandas.tseries.holiday SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • datetime • dateutil.relativedelta • numpy • pandas + • pandas._libs.tslibs.offsets • pandas.errors • pandas.tseries • pandas.tseries.offsets + • typing • warnings
@@ -43105,8 +42945,7 @@ imports:
imported by: - pandas.core.dtypes.dtypes - • pandas.util._decorators + pandas.util._decorators • pandas.util._exceptions • pandas.util._print_versions • pandas.util._tester @@ -43128,6 +42967,7 @@ imports: • inspect • pandas._libs.properties • pandas._typing + • pandas.errors • pandas.util • pandas.util._exceptions • textwrap @@ -43137,20 +42977,38 @@ imports:
imported by: - pandas.core.accessor + pandas._testing.asserters + • pandas.core.accessor • pandas.core.algorithms • pandas.core.apply • pandas.core.arrays._mixins • pandas.core.arrays.arrow.array • pandas.core.arrays.base + • pandas.core.arrays.boolean + • pandas.core.arrays.categorical • pandas.core.arrays.datetimelike + • pandas.core.arrays.datetimes + • pandas.core.arrays.floating + • pandas.core.arrays.integer • pandas.core.arrays.interval - • pandas.core.arrays.masked • pandas.core.arrays.numeric + • pandas.core.arrays.numpy_ • pandas.core.arrays.period • pandas.core.arrays.sparse.array • pandas.core.arrays.string_ + • pandas.core.arrays.string_arrow + • pandas.core.arrays.timedeltas • pandas.core.base + • pandas.core.col + • pandas.core.computation.eval + • pandas.core.construction + • pandas.core.dtypes.base + • pandas.core.dtypes.common + • pandas.core.dtypes.concat + • pandas.core.dtypes.dtypes + • pandas.core.dtypes.inference + • pandas.core.dtypes.missing + • pandas.core.flags • pandas.core.frame • pandas.core.generic • pandas.core.groupby.generic @@ -43159,57 +43017,69 @@ imported by: • pandas.core.groupby.indexing • pandas.core.groupby.ops • pandas.core.indexers.objects + • pandas.core.indexers.utils • pandas.core.indexes.base • pandas.core.indexes.category • pandas.core.indexes.datetimelike • pandas.core.indexes.datetimes • pandas.core.indexes.extension + • pandas.core.indexes.frozen • pandas.core.indexes.interval • pandas.core.indexes.multi • pandas.core.indexes.period • pandas.core.indexes.range + • pandas.core.indexes.timedeltas • pandas.core.indexing • pandas.core.interchange.column + • pandas.core.interchange.dataframe_protocol + • pandas.core.interchange.from_dataframe • pandas.core.internals.blocks • pandas.core.internals.concat • pandas.core.internals.managers • pandas.core.resample • pandas.core.reshape.concat + • pandas.core.reshape.encoding • pandas.core.reshape.melt • pandas.core.reshape.merge • pandas.core.reshape.pivot • pandas.core.reshape.reshape + • pandas.core.reshape.tile • pandas.core.series - • pandas.core.strings.accessor + • pandas.core.tools.datetimes + • pandas.core.tools.numeric + • pandas.core.tools.timedeltas • pandas.core.window.ewm • pandas.core.window.expanding • pandas.core.window.rolling - • pandas.io.common + • pandas.io.clipboards • pandas.io.excel._base - • pandas.io.excel._calamine • pandas.io.excel._odfreader • pandas.io.excel._openpyxl - • pandas.io.excel._pyxlsb - • pandas.io.excel._xlrd • pandas.io.feather_format • pandas.io.formats.csvs - • pandas.io.formats.excel - • pandas.io.formats.style + • pandas.io.formats.format • pandas.io.formats.xml • pandas.io.html + • pandas.io.iceberg • pandas.io.json._json + • pandas.io.json._normalize + • pandas.io.orc • pandas.io.parquet • pandas.io.parsers.python_parser • pandas.io.parsers.readers • pandas.io.pickle • pandas.io.pytables - • pandas.io.sas.sas_xport • pandas.io.sas.sasreader + • pandas.io.spss + • pandas.io.sql • pandas.io.stata • pandas.io.xml • pandas.plotting._core + • pandas.plotting._misc • pandas.tseries.frequencies • pandas.util + • pandas.util._print_versions + • pandas.util._tester
@@ -43236,74 +43106,48 @@ imports:
imported by: pandas._config.config - • pandas.arrays • pandas.compat._optional • pandas.core.accessor • pandas.core.algorithms - • pandas.core.apply • pandas.core.arrays.arrow.array • pandas.core.arrays.base • pandas.core.arrays.categorical • pandas.core.arrays.datetimelike • pandas.core.arrays.datetimes - • pandas.core.arrays.interval - • pandas.core.arrays.masked - • pandas.core.arrays.period • pandas.core.arrays.sparse.array • pandas.core.arrays.string_ - • pandas.core.arrays.string_arrow - • pandas.core.base • pandas.core.computation.align • pandas.core.computation.eval • pandas.core.computation.expressions - • pandas.core.construction • pandas.core.dtypes.common - • pandas.core.dtypes.concat • pandas.core.dtypes.dtypes • pandas.core.frame • pandas.core.generic • pandas.core.groupby.generic • pandas.core.groupby.groupby - • pandas.core.groupby.grouper • pandas.core.indexes.accessors • pandas.core.indexes.base - • pandas.core.indexes.datetimelike • pandas.core.indexes.datetimes • pandas.core.indexes.interval • pandas.core.indexes.multi - • pandas.core.indexes.period - • pandas.core.indexes.timedeltas - • pandas.core.indexing + • pandas.core.interchange.from_dataframe • pandas.core.internals.blocks - • pandas.core.internals.concat • pandas.core.internals.managers • pandas.core.methods.to_dict - • pandas.core.nanops - • pandas.core.ops.array_ops • pandas.core.resample • pandas.core.reshape.concat • pandas.core.reshape.merge - • pandas.core.reshape.pivot • pandas.core.reshape.reshape • pandas.core.series • pandas.core.strings.accessor - • pandas.core.strings.object_array • pandas.core.tools.datetimes - • pandas.core.tools.numeric - • pandas.core.tools.timedeltas - • pandas.core.tools.times • pandas.io.clipboard • pandas.io.clipboards • pandas.io.common • pandas.io.excel._base • pandas.io.formats.css • pandas.io.formats.excel - • pandas.io.formats.style - • pandas.io.gbq - • pandas.io.html - • pandas.io.json._json • pandas.io.json._table_schema - • pandas.io.parquet • pandas.io.parsers.arrow_parser_wrapper • pandas.io.parsers.base_parser • pandas.io.parsers.c_parser_wrapper @@ -43313,7 +43157,6 @@ imported by: • pandas.io.sas.sas_xport • pandas.io.sql • pandas.io.stata - • pandas.io.xml • pandas.util._decorators
@@ -43334,6 +43177,7 @@ imports: • pandas._version_meson • pandas.compat._optional • pandas.util + • pandas.util._decorators • platform • struct • sys @@ -43357,6 +43201,7 @@ imports: • os • pandas.compat._optional • pandas.util + • pandas.util._decorators • sys
@@ -43378,6 +43223,7 @@ imports: • numpy • pandas._libs • pandas._libs.lib + • pandas._libs.missing • pandas.core.dtypes.common • pandas.core.missing • pandas.util @@ -43388,20 +43234,20 @@ imports: imported by: pandas.compat.numpy.function • pandas.core.arrays._mixins - • pandas.core.arrays.arrow.array • pandas.core.arrays.base • pandas.core.arrays.categorical • pandas.core.arrays.datetimes - • pandas.core.arrays.masked • pandas.core.arrays.sparse.array + • pandas.core.arrays.string_arrow • pandas.core.arrays.timedeltas • pandas.core.computation.eval • pandas.core.frame • pandas.core.generic - • pandas.core.internals.base • pandas.core.internals.blocks + • pandas.core.internals.managers • pandas.core.methods.describe • pandas.core.series + • pandas.core.strings.object_array • pandas.core.tools.numeric • pandas.io.clipboards • pandas.io.excel._base @@ -43426,12 +43272,10 @@ imported by: imports: 'collections.abc' • __future__ - • collections • itertools • pandas.util • re • typing - • warnings
@@ -43505,10 +43349,10 @@ imported by: • numpy.testing._private.extbuild • numpy.testing._private.utils • pandas._testing._io - • pandas._testing.contexts • pandas.core.arrays.arrow.array • pandas.core.arrays.string_ • pandas.io.common + • pandas.io.formats.style_render • pandas.io.spss • pathlib._abc • pathlib._local @@ -43526,8 +43370,6 @@ imported by: • setuptools.discovery • setuptools.dist • tldextract.cache - • wheel.cli.convert - • wheel.cli.unpack • win32_setctime._setctime • zipfile._path @@ -43658,13 +43500,13 @@ imported by: • numpy._core._methods • numpy.lib._format_impl • numpy.lib._npyio_impl - • pandas.compat.compressors • pandas.compat.pickle_compat • pandas.core.generic • pandas.io.pickle • pickletools • tracemalloc • win32com.client.gencache + • zoneinfo._zoneinfo
@@ -43775,14 +43617,13 @@ imported by: • setuptools._distutils.compat.py39 • setuptools._distutils.spawn • setuptools._vendor.importlib_metadata._compat + • setuptools._vendor.jaraco.context • setuptools._vendor.packaging.markers • setuptools._vendor.packaging.tags • setuptools.monkey • setuptools.msvc • setuptools.windows_support • uuid - • wheel.vendored.packaging.markers - • wheel.vendored.packaging.tags
@@ -43867,7 +43708,6 @@ imported by: • pandas.core.computation.scope • pdb • pickle - • pytz.tzfile • setuptools._distutils.dist • unittest.case • unittest.mock @@ -44085,8 +43925,9 @@ imported by: • pandas.core.strings.accessor • pandas.io._util • pandas.io.feather_format - • pandas.io.parsers.base_parser + • pandas.io.parsers.arrow_parser_wrapper • pandas.io.sql + • pandas.tseries.frequencies @@ -44207,7 +44048,6 @@ imported by: MissingModule
imported by: pandas._testing - • pandas._testing._io
@@ -44265,116 +44105,6 @@ imported by: -
- - pytz -Package
-imports: - datetime - • doctest - • os.path - • pytz - • pytz.exceptions - • pytz.lazy - • pytz.tzfile - • pytz.tzinfo - • sys - -
-
-imported by: - pandas.core.dtypes.dtypes - • pandas.core.indexes.datetimes - • pytz - • pytz.exceptions - • pytz.lazy - • pytz.tzfile - • pytz.tzinfo - -
- -
- -
- - pytz.exceptions -SourceModule
-imports: - pytz - -
-
-imported by: - pytz - • pytz.tzinfo - -
- -
- -
- - pytz.lazy -SourceModule
-imports: - 'collections.abc' - • UserDict - • collections - • collections.Mapping - • pytz - • threading - -
-
-imported by: - pytz - -
- -
- -
- - pytz.tzfile -SourceModule
-imports: - datetime - • os.path - • pprint - • pytz - • pytz.tzinfo - • struct - -
-
-imported by: - pytz - -
- -
- -
- - pytz.tzinfo -SourceModule
-imports: - bisect - • datetime - • pytz - • pytz.exceptions - • sets - -
-
-imported by: - pytz - • pytz.tzfile - -
- -
-
pywin @@ -48018,7 +47748,6 @@ imported by: • pandas.core.internals.blocks • pandas.core.reshape.melt • pandas.core.strings.accessor - • pandas.core.strings.base • pandas.core.strings.object_array • pandas.io.common • pandas.io.formats.css @@ -48115,21 +47844,12 @@ imported by: • urllib3.util.ssl_match_hostname • urllib3.util.url • warnings - • wheel.cli.convert - • wheel.cli.pack - • wheel.metadata - • wheel.vendored.packaging._manylinux - • wheel.vendored.packaging._musllinux - • wheel.vendored.packaging._tokenizer - • wheel.vendored.packaging.specifiers - • wheel.vendored.packaging.tags - • wheel.vendored.packaging.utils - • wheel.vendored.packaging.version • wheel.wheelfile • xml.etree.ElementPath • xml.etree.ElementTree • zipfile._path • zipfile._path.glob + • zoneinfo._zoneinfo
@@ -48210,6 +47930,7 @@ imports:
imported by: gui_app.py + • pandas.core.arrays._arrow_string_mixins • re • re._compiler • sre_parse @@ -48912,17 +48633,6 @@ imported by:
-
- - sets -MissingModule
-imported by: - pytz.tzinfo - -
- -
-
setuptools @@ -50277,6 +49987,7 @@ imported by: • setuptools.discovery • setuptools.dist • setuptools.extension + • setuptools.msvc
@@ -50483,7 +50194,8 @@ imported by: setuptools._vendor.importlib_metadata Package
imports: - __future__ + 'collections.abc' + • __future__ • abc • collections • contextlib @@ -50508,14 +50220,15 @@ imports: • setuptools._vendor.importlib_metadata._functools • setuptools._vendor.importlib_metadata._itertools • setuptools._vendor.importlib_metadata._meta + • setuptools._vendor.importlib_metadata._typing • setuptools._vendor.importlib_metadata.compat • setuptools._vendor.importlib_metadata.compat.py311 • setuptools._vendor.importlib_metadata.compat.py39 + • setuptools._vendor.zipp.compat.overlay • sys • textwrap • types • typing - • zipp
@@ -50529,6 +50242,7 @@ imported by: • setuptools._vendor.importlib_metadata._itertools • setuptools._vendor.importlib_metadata._meta • setuptools._vendor.importlib_metadata._text + • setuptools._vendor.importlib_metadata._typing • setuptools._vendor.importlib_metadata.compat • setuptools._vendor.importlib_metadata.compat.py39 @@ -50542,6 +50256,7 @@ imported by: SourceModule
imports: email.message + • email.policy • re • setuptools._vendor.importlib_metadata • setuptools._vendor.importlib_metadata._text @@ -50563,6 +50278,7 @@ imported by: imports: collections • setuptools._vendor.importlib_metadata + • typing
@@ -50599,6 +50315,7 @@ imports: functools • setuptools._vendor.importlib_metadata • types + • typing
@@ -50615,7 +50332,8 @@ imported by: setuptools._vendor.importlib_metadata._itertools SourceModule
imports: - itertools + collections + • itertools • setuptools._vendor.importlib_metadata
@@ -50632,7 +50350,8 @@ imported by: setuptools._vendor.importlib_metadata._meta SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • os • setuptools._vendor.importlib_metadata • typing @@ -50641,6 +50360,7 @@ imports:
imported by: setuptools._vendor.importlib_metadata + • setuptools._vendor.importlib_metadata._typing
@@ -50664,6 +50384,26 @@ imported by:
+
+ + setuptools._vendor.importlib_metadata._typing +SourceModule
+imports: + functools + • setuptools._vendor.importlib_metadata + • setuptools._vendor.importlib_metadata._meta + • typing + +
+
+imported by: + setuptools._vendor.importlib_metadata + • setuptools._vendor.importlib_metadata.compat.py39 + +
+ +
+
setuptools._vendor.importlib_metadata.compat @@ -50710,7 +50450,9 @@ imported by: setuptools._vendor.importlib_metadata.compat.py39 SourceModule
imports: - setuptools._vendor.importlib_metadata + __future__ + • setuptools._vendor.importlib_metadata + • setuptools._vendor.importlib_metadata._typing • setuptools._vendor.importlib_metadata.compat • typing @@ -50743,25 +50485,27 @@ imported by:
- setuptools._vendor.jaraco.context -SourceModule
+ setuptools._vendor.jaraco.context +Package
imports: - __future__ + 'collections.abc' + • __future__ • backports • backports.tarfile • contextlib + • errno • functools • jaraco • operator • os + • platform • shutil + • stat • subprocess • sys • tarfile • tempfile - • typing • urllib.request - • warnings
@@ -50778,6 +50522,7 @@ imported by: Package
imports: 'collections.abc' + • __future__ • functools • inspect • itertools @@ -50786,6 +50531,7 @@ imports: • operator • time • types + • typing • warnings
@@ -50816,6 +50562,7 @@ imports: • setuptools._vendor.jaraco.context • setuptools._vendor.jaraco.functools • textwrap + • typing
@@ -50856,6 +50603,7 @@ imported by: imports: 'collections.abc' • collections + • contextlib • functools • heapq • itertools @@ -50883,9 +50631,11 @@ imported by: setuptools._vendor.more_itertools.recipes SourceModule
imports: - 'collections.abc' + bisect • collections + • contextlib • functools + • heapq • itertools • math • operator @@ -51252,9 +51002,10 @@ imports: • setuptools._vendor.tomli • setuptools._vendor.tomli._re • setuptools._vendor.tomli._types - • string + • sys • types • typing + • warnings
@@ -51310,13 +51061,14 @@ imported by: setuptools._vendor.zipp Package
imports: - contextlib + functools • io • itertools • pathlib • posixpath • re • setuptools._vendor + • setuptools._vendor.zipp._functools • setuptools._vendor.zipp.compat.py310 • setuptools._vendor.zipp.glob • stat @@ -51326,7 +51078,8 @@ imports:
imported by: - setuptools._vendor.zipp.compat + setuptools._vendor.zipp._functools + • setuptools._vendor.zipp.compat • setuptools._vendor.zipp.glob • zipp @@ -51334,17 +51087,58 @@ imported by:
+
+ + setuptools._vendor.zipp._functools +SourceModule
+imports: + collections + • functools + • setuptools._vendor.zipp + +
+
+imported by: + setuptools._vendor.zipp + +
+ +
+
setuptools._vendor.zipp.compat Package
imports: setuptools._vendor.zipp + • zipp
imported by: - setuptools._vendor.zipp.compat.py310 + setuptools._vendor.zipp.compat.overlay + • setuptools._vendor.zipp.compat.py310 + • setuptools._vendor.zipp.compat.py313 + +
+ +
+ +
+ + setuptools._vendor.zipp.compat.overlay +SourceModule
+imports: + importlib + • setuptools._vendor.zipp.compat + • sys + • types + • zipp + +
+
+imported by: + setuptools._vendor.importlib_metadata
@@ -51368,6 +51162,24 @@ imported by:
+
+ + setuptools._vendor.zipp.compat.py313 +SourceModule
+imports: + functools + • setuptools._vendor.zipp.compat + • sys + +
+
+imported by: + setuptools._vendor.zipp.glob + +
+ +
+
setuptools._vendor.zipp.glob @@ -51376,6 +51188,7 @@ imports: os • re • setuptools._vendor.zipp + • setuptools._vendor.zipp.compat.py313
@@ -51472,7 +51285,9 @@ imported by: setuptools.command.bdist_egg SourceModule
imports: - __future__ + 'collections.abc' + • __future__ + • _typeshed • distutils • marshal • os @@ -51570,6 +51385,7 @@ imported by: SourceModule
imports: 'collections.abc' + • __future__ • distutils • functools • os @@ -51611,7 +51427,8 @@ imported by: setuptools.command.sdist SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • contextlib • distutils • itertools @@ -51674,6 +51491,7 @@ imported by: • setuptools.compat.py310 • setuptools.compat.py311 • setuptools.compat.py39 + • setuptools.msvc • setuptools.unicode_utils
@@ -51694,6 +51512,7 @@ imports:
imported by: setuptools.config.pyprojecttoml + • setuptools.msvc
@@ -52040,6 +51859,7 @@ imported by: imports: 'collections.abc' • __future__ + • abc • collections • contextlib • functools @@ -52223,7 +52043,8 @@ imported by: setuptools.extension SourceModule
imports: - __future__ + 'collections.abc' + • __future__ • functools • re • setuptools @@ -52363,6 +52184,9 @@ imports: • platform • setuptools • setuptools._distutils.errors + • setuptools._path + • setuptools.compat + • setuptools.compat.py310 • typing • typing_extensions • winreg @@ -52458,7 +52282,8 @@ imported by: setuptools.wheel SourceModule
imports: - contextlib + 'collections.abc' + • contextlib • distutils • email • functools @@ -53069,6 +52894,7 @@ imported by: Package
imports: sqlite3 + • sqlite3.Error • sqlite3.__main__ • sqlite3.connect • sqlite3.dbapi2 @@ -53089,6 +52915,18 @@ imported by:
+
+ + sqlite3.Error +MissingModule
+imported by: + pandas.io.sql + • sqlite3 + +
+ +
+
sqlite3.__main__ @@ -53283,6 +53121,7 @@ imported by: • setuptools._distutils.file_util • setuptools._shutil • setuptools._vendor.backports.tarfile + • setuptools._vendor.jaraco.context • setuptools._vendor.zipp • shutil • site @@ -53351,7 +53190,6 @@ imported by: • qfluentwidgets.common.style_sheet • setuptools._distutils.fancy_getopt • setuptools._distutils.util - • setuptools._vendor.tomli._parser • setuptools.config._validate_pyproject.formats • tomllib._parser • urllib.request @@ -53412,7 +53250,6 @@ imported by: • pickle • pickletools • platform - • pytz.tzfile • requests.utils • setuptools._vendor.backports.tarfile • setuptools._vendor.packaging._elffile @@ -53422,10 +53259,9 @@ imported by: • tarfile • websocket._abnf • websocket._core - • wheel.vendored.packaging._elffile - • wheel.vendored.packaging.tags • zipfile • zipimport + • zoneinfo._common
@@ -53498,8 +53334,6 @@ imported by: • setuptools.installer • uuid • webbrowser - • wheel.vendored.packaging._musllinux - • wheel.vendored.packaging.tags
@@ -53676,11 +53510,12 @@ imported by: • pandas._config.display • pandas._testing • pandas._testing._warnings - • pandas._typing + • pandas._testing.contexts • pandas._version • pandas.compat • pandas.compat._constants • pandas.compat._optional + • pandas.core.common • pandas.core.computation.scope • pandas.core.frame • pandas.core.generic @@ -53713,7 +53548,6 @@ imported by: • pyi_rth_pyqt5.py • pyi_rth_pythoncom.py • pyi_rth_pywintypes.py - • pytz • pywintypes • qfluentwidgets.common.theme_listener • qfluentwidgets.components.widgets.combo_box @@ -53767,8 +53601,11 @@ imported by: • setuptools._vendor.packaging._musllinux • setuptools._vendor.packaging.markers • setuptools._vendor.packaging.tags + • setuptools._vendor.tomli._parser • setuptools._vendor.zipp + • setuptools._vendor.zipp.compat.overlay • setuptools._vendor.zipp.compat.py310 + • setuptools._vendor.zipp.compat.py313 • setuptools.command • setuptools.command.bdist_egg • setuptools.command.bdist_wheel @@ -53823,12 +53660,7 @@ imported by: • weakref • webbrowser • websocket._abnf - • wheel.cli • wheel.macosx_libfile - • wheel.vendored.packaging._manylinux - • wheel.vendored.packaging._musllinux - • wheel.vendored.packaging.markers - • wheel.vendored.packaging.tags • win32_setctime._setctime • win32com • win32com.client @@ -53889,8 +53721,7 @@ imported by: • setuptools._vendor.packaging.tags • setuptools.command.bdist_egg • setuptools.command.bdist_wheel - • wheel.vendored.packaging._musllinux - • wheel.vendored.packaging.tags + • zoneinfo._tzpath
@@ -53984,7 +53815,6 @@ imported by: • numpy.lib._datasource • numpy.testing._private.utils • openpyxl.worksheet._writer - • pandas._testing.contexts • requests.utils • setuptools._core_metadata • setuptools._distutils.compilers.C.base @@ -54033,28 +53863,15 @@ imported by: • numpy.ma.core • numpy.testing._private.extbuild • optparse - • pandas._config.config - • pandas.core.algorithms • pandas.core.arrays.arrow.array • pandas.core.arrays.interval • pandas.core.arrays.timedeltas - • pandas.core.base • pandas.core.frame • pandas.core.groupby.generic - • pandas.core.groupby.groupby - • pandas.core.indexes.api - • pandas.core.indexes.interval - • pandas.core.resample • pandas.core.series • pandas.core.strings.object_array - • pandas.core.window.doc - • pandas.core.window.ewm - • pandas.core.window.expanding - • pandas.core.window.rolling - • pandas.io.excel._base • pandas.io.formats.html • pandas.io.formats.info - • pandas.io.parsers.readers • pandas.io.pytables • pandas.util._decorators • pdb @@ -54069,8 +53886,6 @@ imported by: • site • sqlite3.__main__ • traceback - • wheel.cli.convert - • wheel.metadata
@@ -54147,7 +53962,6 @@ imported by: • psutil._common • psutil._pswindows • pydoc - • pytz.lazy • pywin.dialogs.status • queue • requests.auth @@ -54770,11 +54584,13 @@ imported by: • numpy.lib._utils_impl • numpy.testing._private.utils • pandas.compat._optional + • pandas.core.arrays.sparse.array + • pandas.core.reshape.concat + • pandas.core.reshape.merge • pandas.core.util.numba_ • pandas.io.common • pandas.io.excel._base • pandas.io.json._json - • pandas.io.orc • pandas.io.parsers.readers • pandas.io.pytables • pandas.io.sas.sasreader @@ -54791,6 +54607,7 @@ imported by: • setuptools._vendor.importlib_metadata.compat.py311 • setuptools._vendor.jaraco.functools • setuptools._vendor.tomli._parser + • setuptools._vendor.zipp.compat.overlay • setuptools.command.bdist_egg • setuptools.config._apply_pyprojecttoml • setuptools.config.expand @@ -54960,13 +54777,12 @@ imported by: • pandas._libs.parsers • pandas._libs.properties • pandas._libs.sparse + • pandas._libs.tslibs.dtypes • pandas._libs.tslibs.nattype • pandas._libs.tslibs.offsets • pandas._libs.tslibs.period • pandas._libs.tslibs.timedeltas • pandas._libs.tslibs.timestamps - • pandas._libs.tslibs.timezones - • pandas._libs.tslibs.tzconversion • pandas._libs.window.aggregations • pandas._testing • pandas._testing._io @@ -54975,12 +54791,12 @@ imported by: • pandas._testing.compat • pandas._testing.contexts • pandas._typing - • pandas._version • pandas.compat • pandas.compat._optional • pandas.compat.numpy.function • pandas.compat.pickle_compat • pandas.core._numba.executor + • pandas.core._numba.extensions • pandas.core._numba.kernels.mean_ • pandas.core._numba.kernels.min_max_ • pandas.core._numba.kernels.shared @@ -55024,6 +54840,7 @@ imported by: • pandas.core.arrays.string_arrow • pandas.core.arrays.timedeltas • pandas.core.base + • pandas.core.col • pandas.core.common • pandas.core.computation.align • pandas.core.computation.engines @@ -55077,8 +54894,6 @@ imported by: • pandas.core.interchange.from_dataframe • pandas.core.interchange.utils • pandas.core.internals.api - • pandas.core.internals.array_manager - • pandas.core.internals.base • pandas.core.internals.blocks • pandas.core.internals.concat • pandas.core.internals.construction @@ -55093,6 +54908,7 @@ imported by: • pandas.core.ops.common • pandas.core.ops.dispatch • pandas.core.ops.invalid + • pandas.core.ops.mask_ops • pandas.core.resample • pandas.core.reshape.concat • pandas.core.reshape.encoding @@ -55101,12 +54917,10 @@ imported by: • pandas.core.reshape.pivot • pandas.core.reshape.reshape • pandas.core.reshape.tile - • pandas.core.reshape.util • pandas.core.sample • pandas.core.series • pandas.core.sorting • pandas.core.strings.accessor - • pandas.core.strings.base • pandas.core.strings.object_array • pandas.core.tools.datetimes • pandas.core.tools.numeric @@ -55146,8 +54960,8 @@ imported by: • pandas.io.formats.style • pandas.io.formats.style_render • pandas.io.formats.xml - • pandas.io.gbq • pandas.io.html + • pandas.io.iceberg • pandas.io.json._json • pandas.io.json._normalize • pandas.io.json._table_schema @@ -55172,6 +54986,7 @@ imported by: • pandas.plotting._misc • pandas.tseries • pandas.tseries.frequencies + • pandas.tseries.holiday • pandas.util._decorators • pandas.util._exceptions • pandas.util._print_versions @@ -55253,9 +55068,13 @@ imported by: • setuptools._shutil • setuptools._static • setuptools._vendor.importlib_metadata + • setuptools._vendor.importlib_metadata._collections + • setuptools._vendor.importlib_metadata._functools • setuptools._vendor.importlib_metadata._meta + • setuptools._vendor.importlib_metadata._typing • setuptools._vendor.importlib_metadata.compat.py39 - • setuptools._vendor.jaraco.context + • setuptools._vendor.jaraco.functools + • setuptools._vendor.jaraco.text • setuptools._vendor.packaging._elffile • setuptools._vendor.packaging._manylinux • setuptools._vendor.packaging._musllinux @@ -55345,18 +55164,6 @@ imported by: • websocket._url • websocket._utils • wheel.macosx_libfile - • wheel.metadata - • wheel.vendored.packaging._elffile - • wheel.vendored.packaging._manylinux - • wheel.vendored.packaging._musllinux - • wheel.vendored.packaging._parser - • wheel.vendored.packaging._tokenizer - • wheel.vendored.packaging.markers - • wheel.vendored.packaging.requirements - • wheel.vendored.packaging.specifiers - • wheel.vendored.packaging.tags - • wheel.vendored.packaging.utils - • wheel.vendored.packaging.version • wheel.wheelfile • win32_setctime._setctime • win32com.client.gencache @@ -55407,7 +55214,6 @@ imported by: • filelock._api • filelock.asyncio • numpy.random.bit_generator - • pandas._typing • setuptools._distutils.cmd • setuptools._distutils.command.bdist • setuptools._distutils.compilers.C.base @@ -55433,7 +55239,401 @@ imported by: • urllib3.poolmanager • urllib3.util.retry • urllib3.util.ssltransport - • wheel.wheelfile + +
+ +
+ +
+ + tzdata +Package
+imports: + tzdata + • tzdata.zoneinfo + • tzdata.zoneinfo.Africa + • tzdata.zoneinfo.America + • tzdata.zoneinfo.America.Argentina + • tzdata.zoneinfo.America.Indiana + • tzdata.zoneinfo.America.Kentucky + • tzdata.zoneinfo.America.North_Dakota + • tzdata.zoneinfo.Antarctica + • tzdata.zoneinfo.Arctic + • tzdata.zoneinfo.Asia + • tzdata.zoneinfo.Atlantic + • tzdata.zoneinfo.Australia + • tzdata.zoneinfo.Brazil + • tzdata.zoneinfo.Canada + • tzdata.zoneinfo.Chile + • tzdata.zoneinfo.Etc + • tzdata.zoneinfo.Europe + • tzdata.zoneinfo.Indian + • tzdata.zoneinfo.Mexico + • tzdata.zoneinfo.Pacific + • tzdata.zoneinfo.US + +
+
+imported by: + tzdata + • tzdata.zoneinfo + • zoneinfo + +
+ +
+ +
+ + tzdata.zoneinfo +Package
+imports: + tzdata + +
+
+imported by: + tzdata + • tzdata.zoneinfo.Africa + • tzdata.zoneinfo.America + • tzdata.zoneinfo.Antarctica + • tzdata.zoneinfo.Arctic + • tzdata.zoneinfo.Asia + • tzdata.zoneinfo.Atlantic + • tzdata.zoneinfo.Australia + • tzdata.zoneinfo.Brazil + • tzdata.zoneinfo.Canada + • tzdata.zoneinfo.Chile + • tzdata.zoneinfo.Etc + • tzdata.zoneinfo.Europe + • tzdata.zoneinfo.Indian + • tzdata.zoneinfo.Mexico + • tzdata.zoneinfo.Pacific + • tzdata.zoneinfo.US + +
+ +
+ +
+ + tzdata.zoneinfo.Africa +Package
+imports: + tzdata.zoneinfo + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.America +Package
+imports: + tzdata.zoneinfo + +
+
+imported by: + tzdata + • tzdata.zoneinfo.America.Argentina + • tzdata.zoneinfo.America.Indiana + • tzdata.zoneinfo.America.Kentucky + • tzdata.zoneinfo.America.North_Dakota + +
+ +
+ +
+ + tzdata.zoneinfo.America.Argentina +Package
+imports: + tzdata.zoneinfo.America + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.America.Indiana +Package
+imports: + tzdata.zoneinfo.America + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.America.Kentucky +Package
+imports: + tzdata.zoneinfo.America + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.America.North_Dakota +Package
+imports: + tzdata.zoneinfo.America + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.Antarctica +Package
+imports: + tzdata.zoneinfo + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.Arctic +Package
+imports: + tzdata.zoneinfo + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.Asia +Package
+imports: + tzdata.zoneinfo + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.Atlantic +Package
+imports: + tzdata.zoneinfo + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.Australia +Package
+imports: + tzdata.zoneinfo + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.Brazil +Package
+imports: + tzdata.zoneinfo + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.Canada +Package
+imports: + tzdata.zoneinfo + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.Chile +Package
+imports: + tzdata.zoneinfo + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.Etc +Package
+imports: + tzdata.zoneinfo + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.Europe +Package
+imports: + tzdata.zoneinfo + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.Indian +Package
+imports: + tzdata.zoneinfo + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.Mexico +Package
+imports: + tzdata.zoneinfo + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.Pacific +Package
+imports: + tzdata.zoneinfo + +
+
+imported by: + tzdata + +
+ +
+ +
+ + tzdata.zoneinfo.US +Package
+imports: + tzdata.zoneinfo + +
+
+imported by: + tzdata
@@ -57113,9 +57313,7 @@ imports:
imported by: - pandas._testing._io - • pandas._testing.contexts - • pandas.core.reshape.merge + pandas.core.reshape.merge • pandas.io.formats.style_render • qfluentwidgets.components.widgets.tab_view @@ -57272,83 +57470,61 @@ imported by: • openpyxl.xml • os • packaging._manylinux - • pandas • pandas._config.config - • pandas._testing • pandas._testing._warnings - • pandas.arrays + • pandas._testing.asserters • pandas.compat._optional • pandas.compat.numpy • pandas.core.accessor • pandas.core.algorithms - • pandas.core.apply • pandas.core.array_algos.masked_reductions • pandas.core.arrays.arrow.array • pandas.core.arrays.base • pandas.core.arrays.categorical • pandas.core.arrays.datetimelike • pandas.core.arrays.datetimes - • pandas.core.arrays.interval • pandas.core.arrays.masked • pandas.core.arrays.period • pandas.core.arrays.sparse.array • pandas.core.arrays.string_ - • pandas.core.arrays.string_arrow - • pandas.core.base - • pandas.core.common • pandas.core.computation.align • pandas.core.computation.eval • pandas.core.computation.expressions - • pandas.core.construction • pandas.core.dtypes.astype • pandas.core.dtypes.cast • pandas.core.dtypes.common - • pandas.core.dtypes.concat • pandas.core.dtypes.dtypes • pandas.core.dtypes.missing • pandas.core.frame • pandas.core.generic • pandas.core.groupby.generic • pandas.core.groupby.groupby - • pandas.core.groupby.grouper • pandas.core.indexes.accessors • pandas.core.indexes.base - • pandas.core.indexes.datetimelike • pandas.core.indexes.datetimes • pandas.core.indexes.multi - • pandas.core.indexes.period - • pandas.core.indexes.timedeltas • pandas.core.indexing + • pandas.core.interchange.from_dataframe • pandas.core.internals • pandas.core.internals.api • pandas.core.internals.blocks - • pandas.core.internals.concat • pandas.core.internals.managers • pandas.core.methods.to_dict • pandas.core.nanops - • pandas.core.ops.array_ops • pandas.core.resample • pandas.core.reshape.concat • pandas.core.reshape.merge - • pandas.core.reshape.pivot • pandas.core.reshape.reshape • pandas.core.series • pandas.core.strings.accessor - • pandas.core.strings.object_array • pandas.core.tools.datetimes - • pandas.core.tools.numeric - • pandas.core.tools.timedeltas - • pandas.core.tools.times • pandas.io.clipboard • pandas.io.clipboards • pandas.io.common • pandas.io.excel._base + • pandas.io.feather_format • pandas.io.formats.css • pandas.io.formats.excel - • pandas.io.formats.style - • pandas.io.formats.xml - • pandas.io.gbq - • pandas.io.html • pandas.io.json._json • pandas.io.json._table_schema • pandas.io.parquet @@ -57362,11 +57538,9 @@ imported by: • pandas.io.sas.sas_xport • pandas.io.sql • pandas.io.stata - • pandas.io.xml • pandas.tseries.holiday • pandas.util._decorators • pandas.util._exceptions - • pandas.util.version • pathlib._local • pkgutil • platform @@ -57396,10 +57570,10 @@ imported by: • setuptools._distutils.util • setuptools._distutils.version • setuptools._vendor.backports.tarfile - • setuptools._vendor.jaraco.context • setuptools._vendor.jaraco.functools • setuptools._vendor.more_itertools.more • setuptools._vendor.packaging._manylinux + • setuptools._vendor.tomli._parser • setuptools.command.bdist_wheel • setuptools.warnings • soupsieve.css_parser @@ -57433,10 +57607,10 @@ imported by: • urllib3.poolmanager • urllib3.response • urllib3.util.ssl_ - • wheel.vendored.packaging._manylinux • winerror • xml.etree.ElementTree • zipfile + • zoneinfo._tzpath
@@ -57486,9 +57660,6 @@ imported by: • numpy.lib._npyio_impl • pandas._libs.internals • pandas.core.flags - • pandas.core.generic - • pandas.core.internals.blocks - • pandas.core.series • qfluentwidgets.common.style_sheet • qfluentwidgets.components.widgets.info_bar • tempfile @@ -57496,6 +57667,7 @@ imported by: • urllib3.connectionpool • xml.etree.ElementTree • xml.sax.expatreader + • zoneinfo._zoneinfo
@@ -57890,150 +58062,17 @@ imported by: Package
imports: __future__ - • wheel
imported by: - wheel - • wheel.cli - • wheel.cli.convert - • wheel.macosx_libfile - • wheel.metadata - • wheel.util - • wheel.vendored + wheel.macosx_libfile • wheel.wheelfile
-
- - wheel.cli -Package
-imports: - __future__ - • argparse - • os - • sys - • wheel - • wheel.cli.convert - • wheel.cli.pack - • wheel.cli.tags - • wheel.cli.unpack - -
-
-imported by: - wheel.cli.convert - • wheel.cli.pack - • wheel.cli.tags - • wheel.cli.unpack - • wheel.wheelfile - -
- -
- -
- - wheel.cli.convert -SourceModule
-imports: - 'collections.abc' - • __future__ - • abc - • collections - • email.message - • email.parser - • email.policy - • glob - • os.path - • pathlib - • re - • textwrap - • wheel - • wheel.cli - • wheel.metadata - • wheel.vendored.packaging.tags - • wheel.wheelfile - • zipfile - -
-
-imported by: - wheel.cli - -
- -
- -
- - wheel.cli.pack -SourceModule
-imports: - __future__ - • email.generator - • email.parser - • email.policy - • os.path - • re - • wheel.cli - • wheel.wheelfile - -
-
-imported by: - wheel.cli - -
- -
- -
- - wheel.cli.tags -SourceModule
-imports: - 'collections.abc' - • __future__ - • email.parser - • email.policy - • itertools - • os - • wheel.cli - • wheel.wheelfile - -
-
-imported by: - wheel.cli - -
- -
- -
- - wheel.cli.unpack -SourceModule
-imports: - __future__ - • pathlib - • wheel.cli - • wheel.wheelfile - -
-
-imported by: - wheel.cli - -
- -
-
wheel.macosx_libfile @@ -58056,400 +58095,30 @@ imported by:
-
- - wheel.metadata -SourceModule
-imports: - __future__ - • email.message - • email.parser - • functools - • itertools - • os.path - • re - • textwrap - • typing - • wheel - • wheel.vendored.packaging.requirements - -
-
-imported by: - wheel.cli.convert - -
- -
- -
- - wheel.util -SourceModule
-imports: - __future__ - • base64 - • logging - • wheel - -
-
-imported by: - wheel.wheelfile - -
- -
- -
- - wheel.vendored -Package
-imports: - wheel - -
-
-imported by: - wheel.vendored.packaging - -
- -
- -
- - wheel.vendored.packaging -Package
-imports: - wheel.vendored - • wheel.vendored.packaging - • wheel.vendored.packaging._manylinux - • wheel.vendored.packaging._musllinux - -
-
-imported by: - wheel.vendored.packaging - • wheel.vendored.packaging._elffile - • wheel.vendored.packaging._manylinux - • wheel.vendored.packaging._musllinux - • wheel.vendored.packaging._parser - • wheel.vendored.packaging._structures - • wheel.vendored.packaging._tokenizer - • wheel.vendored.packaging.markers - • wheel.vendored.packaging.requirements - • wheel.vendored.packaging.specifiers - • wheel.vendored.packaging.tags - • wheel.vendored.packaging.utils - • wheel.vendored.packaging.version - -
- -
- -
- - wheel.vendored.packaging._elffile -SourceModule
-imports: - enum - • os - • struct - • typing - • wheel.vendored.packaging - -
-
-imported by: - wheel.vendored.packaging._manylinux - • wheel.vendored.packaging._musllinux - -
- -
- -
- - wheel.vendored.packaging._manylinux -SourceModule
-imports: - _manylinux - • collections - • contextlib - • ctypes - • functools - • os - • re - • sys - • typing - • warnings - • wheel.vendored.packaging - • wheel.vendored.packaging._elffile - -
-
-imported by: - wheel.vendored.packaging - • wheel.vendored.packaging.tags - -
- -
- -
- - wheel.vendored.packaging._musllinux -SourceModule
-imports: - functools - • re - • subprocess - • sys - • sysconfig - • typing - • wheel.vendored.packaging - • wheel.vendored.packaging._elffile - -
-
-imported by: - wheel.vendored.packaging - • wheel.vendored.packaging.tags - -
- -
- -
- - wheel.vendored.packaging._parser -SourceModule
-imports: - ast - • typing - • wheel.vendored.packaging - • wheel.vendored.packaging._tokenizer - -
-
-imported by: - wheel.vendored.packaging.markers - • wheel.vendored.packaging.requirements - -
- -
- -
- - wheel.vendored.packaging._structures -SourceModule
-imports: - wheel.vendored.packaging - -
-
-imported by: - wheel.vendored.packaging.version - -
- -
- -
- - wheel.vendored.packaging._tokenizer -SourceModule
-imports: - contextlib - • dataclasses - • re - • typing - • wheel.vendored.packaging - • wheel.vendored.packaging.specifiers - -
-
-imported by: - wheel.vendored.packaging._parser - • wheel.vendored.packaging.markers - • wheel.vendored.packaging.requirements - -
- -
- -
- - wheel.vendored.packaging.markers -SourceModule
-imports: - operator - • os - • platform - • sys - • typing - • wheel.vendored.packaging - • wheel.vendored.packaging._parser - • wheel.vendored.packaging._tokenizer - • wheel.vendored.packaging.specifiers - • wheel.vendored.packaging.utils - -
-
-imported by: - wheel.vendored.packaging.requirements - -
- -
- -
- - wheel.vendored.packaging.requirements -SourceModule
-imports: - typing - • wheel.vendored.packaging - • wheel.vendored.packaging._parser - • wheel.vendored.packaging._tokenizer - • wheel.vendored.packaging.markers - • wheel.vendored.packaging.specifiers - • wheel.vendored.packaging.utils - -
-
-imported by: - wheel.metadata - -
- -
- -
- - wheel.vendored.packaging.specifiers -SourceModule
-imports: - abc - • itertools - • re - • typing - • wheel.vendored.packaging - • wheel.vendored.packaging.utils - • wheel.vendored.packaging.version - -
-
-imported by: - wheel.vendored.packaging._tokenizer - • wheel.vendored.packaging.markers - • wheel.vendored.packaging.requirements - -
- -
- -
- - wheel.vendored.packaging.tags -SourceModule
-imports: - importlib.machinery - • logging - • platform - • re - • struct - • subprocess - • sys - • sysconfig - • typing - • wheel.vendored.packaging - • wheel.vendored.packaging._manylinux - • wheel.vendored.packaging._musllinux - -
-
-imported by: - wheel.cli.convert - • wheel.vendored.packaging.utils - -
- -
- -
- - wheel.vendored.packaging.utils -SourceModule
-imports: - re - • typing - • wheel.vendored.packaging - • wheel.vendored.packaging.tags - • wheel.vendored.packaging.version - -
-
-imported by: - wheel.vendored.packaging.markers - • wheel.vendored.packaging.requirements - • wheel.vendored.packaging.specifiers - -
- -
- -
- - wheel.vendored.packaging.version -SourceModule
-imports: - itertools - • re - • typing - • wheel.vendored.packaging - • wheel.vendored.packaging._structures - -
-
-imported by: - wheel.vendored.packaging.specifiers - • wheel.vendored.packaging.utils - -
- -
-
wheel.wheelfile SourceModule
imports: __future__ + • _typeshed + • base64 • csv • hashlib • io + • logging • os.path • re • stat • time • typing - • typing_extensions • wheel - • wheel.cli - • wheel.util • zipfile
imported by: setuptools.command.bdist_wheel - • wheel.cli.convert - • wheel.cli.pack - • wheel.cli.tags - • wheel.cli.unpack
@@ -59788,7 +59457,6 @@ imported by: • setuptools.command.bdist_wheel • setuptools.wheel • shutil - • wheel.cli.convert • wheel.wheelfile • win32com.client.gencache • zipfile._path @@ -59877,7 +59545,8 @@ imports:
imported by: - setuptools._vendor.importlib_metadata + setuptools._vendor.zipp.compat + • setuptools._vendor.zipp.compat.overlay
@@ -59898,6 +59567,99 @@ imported by:
+
+ +
+ + zoneinfo +Package
+imports: + _zoneinfo + • tzdata + • zoneinfo + • zoneinfo._common + • zoneinfo._tzpath + • zoneinfo._zoneinfo + +
+
+imported by: + pandas.core.dtypes.dtypes + • zoneinfo + • zoneinfo._common + • zoneinfo._tzpath + • zoneinfo._zoneinfo + +
+ +
+ +
+ + zoneinfo._common +SourceModule
+imports: + importlib + • importlib.resources + • struct + • zoneinfo + +
+
+imported by: + zoneinfo + • zoneinfo._zoneinfo + +
+ +
+ +
+ + zoneinfo._tzpath +SourceModule
+imports: + importlib + • importlib.resources + • os + • sysconfig + • warnings + • zoneinfo + +
+
+imported by: + zoneinfo + • zoneinfo._zoneinfo + +
+ +
+ +
+ + zoneinfo._zoneinfo +SourceModule
+imports: + bisect + • calendar + • collections + • datetime + • functools + • pickle + • re + • weakref + • zoneinfo + • zoneinfo._common + • zoneinfo._tzpath + +
+
+imported by: + zoneinfo + +
+
diff --git a/dist/多多发文助手.exe b/dist/多多发文助手.exe index 8852c6f..6efc6db 100644 Binary files a/dist/多多发文助手.exe and b/dist/多多发文助手.exe differ diff --git a/gui_app.py b/gui_app.py index e079d06..fd5aefc 100644 --- a/gui_app.py +++ b/gui_app.py @@ -3555,7 +3555,8 @@ class MainWindow(QMainWindow): elif task_type == 'image_folder': self.log_text.append(f" ✓ 图片文件夹上传完成") else: - self.log_text.append(f" ✗ 任务失败: {message}") + reason_text = f"失败原因: {message}" if message else "失败原因: 未知" + self.log_text.append(f" ✗ 任务失败: {reason_text}") # 对于 batch_video 类型，状态和计数已经在 _on_worker_item_result 中实时更新了 # 所以这里不再重复更新，只需要处理 single_video 和 image_folder 类型 @@ -3700,13 +3701,16 @@ class MainWindow(QMainWindow): self._update_table_status(found_config_idx, "已完成" if ok else "失败", is_config_index=True) updated_count = 1 label = name if name else payload.get("path", "") or "" - self.log_text.append(f"[结果] {user_id}-{idx}: {'✓' if ok else '✗'} {label} {reason}") + reason_text = f"失败原因: {reason}" if (not ok and reason) else reason + self.log_text.append(f"[结果] {user_id}-{idx}: {'✓' if ok else '✗'} {label} {reason_text}") elif found_config_idx == -2: # 多个配置已处理，只记录日志 label = name if name else payload.get("path", "") or "" - self.log_text.append(f"[结果] {user_id}-{idx}: {'✓' if ok else '✗'} {label} {reason}") + reason_text = f"失败原因: {reason}" if (not ok and reason) else reason + self.log_text.append(f"[结果] {user_id}-{idx}: {'✓' if ok else '✗'} {label} {reason_text}") else: - self.log_text.append(f"[结果] {user_id}-{idx}: ok={ok} {reason} (未在列表中找到匹配项)") + reason_text = f"失败原因: {reason}" if (not ok and reason) else reason + self.log_text.append(f"[结果] {user_id}-{idx}: ok={ok} {reason_text} (未在列表中找到匹配项)") # 只有 batch_video 类型任务才在这里更新计数（实时反馈） # single_video 和 image_folder 在 _on_batch_task_finished 中更新，避免重复计数 diff --git a/gui_worker.py b/gui_worker.py index b65e6e6..151d819 100644 --- a/gui_worker.py +++ b/gui_worker.py @@ -87,7 +87,7 @@ class WorkerThread(QThread): result = pdd.action(folder_path=folder_path, collect_all_videos=False) ok = bool(result.get("ok")) if isinstance(result, dict) else True if not ok: - self.log_message.emit(f"发布校验失败: {result.get('reason') if isinstance(result, dict) else ''}") + self.log_message.emit(f"失败原因: {result.get('reason') if isinstance(result, dict) else ''}") if isinstance(result, dict): self.item_result.emit({ "user_id": config.get("多多id", ""), @@ -127,7 +127,7 @@ class WorkerThread(QThread): result = pdd.action(folder_path=folder_path, collect_all_videos=is_batch_mode) ok = bool(result.get("ok")) if isinstance(result, dict) else True if not ok: - self.log_message.emit(f"发布校验失败: {result.get('reason') if isinstance(result, dict) else ''}") + self.log_message.emit(f"失败原因: {result.get('reason') if isinstance(result, dict) else ''}") if isinstance(result, dict): self.item_result.emit({ "user_id": config.get("多多id", ""), diff --git a/main.py b/main.py index 7fdf5b4..f977bbc 100644 --- a/main.py +++ b/main.py @@ -366,6 +366,12 @@ class Pdd: self.page.ele("x://*[text()='签约主播/作者']").click() logger.info(" ✓ 已点击'签约主播/作者'") + ele = self.page.ele("x://*[text()='我知道了']", timeout=3) + if ele: + ele.click() + logger.info(" ✓ 已关闭提示框") + time.sleep(1) + ele = self.page.ele("x://*[text()='我知道了']", timeout=3) if ele: ele.click() @@ -598,7 +604,7 @@ class Pdd: # if path_datas: # creator_tab.ele('x://*[text()="添加图片"]').click.to_upload(path_datas) - time.sleep(3) + time.sleep(1) # 点击立即发布选项 logger.info("=" * 50) @@ -624,6 +630,8 @@ class Pdd: time.sleep(1) else: logger.warning(" ✗ 未找到'定时发布'选项") + creator_tab.close() + return {"ok": False, "reason": "定时设置失败：未找到定时发布选项"} # 获取日期选择器元素 date_picker_ele = creator_tab.ele('x://*[@placeholder="选择日期"]', timeout=3) @@ -799,32 +807,34 @@ class Pdd: except Exception as e: logger.warning(f"点击确认按钮失败: {e}") - # 验证设置是否成功 + # 验证设置是否成功（同时校验日期+时间） time.sleep(0.5) - check_js = """ - (function() { - const dateInput = document.querySelector('[data-testid="beast-core-datePicker-htmlInput"]'); - return dateInput ? dateInput.value : null; - })(); - """ - final_value = creator_tab.run_js(check_js) - - if final_value and final_value.strip(): - logger.info(f"日期选择器当前值: {final_value}") - # 检查是否匹配（允许时间有小的差异，因为可能只精确到秒） - if final_value.strip().startswith(date_str): - logger.info(f"成功设置定时时间: {final_value}") - else: - logger.warning(f"设置的时间可能不准确，当前值: {final_value}, 期望日期: {date_str}") + ok, reason, actual_date, actual_time = self._verify_schedule_value( + creator_tab, dt, video_container=None + ) + if ok: + logger.info(f"成功设置定时时间: {date_str} {time_str}") else: - logger.error(f"无法获取日期选择器的值，可能设置失败") + logger.warning( + f"设置的时间可能不准确，日期={actual_date} 时间={actual_time}, 期望={date_str} {time_str}" + ) + creator_tab.close() + return {"ok": False, "reason": reason} except ValueError as e: logger.error(f"时间格式错误: {self.time_start}, 正确格式应为: YYYY-MM-DD HH:MM:SS, 错误: {e}") + creator_tab.close() + return {"ok": False, "reason": "定时设置失败：时间格式错误"} except Exception as e: logger.error(f"设置定时时间失败: {e}") import traceback traceback.print_exc() + creator_tab.close() + return {"ok": False, "reason": f"定时设置失败：{e}"} + else: + logger.error("未找到日期选择器，可能设置失败") + creator_tab.close() + return {"ok": False, "reason": "定时设置失败：未找到日期选择器"} # 绑定任务 ele = creator_tab.ele('x://*[text()="点击绑定任务"]', timeout=3) @@ -1101,15 +1111,62 @@ class Pdd: try: # 定位并确认勾选“定时发布” if not self._ensure_schedule_selected(video_container): - logger.warning("未能切换到定时发布，跳过定时设置") + reason = "定时设置失败：未能切换到定时发布" + logger.warning(f" ✗ {reason}") + result_item = { + "index": str(video_info.get("index", "")), + "path": str(video_path), + "name": video_name, + "ok": False, + "reason": reason, + } + results.append(result_item) + if on_item_done and callable(on_item_done): + try: + on_item_done(result_item) + except Exception: + pass continue # 设置定时时间 - self._set_schedule_time(creator_tab, video_time_start, video_container, idx) + schedule_ok, schedule_reason = self._set_schedule_time( + creator_tab, video_time_start, video_container, idx + ) + if not schedule_ok: + reason = schedule_reason or "定时设置失败：未知原因" + logger.warning(f" ✗ {reason}") + result_item = { + "index": str(video_info.get("index", "")), + "path": str(video_path), + "name": video_name, + "ok": False, + "reason": reason, + } + results.append(result_item) + if on_item_done and callable(on_item_done): + try: + on_item_done(result_item) + except Exception: + pass + continue except Exception as e: logger.warning(f" ✗ 设置定时任务失败: {e}") import traceback traceback.print_exc() + result_item = { + "index": str(video_info.get("index", "")), + "path": str(video_path), + "name": video_name, + "ok": False, + "reason": f"定时设置异常: {e}", + } + results.append(result_item) + if on_item_done and callable(on_item_done): + try: + on_item_done(result_item) + except Exception: + pass + continue else: logger.info(f" 步骤2: 跳过定时任务（未设置定时时间）") @@ -1363,7 +1420,7 @@ class Pdd: if not date_picker_ele: logger.warning("未找到日期选择器") - return + return False, "定时设置失败：未找到日期选择器" # 点击日期选择器打开面板 date_picker_ele.click() @@ -1411,6 +1468,7 @@ class Pdd: time.sleep(0.5) else: logger.warning(f"未找到日期单元格: {day}") + return False, "定时设置失败：未找到日期单元格" # 点击时间输入框打开时间选择器（优先容器内） time_input = None @@ -1439,6 +1497,8 @@ class Pdd: time.sleep(0.8) except Exception as e: logger.warning(f"通过XPath也未能找到时间输入框: {e}") + if not time_input: + return False, "定时设置失败：未找到时间输入框" # 选择时间 hour_str = f"{hour:02d}" @@ -1510,6 +1570,7 @@ class Pdd: # 验证设置是否成功（优先从当前容器读取输入框值） time.sleep(0.5) + expected_str = dt.strftime("%Y-%m-%d %H:%M:%S") final_value = None try: value_ele = None @@ -1530,20 +1591,88 @@ class Pdd: if final_value and str(final_value).strip(): final_value_str = str(final_value).strip() - logger.info(f"日期选择器当前值: {final_value_str}") - if final_value_str.startswith(date_str): + logger.info(f"日期选择器当前值: {final_value_str}, 期望值: {expected_str}") + # 完整比较日期时间字符串 + if final_value_str == expected_str: logger.info(f"成功设置定时时间: {final_value_str}") + return True, "" else: - logger.warning(f"设置的时间可能不准确，当前值: {final_value_str}, 期望日期: {date_str}") + logger.warning(f"设置的时间可能不准确，当前值: {final_value_str}, 期望值: {expected_str}") + return False, f"定时设置失败：期望 {expected_str}，实际 {final_value_str}" else: logger.error("无法获取日期选择器的值，可能设置失败") + return False, "定时设置失败：无法读取日期选择器值" except ValueError as e: logger.error(f"时间格式错误: {time_start}, 正确格式应为: YYYY-MM-DD HH:MM:SS, 错误: {e}") + return False, "定时设置失败：时间格式错误" except Exception as e: logger.error(f"设置定时时间失败: {e}") import traceback traceback.print_exc() + return False, f"定时设置失败：{e}" + return False, "定时设置失败：未知原因" + + def _verify_schedule_value(self, creator_tab, expected_dt, video_container=None): + """ + 验证定时时间是否设置正确 + + Args: + creator_tab: 浏览器标签页对象 + expected_dt: 期望的 datetime 对象 + video_container: 视频容器元素（可选） + + Returns: + (ok, reason, actual_date, actual_time): 验证结果 + """ + try: + expected_str = expected_dt.strftime("%Y-%m-%d %H:%M:%S") + expected_date = expected_dt.strftime("%Y-%m-%d") + expected_time = expected_dt.strftime("%H:%M:%S") + + # 读取日期时间输入框的值 + final_value = None + try: + value_ele = None + if video_container and video_container != creator_tab: + value_ele = video_container.ele( + 'x://input[@data-testid="beast-core-datePicker-htmlInput"]', + timeout=1 + ) + if not value_ele: + value_ele = creator_tab.ele( + 'x://input[@data-testid="beast-core-datePicker-htmlInput"]', + timeout=1 + ) + if value_ele: + final_value = value_ele.attr("value") + except Exception as e: + logger.warning(f"读取日期选择器值失败: {e}") + + if not final_value or not str(final_value).strip(): + return False, "定时设置失败：无法读取日期选择器值", "", "" + + final_value_str = str(final_value).strip() + logger.info(f"日期选择器当前值: {final_value_str}, 期望值: {expected_str}") + + # 比较完整的日期时间字符串 + if final_value_str == expected_str: + return True, "", final_value_str[:10], final_value_str[11:] if len(final_value_str) > 10 else "" + + # 如果完整比较不匹配，尝试分别比较日期和时间 + actual_date = final_value_str[:10] if len(final_value_str) >= 10 else final_value_str + actual_time = final_value_str[11:] if len(final_value_str) > 11 else "" + + if actual_date == expected_date and actual_time == expected_time: + return True, "", actual_date, actual_time + + # 不匹配 + reason = f"定时设置失败：期望 {expected_str}，实际 {final_value_str}" + return False, reason, actual_date, actual_time + + except Exception as e: + logger.error(f"验证定时时间失败: {e}") + return False, f"定时设置失败：验证异常 {e}", "", "" def _ensure_schedule_selected(self, video_container): """确保切换到定时发布选项。""" diff --git a/user/user_data/BrowserMetrics/BrowserMetrics-697795FD-4B54.pma b/user/user_data/BrowserMetrics-spare.pma similarity index 82% rename from user/user_data/BrowserMetrics/BrowserMetrics-697795FD-4B54.pma rename to user/user_data/BrowserMetrics-spare.pma index ef16219..98fc2c0 100644 Binary files a/user/user_data/BrowserMetrics/BrowserMetrics-697795FD-4B54.pma and b/user/user_data/BrowserMetrics-spare.pma differ diff --git a/user/user_data/BrowserMetrics/BrowserMetrics-697CC4B6-2F80.pma b/user/user_data/BrowserMetrics/BrowserMetrics-697E3630-DCA8.pma similarity index 83% rename from user/user_data/BrowserMetrics/BrowserMetrics-697CC4B6-2F80.pma rename to user/user_data/BrowserMetrics/BrowserMetrics-697E3630-DCA8.pma index d08bb39..4e6044e 100644 Binary files a/user/user_data/BrowserMetrics/BrowserMetrics-697CC4B6-2F80.pma and b/user/user_data/BrowserMetrics/BrowserMetrics-697E3630-DCA8.pma differ diff --git a/user/user_data/CertificateRevocation/10307/_metadata/verified_contents.json b/user/user_data/CertificateRevocation/10307/_metadata/verified_contents.json deleted file mode 100644 index 5d19e73..0000000 --- a/user/user_data/CertificateRevocation/10307/_metadata/verified_contents.json +++ /dev/null @@ -1 +0,0 @@ -[{"description":"treehash per file","signed_content":{"payload":"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","signatures":[{"header":{"kid":"publisher"},"protected":"eyJhbGciOiJSUzI1NiJ9","signature":"L9wa9CxYCiLN3LGfDCio34UqBituUk-4k_q3H_PNf_fAhQAbVru03IuMWOOWu4l1Q1aW23z-YMLV4ODnFoTAgGlXO7rjuyAt_5mBt8jluTAe93PHS1P9rKWTqs6Z3qENYaW79ProSkUzUlVrrxL22KmlOxQNTB-xRKyY74MVLQgRdjiaao74MR28V687FfBXhq30HuJSUpe67Kc9s_cv5ljML9CC-zKS7XukzzggnKT015KjBoOasBC4AGKGteBAbg1ZhlYqGBMlCcNIl32a1t1aCtokWRXFpBE3u2QQ7pyC8_v9SjMWw8tS5oqSO39TeN2JQh4cPQLMx4DtJPrbOw"},{"header":{"kid":"webstore"},"protected":"eyJhbGciOiJSUzI1NiJ9","signature":"exsPHW9GxYkge29gKXpxCyw-Fc5nv9q6wf5yA6pb2nws8hnKA5iyDy4jTFZGZMI8ecuMvbTtNf634nqeuAMVjfY31MpkM6JLOCBolKKt-0UkgDQUcMemUQ2Asz-PrYhyZbkCcHdp3T_0vxH73Yr57hHDWdwy2BL6Grdbc8OW8roMrKCbMoPJql8MKZ44Hz6dha2EeZedhSayroCYO3sVTAxx_yGIhIj461kH1bq7ptp09-Xj17KjSVISAAR9MKGhe6p_hlOraOsVGDBkN0K9ZucjDDjqkruW9mQFJRxStTqYYOziMJ102LrbL_qXjPIttE8MrsLlW73IJg2YXcq82g"}]}}] \ No newline at end of file diff --git a/user/user_data/CertificateRevocation/10307/manifest.json b/user/user_data/CertificateRevocation/10307/manifest.json deleted file mode 100644 index d8849b1..0000000 --- a/user/user_data/CertificateRevocation/10307/manifest.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "manifest_version": 2, - "name": "crl-set-7963983377537360531.data", - "version": "10307" -} \ No newline at end of file diff --git a/user/user_data/CertificateRevocation/10307/LICENSE b/user/user_data/CertificateRevocation/10317/LICENSE similarity index 100% rename from user/user_data/CertificateRevocation/10307/LICENSE rename to user/user_data/CertificateRevocation/10317/LICENSE diff --git a/user/user_data/CertificateRevocation/10317/_metadata/verified_contents.json b/user/user_data/CertificateRevocation/10317/_metadata/verified_contents.json new file mode 100644 index 0000000..c242a16 --- /dev/null +++ b/user/user_data/CertificateRevocation/10317/_metadata/verified_contents.json @@ 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- fastpic.org  filmora.wondershare.de  financebuzz.com  flemmix.art - - forsal.pl + + flemmix.irish  gameswaka.com  @@ -100,9 +100,6 @@ anizle.org geekweek.interia.pl goniec.pl - - -googirl.jp gowdr.com  @@ -112,20 +109,11 @@ googirl.jp  hdzog.tube - -healthblog.life - -healthy.thewom.it - - highporn.net  hobby.porn  -hochi.news - - hotline.ua  hotmovs.tube @@ -136,6 +124,8 @@ hotline.ua  inporn.com + +interestingengineering.com  kadry.infor.pl  @@ -151,8 +141,6 @@ inporn.com  libgen.onl - -life.ru  lifehacker.com  @@ -171,11 +159,10 @@ libgen.onl meduza.io  megapolitan.kompas.com + + melisa.pl  metro.co.uk - - -michill.jp  militaria.pl  @@ -188,18 +175,24 @@ michill.jp motoryzacja.interia.pl  muzyka.interia.pl + +myshoppingblog.com net.hr  newrepublic.com + +news.ohmymag.com  news.swiatgwiazd.pl - -newso1.xyz - -nv.ua + +ngs.ru + + niezalezna.pl + + nudebase.com  nypost.com @@ -210,19 +203,18 @@ nypost.com  onninen.pl - -otonasalone.jp + +outliermodel.com  pagesix.com  parade.com + + pc-builds.com  people.com - - -plejada.pl  pogoda.interia.pl  @@ -237,6 +229,8 @@ plejada.pl privatehomeclips.com  przegladsportowy.onet.pl + +radaronline.com rg.ru @@ -248,39 +242,34 @@ plejada.pl rivestream.org  shawarmaday.com + + smaker.pl + +small-games.info  smart-flash.jp  sorularlaislamiyet.com  spammy.permission.site - - spidersweb.pl  sport.interia.pl  sport.tvp.pl  sportano.pl - - -stors3.xyz + +suburbanfinance.com  sundayguardianlive.com - -swimsuit.si.com  telemagazyn.pl  thehill.com  theprint.in - - thespun.com  toutelatele.ouest-france.fr - -trending.thespun.com txxx.com @@ -296,14 +285,10 @@ unherd.com upornia.tube  us.safecomputercheck.com + +vegas.ua  videocelebs.net - - voyeurhit.com - -w7.shahidwbas.tv - -wearmedicine.com  wiadomosci.onet.pl @@ -328,8 +313,10 @@ unherd.com www.3djuegos.com  www.adnkronos.com - -www.advocate.com + +www.agroinform.hu + +www.ahaber.com.tr  www.alvolante.it  @@ -341,15 +328,11 @@ unherd.com  www.apartmenttherapy.com  -www.aufeminin.com - www.auto-swiat.pl  www.autoblog.com  www.autodoc.pl - -www.automesseweb.jp  www.autoplus.fr  @@ -364,6 +347,8 @@ unherd.com www.bollywoodshaadis.com  www.boredpanda.com + +www.brocardi.it  www.bryk.pl  @@ -376,16 +361,12 @@ unherd.com www.championat.com  www.christianpost.com - -www.closermag.fr  www.cnet.com  www.creativebloq.com  www.cucchiaio.it - -www.dailykos.com  www.dailymail.co.uk  @@ -398,10 +379,10 @@ unherd.com www.dlink7.com www.e1.ru - - www.easeus.de  www.eatthis.com + +www.ecranlarge.com  www.eldesmarque.com  @@ -409,6 +390,8 @@ unherd.com  www.ensonhaber.com  +www.espinof.com + www.esquire.com  www.euro.com.pl @@ -444,8 +427,6 @@ www.geo.tv www.gobankingrates.com  www.guitarworld.com - - www.gzt.com  www.happyinshape.com  @@ -476,16 +457,18 @@ www.geo.tv www.infor.pl  www.inside-games.jp - -www.insidermonkey.com  www.interia.pl  www.jeuxvideo.com  www.justjared.com + +www.khabarfoori.com  www.kiplinger.com + + www.km77.com  www.komputerswiat.pl  @@ -500,8 +483,6 @@ 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+www.telepolis.pl  www.tgrthaber.com  @@ -655,8 +650,12 @@ www.rd.com www.thecelebpost.com  www.thedailybeast.com + +www.thenews.com.pk  www.thescottishsun.co.uk + +www.thespruce.com  www.thespruceeats.com  @@ -669,6 +668,8 @@ www.rd.com www.thevoicemag.ru  www.tmz.com + +www.tnaflix.com  www.tomsguide.com  @@ -708,10 +709,6 @@ www.rd.com  www.wallstreet-online.de  -www.wareable.com - -www.washingtontimes.com - www.wcostream.tv  www.whathifi.com @@ -721,8 +718,8 @@ www.rd.com www.wionews.com  www.woman.ru - -www.womansworld.com + +www.xataka.com  www.xozilla.com  @@ -745,12 +742,10 @@ www.rd.com yorozoonews.jp  young-machine.com - -yourchamilia.com  yts-subs.com - -zielona.interia.pl + + zawodtyper.pl  zywienie.medonet.pl  @@ -789,6 +784,8 @@ www.rd.com 827277.com  895yy.com + + abccprmi.com  abiceyo.sbs  @@ -832,8 +829,6 @@ ads4pc.com advtpro.com  aerodyne-int.com - -affinityglow.xyz  afterhours-fun.com  @@ -846,6 +841,8 @@ ads4pc.com ahimoma.sbs  aicompamatch.com + +aicompasslove.com  aicyly.com @@ -863,6 +860,8 @@ aicyly.com alternative-gals.com  amateurkinkycouple.com + +amazing-discoveries.com  amigaslindas.com  @@ -887,6 +886,8 @@ aicyly.com amplozing.com  andbestest.bond + +anetchitic.com  anexe.sbs  @@ -897,6 +898,8 @@ aicyly.com antrojoynd.com  arabellasalon.net + + ardorlink.xyz  arindytolof.com  @@ -951,12 +954,10 @@ arumuf.sbs azdjevents.com  b-d30.org + +backroomdigital.com  backuptwitter.com - -badandsexy.xyz - -bagelstravels.com  baldopalagro.com  @@ -1009,6 +1010,8 @@ biqund.com boldaffair.xyz  boldmediahq.bond + + bond-dash.com  bond-place.com  @@ -1019,8 +1022,6 @@ biqund.com bookishlove.xyz  bookwormduo.xyz - -bountybond.xyz  bountymatchmakers.xyz  @@ -1062,6 +1063,8 @@ brivox.lol buscasencuentras.net  butfishmattis.com + + buyflux.space  byomo.com  @@ -1113,8 +1116,6 @@ cdsyjt.com charmchasers.click  charmconnect.click - -charmrealm.xyz  chat-corner.com  @@ -1129,6 +1130,8 @@ cdsyjt.com chickengladiators.com  chjtljd.com + +choosegirls.click  chousyokufes.com  @@ -1151,6 +1154,8 @@ cdsyjt.com clean-find.com  cleansincedisorder.club + +click-circle.com  click-space.com  @@ -1160,6 +1165,8 @@ cdsyjt.com  clickamour.monster  + clopeate.com + clureple.com  coc-servers.com @@ -1211,8 +1218,6 @@ cdsyjt.com corporationslabs.bond  corporationsly.bond - - cosigona.com  counterate.bond  @@ -1223,6 +1228,8 @@ cdsyjt.com cripobuild.com  crocketsquaybistro.com + +crush-circle.com  crush-dash.com  @@ -1241,6 +1248,8 @@ cdsyjt.com crushloop.click  crypticoins.com + + cueflirt.xyz  cugoja.sbs @@ -1254,10 +1263,8 @@ cugoja.sbs cupidabo.com  cupidcompass.click - - cupidecho.pro - - cupidecho.xyz + +cupidkey.click  cupidsayshi.click  @@ -1271,6 +1278,8 @@ cugoja.sbs czhuik.com  dach-liga-homocystein.org + +daretodateboldly.com  dashuncw.com  @@ -1295,8 +1304,6 @@ czhuik.com datecircley.com  dateconnectly.com - - dateflow.xyz  datefusion.click  @@ -1321,8 +1328,6 @@ czhuik.com dateuno.com  datewaypoint.com - -datewhisper.pro  datiklaw.com  @@ 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eguwi.sbs + +ehlkelawoffices.com  ekuhuguy.sbs  elahiyuf.sbs - - elayixog.sbs  electionhelper.com  @@ -1492,8 +1519,6 @@ $ecommercesoftwaresolutionsonline.com elegant-question.com  elinizefo.sbs -# -eliteconnectprofessionals.com $ elitematchmakersconnection.com  @@ -1512,6 +1537,8 @@ $ eloritiho.sbs  email-cible.com + + emolinuba.sbs  emotionforyou.xyz  @@ -1557,6 +1584,10 @@ erelda.xyz exitthewho.com  expertjobmatch.com + +explorelovenetwork.com + +expression-freedom.com  exthe.lat  @@ -1599,6 +1630,10 @@ erelda.xyz feedtofap.com  feel2more.com + +feelmylove.click + +felicitymatch.xyz  feman.bond @@ -1628,8 +1663,6 @@ feman.bond findshortsmall.com  findyourglow.xyz - -findyourmatchnow.monster  findyourpartnerinlife.com  @@ -1651,14 +1684,16 @@ feman.bond  flirt-club.com  +flirt-hive.xyz + flirt-line.com  +flirt-pulse.xyz + flirt-vibes.com  flirtandlucky.com  -flirtatiouslane.com - flirtdreamworld.com  flirtflow.click @@ -1666,8 +1701,6 @@ feman.bond flirtfriendly.com  flirtfuel.xyz - -flirtlounge.xyz  flirtmelt.xyz  @@ -1676,12 +1709,8 @@ feman.bond flirtspace.monster  flirtyfingers.click - -flirtyneighbors.xyz  flirtypussies.com - -flirtzonehub.xyz  fluxlove.xyz  @@ -1704,6 +1733,8 @@ feman.bond freeletterfromsantaclaus.net  fresh-vibe-place.com + +friendlymeetworld.com  frillier.bond  @@ -1712,10 +1743,10 @@ feman.bond frontline-selling.com  fruitful-connections.com - -fuckinghotmilfs.com  fuckthisgirls.xyz + + fulatilly.com  fun-2night.com  @@ -1739,8 +1770,6 @@ fynweb.com gadgetreviewblog.com  gallymatomine.com - -geeksunite.xyz  geguruyuv.sbs  @@ -1749,18 +1778,24 @@ fynweb.com german0.xyz  getcorporations.bond + +getcreditscoreww.com  getdemomax.bond  getecodeal.sbs + +getfabulous.bond  getflash.bond + +getgoextreme.bond + +getgsm-tele.bond  getgsmmaps.cfd  gethorny.bond - -getinformations.sbs  getinterconnection.bond  @@ -1785,6 +1820,8 @@ fynweb.com getmobilenetworks.bond  getpleasure.bond + + getspace.bond  gettechmedia.bond  @@ -1811,8 +1848,6 @@ fynweb.com girlish.bond  girls4loves.xyz - -girlsforrelax.click  girlsteam.click  @@ -1823,16 +1858,22 @@ fynweb.com girlzsearch.com  giyab.sbs + +glimpse-vibe.com  globalconnectionly.sbs  globalheartbeat.top + +globalists.icu  go-love.xyz  goextremeapp.bond  goextremehub.bond + +goextremelabs.bond goldengoddessbath-body.com  @@ -1863,6 +1904,8 @@ fynweb.com gsmtowersapp.bond  gsmtowershub.bond + +gsmtowersly.bond  gsmwifi.bond  @@ -1897,12 +1940,8 @@ fynweb.com happydayscertification.com & happynewyear2016quoteswishes.com - - haqamutaf.sbs  haqar.sbs - -harmonyaiconnect.com  harmonydate.xyz  @@ -1934,6 +1973,8 @@ hclips.com heartstrings.monster  heartsynergy.xyz + + herducal.com  herecandy.com  @@ -2015,6 +2056,9 @@ iampua.com ihaveaconfessiontomake.com  ii41.com + + +ijoxiq.sbs  ikimeciz.sbs  @@ -2040,11 +2084,7 @@ $  info-feed.info  -informationsapp.sbs - informationvine.com - -informyouapp.sbs  inimema.sbs  @@ -2054,6 +2094,8 @@ $  instantmoan.com  +intelligentpairup.com + intellimatchworks.com  intellimatelink.com @@ -2100,6 +2142,8 @@ $  jiggly-hearts.com  +jimocelons.com + jobcenter.bond  jobdiagnosis.com @@ -2146,16 +2190,18 @@ jssfgt.com kiirajuniorprep.com  kindredspirits.click - -kismetconnects.xyz  kiss-circle.com  kiss-hub.com  kiss-link.com + + kiss-spot.com  kiss-vibes.com + +kissdash-flow.com  kissinferna.com  @@ -2222,11 +2268,13 @@ laloci.sbs  lasolascafe.com  -lastingaffinity.com +lastingbondshub.com  latina-match.com  lbl-holding.com + + lbxcy.com  lchpw.com  @@ -2243,6 +2291,8 @@ laloci.sbs leipprandi.bond  lejux.sbs + + lennaral.com  leonprous.com  @@ -2251,6 +2301,8 @@ laloci.sbs lex-press.com  licktaughigme.com + +lightheartedlink.com  limano.xyz @@ -2318,6 +2370,8 @@ limano.xyz lovecupid.xyz  lovedate.club + +lovedayapp.bond  lovedayly.bond  @@ -2362,6 +2416,8 @@ limano.xyz lovemethodslabs.bond  lovenestonline.xyz + +lovepathcommunity.com  lovepulse.club  @@ -2374,6 +2430,8 @@ limano.xyz lovesitehub.bond  lovesprout.biz + + lovestir.fun  lovevibeshub.xyz  @@ -2389,10 +2447,6 @@ limano.xyz  lustandwhisper.com  - lustorbit.pro - - lustorbit.xyz - lustwhirl.com  luvclicks.club @@ -2412,10 +2466,10 @@ limano.xyz marketingshowhq.bond  markting.sbs - -maskedhearts.xyz  match-dash.com + +match-spot.com  matchmakers.lat  @@ -2424,6 +2478,8 @@ limano.xyz matchmakerzone.xyz  matchmindfully.com + +matchmindsconnect.com  matchmindsdating.com  @@ -2434,8 +2490,6 @@ limano.xyz matchvoyage.xyz  matchwiseintelli.com - -matchy-corner.com  matrixmingle.click  @@ -2458,6 +2512,8 @@ limano.xyz mediafruitlabs.cfd  mediagurulabs.bond + +mediamodehq.bond  mediaonlinehq.bond  @@ -2484,10 +2540,14 @@ limano.xyz meet-place.com  meet-spark.com + +meet-vibes.com  meet-zone.com  meet4ripple.xyz + +meetaffair.com  meetandglow.xyz  @@ -2498,12 +2558,18 @@ limano.xyz meetbloomy.com  meetcirclehub.com + +meetcircleonline.com  meetconnectionhub.com + +meetconnectonline.com  meetfriendlyy.com  meetgalaxy.xyz + +meetgirltoday.top  meetgsmtowers.bond  @@ -2548,12 +2614,12 @@ limano.xyz meetsuper.bond  meetsuppliers.bond + +meettechnology.xyz  meetteleguru.bond  meettelemaxa.bond - -meettelenautics.bond  meettelework.bond  @@ -2637,6 +2703,8 @@ melvia.xyz misskrystal-lfnusqh.work  missmafalda-xfwkiqo.work + +missmaggie-rfmvaik.work  missmaybelle-gzsievl.work  @@ -2686,6 +2754,8 @@ melvia.xyz  moneyhub-aiwealth.sbs +moneyhub-aiwealthhub.click + moneyhub-aiwealthpro.click  moneyhub-aiwealthpro.sbs @@ -2697,6 +2767,8 @@ melvia.xyz moneyhub-analyticspro.sbs  moneyhub-bizpro.sbs + +moneyhub-brief.sbs # moneyhub-capitaladvisor.click ! @@ -2717,12 +2789,16 @@ melvia.xyz moneyhub-capitalnetwork.click ! moneyhub-capitalnetwork.sbs +" +moneyhub-capitalwealth.click ! moneyhub-capitalworld.click  moneyhub-capitalworld.sbs  moneyhub-cashpro.sbs + +moneyhub-compass.sbs  moneyhub-consultx.sbs  @@ -2737,6 +2813,8 @@ melvia.xyz moneyhub-databridge.sbs  moneyhub-dataflow.sbs + +moneyhub-datainsight.click  moneyhub-datalogic.click  @@ -2761,6 +2839,8 @@ melvia.xyz moneyhub-digitalmentor.click moneyhub-digitalmentor.sbs + +moneyhub-digitalmind.click $ moneyhub-digitaluniverse.click " @@ -2843,6 +2923,8 @@ $ moneyhub-finvision.click  moneyhub-finvision.sbs + +moneyhub-finwealth.click  moneyhub-fundspro.sbs " @@ -2853,8 +2935,6 @@ $ moneyhub-globalcapital.click moneyhub-globalcapital.sbs -! -moneyhub-globalfuture.click  moneyhub-globalfuture.sbs " @@ -2881,6 +2961,8 @@ $ moneyhub-globalvision.click  moneyhub-globalvision.sbs +! +moneyhub-globalwealth.click  moneyhub-growthflow.click  @@ -2901,6 +2983,8 @@ $ moneyhub-innovatepro.click  moneyhub-innovatepro.sbs + +moneyhub-insight.sbs " moneyhub-investadvisor.click " @@ -2943,6 +3027,8 @@ $ moneyhub-investvision.click  moneyhub-investvision.sbs +! +moneyhub-investwealth.click moneyhub-investworld.click  @@ -2963,6 +3049,8 @@ $ moneyhub-marketinsights.sbs  moneyhub-marketpro.sbs + +moneyhub-matrix.sbs ! moneyhub-moneyadvisor.click  @@ -2979,6 +3067,8 @@ $ moneyhub-moneyworld.click  moneyhub-moneyworld.sbs + +moneyhub-monitor.sbs ! moneyhub-networkchain.click  @@ -2993,10 +3083,18 @@ $ moneyhub-promentor.click  moneyhub-promentor.sbs + +moneyhub-pulse.sbs + +moneyhub-quantmind.click # moneyhub-quantumfinance.click ! moneyhub-quantumfinance.sbs + +moneyhub-radar.sbs + +moneyhub-review.sbs moneyhub-riskadvisor.click  @@ -3017,6 +3115,8 @@ $ moneyhub-smartfinance.click  moneyhub-smartfinance.sbs + +moneyhub-smartflow.click ! moneyhub-smartinsight.click @@ -3033,8 +3133,6 @@ $ moneyhub-techbridge.sbs  moneyhub-techcore.sbs - -moneyhub-techflow.sbs  moneyhub-techfuture.sbs  @@ -3049,6 +3147,8 @@ $ moneyhub-techvision.click  moneyhub-techvision.sbs + +moneyhub-tracker.sbs  moneyhub-tradechain.sbs @@ -3127,8 +3227,12 @@ $ moneyhub-wealthworld.click  moneyhub-wealthworld.sbs + +moneyhub-wise.sbs  montlakemadness.com + +moonlightdate.xyz  moonlitmatch.click  @@ -3182,11 +3286,15 @@ mrgay.tube mrs-helene-utejypd.work  mrs-icie-rhgzfri.work + +mrs-kristy-dunupve.work  mrs-lurline-wacejhm.work  mrs-maci-olqsgns.work  +mrs-retta-kezcwer.work + mrs-rubye-qmrnvtv.work  mrs-sabina-rkxmcpo.work @@ -3205,6 +3313,8 @@ mrgay.tube  ms-astrid-oayfoqy.work  +ms-elouise-juoabyi.work + ms-emmalee-sbhujum.work  ms-felicia-jrgorfj.work @@ -3224,8 +3334,6 @@ mrgay.tube ms-meta-wbqitno.work  ms-rosalia-iksaloe.work - -ms-rosie-ichtqdk.work  ms-tess-lijvppo.work  @@ -3277,30 +3385,28 @@ mudire.com netteles.bond  networknest.click - -newarsinsikkim.org  newcumslut.bond  newlywed.lat  newsmediaa.bond - -newtinder.dating  newtoki115.com  newyorksbars.com  nextdoornights.org - - nextflirt.xyz  nightfun.xyz + +nightlane-vibes.com  nightneighbors.org  nightromancecity.com + +nighttalk-link.com  nikecompany.net  @@ -3308,6 +3414,8 @@ mudire.com nixode.com  nlinebest.sbs + + nocatint.com  nocortossm.com  @@ -3324,10 +3432,6 @@ nixode.com nonymous.sbs  normalhq.sbs - -nosehabladebruno.com - -nosseropers.com  nostringsmatch.com  @@ -3348,12 +3452,12 @@ nixode.com notshylady.xyz  notsleep.xyz + +nowmeetgirls.monster  nude2babe.com  nummusely.com - -nuviasmilesmail.com  nycppe.org @@ -3383,6 +3487,8 @@ nycppe.org olkl.org  olomuxab.sbs + + omaroxujo.sbs  omgsweeps.info  @@ -3407,6 +3513,8 @@ oninir.sbs  openeco.sbs  +openerobox.sbs + openflash.bond  openflirt.xyz @@ -3416,6 +3524,8 @@ oninir.sbs opengsm-tele.bond  opengsmtele.bond + +openheartedexplorers.com  openhorny.bond  @@ -3470,6 +3580,8 @@ oninir.sbs p-upssies.xyz  pair-circle.com + +pair-corner.com  pair-dash.com  @@ -3502,12 +3614,16 @@ oninir.sbs penisextendersfeedback.com  peoplemeetplace.com + +perfectlabs.sbs  perfectly.sbs  perfectlymatched.monster  pfll.org + + philip25.xyz phillipshomeinspection.com  @@ -3566,8 +3682,8 @@ ppgopp.com princessaliza-kmgscbf.work princessamiya-aotnakx.work - -princessaylin-wmsqytv.work + +princessanna-nfiouab.work princessbella-gncmbqb.work @@ -3602,6 +3718,10 @@ ppgopp.com princessphoebe-bwypsix.work princessretta-sfkzthf.work + +princessreyna-aiygmnf.work + +princessrose-hdscdpq.work  princessviva-atlrwpi.work ! @@ -3658,8 +3778,8 @@ ppgopp.com ptaimpeerte.com  ptifirelaria.com - - purematch.xyz + +purehearts.xyz  pussy-airlines.com  @@ -3674,8 +3794,6 @@ ppgopp.com queenalice-buogybc.work  queenaudra-jigqwlq.work - -queenayla-irejltd.work  queencamilla-pyurmix.work @@ -3698,6 +3816,8 @@ ppgopp.com queenjeanne-kroijgs.work  queenjustine-oqiekdg.work + +queenkaylee-bsaqbdv.work  queenlaila-garrjxm.work  @@ -3771,16 +3891,12 @@ qukoju.sbs redsevenlinux.com  reignificence.bond -! -relationshipadventurers.com " relationshipelitenetwork.com  relationshipgem.com  relationshipintellect.com - -relationshipproelite.com  relaxedromancezone.com  @@ -3811,8 +3927,6 @@ qukoju.sbs robocaller.bond ! rocketracingproductions.com - -rofforoofing.com  rolaurbusly.com  @@ -3827,8 +3941,8 @@ qukoju.sbs romance-wave.com  romanceflux.xyz - -romancefun.fun + +romancelitelink.com  romanceroute.click  @@ -3867,16 +3981,14 @@ qukoju.sbs savesaintjamesthegreat.org  secondchapter.xyz + +secret-discoveries.com  secretneighbors.xyz  secretromancespot.com  selfdefensecorp.com - -seniorspark.xyz - -sensualoverload.com  sententias.org  @@ -3889,6 +4001,8 @@ qukoju.sbs seriouloveconnection.com  seriouslovelinks.com + +seriouslovepursuit.com  sex-friend-finder.com  @@ -3927,8 +4041,6 @@ qukoju.sbs shekinahgospelmissions.org  shenaniganbooks.com - -silentkiss.xyz  simple-decisions.com  @@ -3957,6 +4069,10 @@ qukoju.sbs snapheart.xyz  snappyhello.com + +socialbondcommunity.com + +socialdatinghub.com  socialmeetworld.com  @@ -4033,8 +4149,6 @@ qukoju.sbs stimprograms.com  stjohnonbethalgreen.org - - stlyz.com  storytellerscontracts.com  @@ -4055,8 +4169,6 @@ qukoju.sbs sugarchecker.com  sunprestion.com - -sunsetdate.xyz  supcurtee.com  @@ -4087,6 +4199,8 @@ qukoju.sbs swarpshles.com  sweepscentreusa.com + +sweetaffinity.click  sweetchapter.xyz  @@ -4113,8 +4227,6 @@ qukoju.sbs syncdate.monster  syncedsoulmates.com - -syncsmartromance.com  synthomateai.com  @@ -4130,12 +4242,12 @@ szfywl.com takaramonroe.com  takemynow.com + + talk-line.com  talk-match.com  talk-vibes.com - - talk-wave.com  talkandmeet.xyz  @@ -4151,8 +4263,6 @@ szfywl.com  tcheturbo.com  -teasetrack.pro - teasetrack.xyz  techmediahq.bond @@ -4188,6 +4298,8 @@ szfywl.com teleriddleapp.bond  teleriddlehub.bond + +teleriddlely.bond  televolume.bond  @@ -4245,12 +4357,12 @@ thegay.com theikarialeanbellyjuice.com  thekisstoday.bond - -thelovealgorithmworks.com  thelovecode.xyz  thelovely.bond + + thelucky.sbs  themattress4u.com  @@ -4277,6 +4389,8 @@ thegay.com thesuper.bond  thetechpark.xyz + +thetele-g5.sbs  thetelefon.bond  @@ -4291,6 +4405,8 @@ thegay.com thinkanddone.com  thinkmatch.top + +thorhortizinity.com  throbs.bond  @@ -4303,8 +4419,6 @@ thegay.com timeoflove.click  timesbestseller.sbs - -timeyourdate.xyz  tjjinchanyi.com  @@ -4313,11 +4427,19 @@ thegay.com tomas-moviez.com  topfabulous.bond + + topmatch.bond + + topspace.bond  topwow.bond + +tornillosmarina.com  torridcard.org  + trablenic.com + trailmate.xyz  travelall.lat @@ -4334,7 +4456,9 @@ thegay.com  trendndailyus.com  -truecommitment.xyz +truelovequests.com + +trueloveseekersclub.com  trueneighbors.club  @@ -4352,8 +4476,6 @@ trychk.com trydevtools.sbs  tryenjoyourday.bond - -tryexciting.bond  tryflash.bond  @@ -4366,8 +4488,6 @@ trychk.com trygsmworlds.bond  tryhorny.bond - -tryinternetmedia.cfd  trykisstoday.bond  @@ -4378,6 +4498,8 @@ trychk.com tryluck.bond  trymediabuy.xyz + +trymediamode.bond  trymediarea.sbs  @@ -4442,6 +4564,8 @@ trychk.com unonstistret.com  unreal-chatties.com + +unrecaccess.com  untiested.com  @@ -4459,6 +4583,8 @@ trychk.com  uriosibobs.com  +urisconeremid.com + useboldmedia.bond  usecorporations.bond @@ -4467,6 +4593,8 @@ trychk.com  usedater.bond  + useerobox.sbs + usefancy.bond  usegsmtele.bond @@ -4480,8 +4608,6 @@ trychk.com uselovesite.bond  usemarketingshow.bond - -usemasterpiece.bond  usemediafruit.cfd  @@ -4504,6 +4630,10 @@ trychk.com usetelenetwork.sbs  usetelevolume.bond + +usewifiarena.bond + +usewifilead.cfd  usmlepearls.com  @@ -4518,9 +4648,6 @@ trychk.com valuesalign.xyz  vdajyi.space - - -velana.xyz  venturemetro.com  @@ -4590,6 +4717,8 @@ w-news.biz wifitechs.bond  wildandffun.com + +wildmatchup.pro  wildpassionhub.com  @@ -4600,6 +4729,8 @@ w-news.biz winky-chats.com  wireblockchain.com + +wishaffair.com  wistchish.com  diff --git a/user/user_data/Crowd Deny/2026.1.29.121/_metadata/verified_contents.json b/user/user_data/Crowd Deny/2026.1.29.121/_metadata/verified_contents.json new file mode 100644 index 0000000..ad49282 --- /dev/null +++ b/user/user_data/Crowd Deny/2026.1.29.121/_metadata/verified_contents.json @@ -0,0 +1 @@ +[{"description":"treehash per 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C:\Users\27942\Desktop\codes\haha\user\user_data\Default\File System\Origins/MANIFEST-000001 +2026/02/01-01:04:50.077 defc Recovering log #9 +2026/02/01-01:04:50.077 defc Reusing old log C:\Users\27942\Desktop\codes\haha\user\user_data\Default\File System\Origins/000009.log diff --git a/user/user_data/Default/File System/Origins/LOG.old b/user/user_data/Default/File System/Origins/LOG.old index 72b947c..b331d62 100644 --- a/user/user_data/Default/File System/Origins/LOG.old +++ b/user/user_data/Default/File System/Origins/LOG.old @@ -1,3 +1,3 @@ -2026/01/30-22:46:22.373 18a0 Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\File System\Origins/MANIFEST-000001 -2026/01/30-22:46:22.373 18a0 Recovering log #6 -2026/01/30-22:46:22.373 18a0 Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\File System\Origins/000006.log +2026/02/01-01:01:54.557 b8e8 Reusing MANIFEST C:\Users\27942\Desktop\codes\haha\user\user_data\Default\File 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a/user/user_data/Default/File System/Origins/lost/MANIFEST-000001 and b/user/user_data/Default/File System/Origins/lost/MANIFEST-000001 differ diff --git a/user/user_data/Default/GCM Store/000003.log b/user/user_data/Default/GCM Store/000003.log index fe69971..6505a25 100644 Binary files a/user/user_data/Default/GCM Store/000003.log and b/user/user_data/Default/GCM Store/000003.log differ diff --git a/user/user_data/Default/GCM Store/LOG b/user/user_data/Default/GCM Store/LOG index 9a54e38..0c41954 100644 --- a/user/user_data/Default/GCM Store/LOG +++ b/user/user_data/Default/GCM Store/LOG @@ -1,3 +1,3 @@ -2026/01/30-22:48:26.857 4cfc Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\GCM Store/MANIFEST-000001 -2026/01/30-22:48:26.857 4cfc Recovering log #3 -2026/01/30-22:48:26.858 4cfc Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\GCM Store/000003.log +2026/02/01-01:04:55.332 b5c0 Reusing MANIFEST C:\Users\27942\Desktop\codes\haha\user\user_data\Default\GCM Store/MANIFEST-000001 +2026/02/01-01:04:55.332 b5c0 Recovering log #3 +2026/02/01-01:04:55.335 b5c0 Reusing old log C:\Users\27942\Desktop\codes\haha\user\user_data\Default\GCM Store/000003.log diff --git a/user/user_data/Default/GCM Store/LOG.old b/user/user_data/Default/GCM Store/LOG.old index b084370..4a8eec4 100644 --- a/user/user_data/Default/GCM Store/LOG.old +++ b/user/user_data/Default/GCM Store/LOG.old @@ -1,3 +1,3 @@ -2026/01/30-22:46:33.257 d78 Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\GCM Store/MANIFEST-000001 -2026/01/30-22:46:33.258 d78 Recovering log #3 -2026/01/30-22:46:33.259 d78 Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\GCM Store/000003.log +2026/02/01-01:01:59.461 b4a8 Reusing MANIFEST C:\Users\27942\Desktop\codes\haha\user\user_data\Default\GCM Store/MANIFEST-000001 +2026/02/01-01:01:59.463 b4a8 Recovering log #3 +2026/02/01-01:01:59.465 b4a8 Reusing old log C:\Users\27942\Desktop\codes\haha\user\user_data\Default\GCM Store/000003.log diff --git a/user/user_data/Default/GPUCache/data_0 b/user/user_data/Default/GPUCache/data_0 index 606f22f..7ed72cb 100644 Binary files a/user/user_data/Default/GPUCache/data_0 and b/user/user_data/Default/GPUCache/data_0 differ diff --git a/user/user_data/Default/GPUCache/data_1 b/user/user_data/Default/GPUCache/data_1 index edbb8ed..b4491eb 100644 Binary files a/user/user_data/Default/GPUCache/data_1 and b/user/user_data/Default/GPUCache/data_1 differ diff --git a/user/user_data/Default/GPUCache/data_2 b/user/user_data/Default/GPUCache/data_2 index 97e8984..e8107f1 100644 Binary files a/user/user_data/Default/GPUCache/data_2 and b/user/user_data/Default/GPUCache/data_2 differ diff --git a/user/user_data/Default/History b/user/user_data/Default/History index 69e8545..7b4839c 100644 Binary files a/user/user_data/Default/History and b/user/user_data/Default/History differ diff --git a/user/user_data/Default/JumpListIconsRecentClosed/3764588b-9fe6-403b-a41e-3e9a473bedad.tmp b/user/user_data/Default/JumpListIconsRecentClosed/cad3c7f4-7edc-46c9-b13c-aba122b3b5c5.tmp similarity index 100% rename from user/user_data/Default/JumpListIconsRecentClosed/3764588b-9fe6-403b-a41e-3e9a473bedad.tmp rename to user/user_data/Default/JumpListIconsRecentClosed/cad3c7f4-7edc-46c9-b13c-aba122b3b5c5.tmp diff --git a/user/user_data/Default/Local Storage/leveldb/000003.log b/user/user_data/Default/Local Storage/leveldb/000003.log new file mode 100644 index 0000000..511868f Binary files /dev/null and b/user/user_data/Default/Local Storage/leveldb/000003.log differ diff --git a/user/user_data/Default/Local Storage/leveldb/000005.ldb b/user/user_data/Default/Local Storage/leveldb/000005.ldb deleted file mode 100644 index a2576fb..0000000 Binary files a/user/user_data/Default/Local Storage/leveldb/000005.ldb and /dev/null differ diff --git a/user/user_data/Default/Local Storage/leveldb/000008.ldb b/user/user_data/Default/Local Storage/leveldb/000008.ldb deleted file mode 100644 index ea0b1d7..0000000 Binary files a/user/user_data/Default/Local Storage/leveldb/000008.ldb and /dev/null differ diff --git a/user/user_data/Default/Local Storage/leveldb/000010.ldb b/user/user_data/Default/Local Storage/leveldb/000010.ldb deleted file mode 100644 index 4ae1af1..0000000 Binary files a/user/user_data/Default/Local Storage/leveldb/000010.ldb and /dev/null differ diff --git a/user/user_data/Default/Local Storage/leveldb/000011.log b/user/user_data/Default/Local Storage/leveldb/000011.log deleted file mode 100644 index 4d0d8ee..0000000 Binary files a/user/user_data/Default/Local Storage/leveldb/000011.log and /dev/null differ diff --git a/user/user_data/Default/Local Storage/leveldb/LOG b/user/user_data/Default/Local Storage/leveldb/LOG index 0713f30..5217b6f 100644 --- a/user/user_data/Default/Local Storage/leveldb/LOG +++ b/user/user_data/Default/Local Storage/leveldb/LOG @@ -1,3 +1,3 @@ -2026/01/30-22:48:22.438 2eb0 Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\Local Storage\leveldb/MANIFEST-000001 -2026/01/30-22:48:22.442 2eb0 Recovering log #11 -2026/01/30-22:48:22.445 2eb0 Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\Local Storage\leveldb/000011.log +2026/02/01-01:04:49.210 d810 Reusing MANIFEST C:\Users\27942\Desktop\codes\haha\user\user_data\Default\Local Storage\leveldb/MANIFEST-000001 +2026/02/01-01:04:49.214 d810 Recovering log #3 +2026/02/01-01:04:49.217 d810 Reusing old log C:\Users\27942\Desktop\codes\haha\user\user_data\Default\Local Storage\leveldb/000003.log diff --git a/user/user_data/Default/Local Storage/leveldb/LOG.old b/user/user_data/Default/Local Storage/leveldb/LOG.old index 444645b..40cf887 100644 --- a/user/user_data/Default/Local Storage/leveldb/LOG.old +++ b/user/user_data/Default/Local Storage/leveldb/LOG.old @@ -1,3 +1,3 @@ -2026/01/30-22:46:21.597 5448 Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\Local Storage\leveldb/MANIFEST-000001 -2026/01/30-22:46:21.601 5448 Recovering log #11 -2026/01/30-22:46:21.604 5448 Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\Local Storage\leveldb/000011.log +2026/02/01-01:01:53.690 b404 Reusing MANIFEST C:\Users\27942\Desktop\codes\haha\user\user_data\Default\Local Storage\leveldb/MANIFEST-000001 +2026/02/01-01:01:53.741 b404 Recovering log #3 +2026/02/01-01:01:53.746 b404 Reusing old log C:\Users\27942\Desktop\codes\haha\user\user_data\Default\Local Storage\leveldb/000003.log diff --git a/user/user_data/Default/Local Storage/leveldb/MANIFEST-000001 b/user/user_data/Default/Local Storage/leveldb/MANIFEST-000001 index 8f04c72..18e5cab 100644 Binary files a/user/user_data/Default/Local Storage/leveldb/MANIFEST-000001 and b/user/user_data/Default/Local Storage/leveldb/MANIFEST-000001 differ diff --git a/user/user_data/Default/Network Action Predictor 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","hash":"tA+TGTqmOnqzcuikk/ZeDDQ6JWc=","signature":"mLVIYMbhgAF9GYIYnF9Tdo91enWMgEinbHXEQHp5PGg=","timestamp":"1769784565"},{"data":"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tUOC6m2rj6T8aBlnS+ghSiFe3R/m7bXuZv4VxAT7pQQSqqxKWLBqTx3nr9bLZ2NmhoHwMraEQH1G7L4U43anafB1tseCU3QjDlOW4BA4cYAYlWSFUt7HuSuO4bJDryKjjLCNa4Rfyyrga3n9SSMGQt8mhAypLK3xR7WXhHZYgVr+aSWcjHUyJ9yN06D1R23mBNirQWy6F54VZOca1v1YSRhH9rwqw1GW84k5IUwuxPs67+x3JzqRA9Gvncw/vy3OvhBMH/NdzMHlwblX7fL4Yg/EQRjRIyOt+6/W4cbBlESLKkQTkuk4H1WDpxXIIVTOEFlldzT6pAdm1Rjz5Wjl/Qs+2Gb3Ix0eWtXubVHl9UTJ1jfqZRwq0RBBEi6tH4JTnNzC5UuUkQSAxAbjs8ere81t0CXn66dYjhVdyb+2dYXsul3i9kIf/LMQWv4ua+nankdVzU1hwlYNNWIyCxKto0c0mZncnz7GBD5qaDf/ulhnwpsCW/5cQEBk32UJ9rWMveHG7HzNuPPz6nJONmiwpWqHk197kH5A7jldzTL1pezUXlmAksz3HbP5jD4V0WvJZ7vc0bnuZXExS8lntcUA/OZjYnOWZv7wxJGwfwKu7uzYsMr+VurXrHwNzLS9j/vGqTGPTpzUeF3e0Nt+DQw4d7sFzheCWHSOObgk5QyRyqMSeCkue4p/nV4HFBvf+ah981kgtyCJg1uc6mw77wKea+aYlvzMg3gPMLrOiCPj8c8nJM+4nDYN2Nnaa8iuTkVRzJqy3KK/oh37u51TotC0uAyZsCaKvjViOtTqTj37a3WBnN682K19pWyYIM3Bo6nuX0kjDAXwl4uHJYpVQCUeyKvNe3vpC8aNxFuPhu717m/0EX9UL7yp/sd6Wp3yJ4NfHEboZX4n74f9ALZZH7zsml8h5kzYYrn1czcr8XG4FiWVSpztnAuFpXf8DxnN/k6Y063Y9XPb7dsSKk8URasEbdCCpifCBeCabkF9ag1cn7ukSDNiE6ry159iDPwQLHq7hohrRnPAMbGDJ5jjGQyYiVUXeHN/ZL8wxnYbOmGDk1VxeaENXYlqR6wGCBFVuheeb3b/ZdmZICsyz+kTHMCO7mtjzL9SBMaH7PRGl0tl7o94K4AVNgHv6oLv4c2vIqbjBEM2IAOjzy0qF5ixq2gaUsKdWUCE88zTSEOwRmhBMgJRsI3w5QQYxAFuFrly4cmzURFlnzLKflWc6UV3I6whvWHRbkOysoJQ9MbAK4QhWe5ZqU4F9B+VfL/CuLNeJ804ULBsTf6AHXS454q2IjXiIs+qPw3mrrs4fXn4I5lv9NMY4oqk7Q9JzbF7PBr3hliBK0glKiHi0t0/zS9smhtYnE1mAh77dEHTTI4qaM2JxVVX/Uu1EZCVEZ9X5zZWnwuanPIcWCmqa8CpTCOTxL1KQhNYKWVwESjmOzO6v+kXYxm2o+I1lNRT069LL1/KYhboclRGl0fcCwJ2+Tah0ELbbUeZZjjcYyqEUD8jF/ecFs+NvawBCVqONZYEU9SsyNs/x2dfVTQkYplkfj9J0G39zTQgXPcQuWBhdeyflDKM9yvXk1F8dAOiNWRFvsu0291VLdB87jkvD45wC3iV7geJYz0C/FSmjdhyvvXg0LrgmzcPuaCNMZojc5MppqkNHUmJicnFgGWdQe23nZyz+sIBERdhoTy9yfV4JeqCHWQZEmJ3ZMMpg+gAysfUNJl/WGOKyYluIZoeCmYRW8QglvVUQZz+cgyZSM/Ft6yDEIStEC5T3ZGXC5WsoT0BFrAVtXx/2UfQtPWYwmhWJLHVp9rrllqG9bvEIAtWAmeqBxyPvshwc/QmCOUhrHSg4Aj21nXs15QQ1SDDVrsFHSLH9D1QcRviuJ/a8QlKIzOlWgXpl4ftZSsJV6gFoQdF2DZzO1o+zRVpNby+bcWLMMdihIPVleQ+opsGJFdNn+ROyzrNbWsEpDphxuytLE6nYRsE72h1BBKdqiptvtbLrYpqrgEO6h0ryacwF/QSG6ocUnXc84dA/whWt0KGgkExJTY0vk1aOJAxa/CjONNkjDQ49+xHfzUjdIPEEQDmIN1NzF9OqtOlNPwm5nXsl1IhUaIQCv4hYxpIeO40qquI9U8OxlYTqG7xTwWSkaUNkpGz9cv7DlKDxV8RrOBLTCVjOxF9oU4hPYukqVybArjyUD5z0GjJCJO5sVzmHJqhCeePMqTikkOfMqTi1cxEVzQh9eyZmSlZNeMJBKWZImUpEmwhX059VcKPQWVKKAomYfLJxn18Mfvut5jpvLwAKGGAp3WXjNCkpRQMEdo4cbHqU4wpkmcg4HOQeIsxg0M+hy2dWP+12GmQ68kqsAuCUqkZZwJwVW4ZWcF0n7kEbwh6qky2uQt7V5JVeHpOsToRMCYUS4tob25H1nogZ6k3eRMFRQ8hpuNERRPqcxMJch2bcysI8R1zJI36Pt8mZPhFXwcF4ZXo3ZERoQhsJ5FecubMa9XkVoR3jqxKs4H+Eiw2sIU8dxK9cQnuMstYVRvIqrI0RjXH0hAatfzNo8nBnzthb3RWfhAE5j/qbgHJjBPMwY4fCoikcSi1OVPKI8Cjex4GkY3aubdt+wr2QgOf21js+4mfDAe2VyACTLMgIUgh3RcE6iHg1wyhRraDYopKFYE8UrTtql5lYyh4WmZIi8sSVDJJWuKzuRKeVO1pX1iEw1JcMD94Ip6P+SiHvSO9UL+Rz2XJKICiIRLZDFKueKV74MvA5KMi+Uoj0Sy4YumvF9/A9oIol+PSFjgNKiI4KuV/a+2L1nLVwwI3QceBWwwnIzItzgL4kzsr02udrbvPcyQVu0dEVq7OtagUPAgXC+1Yy8cRDHoHNOU4KWpjVaB68n0xV5KcK7gvCOyNC2IwyYkqFdhgztMmRoB2JJLVQjImMIr+R6C7V4FRfHCHV5FZfOCOZUTnJ41ChghVLQ8ApuPl6hJpnCLb0YiHqNnLDyaKtJfWCavqiSpOzSRD64EOcC1gaEEh7KhJKoR7unRo4JHRS2QuodHmmjljVhk9svhWVKwotC1h4BSLP07L4eyY1i4QZt+nDS4VVIv5kV8yLgYa0GjnAQCr1FB3T4/MeDiUFjTSAOEap4pBGqglK8zKA7ncSYyvaZ5eEuEJKmxUiqizkm1JLSwlaMEhCplpZICGpDmZGJhyW0OWkEvWTlYKwFz3JYolhJNg9+Y4NlN2fHs5y9LGsciTguCxVINTxAJDn9oCrPcrWInRdC6A3nFVwUwyu4mdgoXcDAKgy3MXCEES3Q8DujxFvdhQ7y4LFB95dOWj+n3ZrJcOABw3Pce1eIqSooxcqow1yVyZUXR6vCDLw8eMfAJ0xpBgtzMAebWNiOYaYCshRiRZQQ0rWKaceslTi3gsvEHHzB+ZewcBznu6mAxZjqHmH8s/g+R/b8J1Qt0JRz5sr5/cKqkcW4WlCK5VCNc39E36xj2wEKOFoQx31hYAlL2uUlCysUojVyjraZX33fiFUQi6k7QAVBKVojkwvsrnVPvx8qia0bMz2kfdN+hym2LLgQ7NrOAUsLWtRuRrGlCVaPzm7YXsXLtfl1aVyWQyMiapfquv/INliKeBWXS2XnXBYOY/iWhW0KsTLqdv8gtzvkfVecqajOE1mYgnPNY2EBhgsVkKAQy6HlOa2sbOadMfwDydLIt821kI6X7ftBGZ4FJRl/dMGKhZEdqnh9XJUuMe4jwFT2j2GPK27SEZ23v742v9dweQjoUY76TKOkZcmpcq2YK3+41wpOMYMBRFxQTaim1CVjTI+O9ivX6arbgxmyradu5HT39cW55+ENW8yCK2ZXgItoh/Y7az+uCd1/AsKlmaDGkk9gxdKoy8tmD21ds3qDudFPJAtubD2s9rKemjclqolsPfRv93LfhoZvHxIEtpsb7538wC5s1Ug5x/THW8ckVy10JojSIo+uBzrtjczMDv9VjpRGMW8gvkIrbSmIMLp5sKtVEhY8+tBjqf5J9JBJEPfzp3rUS2/tq6rTsJVUsDWaFnzB+8nJus3hLa5gc+hC2LFaPGFC/7hni2T+Au/eXFm/Xp9nsl0/Z9eKVs7H2SEyIrx130mu8/UaGdG1T+SIgfXX5ciIJt8uLTG36sHIRD9t7+65I6y1UXjaoISWD1zzs0fp4NxkbFbGVIUrzQiXT1uNW9uw0uvecFAjGTF4LZB61274wZz+L+Xvp9oeKnBc6LIVNr3B319pBm8GCEpxBYNmetrWrT77Wm+YHp+hoDqMCHYVUR5mRHmUIa0VTJXHn7waK49zeAL8JfMncUToCzl+vJpboRT2lMVjXCVMUfMqbj4nDOFVXJKpwPMq7paeLIBzDHgdwy0pg1c43HtXAmKqEhPxSjNBwyPuzQBYuowRFGIHdJDZnXo3ZZAjrCxgf9FBCsKqOWEVSfVXyOpMySu4JFNaMO7DHAMsKVOs9fToqsP5QbNOVh0mtZMtatXz/IPQcdfawWRpJ4Io7cqiDdq/cm915z1Nj2BjHeiYVgqcqEcTpp7SJLZffV5aLOhR3+mGUzVDf1hIWxm2KOXKB+9528EGUinRvuTbYNECvdut2B5ys+5UQlRJlhpn3uwsNzZ95GEoT1BmohXakNGw5YCGHZ/AYjVZEk5nRRtksjsr3bxSjVfQpRijgmiBuj0q3L6p3h4NqAkKm1YFNsviWxoWfZGqaY9O9Ks0o/1SKx7iLX9aJImOSG+zrU5i2VK74RwitjEeAWrjikMllkIRu/ZMFNXebyG2F8/RViWtGbK0ceCGDg/CpGLs0B+XTy948mV6GGRjj0SokYZCrI7epQa3Dc3zuQvbWDJVseKja1S68CGrVOPKkaRdwF+ayIGo43WbOcPqOY+HE/+1XRLdMXBNuzUZeZL31QplNz0c5WI5LBjoRgS2+Xh0tvl4q6bZPZtBnoJX/dW8sxleBQrhOyNOY9BwRcexZ7YE3oZNemKtTaT2qUexfRZk3GfhVOSpJnsunIAnqRbMCM6cMEz9HtQhZyst3jC+LKHhQvCe5BkoOZdwnubQRRyNtt4+VelEVLU7cMycMPKIMlLW6NfmFIINYcSKMGJKGEHEzCErdILXEvluRjDmgI2ZQFIMLqw5YaWLoCQeoGl4yicykMyIgHybN3v4uE2+D2meWQoRUOcHWbUGdt9wnGCms+JI5FW3wp/3Riy5D4vMCH8XKH+uxTa0aEPZFuPP6Ewy2rda8qRuJSN/1DPVnOD+hrs1DOqtHvjjG3viO6Qco+vFx7RsXtqJwY2qIo2qIrVVEXoqQk8tu8mmMcQmTsQLm2S8XlVwOdgumo19C8nEWcuSjCcwTRW3AJvnKu6rkiDfqgRs4BSoeQW3HovJ1wjumvJq7jTAdSsxHI1udTWr5riqkXCFLmKKr/1VpGGANIyCNIyGNIyGuLSJJicObXOwEDTSROFBEH3Q5mt9bzu1OukCaXTbiSWUNDyLJQKHiHfQVPpSLX0VioKjk3ocuzNqO8xkJV6Mk5FyguStuJKcKAgnSqlzsP7AOxhbut4PsrMtvZ2QChX1qGl4j50zjg88ThCOoh6pR8xirrQV3xKEu+iKthr69hy/qFMfyRtSTxYIxh1elhiQrOiErny8cTt2N1oN1A3B/5LFDk3OebczsePqFaAg1CpRaoCNkAS7KZFvzZ7lyZtp7bZ+n1B5TvdjBKHFOzQvUzv2W8c8IAiF2ALZjLvp++prBR2coLu3bLFuUZDGUJDG0JLGIDOJaCULMpoNxPDnQSCwMwwXWDEAOTabUsk10/0p7MFVVEm0WE5D3KhFnauUZBuloBRDUfmyNz7HHLUfAHPURm6Amnh03iBp4UL50Bbjw0iFlflojwaE5+gerayK4LSSNJWSzBNNiabXkPpqCY90mUR3VjRFnU+8ERZgILSbQGeBFQNRK0VZ36nbT1fFSooIebpHyILiN2svWnWF2Bo1jhzsGHS1wzJ4rDB+i21dmaXislUlizS6cvs9S65oov/R01UHjA39D4ZZp3fTw6ZZW9r+wzBjnUOtvwTUOPrLMGuNspk2r/RnI07BIfqurLQZX3JaqYtVgyvWg6y09KRjQCVXwAnN7WG389qh2BQy20yIQGPJvqOSeEdZsTUyvWW74F7u4HOwkRbNGfcmi6vXEkWr/4Oim6FWBRZRs9PyV8EJpSyvjNRoX3LFqOkINSRJKtwfajIUFWS9wAtKsTr62GCAyrzX19kwkaXWisQTXQ0ZpwIR/YSGhbTawF/XR+cz/kBC3qpleH1axA9bjJ/i48Os2JBV8SxHJigYRFdU+qJbt8F+de+BG2muytJq6+dtFZVYDiEYW0Vl2P6U7FOYCOYlhw+oBKVYAZ37uHz86+EFgXjNy5kIZaRVkLH5WeLWrYT0NcPVGqHNGShHsnn+mo1TSuEXjsg0seKQ8NCLJrhgYAQgBRbPYDcaCjoWQgvsx+ZMBKEYNRbwur3w9A2VVavI/XCSOllqFc+BiUFRX5dGwnTncS3FgCCgrneH4tlEASUu/2g96NyS0dibjImVk5ZaRgLhyHtlyCvzfYdcIVVDcqiNc6OYtKJS06yYtDItJq1URpknSysRNctcdGBs46xNsE1aLRUbJuoiJUSGCZF0Yjga8bD7tHSrFiHYfi5ma5bghC2mVv8TualHs5vcaGdlPbepZO2WQg61yy66kjnEHS5Yyfa0UiyNqnSIbOmYFuEAsy2wSaEgGwP0NSvaIturA684Tpv0FtaxZB1j9G05oQafOnxMaJm4EtqSoWhZTGxwWJuLenRmTo/Xpw8eW06YsMUyq69ufLVS2nPQkHyj/eUbJ9R18Zgju/YkzvhtljLoz4vjvObOS3OHuwzpVzMymQQiYPASx7esqsz7GQcayAvW7Mij2fuGCQ2lNY89ihk9Gq1571EdbkfSJR9uwiVl4L2rKKAtH6afWlZqhRryizxmpYlyxNsMOCQrL69qz7C7tRTAFhP+rOiJ6rv8qP1u0OsxEH9NyatgDRb1KvigJ2BaeWILPnYjqVw34gTbuMflzIK2I61hTRkaqsMroR4J8uqObTZYzZDcxxSCSpykRo87FDapZLHfG2ZPUhujksDYPirSDqpiQkVF3IUqo7sQzMhTTzDW5Hcp8tuW/ObJbyfyLEue5cizPHlWIM+K5OlM8ruSZyWC8SK/vclvH/L0JU8/gg8gz6oEU408q5NxXIP8rkne1ia/g8mzTpHdC/XJszF5hpFnM/JsQZ7h5Nma5G9Hnu3JswN5diTPP8izE3l2lqxo/OxKvu1OnhHk2Ys8+5C3fcmzH3n2J89I8hxAngNJzsHk93DyeyR5jiH+gii6PxpNwQwKYgngFtDUIppaTsEKikykqVU0tYam1tFUEgU7KLhB3z0hm1bwlCKfU+QLmnpFN7Te0NQ7CtJYAi5Q8JSC9xR8oyBaQXlRENLrKdhIkNxm+m4rTW2jYDsFO+i7XfSDo3TNkUyRxynIojkf01QuBc8o8iX97jVFTlYSsJSCBAo2YhdAgSnqdbd/1J/q3pfhQ04MQ5UfrwSqwcngJpYBjqjEM9iNKMjK5OlB8HRotiS/W5HfY8jvcaSUKQyZebNogx2jIKNEK36jDT2ZJSxPpe02nYJbFEyl9VhAm6FEE3E7KXIXzbKHgjcUfKNZ0mmNL1BwlYJCCiarCFhCwVoK1lOQRsFTArjZapKaS8FqArh3NPWBgk8URGlIVeZqSJaNGtIEmwngzhMkXKTgGgUPaM7HNMsTCnLpd89o6jkFLyh4Sd+9pqnvpDzuBy22kILpHCE9n4KVFGyhYDsB3G6a2kvBfgpe0HcXEEldQoTYGS1JpVNwgYIrFFyjYKYpybnalBZEQRYF08wIiKPgtBlhPpOm8imYraNdrCPvltPUWgrmmxOwmYIv5kSKJ+tJeeeAsBtnQd7FU7Ccgi0WhNg2C5JzN0Fye+i7fRQcpeAYBTcoeEJzfqWpbxTEWlImKNhDwXUKHlLwyZL0wxwrkoqhIIuCVda0RhRstaZjl6Z2U5BmTfi8RMFdmiWLgmwKcih4SMEjCh5T8IRSeUpTkwx0/hHAzaBgJgWzKJhNwRyaM4amYimYR0EcfRdPUwsNpD0XE8AtpchlNMtyChIpWEvBVZpldSmKJIC7WYrUL5MALt2GIM9TcMGGjjoKMigyj6byaSrKlqSiKZhDwWU7WjpPZz8FHyn4zFMqNJVPU99pqoCC2/YEvKPgAwUZpWk/lKYTiPiw4RV1ZR90JKnDFMwUCHgskIEZ40QHLQU3KfhGQVxZAhIo2FiOgEnOBEyl4KILAZkUrHOlo466zu+6kdR9N9rvNJVLwdRKdLhRcLYyyXKZgisUXK1MBy0FGZUFFVYApVMX9bQIikT/qwD+VwH8rwIQ/lcBCP+rAIT/bxSAHTq2R7g08vCnWuBYLOQGRyY4Ig9be0/1Ao0fbFORIFCyK8ySXWFYyorj0NhKuei88+Pd8HSsFMiqBBICA6K0SlWQNThdaeLWXExl/noKkqnoP0PBWYpMp+AUSwZbRnFFwM2kcn22gpzDCRs3/K7zlqlIck54IXuNmPAy/WISDCTOhJpkWe/8++Ai0RGtWD431gxtuQmzC3Hc94xjShwXvlwN365y5DTU+aC5r2aYrnwCVwrw7inxbJDNhE5tZ/Zts3RMolR6RdQn1t4l2WNRCqxlJOcoPm9jShxvejl0wgJ1KaxR9sjhq9lQETsEwFXUo7ltuuc3WVphL96aBOxuPtLyw/h367Im4sAMvH1JNg5Y0Ig6ZPnckHxq3AkTcirPCulHhHu0gPOT8CYq+RzHGRScuFSD7b77h3TqzoA2VFfFBS0IjySnmBgSA6wW7ZDVMje1y7fdWqkYK7kYOzTDLDWm/sf+Qb9wYIcyam+YsGXC2eS/+cq2nyIzx6v/+F++0qPOionDR797MV+OY+7jVG/t5cyVUySEBUqOWLH7VWkzf9BIJ4js0QTT7c+qKiddxdEtdK+KvAQBFzb4XMtG05e/PwGcHDmjlrZ+YpNy5ltsOGIHCuITNaAJTcKbVE1fshp0xCdI9gZFC3R3wuWqt+wTzIqd7hrlumTWne/l9kltZ4HMzNS5bluO3CJ79ypBLQagGs+njB74sOFaWBLrzCu4N8P/6vCpq/AphiW3GbicxBLX36xHGkg9reU5buVWK1iXwIsByDB8zJgBKfNu/LdfeqNof0dlo2b9KsPxNOwP7lK0F/oVuxh5NbfZH7KCeMTFhtHzEaIB3dvU5FnHgXMOSf2uJv1uga6cj3g1cfa+SkD3lXCVbAYnrnrtVecDLPrvGNOjpqr6oWdThIryEc9HZx3rJu5YYzzzWRVFs4Njknwn7oSFrNxTWjItS5FpCZJPUt57AhrK01kcjLICjh0dBTG94KaW9txPG6fKYtuVnBz8pBUseTWnAyApuuluR/I6EgelM3gR73Ao8WPhXyNoCN4hRtzAoHI5MU7C524e8MyFZ4HnWXAnLjkcp+3Ps1BVOrPBkuN1dTDTUI8UUp88G5C9r0a8kmtMgqzpyYxmxNWmIOYydmeH8yzXime51rySa0Ncn+1IvvbE6cYSpxsrOd1Y6Myz0JVXct1Inu48CxGiNVoeFZtQYUPSBTjBkEHBQjfRFjVwrVt2w3pVRexq1nIR0nEZ7ISe9y6Oed2jrsPPb6xQGvfpeO7CbfYQxfEqmIjDzazQhZWxhXd62K2AqNoYCUTQ9fjKDRxh5fgOLivJjvtJrRRHjmNWjjPSnpke1YxOT32+v4GPNA5sUP/4x3GGfa0+gAPpRhXZCcIj5lqtHbvMmuWfl0SBDepz6/th95XnF/2Ss1TauWuvl44eI0lKHRrevuai0Ox+D4k41CH3P7uOmzTPsy9JWiPf+cq5DhmqP2EPlsZfVfBaLVqigXF9bd+sTFqJAwaVYCdg3OEl9W69ORVwmMSiX9YLahHQkqgGiVWCuBkk0GFOf9EDZX/f1tMs6OJcONFO2o5TcebCLBw2AEKMkhxAZsnJTxvBXZzMoFeGD/EVrCYlQeFaZDwvQca7qVCHV3F64TkmYcDh7dg1XomEgljxKs5f+MqQiJy+JCbLjGrfsjSgtwMNd2lKtxnwsZ0VSkHHc9xbyeIn8VBqevhBtEGO6+fenxrdPhLozm+IFE7YEu3dgl6lb+jZDJ7nS8eVeRWnEp7SHeCWf9HXCKtxbCMnkM5GQg622rTCNo+/DElT4QO2BM2EJTyv4cwBhD24mxvzwUPcf+wqK22ndiadpxEnMig4a+aLqwvnOUPGTJUkr3FQ/3eGBPXnqElQ/wuRBPXvF0ixFzSkoFMKsh5tRLYR9D/H/5AnPhYiBR5pSMgaTFPQOGeOxjkLOBqzb6Ntzx/Xnz0FBxkBOddEdzZBRaKyylV8NqpDxbExOK4RWMFctEcXLYd97nb6Qwy0ISPblBwEwhsArNgZ2Qx4oJuxYUgU/KhNOh+zWYqwZk+Cbpzw+WnOlRxzFgm+JnmGkl3TTuT3UBLKFsNghzSON5mJR1AaC3EKUYc8FlWbMbDdTm8yoAW0y36iesTMiZ1IzIcUuawjpoYFlBIUohdiMsq1MDVp2BSy8NY+FrAOpHnKE/HoQcRfNaBnaCbAWkb0QPGOrfeZ9P/YCm6wUmiqVqCHXTRkb0xFCOEw3PICK5ZFpUdpvo3+/KUh5BtPWXkQQVWNPEOhm1gZDerZeodm26pQiEbF3mukflJy3WACr+auMxDHipVRu2txsc+rtgqHOJY2L6eTtoGVpEEx1oGYSx5iTdTJL+Fh/zwrb5guB9KA8bA7K53T0skhV6VIeQ7kN/6+Iipnu+/TkdGlJ+DtZGNONcmpKlaOPTrkNtixWlO+J9STT7DhTcdS4CCWQ+p5D+4dP74oE/rLJcqvZQpzJi1r5PuFfwedJXakHoHyYnnUR6E7P/l6Oz18aEJxJLCxG1G06eUgz51I7IWVTpvlBT/vD+fw19WkPHgoV//y6n2Z0io3WIwFxlm633hRCfkqIn63X7+xvEKzcl6SgVoaDe1y4OSbR2utoGdR2xTjNbKiIvZdt+P9SZy6Vj7rZAGlREdkvdxj8YHzNg/gJSN1COVYGkNlUONv7eb7TOnrB/EM/YgMOZzNA6qJBpTi6rkso3B3e2yRSUfEFaIt2u7fJgtNOuMA3xlivxprJyBr7/B5YerIUvDQeBbKOGjWMnAdn807mJaz3PXkvqXwmSnewUaeBDQq+mKl1J0m+yGajlOWw6F71SCUkhLt0LfYd+OPTC9VpcTqRwcWoiNa7zu2wRyv+k5w4T0jdwjeoT4TCi+74Rhq7Yvmw0X/spDqJtW1iL6a5hcFNNrN6SLXs2A1PMOxsNdpbFkciVJl4axCdECrVaEbDt/3s8biCs8RhWSXYA7LoAX+TdOutW9hDV8OYCl5xr7Y8MAh6HXXRgzYEnk4ERIZEiWADW5aFdbYEC6op9/bVgkVO5SB3beKfW2sC6/hLkyAe2sZ0RfFzCpf6sj5pvPg+CZjF+PG1xDDwygysBIqR4ROnjskVRPdUcdP6/k6fVa5wqQoRtqYpD2JYRwLOcWZdkN9rq56WuXB+HwcXf/zdFfjQSlP1vooxXLQFIcO9sEw090YqPGPk50tMRaMHVEWtZzQt5fLlI9VIP7XSU9nZBVUO/lrdh1ILYTjG1kpHPaf6l0enbueFVh2b53DcGncT9Uuqm55VPrKjlbLjzBfYKI/duIQTyeer2p5vuKt9QWrOiRNr6qfI4WruSDTzZ+vhKd2UEMBQ4L0i2qKSkxdAT0qu+d+R/ajKRxhignvIq3ghDZYDEgfFcUPhRdUQyklcc4VDRLzUXdD+kY9MoGpypKSTFIcLB3bog36Y8IWXd6+9w9/uiSiHGpvMiO4szgeYAMnHUU1yiutsZzyyCr0jN5y31IlfNMWG1u4zKLJ7Y4EIcn1i80qBDEyN5IcVxt1DlQzEq2M2quyotseHbkKMpVExkpinBCXWZcmVSWUfaaxQ8p7/UFyrEuKrpH3+5VSY1NB4IR6L+8yK+Jak3OQUqiWu9WM5+jkEVSiD3qb2sx71KiGz2DydYYUqy6m82icRzc6eJTFJs3n0cqLzdO3aCDbkVRexa2lnpDrFMSxZDxROVEReYd6+K99P/MDFPyqUXFXd4MJAiuWQU57rn/eV+lJJHwuVFKJUTQazUQvNOSD8ke3z20uwTPmb2qvMVoAoDO2rojQyZwuf+zeVx8ezzWVaXFyE2C77cIEYsXcw/13nRHtkf00S3DtuErzt8qzyas5zPX8WaH/qDzDVsfFpw2/OuZvlefT8g2G3ukzceQ/K8+H55u3zekwOvFX5ZlsVrv6vu4TNL9Rnve7pT99vK1Ssqw8z1TVxw8ccVr1G+XpP2RsTM1K+8L/VnnerG46TtvFY+5vlWfvvPBCt8S66HfKs+n01D0TZ1ik/qQ8q4/pV0ZYE1L/V+X5af42ld2Kh+a/V56HHlc6XabXiFa/VZ6vvt4e/CVmfvzvleeW8KC+GxWV9v6N8uwwstRQ5aS0K79VntW/GQouu7Yx+Wfl+XDwzVL+Ewum/155NtjgsPb+/Bjt3yvP/PUfftSK27Tzd8pz8ONch8ya9mX/UXk2d+s3wSzE48T/pDzLo8pNanYelONQALlVS8h5TQk5/3nWzRPvU7YGk6FlLlZGXqtqcU62927iM2bGI/W/l/VD3aw6fAiZ6PK7FYAzqvDp3Zl1C6sBHFX+JOuNgkgSmmh1l+otvo69TyQ+Edf/JPXtG/d/PbJpiJ4cFjNKfVOxAsrdvGZHr2THOCz1jRHlv8j9ymjx2MyJbV6MioUY3e/kvtFYEL3Q6GEvnT035rWBWMwb+z/rAE+Untni4g1DXAWiA0h1/lkPuKNP3g8yOn2dMhTa/q0ewJJQms1EE3x7PL7aHv2TN5ByQSOPBPMSmuCGT8cncZ1fxMNrSRMUK5iuUn/VBL7oXuON8wwnUv1goecvmkD9kybg1dxTMzgNYkU00X+695LDQ37AHNNipaCfNEJF9DDs7eqIjedXwaVDKnoqYavhZ82gE/3RyllVfxzwCmyAzbViIdB/qxtYrluRfpge0m9BXh0vV0g9WKQf0D/pBz16Gp3w/Km9z3vZ/St6Z+S20lUfAMYgQEf0Z60HbuttSzngswr4hPdZ6v+zIyYgvp3L40mPViPYdkUXtwWiHfFp70zHnd4CMVbGm6qoB4m4DI1djL0jGkCCP6/hzACERdh5tHN4wDLO/kU7stbOYtG5cRcLClv2zoeZpzdPutmc18G0qdln88n1oYKaN4cb8zbckJKzGF4HBx/s/yClzXgd5BY8yZNz62Det5Tsb0XJ/fPfJn2nSQteB/vm5278XvR23er7OVIS8eaw/OqkuT9o8jDLm0PCuVMPpPRahjeH27durC2g6VQFr4M5X159LyiiNun18QR67amg4nVQcPfGnULjWw2kZS2sJPzBI3h5495qRthdjufg0eHEU4zQgucgftPF94xgyXOwOj13K44jRbDky+11SmGyhudg++M355WCO4/gxt7ou0phppLnYOXX/ZdxwD8Hae9y79Jf775kn9MIg3kOnh79/lRD9gCqzo44O7dPe57KDVGPTI8d8LL4cS9RQjijHkc3bW9zpfxFOHUNy/11PnC2OnbV1oc1zXmO23GKgaMPGXEYMmQ1fejwYdh7+HGDx4eYLeGqgee4GXYwpTQR+1ed4HtFItjj3IlkXudDzN+z1YlaWVCfV3FrmpMDPfM7kTE7vT/Jvnk8ucdqSxwDJzfS+3SOPmTgxDRWjESbquSIZz4M2g6T06vwHPe9IsS5Ey/OOh9ewZ2tjsMU65Pi1jQnRIto4+NCm8fjW7XiGBJRTakrcaWKyuC13LFsFazPwE7VBQwaN6bStRs3qu+E0x9D/6aeKu6qEwG/1FVL66qkHKkoRzrKkRnliKO1VUo8aWWe1JgnAfMicSWU5EuHNg+OPj89elWIdFnkuZzd54NmeS6RD0tu7WU5OKX/qR4y4q7J3NVJM2u3kRGXHu51WjV/2WK6qSTqkdtNs63BlxM4GdEp6P2TSwtdZ0mHjSxQwJpyi/bFD9VhkQ4sOX8UVLOwye78zVvlPOv/DF7SWl24S86jQ4+eT5ozKHBnK8KrDUrV/5k66HkyJyk2taTYLFDjvGCvzfOWB4EXQXmJFmjpqP2Fq6Y+HwXdCaq7aIPG6Nrv/NS6nju+kY9jyT4IPuFpg75uLZ2de6JBNRhMXrjLRz8X7basFD31cxV8GSOwgi8+S9ps1HGh/O3ZhG0P0QZVD+ha/d5D581kh6E41Rvd0863+HD5E7nhjsWHCSSqT1WHAzY1DVsI9MbGAFGP2jeabON//eFkQtVLtEG+p3tuONO7biEEkTyuMtUelbO6JC1/cuUnXm1Q8N7yD8e/79bgJz6sUGalD4drNKu0EetmoGdhdOjlLtXJpvPPdCUta4HWO3gJLWJMn+Gj6OT0ggUqJ3r3uZw+vIks5fUo8m2DxrdyXx4HM54FvLX6amoXj7wGSZVAJUW/t33du8XXnW2G4p0+QKIF2jL/7cnUyVvXkzMQZmAu6pDP7Q7LBo0/EyVtBCx9XMutZ2kTe5J0QkzI7fxmJvHZsPv6jl1UrvKmsEdO4FvlrG7zJ0o/dtgN+Stcia97ETYJzHg1B2AglqU9CeSuTpQtIntA2JUfRnRMBJnCkxjYhCfvPQYSWTKtlpsLlXmOS7HEwQqR+NY2R3juQk4xx/nCgnq8lpv6WAVHTmlIY3TNvtD/Tna1/qTLyuOj9IFTa57S1GkiI1roGMuI2yePEISFqEcwdeHU8Rk3+svzJLrLlws9Vx9qLeeweeJaZuHkkakyjaYFkTWcHlhdkBHvbrt/Ojo9pIr8ydSZ+fdbLww6ISP+vDLn8V1D9mu5lLDXf0y4NOTFSZmG0HzOpgBk91RC+KK28ZOfxXMxW6AamVhmRB/ryABT/nzGilyZyYKp6IseTzlaXvGyXfJ/9Zkjult48dEy9stXySthajyGBfQoiyMaN77dhMJuVhN+k8ELHXtolxXbb0k8eBW7iqHo9lnjIZyiQt3Rhx17G9cc3b02uBKatsUux6TGBgtqKbtOdEctOy9WMam75/1H2Q2o9sYr7MYNvRXSRTVA9rzc0XzPBp8cb6zuTK7oKjr19btCv72zMWtz1jnsP+QxxazpgCqOLUf+hzzeaXn847s714+U4FGPFpxsPWGW2TAq3juJetRhv+6i23eb6jIiZV/LiM87JtGTorVEPbp3KL9csGOPCzJiQaLK+8ANfkzRwO4fdtQs80GqdPpEj5YmVroiDJjvLudo/sznTpmrzqZyjoyTWUyp2ODxco4s/zpWW7utCpJyWKOvNfMWJiwJmQ6r8bZRnhqe4nCFeU4dprWAPbMlB4AOvWLmeq5dt3mvpOA6j+82+ELzsQ+lo6MiumnhFnVKGMPBjqzMt9jmenpg/6Q8o5HFQdrlj9Ow35KDFbMf7FGT3cybXQsGZub9ebkoBCK0cfyNrrM/k/gJlphINh8b5NZ/Z0rVokq0RZ9rD98o1rx2EL4UssWvULBAk8yvrhw0R+SLXV87ZNzKXbEVmhvwmMcdKPqgsTePucYPj0uFOXhHEqRzq3hVxZGzKUpyBgXPsiDyuzUMEnUo52v1Gdc7LDpKqm9AC5/U8Z10sFUZqdetpF7v7jZPeT1xdgPp/lID8sprelO3hnWQ8iGSz4Ayn+XkNPhceslPn0/PCOlZULq2jbS7q0cTQhY7JSdW1MqIe08jG/FtXgySu3PmLTdd0tLzhVKJejTxRF1mVtSW2dIhXwtUd9r6wKOxq96AmaQrXFC57ufa312jOUv9pca4IK10ctqMXGrSBQaL9ujYipFB06yzapCje8Yjh2rp9JTn2A4PfduOOQ5zGGNEAtCjiPhjS9Rqife+et3au+E78LDgaCrq0Yxt8w59qZ5NZTNGvB2859HVW6svSQg7VP383tO7g/z0WAoBPRiPBZSZKKIJ2UPyJxy9pIN1eOb3g1G8mjvK4Ovc1NwRJRRiw+2ZFmZhnRVtgKP4lu6Qjc4ua2fUbiYNZAt0qqz/qZODw2oUu1XGzg25P1wZN0rOk/5Jm+y36UwzfFASFIJB1CPb7ltndwz22irncVp2vNUPe9ez2F0AHKEzu++EUs8iXYLlUJCoPX1v7O4bFimHAHyLf1f9Xd29LuSWIEZy4+NPq0yqNtqv1tTDsjm40buZZ/O8MIWMuDE77O6HLyu6yWfR0rb41lyu89dLM8MNvW6+YueIhq9C8N2Exm40XrhA7zTEZ3MDoa5YEbnNH55ZT7nRm15wifOynK3xrmZySVNz6ghcYuqmMy3Qyne4zC7lNPdTXPh4OY7J4q5JdNcTM8xkvqrW+wHfBrYpOjR38tTLvvMGb7eTEXUWJC6vEX7/m4x461NzT9SQQ0Wf5Nyqdqy+8/vhMoKfnzCQr2X1QEYc7ToYzXauWHRBzfkn1R/P62wlyIh2u7+A15/pi+UeO9x75NHeOywmyj1vgV46Ld38ZNq1ecXuPJu0en3DGus9KhLnODnVS6wsf6gtWqEqY6pvLrSpVRUM1HELWMZeXaqcsaJyp73Sos0CzeoztPb6Zzs+FDPy7rUNulfu7pBLUh4b9CxCG7Y9tNFTWPQcG0z328Abet6y8Ivli0s9EjvI1FruWxQ3+d7EcsWovVnR4lmlwKHdpFnvgFp+Hod65qcOhfVzaZw6vjqxCvgKT/BF1MO9UvOXP8jN+ru3euR3Mcc5QrcrTV6ETjiE2l5QOl+VEUPPJ/+x3nSxVkY84xZUFj/O+1NG/Kj5qppv5sCOEsIOnVlbqlU8f7MdrN2ydaWW52B+RkaMitRnUDL7oGaLws8gkpOCOHeFO6497PbEibBj4/pHiOcgM37+e3qnS8X5LVaUmfg2Qy7KPGTBziRxnqukefQIDtWunV5vTxF3Tt+6h63Jj+wlt/WUJiuWfTJvkCDdaaOUjPhqaFTGCpeBR8e4wh/FT47/dD6bHps1BgZI00V0Qm3ir8defz9uG0RFjcTXke2yh6w0R57jsr6Gw49XXbEWbVluXUiyVyOZ1zbOdks/HntbRkJYoNq5q2fMn39thdy5FujN5fgOH280T5RRBhR40Dx+gm/ECfDmWQ4ftrYDQTQg9Z0jNxdVPLie3HyqopFjogHFN09jxk44cQnHasm5LdCX2b0Mds/t9gKQs5y4KHXDZJRv0i2l2NCq8HJi3I0bZqYyy+sqpLzcHlj/vNSaDmhnzYJt59qH5kMelrO7lPCCyF0NXOREB/R40R81+jZwevl3by3QPsfkvFs/TGOxMiKH+O1QtQNN8jdeP3QTpqXPYIoU+gSRR50rvS0YM21XGkRtvo4X3FmbWDi2QiFMEB2Qg1VvU+c9c7/BtWrE34pXI1jO1hRALI1G2iVUOXLcVgOxf/AqLsGCON+iraDQmgyI6R2bBQxtUjOFHA0m99MACKxojSY+GDxmdUbZPXAA65TNDBzHLvBVbVvY6u+tT4G3RBPxas4K6ElfN/CQ7i5uLKjEiqhlvfBF9/rvmAnL8Fs7cCBOQyx2K4Ibr+YaQ0vShs/0Zo8uZA0zgWRWurZXSW50qyhoRHfUIlnRpeCbxTe4jsgVMCzXGEfNQUee5fD+yyAygcfBTIaEbA47GrQpu6dnU1nQTVdeGRHqmn2H9LSKoA4EN164d8E4DqPwek4E9CA/ZtCi9S5bSHjXLaUYjgoyxysK7n/OgUfyHUHFLgCRj7IDvVuFXgLCFru0BtO2Bhty1wq+XcsJKojuqP/z6j2CLJ5kwoQiC5lefEDiHKnuwXcg+kJ1sSuqEXZnepkTdmnwYy9ukyQWJmIPzmcFcVPFYMcN9rnwKu42R/pgqynk4nuBkqyIq2eRHcn4QuAV3HM3nuNe+8OrhqSXojvD5zFiPVRjdM8MnU98O3g1RU9W7xy+oDOHenpogQruNd6sftWQeIqiOwv4rsDPY3iOu7SKgUdXGbEUqlU7t1T2n0G1IQe7vuaxsJsVSonDkFvg877eQd8awNRtDrS1eTU3hYGtjPFenSTsITNWi6XVUnMZariNXVAvBDJcn7vBa3/C0qOr1DH2kez9nH5CQ0AvXsO53mQrYfcytSigIKvM/VlXxtWDWBruifMI4MqruWAIF1hRQFNZnz5z3tSu+vsc745vbmVWkwmG2b/LMculcV7Bsr1//i5HCLp5+9hZXcaUxnB8Gl7l18D38pL7BEYIYTzHHWLgGUMquJaFVyzprEwnnuMWucETHxpmGwz3Wgg60RY1X1YhOslvVBJcotcaBRJ7rLFoi+Iu9h4zrdVTBeynb+zIm6biFgZleFhMah88VwcLypTY16DD2Ey+JIMj1+QigQp2Opy10naS8bJuc3LhpZqEZdiRYY9viBBo6DoZt2o8bqWrV6Rb0GEwHmwM3s6UrtLm1dxxFl7K10viAaGBaA77XVKqvndFDTa1h4vYv6InVz9ZyQXihYmCFEl3IV3JJbZKcixebYzDpReYS/ef42vY8a/BxvvPFRxhZAMDx3657HK/ChapRUfk3nX8ONODPfOgvvRPBBQSL/Si7wHomqVl2KSPVb/CKlP5TnMalEhvO9GQhlLKG7x2UiSK0thcJLerdC2wdO871DVyDIN5BReNOSOXkIv+qNLBD8lWrcd3glSFxBJLrhqlDVJ0x7ka33FO5AG5uz0QOTQzyXzwvdMnyFyjkZtRzQk4eo9XE7uHLVYsx8XeUcOqqzhevGBisHbF1VJlQSddh4IdI3rkXJB8oJXTLLoQLyvaoHvjQ09WH6C8QKQcufgEWKG0aEC+aF+bmis2bwOdtO2Cw+/16PrhiH5p4X2XSYtuG/QpY0jnei0inEBdzOeqFu3R/DUdJthfvXsJCrvyCu6WXr54TiHaI4sGfrmZDes7gV3x23UAm1X2KNrzs41Tdu+vf/PSgI72sLaoWVEVTG7ZpCYO1u0nFluNOD00gVqlZUQ9+nq3XmEpVIbGruPl086lu9a0Cjq+SOLcgDTJ6tU9TX4USktXC2lhuvT8uIOzah5oL13QoUcVrCv9WF2hjQ1BVBArIPuJGUMntL1qR/SD8UaZn+8A16O2y+dcSpt0epbMQeDLzTVGbLxuIvFYBy2vN7P9vPTpPCx+4sxz3KZZDDxLxCPn8kEqJldlYIme9IWBQ8uxOJk5l4Ml2/B+3NF5peBUqh12OHcJbZJas2ufosXByObqadXSZhRbFo6z/TgnMaH1OGmp44xs+IAjJx92WfY/XmSe0n9HPNKOHEgiGX6u4f4ym4bmWPbtJK/sGHj0FH2J9pIRTg0Dxm89Gr6BIEB0Qrk2l98mVH+6EOhli74lruzBVG3R9vLxdjn3FkTAFGWJm771qFTh9zk/gtKd5OhySPtsue7+nwZiMhoHH/aWFL5985k94BJW7DjIfa6J71ON00BpkalH5olhGTX6hJWTEBbow441+U/m7Boh+2wskMpreOaLk24Oxdw4ofUiuNvvt1SQl8aD1z6/v8jKpJrsyfijWcjT5p55j2U2nzbe/XK9/s5HaS4ZR60NemazLzPpY+VUaGE058k9gS6oWsbFprXbVRsFRyXzkkSTWOOtYwbrK+lmOlFEM+qMaxcV5FAPHuBTSHWhufFOPby3poSvymK32F23gm14IKrGvLnle+3RZHm9bRld9YRzQeFMOGvHq/G6mt4lCF2KEaFX4OlR+27fFrpmj/aVPrZB6W2WXZxa5UxZKH7tF14R1De8+zG4edUosJP+e5UelYupmvSoiyUvd0Kdhnlt5jj8WCkvwl2POL671qBNgoz42K1LlaVxUQdlRMeV/e1Wjg1vLzfvtLZ+1exPX9CBj/HiF+CIj6JVVK2K9ft4dP3lhQUae+dSyoaWP0k9PWoz9MWoyxef1ZWcBDpUpp/ZoS6anCqSs9C8zm79EL/e7+WyuUudorSvNm0g6y5yZAW0pGKueyLSxnVcRb3slnj2Lz6YM16X5yOPmzqKaYLb2CGv5La4lHWv09v3FXLlHMv7Bjwo7H6wQBJF9iizRtX5/i+dDhBz00SwKnFUqotT7u3Pices5RLXOb3b0etQjyFyy52q9/SjvU2FdKkAO+R4w+7qc27mu785eGV/bkL42TrgLDPTsKW3prZt2R/S3LZALiPy6ugshEbENlcQ1ILhW9JQ7tG+MsoGpQ95WiMh8q0HyHfVEZlkQEs8364cdPlqmxIaqioafXFwBYcD1c7AhopF10qSKJpAeXz/blzvzbln1kznW00Whc2ea9e8arGoOf4PaOR/n/Ho7D6rEXsrBO8grj68I4JvGmUgEfdu4YV+9hu2NU2TxVdqg41tHc2bdJURDbwvNx154k7XotHJT6h/bMHGeKnRbdBhMWNNzO6r238RSVcyL8T7DL/wrphIyvGqe3ZQYusA8nEN0QYp1I4933v3XCopU1tJmdqgvn0v9enz6tJK6XYlpbyeXjjs9Gch08VfUmIqosRsUEbvA7l3O9f1/Ukr65HBekfF1elcC3mQKOZO7HHM5PQzCVEbHVvqkKO/GHwHprqSRTde/AnE7sBmsYL+m4K7WLycUkAy7oYlCG7hbnhjCT9sxNpIWBzipbA6WO7fU/AbXnd0tM3xvv+eQnYfk+tbY8fP+L/goY3D9oZjk57/ewoVv6xokfTgi+bfUzCLvjhC5zJ2+r+n0GnHLe+DO8L4f0/BK8rk+vwG25b/ewoLOjXQp6wamPbvKWzZWXNTfFDpC/+eAjIrN7fCxTYt/i0FS3Rz8aHbO/oNqQ4zseCwJbOJiUxdXymn8rkiN3lUcNLZM5sayzL95cDPzernRibIOfLD2Mpz7rQskquuSvcvTJPg8/In9h0y2rgHWV8pUgNXBwwYFPSxlbw/m2XxIHrE3YNUCw0RAZUpn95pRPQbE+IAmYlFWcYCb9s9Bz33yvbwqhb7prwZN2OhjKjfyTV9T6+07jLCv4r3jxv+yUkSoiZqalP4ueDBEWtId5aCKfG2oQ++kQzCeTU3nTgCftdiNdHNZW8jq4yZ9fHffr+60+TmvS5XPPdvv+8Xap7rU6F74L/9Xjc5ZUf8YUuzf/v90Q9bY54/XXvv331vj3Z7bE16+zZlBNSTlzpYiXpCIHb8edZ4ZL/YbeNPNqUHqhj3YWLtdOgMy5hiG76s8fpMYsJbE7sf7584onqFXfmP4fGjwVb+J0JEG9P9YdETXUj/tLLyA7f9kMDTj2TTkOjNvzERjxo6P1kpLDklaUkDyu7+/UXbYceeSVpKK20e5g5+Zl17ydU2P6EfT77Z84+Vru1+Qvvvvuec53yrbwm0CxJurslNvrNizf9sKq+qe3IAaMSk/9xUtkcqv+uDX5uunApWdH7+H+7eOyCqXesDdfoObUKHoW1FqpUtAnaxYkOwYu8Fe+8FC9hAsCBSxIaiCCpiwwIKiAKKioggVuy9N1R4X1b2bEfP+e6Rc+737n3vH2YmJNlJdrKysrLW76f2PoTzzxmrihmNHCPvC6rw9f2LJtwoLDL6RRU2RS7OBu/qPi5gftEKlGhbNesWxx8/PMwPVTtU7crORXmbBurh9U5w3SXhr7s0QLRh7P91w9uhdT0WJRy/vDLsn9ZzdpF7C5P64Z7/rB59NKrDZ8OkboHdhUh1ffTQZMbgIIlHNY1b7msF0zPa+k5chX9oLMkvR05Ibek2kxeH+uidfxOredmtYvnAT3dypVlRb03h6MJVggzVjcu9W4ib1BUSPAt776rjlDZbSEi2mrHeYEFSS+GSbe/UuUuyzmzIFK4Lsi1XjnToO3OqoE32f7UrPuKQ2R2Ng/WS9ukl23bPaSsoxcHvrpVVe1ajiWCwNkcvT8zBKd5oMg6gcAhNVTIsYy+Ty/c34xPMe31fCpjXFBoVE04Dr5ioM6/kHZphOQj0UAnPC2CJBvRrkmrQtoUYB22UqOSEazVATHBWaJ9i7Ed0/Lxrua7Qp4byZa5ztwz35ftkhqZ30am/6UD2Nky53DZJ+Bmqi8QxKQ8+Wc8v472unqWX15p3/boHD05R4TJ0qyh6w24cJQVY/RCiZF4YFh4ytf2mE1ihoa2Se7j0600avmyQuEfQknVuvbyd0OsNdfdoTY4mkUd6XDZeSi/PyRusF/qlZs1GjneEBAvPYR+/NX0k5hP00ff9O/IX+spuEV8ZAuBJODJ25u2765vbGo8BGUfO6LqsgjNFO3ecNPcJ3VqNBJzQ2GD4hz4aXWRb/XlSi9EalexvFDOyTd8NSXieGhiUz/ugperR9Ys7egh5lSjm7iuPIpMZg4StuX1Fb4uhs8okQkLDA5cDbDOlbrzBQ4mGmHYacthr8jw+gUXPN3jOOD1j6368SA4AAhJA1CQaSIgIHyV7d4cXIVdzH++2EW6qvztKQt/Zrq4tJCztXLFr+ZIBW4QEm/RN3Xv3q2MgJFzWi5xevn7KdCGh91sbxfvzb6R8git608Ny8trAbgPxeReyfMU4g8jKLxIMlxURcvyB2IrX6OBcXeKua4yfmHLGiF1zYf4EpVEPXgiDSz/niaznNvIreps8Et/pRtD3SU0ZYvz4L2tUyZmnVnh/9f85yZjsUswcHlfDja9Zzkv9oCWm73R6Wy77KdkApQTHL8VLz43EJyhSqYIzQTdnvTxaefhBBU6RAk4NyduXU6GD09eMHrlnWSXeIAUcVTFcX/UAZoyaJ7YnyOIlEXgXRT8lZYZxKtSpuodu7seRRn8so48uTK+3pYviVWcNUVa+12HDQKvic0KSKwpS7d7mO6/h4KqMbyPENC7/Wthx5Qp82LVKA8npo/Pd3Q3av0jW1ZCdNxpe7eMgqzzPT89G6MjxmLwXba4HVbl6XTRomORt2pODfjwgw8o+s488GyWajneaCJmUSGRypsvBuExDwc2noyxi8LjwglQ+wQg9zH1Rl2vm3R1v/1HOCIVOqf9BvmfQCM1UV7RsiWLuhNeDYvCRZgSBA5SmOBG90VQ397kWXkNi+KAMAE43KHtncuFMyzj80f4vSqmfxKEGF1Zl+96PaYYrfr9Mmu7jA2OHDgr+/ee4ou0bV5WO2LDGCD+qT9mo4BVkSvAXyf869BxaOjjDpmGTDsvwaoffflLMicfHbg6L+FyV6eeJJnU4F/At9rv+317HrmjdxKmhd4y7JuKjLhpd/NcPNkSG3p0fj2rWsggTgCXCISnnODRn0G49vQ3L3PGb338rIxRaaF7yjET8/HfLOKMHunqeA7rdtsFbdfmnEyXSHxPa6YcignQvZ4oRfq7FcahGTNYEtn2XOXjR774LfVTQNjltmsd2VlB0jND+fZeP727c1O7n5WO19NtM/37WG3kh7YZcW447uuWo3TFc2kJ4iwwdRBBJhQwuJleTkUocoK/x9r0sk8uq93evX5W3b4TsDx3Oswz3v4wTrDVeaGXBflvtMRlTqjJnXVGtL11nuuhYMVWZBm7IonHgasPkfs5V7e+Emx2uXir0q6Kw7T57wZkFBT0UVZaGruirtGhP5+QG6VUblNQmexXml3JfVm1Qtq5ofaGylduqqg7Km495HoVv7zaqmgio/6b0YYhzSezfFgFK1Nv63Td/35Fqk4YzCohudvZyo+OH8Jp75EKrWBu/0IP78e+m+IQ1wL28H46jA0ScMxI39x7+wG9PwF/nrYOGTrz+tP4mIz98NoK074UefmWgkjGQTc6U2uONLprZW7532LpqYMNmv5XdCGlfNvIasY1LoGuUnsqNUJ9uL5xcWhYP0Ex1Rd0vpzqbaSU2rNp8SHSVPS/5bFlWtfmwftmovCGN6/pVdT4s3XCwOMUOXarKfHBEDV9bhS0cP+waziOOI/kiirAu1mjvYzFeRxynHcdXNLv1IXjY74tGN3Qo6EDN2w6VXFX7Mr+h5/fiCTFeVevL9XKbzq8GjY7/675Ins0+267bhde/3xdXtPNp8seP7T+3qNoc2Px0ekiHbgXZVZkDrohNKvnYnZX1r0r/XVHM7aHOPnZfJlVNTG5qWLBwaZeQw1UWk47oyLT0uY4N7db89YCHue4Qtdh/runvD7gSpT7x9hrj1qsFL2caoHbb9ZDxJ71O+EkbFcMckuLPUvDKuaXQmEq5ujhSKdTSALlvezHE++02P7yh9e8WckXfZVP26HXsXVK1dx2ToWjXu/GVtVV510rk2eiCV4zNdy++m4aop7NnXvS+trOxmFdXFFxd1Ouab3rqysft8HUSNdkUtwYjHnG364EHajxliSHeYcwZoq06U/Z5Kt1TfqrE7nK/E5kzuqPfrSTSwnDGyQ4T4zQqaY562+Vmvq3sex+HO6vETOs/vM5fJ8/Pr7Ueuh86KMDId54tTlUrgxJeHZMwD0UaA0d1suZIb/KW5QO+pxj+vQc2R33b7aucVseyEm//O+WV6JL9mPamTSvrCcYlVD941rJacnrNrcUli9Aj2W7WsaDyBC4MMgPvIQWQgiCg9yDOWz2AdGgsSzak5cQJTMYkiVgCnXZDxFqpZMxGYseQMfcpfV2WBD7SpBCDWiIDFrtYCj8diVhCc1isDZGiL/QARQ02KpWEOWGtkjGl9lBsowuLVBLmVHOVjDnUlUUqxG9+rJSri8y9j5WFjNymS+y+YqYVzIGxf2K2VpurQ846tg9Mm34ftxAcYmh8t5RzRFPw+0krjaY+wrsM1Q52KoZWBQzQJTIcqwCWtXKv8s+ZHoMbEQQxYmzVg0gNU/B7U/zAdYEtW4t37zLC5pwbWtWxuPP1nWl78CrRTzEeP3AlJRqoaBRVkvgOf+uk06l2yzpaABUnAduPZGDu90PTpC4QNqFgiUeV9foHQzzvD5j8kyGiPXIJW1bu8UFfn/fhuR8owoc3kiyFSeTvizPk7+G7RJV5GiDG+XGk3zkHFPj4YYK7cqHSCK/8aMq1R4vepm24bnV2Io78hxWduHwMT+mSn/gPKzJG5ntWmEgdttb9ydbjhByyGt5uoZfxGpeEkDpgMYBIB6GgYpi7dfFuV1bM2aF5OglRBWOd1uIGAucZwzOWiSFIVw9jrj2qYXSkevK8YgbvOkmW1XUDnEccTWNq48AGKgmT7q2SMxf64tzRKgVTOgsnrPrZK2rvEgVeuZrhHNGk45dTLlqOTsZmYN7kb0C0fjBh8ZcaO0Ro9VgXfXwYReGzb9ZKhG6Qb9AN+EY7QrCCshvj057glLuzAwSDLu4GK/VeP1iGxSMh4vrdFIgGPRdAUAPkzItQwtguZ75uEUHc+eqDIpyVIwJE01N3SR4tZvc3EU6IEoNf5qX7ctZUpcV8zlPgM+kMq8PZoBH1nF2m15Z1w90AMZeOGs9GijHXEbXQjz/+drF1SxxEXQPm8l4cP7y15HxMFM+uhtU8kL+wxnFj0MVbqan5Bysb4o06ajZmhnol/QzVSpeUEpaUGXhpmEGN+lCjqQYtmNb/QsZlj57ltjtv/TLlPE4XCzg8lFdKhVmNfJOG3on/0GiD4l/n00c1hz2UWO1Mbwf++GJWh8OowJh9Vru7ezwY0Z8Sy6qsNHa2LGTdEZDLBPL2/oPd5s6d1hoKZtLF0f4Oy28pmvEJ+mjTW0uLgW7Ldwhxd7ZInmgf7tFo6G78Yg5kI6H3L3VBjG0xwIFmgEftaNW0zuUartVJpBLkoRFlasBqJRq29W5IzWLPcsFYP27ux+ynDgO7CQkzhj9qOt8r9piQED7H6wua9K0vn2CMLK+G9LLUy4n9SSZZo6mrrxX0zyzSxgUUS5o6P8mZezK8SMG1QPE9ykVazldL8eIsfZWWWkLAoP6GjOBaocjx8ytzdh7qhzes1FdJmMPTVVJSCymzkZQpTBLhf12HEfrqE2oV1qDcGu8g56hsY5xtxrVAhkubR0x2bxX4N5umj0b3u9152ipFY0GYu6L4J9/qj6zoE1g1XXl7p8MjXW0t5latlL5npkXHtJmiqpXyPDph5pgS5nHVSp1OfWTk3L5+fhXPAEUHT7hMO9QYX65KqYfsluzhrQbPq5otoWLWqDFFJqW1/7YtwRMV14p3++C5tO4/qGLxPYvOxZL6w/92FY7oRtfQ5g6vBv7GOcb1m+2YndN96v/+OYZDFwIb320yMvNWVWyKY2ve3i8zWdAcd1RJGS/cm9NHte6xFeNGufSCy33C6muELL2jOl0oyO6E88n6zwQXeVMU/cCxa88vAzlguxTzUWRSzgkVhC/xuHvgYyxOO04u0E9o4Y0EFSloqwhHXicr7kicHt6cRO74P27pO6FbaF0j4eYrzmPKysHVqi3glWAzdNZB68vcz2UifDharkJMgA8PZq5EI/NeRIfpT30D0V7anC7KnNl1drdLN2N5L8t+a4f0WuM/uzV/aaCPYi6vuHljgNRJI95xdFqjBeMbWHphiXDJHhDb03dzesBAiGMVAV63DIR6di/Ft56XSzhBqK8qnFwZ5NTOAHLKwNFz/mpVx7GvhvhCExqgFrP6H1mmMyQdL2J5IDJ/AFwB4gSAbibRCFFigbpexjVDOOnN6h1Pt5TgUwpQUcVCXJGSpbyJOn9KeE6gjrnmyN+q2t0tH6qdJvhZandMMe/doYniJOdjPhT8Bk7CG4y5aajO+ALdUcZrF+P7R5cZUZZ4wJOWUGZr0nzKIsPEawO0dLGShPEQBCnilq+SMW+dYK8ObYwv+xCt51htHHqtmUqLObbypBgv+nhEotJlApLKpALcuC7aPX/M56cf/Cv5i+OjHSwm4hvWzfifn2okN0hv5esOPx3Qw+d1muxY7DYFHydvRxsG8QKZ5g9EuJJ8PpfgHVLOGU39PK3g2p1Nj/AG6h1JlliqBD8nzTuowFsJRMcJZ7yvHmeH2Kt+c6/su1cXz9KI9TLFKghtIfHVHrg5p0QPXikX9Gs5qkI4pXVyPj9yie+hQULCIuuBydrRKR8Fu+VMdzTogGPUanxiLgWK1nj6Snt8ggTCbe+Ab/hytdGm525j08eN+YIP1vgfgWJK4kFVcqZAjg+S49d2LXycuENs1cPvlFxN9PLd1yOJFjvTcWCN/zWXIXr7eemyuU6bLHE9dZWcHYo5WRR0P0pvKF55SKRmR8WUUIFhDu4T4UuZBAwH1To7cez4HqnE+RkizynStRL1TJ05u79j7ZfC7bxs17vo3Z6uD4SEMQPSa4pvmbUXEua+rbjzxi/XAhIcOSWa2rEBy75SZPMHXCUKG/Txxachei+Fsdy7PzYnuVx8W3AvS2eGfAvpG3EXEkw4JZp5P61jeN3bxkKl7yLO7uhVeb43X0QfuYmn2UfL6r+HG3gZYAAEDM5bMGeTXwY5R2AahZtQws0tYyxeaCQdudXa2bFl3AWNJA+ftGG2z+Zv1Ujq9alLRvLG0HSBD0IfPbw6uGXu2ruWGkktvF58cA527aHRiLIhL6u3lQSlYC0eMLUnsn07NOLli9KL+N3arWtTRYS36cNFA5UcVyQEJIpUchycf/+dSMXgDfm7N0hYpUqOXx5OPiJRMXjH6lWp5LAqx2fWZEcTJK4bb2/FKVjMGaNpXcZ2fXWyrzdmfnLOrpbj0MX7SkR/4TLfZ8TdG06xC2Kqsj0rUdag3ku/vWrNwcGCKE+ebptjSkZYdCRgwVjK6nD6aPZrp7l99N7tEfRqU7SxEHsNCHufDLngrIEV4E7ueffhpOpT2vvz7k9SgVvbEd07sH6g0nrgFLxIqTlnAQuQeKPJmY+6BAtPH7kPdGwbd89mvhByYYS65B833OQbUQfHmQgeRdWRcZ+siXEFFxrhmry0hFM+7wGGsDZnjorPdtmYOqlOOUgBOcg2ghVHYEPnTM/NHMcNnAHgKGpOeHVJF7SrbO7UGqJbHjjtFVmQ38OpCEo8SmHDcstEOH0D+XYrToLXBBLSmj1bmuaXlX0vximvf6+ILlo9eXfPsSeau/LCMr1tpcny1Cbj+G3Qe0hUY/86u9sIFAntDw9s+vXx8Tl8dotnHx4VJFcbyv8sCbtVWu11UGv+Z/7NUS/3iRyjeQSnb+4vU5Mv6R4W7iB1UZg4evurXQe78QXEtVpfSr2Yc5V/+mYvr7on0/yihZv7adVCohO0vr7GS8k4vgDcTn3UJGrc0xFJit64K9TbldNFNTzuKT8uNDrG17t3sMerGWOUd3mQrvIesXV3F106hOOj5BBsLsNfdxCShoZba8S7iZNN4bi2VMSpkCNnmR2ve90Yx+esIgQmpysccEVBXfBXGupY3CR4//YtfGuDSr/O9HDYN4xXKZSoXWy3Qzq1Wnbjw71UqHGNN05+vu0W48+l28hp/Pb2Gvh0hQOrw+miDYb7nBq2G9mRb6JIEj2rc25+Pn69rrGKYY4ecsMZJwmOzfcLV67vDJ8WxPtTWSG3ywc6vzr0WRuvIha3lSJACN0qwieoobY4r3hi/Iv1RbiMSAQxWybibJFzq9U7t02L98cVrX9Qv1TI8U5GTf3CdUJRS9w/97cq2IczKTXHK2rK6ADqAAtn8bqgEOjDxNeBSawHk1jBm8cI5gMdi8AzBXe6vp7lKoQxVDtnbrH0QOoKPsEYLQrPLpuMekRCmKQUgjGITndh4sThcbUz7IUTqPXVz9WzbixzF2py9Ptaq43P4H18DkNkuf55B9ddK3dpdNkQHdukn/R5wPpsjUQ/tGTRgGXvEwP64mMJIcMEaofGAjcTgbQETQQ0l1cTWUalxURFi3DCNWKU+BFEL1VpM3dzeuLEmzPYUFLzmpsG51Ke+BT+u2vug5zXnVMG7+ozABdkjSS3Uib4oxlRizeLcGAKmaIx6yT4URYFIU7/JsFLjhM1LzCIMO1Exmnjh1eJs8reSyY4+6C5imHOH3TEpfvrcEYoq8f3OuOLPljhbybqmjlfVPvaxNAVOrOG4aKkkf+WB1mgJMmtCVNME9rjegCKpmZgN8Ik2DG+c85sw3H5YfA+7Qg4TMblprXHTJqKeVoRzh+1dA3xD1mp6IG37ST2ck8CLQSWockUk5BCnWaJwDS2WAyqZiHRmk8J4Mwr5KBvJnpBnrhBYExLn89ilRYTt0OEi0tEgIBbpL/g8WPf9Bd4F7EzhItovWJaL9naCsX4lIRrjTKcekSs+Mrk4wPcnzdJRouSY9BiMf6T5nB10fIrvt3tOINe+FyZ01+3bp0IdXSO2Rc/ZHN/fC+ObB0jYQOZDPr9fCi7SgRlo0ickYzZIwLDfJqIJUb4KyKWqN5PiZEQaDPJ0XIradhpMdjl75PvqyhawGHy5yEZsxgp7GPXpDiSzOMyGU6hV6UhCvyGWHcuZQ9QPlo+IBGPg522/R/CU39wNKmt4lLM8MAH+lxNlFLufrzT5mXrcAY4pEIAljYcKa1UciaWkFRxnVDLVUabv437sAxf7AbIa1RuqP3cgXpOzTBH2W0k6sJqPhuVnHnrhEMbc22RX4DfwdltJ/rjk+G6IO/SKY09kXdSCGKi1QEtDj25yGk4sYphHlVq4wcFmAsXo7dWZ9Y/ycqJxunRJ6hybK5BUqUFA6AL5DQ7RUBOsxoQ+VlfOEphOKkhOKkRV32rPxDTSH/w5ynoMVCLMvjUpH2sRU9cSnri0qInLik9cZFFUQxkl0wZZV6MpCSEb53gV2hjyvHnAxPh1UQNmUSG7k6CGF4zkUsSnuFOThjuIJWw3Il/jIVKS314Y4nJ3jx4z8XBGx8MwCnbRTyIgByWD6G1I5Zu/kGcFxpfsbjJNbc2awi7Ao0oI+NnA+NXnR8/8qplgLH9ox4tGBsMlEnmrJgLFqFpkp3pYZOu98bnfKASfajEFCpBavwtvhIZvAYpHFUUfEg+qY7E6pBYeTljgx3A+WMmDqcK1RMRjqPETS/oR44EhvqEFKzp5wl/q0rOfNPCN3W5vSLEXukxfKerVzG+TmJXwYaMVaC9Ai4BJv62NeCWwwk4wpQ8R1hLnhlMzLRTiQFnpROUApQCovYwPjRyF15LN1hI3aH5PVRi3EslxoRiqh8c4gnuyQCVFA+CXIPh7xBKowN/hwED2QhWxh0RoWNRzPOJk0J34EcY1gTIGCJQyDAaaQwjgsWspwEKIRPsDwjStcAerw05dViKeQB3CPBXCW8TCzQ9BtB6Q36UxNhMJcYWPGCElUrMWAP9GvlPdZUYO6jEuIlKDEikI1g5oV0Lu7krMHrH1bs4iiKx9oSGY2i44R8arvtvbLj414b/q0Zzpqhzua6Ry5JxOXC6E5MmAqCSEm3O/OqjYzVRzqt6psh1U5+8Kfnx3C85TdGEyFrKSf2zd/0S4WqKtC6qtP2f19fnvdBlgM1D7G+nZQ3tp/lbffrlH1bocvddz7v7WxzFTWHAFDBgmKfd4lDNJQl1+lb3EeM7vxvAwqG+b2Y0SwiafeL3y+ijw9X2xLk177sagl7ErCFnjbY79A18tFfnKX4vohRuKikGUYmNwSe6eWSDg08vfcqESFvC8GaGjk+2mdan8fXZROnTzKxEYR3DzrVzitomGAs+7nihPeP717mCMXH0dptt386sbyAkXLtSs6i3fs5dIWGI/nI2o06HRULC8KfK8NfLN28RErLGfn9qJfZ/KgSObHx2fIPbmxuHyOhibVbO6SI37/Mu83YPHsQfVRI9RmZduIVb84eKRuZhW2ofMaOIXUbk4L+uad0BIe7+AHonZo0IRtz72ZFu3XsGCXn8++peKxlRE2nk6bEirmXzZTn6fB4lGlfecIHOmpaGQoJXYJNNPZen3OYTdNEKt7bYa5XMTI3C/GhRR8sp+YuFo6DH1ob1s1dfOcw3fO69jkleIVx1/iebFL/b9svTV/zZr/rDmkPP9hv6QvAMN0U1F6YHZ1j6XcE0BKMWXJbU4gxRu1UPPt6IiHfEIRJQ1UMIFdnsh/6r7j3a6IcvacPpLEAMIRGtYFEyQDNeGwjGyVw1ZMVcfbQv1yahZKRHPjneaOK2073jBxQ9DconU6h9uytmk9mrc4QTqjFatHTSmO019GYRmHrMR8ARb/s9pXNWuR14IuS0QwMXGqac9Bw6GJflNSDuOqNxKYFVPrnGRMUwWdnmOCCdxPd3vpA++HOLD878zKuOhnR9zVQ+GtMDU1R1Hk54k/CDcLouDQi924e9CjY2cvRsdWLM9Jj3LaJ5JrdXxeaGCz8lR+FHrtCc4UCfeJqMlJw9RYwf+bLx3WpFoxk4PZyef07IgCdvLfVtGA45Swy5ShE6eUQpWrNg0XJ8JPOSvUrCBBA1JYASUARIQaMIYFgH8oFZAnSeQXWIUzbgHXKWZQnJX1F1qoLUYC0J3XNN1oawBNixPsR9w4EFi2uxI7uTXCgcd2bvE6FwoDa7nfw+VZddRHbTp/VZH8It3oBVqWTMFjeoMbURcBoGNoMGLWoBWlAIvRlPag0fd9vCLrzHC36FdoI2h3nDBXmyL2gbH3vg+36g1DwciU+PI8A1W5U4PJGshOWx7Z8ZvC2hEGCenDHKbnoqqDRyki+moUAO8BIw2rOZjb1T2WgezMf9xK7ZaU7uqzM3k/P596REivYp568/iu7LV6VEwXu7TVK99q/PWxwx+rhc3I7zlMxSV6KL0u4taBRcb2Yev+569r89YdTZ1WOF1pReW2lvXW8x+qU1Y0crT3Y95BrzozVTD8+vd6f3AG++NetF6I5k3sjcVY7J+H4tYB4VY2Ikb6ESg7wh3l1Uv+wiaBUS0CrEf9AqpExPWD294HdvlZTxg72iD5ToC3/7wV/gHcUD4bta5yC6zlA+aGYe2tnyWnDnyYPe4b2UHVVMkIywF+/1BYQz2Bu2Vdom8s0XWkQ2uh7QYsp9qm4JKaFuA+U+JTrVQJWYocynhHBCioezYu62COU4Nng2JJprgreeE/ERlsTHQUw4lXEDkA7N4Bme4CmlR/2zcFuovz0oDV6w9XeAlnUE7QwLVDld4Nm05frA2iqFcdQDjysJjKQejKQcuFv1oAcIxlIMY4mhHwz0wwg4XLWA75GBEWVgRBFocbqgxSHQ4rRhfFlOibbnX23f9btFECZEr8PJPLiq96LrgaN3W/w3zYM5aJvLdIv91n1a4jzz/xfnARmS2yK06PMHD/uwod3+fzoL6qEcz+7uAd32BeFpoCM6g3ono+dmLGd1wZdNB5pCzuCNUd9r6Q++4w7ncZ6YxxqkDlQ8pCeWg4cRKSMXLOig1nG9Uf9jjzuEpoi98F0FnBvuijT8eMQa+7AjVKTFg8ZRhHziCyTRhNhVyZnTEhwu5exQrWo3j2vfrdEEevFz+6VwkBRjJWEMzTML2OcRYY83iP6k1ZTqSAwcASZcR/TYp22CXcI9bXxf8hvNRADZJgbeGj0KdglHNzH25HRRQta17331Qofw0vvJ08MX5xT0W8vr8LroTr1DNtI5G+T8/+O6je6hmtIkRtDx15zTM/V137UGN+PRDqWMHSZsES5jnf2G3dk4R/AH1Ed36z16VjCy+L1G0voxznPWsnUeagQ0B6dNaRN8cHYApi+QXHB4TWoZ7RY5eaJGrhvdQ4veS8K3AL0CJcSR7ajYb10m2wfcu0T9N0NtC+fc3n+rbAyJedRihvN3sAquNUoa9frtxvQmrv8ASKw68q4ZV9ZiwJZyXItqoWrcAAjvtcI1uBQRGitrNsC0xroIfD5QD85fUlD7SFBwgRQ+Eqm9IwU+8CH6UaIDH3v04CMXw8dJWi7OCArcoR934QPfox8P6cdj+hFoDFlWwAdeRT/eWMDHO/rxtTp85DvSxzqyUu6YCBnnvHg440zeQnzpQFVavU37P954JVoy7KF2j1Qlxft1IDDCC3ck7dPJo15hiHNGZe/3Hh25LCoBH9dRO2GTozAmZuQCEWF9kzN7tXApuc0Thx0qdo78piXcXCrRaqduy090OGHOX+Xqo87Pw2pxDzNX4J6QpyeHUUWn2vtl3azrgHrzgMR+P3O4wTzwmZfPU63oC4hp175/WbN0Wq/BGiBqnzMMbCYv+eypAaKWlOEQ/kxaTYe/YdZHxzYuTDnW9XYrjTw+yWjZ7bl+h4VTYhOu7YJvRV/UHnO66OmM+/b2sUOu8VD23mOHD3d3GKH9k7+qEtn5fi23vndeIlxiDKyzqk3yDtfL/GHKGNXuN9G5+Oikyp+w7Z3R8RO5zR6ZNQcQNjWZHBELxDXmhghvFKsxO7iaaFr3G9OOhj8YjxN+5P01lz5SPJ59vXbC99rkYE0qIqwAR4yKSiuQu9DLW/Z+lT1Wn3sn9LLmq0eta6o27YJeOqK1qQVWw4ZGLcGpOjyJxZ+3yRFtcrDX3RM9dNRf5ayBnqRoXfTae38/3qXO+cc8XV80kt58rGv1v+fRR7Ni2l+1fn+sG1wokP7po4GP34XMPjPeVUgyRt0Ki2d282g5F0sF1ANy2Fu19nWDoconMb8kByWGrt2S2+/UL8kfVpvYDhnp3+SX5Hh2quu2ilOxPyXXRpkB6ZtXukc2wid01CZHuFL/s+GwR4HsXUWLFvJNeLdm7j9216jPlk0N76eO0nidOnpu1qsjPp8VXqfh1gZLZ2r51hJeZ4fjrK1V3JgUfg/asPhM02WXylcIBc5KCrlBPdeNFwrMf5u34NJiZ3q2N0PGfm3mRtzpZ4DFsLmv/oGt/Sl8Y5ZRd7fH/DTuAdN4LCprVLfX1WbtD+GNFPQhmZoR9WCflWt4yks17gSkYI2T8tY4CpHMgyOzPxxx1Zj8Un6HcEB5ObFGayOWX8MLeFnky18yKbGBSswQC7IT5riGqPmpCZdvjgt/iBdAY1tDm3TUHC48Nx19QRR21Qm7cqMQHt6lQp6BS3CGHDrzXMQXJJ2x0jAt0ntRA57ujt6IqsFxKaUnhmYbsRIeDErGY9K64lZcLVT76WZurYfNRkJBQB4UJtawYVrCg1hwCCFUFXOfTw0uSE1xFdxhJOnfM8/X7r9KuI7+cmHxmazqtU8IgfHd9ta+uiz5ywQhofjAMcvbq/tv4UWiLpodvtrzTKMnTrwR52SdpT5+0pNiYmEj0p3TR5YRvmvd2OnpkESXm758efJyfdtCoEzQwUpOiYYO3uSZsTtnExlnTAT81qmGt6adVVhq1DRvZsD1lOzUiRrFHkWbB+m/HrqVL6ZEyzy43b6zGDfBay9p7YfPTSousLzRKTRqYde1tR+P49s7anF4sxE7t2+Dha/EBsS7poa8xc3yfjc1xMPoBfc7No6Z/U0j6WGD3GL/OacHC0nmaFjqS/kpdxtv/FSLp7siFpMQ4us8X7FlsujT7DR8UkBPFmymtYmOZ2rRe55TW8p20ZNTopfDO7f/npVzkV9wVigt+rJn6RL5dYJ1yM9/6gmihfW4lihhz+GHAWdNt+FckQZJTyd4jLGGg730p9J0xehhQ84U7bo5s6x+YudScEkW8Rdthpwzuu6SkfispOU0HK723/5xxy9UDSgyVsiv0lUW8HbwV2z3J63UR7fFTqZLssPSBfx7U3S2dUyfvDsV1fnHzuQfq0QNMhp/3R6eZC+ovf2bl7h3umQylc85Xsi5/mDkvYmx5S6CcNrmF5N8ecQmakEhs1YVqdjd8MhsCpg56390bv+uojeBpxvuEmB0fKtJNnyaF1kMCROIwlEchGeUbL0jVHrHf51e3QS5LV9pfVS3yRsP/zndxuAoOi4KGJfWfxgXiTDEDy5um306/9xVoqtSlyRGgbW4+mhXxRWzN2krLhFn2h9vr53GTZQ2VCXjq6qLPMMvjepv77UE7/jhhamZXy5ww9Ax2tFjtqOLsvd93hfLGM0PXuYVvSDWABtqgEWZIrP1T283v3plPt/E6XwTlWiI57tPC66GUJukP2eKdMqTrL+uVs76pTNKNMrFurB02eQVgol7Sg2LczufXaWoRjMI/0vjFjslrrHlfF1KFDBqwYBK7y2rhQCHuHr2GWOXPP3O16GLJswdbFi+c+oUWLZOqEdTE0+TxPZd/9IF2Am5h66UNTqZU/kb3sIjrNeu727aWw2u5IR8dTLv2J4sG/WXZR3R5aS4+P2FdR/wWY/q4gxDlYJZtwBvOkJy7j+qi+9nkJwf9BM7rd5Yfvmvc5bVynQf/2To9L/OmdN9vf8CRb+af50z6+zql7PfPcj4q5y6yHvZxZfd9m9I4gXng4mlm2oOC5Hz3kd5IYZbP2Y1H0OMLxgD5a81rLWOM9OyJXebv+IH0RjdWDBhVO424yG8MZJaGk1RaZv+XS48qLOOBxtbyB8zrdDnWissjDKnT4HTs0jtWYxpTJQtCrlx8JZPYVgMngHlHDRWnQ7IU7LV9Z80uLJy23tK0+TKOSGnzK9fC2bodOZJERw0FoyempMJHC5NUGmjbYHrNhzMxRfdVQx1eYIV00bnhfjxjd2DCE0gQ8NViD6ju33NjVUP7rUCR8FqvFyzRC2T5w5y0dNCOEkC7nrEzyWLnHPAqTOvQW7Rd79T4ylSKiybVp1blUX5XVNzl5ij/sM2eGe431+MI8S8IYNgWq0g78Ih66oo6trsjfyrGddSPGLhzS/J/M8+F25FvGjdYBivim1rPNl5csOZEfgptVrREKHphP5r5MOube7NihEwymqgiY029TwU5e6nFvY/+qoFlynENOCqZdjni47ZZKGYIerXaMP2lM7eAYQanFwdfCMnnVUnTZrOTO5vSfjb+JEhlzrxD2yu37bPT+FvIsX8TaQlGl2R5CIysvmGV1OSDiO4ITfDVqyc64dMtVdIomW1BuHAq9MFy48jri/cF54R48VEd9yggIv3LAav0wL9f4UOTiIv+dByMsFjtonwu1OE+STi7BR8LWa5iCsQIc8HhuNWXGuSgE/Fi9R804yItYUZYgEzxBQ2UF2NWyEGtjdg0IZLXy1IgbsmRg/y6FPDFwhinhQKvtcAW6ijSsyQ9jcSOAV8NW7cp4C7wHIRnMi3iYC/9bRGTMcaMT5DciTpwXXFcn28g6qJYWa42JKzQAY9QtMs+ipL8XAwQxE3VuL3QCK/QkSo1dB9y6N2NWqN4z5lEd+nMDPisWJJHOtr4BxHEoQ7WCVhbkxRaZGRwzHbqEND8gMRvhcGLknLZXjHEtLBiHDiUXg1g8Ffw4hr18GtRvjLKuJz9nF5DXz/tKNKxpCRJrFSFVtFuPTSKfI98UCYGMd8yBQTL6VBrWPEx3oGBOPbw2HoGRh6CrtsA0NfA4beAYbeHIa+Ogy9Gwy9PQy9AoZeh58/UmDZIoMuhkEXC1NmMDARLBfhbZTlfQVZn0l6eLk+jC0MAWeIvP0GHgpPEp2GNQ9SiOuFtD6s3/G6zMFT7XyCoL3W0F6FhveShJ8qwL3CaKr35Jimg/VYDd9ibqcIOQyektBmWs3N+MJw9dIQ7telULGORpSk5E+OQBoGWkjTh0cY/WEY5GQYYA42+mX9yJk8Cd5GogRXyPBSeoAutsShJAAgxxFvrs9ZoCF1AySnjok7ge+WEfgv8IuRG4DiC5hQ18YmQ/HbxTRkRw/uTun6MIWXRNungPbVgPUhh/XhDm00BWYeR3CCI7Ro5M3k1MV73Fktzgj1OzjZ1ooNaoA/EMthfdwIgIqC+2uPjlixeym+JObnOCZQmlHHet9Z0qkurmhF/SBUCrAcLxXxmVQwHLoqBQxHIDkQmHgVlLuPruMDt9AEzrAfGln+5vuxm8F2/weS54IIuZUs6Pph92h9QfLYqJlXBMljpnFWZOCtIw3Jo/N/J3lkVPLIqORhCMzUGnrL+78KnePhW7Y4t8/a+OdCZ4DbuIEbmwx89V8hdCJFaOTZtDnKETmXqNBRS30DDR3eGsaeHmecYexNNUSPO4y9rYbo0f53iZ6ye5ucOnu5ZWmIns4oZrRNZBcz2Sm16KFktfWgvSpe8RdjmcCjJoFWyngwAWLj4AF2sREROO/OFJoXZfa/898ucO5Vbn72pqzatz8ROB6oSwZbcaXL6734EcPLG+rpR2PQTfjbIrUqoc1LF21uFpryZZZ8akqNYhw+BEpq8VRFtLwOL6SV/ATW4UuKBfIJ3i+eYdJ4NisJU07+nJYIbksSBjxJf3acN0SNPd5uehKxuhWQlMFlFrdYhBIy6oTMsS53xCW28Dp6w+vQ/ol95MfGIuZZwvitBWiG9QRgYSnpLT/nNBFwg8WUA03tVaVuGUVFNkNrvcfUmfZ65X5cTNU+wjphAW5fHRtdjC2sbnMF04AeeiLVAyoJKWeDSrkNegWT167BhJoSsKMlDCBvAGgGVwMdDS/Y8TFyfS4uUlCOPA2UDppHhV5++pjY8ZHuXbxTBNH4ttCf3ngGZ4tOrw19Pedo9D78lUQkjMXLhYL/82o3uuBTJHyu77SjTWNHsT/C55L77z6x7Y3NFsGuXi2pdFfCzQk5wlnzzDZzJqSDi4hPaIwOTH/Q+OPsFtn4rFig9mFg4LUFkyzcIwJnlTFsVFZkYhB2qQEpbWObeH8ZhE9002B01tIwwUg0giNNoCqwPYFiY8y6wrIx0PDplcANsTYEd2Lq1SvV8FmOlcLEg2m2jsHx2lySCKVNXXJxxLSau3FMlO0fQBa0hS2EMnJps4S6Ssk+IYqmMRtMfGes2PWuKhnjyOabqmSMO7uBbAWdWSAh82fH0WbUp87FKupcLFc7UEObtKhzsYQ6F2PqXCyhzsViGtApp4EOJEz46+eQj0GSDhqRsweTbrczbGaVoJGkXfx507tdg4docFNMrH27bp3altn86zZFxZ/Ep0xbiTv/gdii+6oDqrB8zoOIYIzALtG2p0nM4exXcQJi0ZB2dU9XO/dVgQep5IwBNoJHdHx1rJ50vdRJyNW9Td6FxnW+PP0pl9nR7w0b2i9oKMy7w1PEDvMHmbwWrCCXPpy6s8RmaE3BOS5+3vQGBSsuRfGntiQc6hNloref/3mkxUi//SYJ6jipBmmbD91JLVC7AL4vyghwic3O4s3zqOSmwn/mzjDB+Ut559Xxa5YqXd7KKc6sXb1o/ZBAwbWuBqpIadXb/o3BSmpAMuBtzOqI1KaY4B+brn8z/qavT1chwvKxnfcqbuaVK0JCrQUNslJ31jUQEjKmvrh88k5pmXBl1ib4XlFGcuvhwqMNUL824wut4ju0wMVS3hlXieKzLCc41K/vKpjsvivmf/0wvOlWIcGWcbV83bz7ByFhe59dSy/EzfAUEp7M9Go044ZtpZAwZnvMssSOR9KEhGXiVSP3TRljIiSsOvp5RbNXT7fwCY3Q4zej3uuFfXXCZwpM1CxScLfCAA9lvAgvIVpIhgJf0QYsjd2H9PHaChXXEQ3InRYz8+KTOJzxHvz1rYh/CkO838bheHJueyGFvQPKqrSYx7HaePch6hK8tkJFosweOeGd91tyxuiVe52oHQPaWhL/A/7orMMZouWD91WsivCYQa4f+KBFQ3S74/GIBZKIQRqJ+ijh8EK7zYaPwggjFgGdJkxf/W7WNMos6i28mmFK7SOrcm2mCXn0UYbujlll9VrkaiQZXdg8J9u3XjcNxtR9/Z88zHhl1kBIMkHGdu/tjs5//AkHuKkY5oYZjrKArMfdemi//7R4GFbwuNuG6NiEyPqRFSPH4BxtsBXkaHOGyKf6qamrbB5a46umkHiVgBjexfVyk/xbYeKiQW4/bGAlG7qHr57yuMwRs7CSpZwt6hi3OXPitVoGOLboVFo+9Y/Uxe/2F3zkGdGJ38Pbt/q1C/Y/9ROaYosCeg5dFJW5rt2/KGeL9mDOVJU2Ru9fVp5aK0Aqudt1tkblXY7l+sab7Rz0L8s1n5NY/9nK/QVCOX10JTVupHvrsDZCkhLZJd5+flVnxSFhz/qy5Ebw6/iTdYSE3SP6Znt+WVgigAf0XmPqWezqmKNRS62YqQaJ4kcmQp7CuLfuU+Qz/bEHjCR5OWd7vFg9rPr3JJwlg/eQJeNeStGxpq+vDrMY7orX5x3ZctZcpcDxj3YasTKVAn/Y9siCVagUeMODLx6Qsmb7YeLmpMD702KJ35ICP7n4pBf86971yL6sXKXAqffXTYFSkbsezoQvW0+WLWQJFXHRkrsB5MjB4MPLQpfSb2s/H9hAv63+cvkIwalh8PqHjzIhkhHHh4U/IOdvBn9O/PqdaCYM/rjjwW4SgsjgBwcPHRdDvrcndl+i3+ICEx9AZBZefPT6chLe/GH7y5USeMKi47kRZKdk8OIdX6KJ3YvBS1bmxBFRwOCjFU8PSOAJnz+HHZVAbQWPc4rof0sPBJXQtNvXAm7T+tZGnn1BS0ReznoFEDc450vIYpI/ev/SYCk84XTZ8xIpa6VicGXA8iAZlFxalrxKBi2JXHsvTMZ6qBicd/XsJhmMU3D4+U0yeNa14MxMGeuuYnD4nrtZ5IjI4OU7dpXR/y65XP5NxtqqGFycvquC1pcTuzuSqCAMvv7+2DY55ItIepwmh+du2PkyV842VzH4Xe6n8zQt+kLJVTmUjUusfCJnTVQMzv705Qv9767DG8tpLe9eR36j3y7s2BekgH5nl9xao4B8yWtOJCugloMPr+YpWCcVgwOL15cooMS2lK23FOADP3iUbUc/cV9dnu3DjNNHezxC7jtJW28UIvyU6GK+Z/ZXm89qTwtT9HHPkXvdTCaU8NfqYt5Ga4WSQuPTSkvCj8FlrfqmRsJDJemjZi4ntzg41X+oIeLMu3yKyNzTapCQVB0Nf1TD4K5p4S08gI8kEyISeboTQzSzV3ZJzpl9a/AWwomQQ2/GXdafqR46f4gfv3U/9Zmka1Zyfwb/s8ewlVaLZd5StTN/UZs+2elFMsE9+GlO8d7t15faw40z0YKki3bNMfWPdCfij7HABMl2keeLYOtpKe4CEknXogsdxeE69gLsiBH6ENb87MKEKQl4lwhIOi1YBYdRs8t9rM9rd6X+8hXkQvVty7sjeg47K+Wfp0Rjlhkbpt7YNlBImDq69pduMzeOwI2IYyhnjIYf62bX+duKWz95tBijoBZ2Sa8PWtT8BfapV7L429Z9vfb+OeyTJ8p5+2HNkV2TxvxtHBx9ZPol76nJ1AvBeKlCJcGBRNR1unb4eDWD4brYF0bEl/BCnrn5ce2nDz2EUXs7K7eodcXkSOwNp0EVt1yEJjQ9MnpohykheG8H4TZCVwPxD8NRzAQOjtoQD4QE6DPMw4Bh4FAlk84O/rrAacKTd4pFEIxJnNzCRTiLGlsWE8W+UAw4backOJ+cr96nNHy+x5dZgWOf6vLTW4u5HirFxRWEUqc3Gm63bcI77esqnCXVAGVBv5w8ZPwBXiagq/GNpX6EoKG4YOorPxmHizgb1JnL23+xImMrXr2EdHTRQYnGk6VcW9SqsnHY86vySfhIhD4PpUajmRzhACMWsGnIuXitCOeJhAhBhkQI4peb5NxgZHPrWs7EW8c/4YOGf/D3kArmDARjSKOsMLi5GoPpwxJGyw67QGcnQ0dgRNWxtJwLsj/e7tP8J3FGOIf4+YvYHVREOMNRlgE7pY/ahQTrsQy3WoQ66Q/3NZxq7YoPNtMwuYyDwe0N7fSGduoJFwMKOO4hVkswyWFokzHMHEuowQ5mhQv4aHiCq3AvlQIGHEY+i34spnTNhWJhHpijzxMemI+94N0UZ6xDKi1m7xsJXh5Kbq4Godj3gR3rmo1/jXNlwmSV/+HyXz2UcnIrBf9RT1QxBKKRxkmgcSTVE/dSz4RZKPXgh5EnDtbwxUUQL0Nutf6stAxKK6BrYpjkUnglMhrkTB4NV2G0axLmFEmBAGeVhMnUokB1EgGoTsx1RrtbpsxKPev0HD+Ra4jwFtDFjtDFxtDFlkKsnnqKS8GMg+GpxtiSFXO1UUnQMfmMr75eOJaYgzxxLyB4n0xjNvnRV8+a/mgf27pifMSjZPzI4Qf+BnSJWr6oi44xLDVLmJd28I5dwHzrCSm98GT6PsU/v09DdONLh9UunVqYQtiyDoB9mqNlx4MTU/wG3iRmMAlzkwi5CH182phTIo8blb2MWmWl8SfN4ehikK3+oSHOJfgN0ryyEy4jxBQk5ieboBpXUdNeTLGfpGB3qQ5LuKVKzvjg4SzDeaEGTSraeO1a8hWXmwn4RZSXWg/OSIRF25gvywB2LKmvAbShJWvN1yTm5qKhlnpjy97U3I8fWoDP0lHN4F17tc8SI4W1LYObHjmMoRrAUReabq0B4IiE1aWCka8Oa88JUhpAl1piH1bK9UZ4Ucfj+q3z++Krcg1nFrGaPZrHr6JGdrnAVq4LTzCEFAvI5wCATST0aCreIeLaoK+sos6FvAW38XG63Vlo2O7QL7Y7arUjTuK6wPdtQSvj2qGejNaaPYEDmuC9IjVbkeAEx2gIRbXtT/0mddWxsIwFduA8UPvNR1bpN3n/CC+m9dRTdxPTE62Unw18aXACIS3wQez50DXnZ86Zj29UzFXJmfe6uIzYg+54wMoo9IEIqYIpMGc+byPCNe8RUb61mPU5YvzsClGYtZgvG2U4JJlAb7VCA9JVB6NiRvTH2aeXimgd2irEFEzBn7dRqANSAwkNWJ8DPlHMsyuSn+qwQh+Wn1l/0+rwaxwQcOKhSKXDbFp5V4wPPPsgYZtwTVDPi02+9shTqXDBhWYqOXMf4fe6hHndgbYc0afKaMvNCXjpNhEmTzXg2qGaW2bod145xQYfODyU5icAs4U+uGAKXNSRVqr4Vupq9FP8UxstUayrbV+u77f7OCAgdqpKh0k59FmESTvZJlygCDUc6vd0pFN5O5z9VX3DDMd1hnduYGS8JVeLuvnAmzGE9aOC77Ywd+rDXypU/OD7LLBDbBfhW9QEvZI0ulILlxPAhkQjuD8pssAFdqyMm416derfIeMd44ZfrJbQhUxtBryZQ4G1wCJtKDyMhrP44VkqGbOdXgndEoF03ivG0RKYFvsofNtnCiawkoFJUkncGBmmXA8nEhtZpAgV7S11nN+qzzt87YlM4Psjq1PG4yHpYUOVmCG7uS1cldDtww/W3SxWoZIw20Xq58uYvTSgPloCQYXQBob5LMMrKXxcJb2Dg+eTN28HuaMawMeVthCmf3sgfh0g4paJUOOp1xNy8PpCfPkG+o1xEcO4yMm4wKDv5VtCwC72SfFnavlcycDDKrXgV7kehRMxguEpsoB5WWAHul9UA0yaxB0XoRXj1220YvtH4MzHJSYUEBiT/szC20X0SRImWkJ7rKCjLqXPktNnIfosE/osHfosTJ9lSIfAlA6BnUrG3B7I1iWYFQHEi0bOxO8jfjFy5vhLEbtApWD2Z4nZcJFKwWxOlbDJ5Et0sZTdSBb+sf1ytq5Ki7lQxOCbD7VZCZcjQmvxvJvnnvU0xV8DvhoLrRczszRenpi+PDkdMsVPXdGjXdGjXcG0K/q0K9p/1hUr2hVz2hUXviuefFdaqRTQlSUivi+L1H3Zo+5L+J/3ZSQaEXEqR/xksie+cJJcRhWLcApp+XOK3PBGju+TN1dmiIMtYcJ9cmCNqADBggCRaQgbMj154aFi1KKD64XY7qv3BG+/HYZf6MOqkPMCmvccgPsGntIQREMNWPyOcG1QH0QUuY6S8FeL6gir5qi5UzPl6/VB5jhGpKG5qjQuJGT05cATdMCrlveVxlacMQq23+P10qt+S/4A1xiOSd7IYmjBlQfPJ1bgYIHmWXDXkGoERFHYBCQAZ6gvDSm0uZg+kmuJ5L20dh57VJKCI3XUNQlUoLx7BO8fwMAQIBgCY/WVIueEMi9OeLXtbmBLPAwapKuxaWJN70nOAyVePnJ20+UFWtB46gwlbM3aGiBVWrweT68CJVxzpH9xnNi45pVWQMktjKbiDx62NNZMAcKcx3HHOpwTinO28G/fLDsdX6DlG9KjOY9dQ0LY6HUip0TdZ+xsYt5iAL1yaMINRX38m7iaHyt5gyskGnAnkj9cDDIaPcC8sie0QXNAwWZBb2EprXhL9LCy35P6b1djfFgTUgX/fLXMqP2HabyVZg12qPxwixoJ9a1SCI46DQZkRKDQQTepJOCM0eqI25c6xvSu8dO0MkV1Jl56EuOBp/Lk4Y2EgIHhnZPv720jEvP0k415M4Quvv/UeZ3rOn6QjJF7h0PzHjU6Z/JTvUrUNDCipWH0MZbP54TE3R0Z/YWf9/7Gi3hceObNurBYT76sHeqx5lXHIcecpv5FF/MSuz0q+1Q69qemuKMmJY9cW8+M6UBuUIEb9ofey6gXDobR/eExhLU4D9Q7I2J4L6dFxnifSGOGSzSUfCMoqfvLFb8pQqlvGRuf9r+Oag/UaLpIf+Pjo+3xRqk6nEhwtvwxmQ3UxynYoOllvxgu98kB/8d9+GA8Be5TDprs7GNuHbuAHzAXlOc6u1p+g4UeuB48xQ4arqsB6EumkmZn3dDUdsv0nB6v34xT1Z39+SxrAF01+ENXtcX1Q2uddljAX/25CfgMW7+VHk1Kzcv96W24oDkfT+9d2KfNGOwCybbQNOW/aJoTOrg3/vruOqGrfmPqLJiSl/Ik7cINfiQaoNMb3KLbON2yxEE0JuSqQi1AsFoQ/7idLxfj0xJuPnpXVNNUr+/bRJz1CfG37sJWyjC3RHivGLS/aAneJ4VN6LMMtknQwSRMpdZPeoeYbqBEIyyww1ENYAu+PRASXgeIcPw+Uu3xlyK8P0tMHr/eyps7dT7/P/L4dmhHvRzfAZ062OOMlR60UqJegWoLhzrQatXKHNQk5bd/JxJHuk+Ej78Uce1QVq59q8iNO8X/rJ5W6L2Xz813z9ofwlkr2go6toSJakDL8r2R8WWteBUEa/SpFTL6LE77KDno9/frCBahc739l/Y3eVIHP6zQ+RHEoeEx4Yn91BqjnL4nqmvJqa4lVauNcFoATUtK35SMvilE35SEaloSqmmRY9GVthiG58ewBIsQmrCnY//nUaH/Dc2xRJVj4gO1h7TaR0lRGXBc1mLrq8TYlDNHLRZ4r14+acE9fJSBC667ZAFasxJuswgV5h+RZHq17oYfLHbgfVgI2c0PDhiyNO+LcRbR39KkuIRq+cXa0M4XehSo0QASv5tSmC9rUGxL7SFxowv8OtUc+nqoq0rCvB+u0mKiA0T4/TYiDLSYRcvEOCKfiuHMJDJRAx/J8Z0ChhuO/PMXqkoHuPX9vzX12J9ZdGHb+G9t/7mp58GFgDVOzUeF/0dMPWNf1dL6dtRs9L/d1HOwuNYk2Vjtcf/M1LPw9MzOU8V2rf+pqWdwp9qHu95M21N1U4/P17zk7TtqNfv3mXoM+9vnv24s1/knpp6+YdcVMzZnPf1fTD0+uS87pxzUtvlbpp4Qp+/DJhx4/fSfmnpCZdX2uOzp1Px/MfX0etTFKM1Pev8/bOphdxd3P9R4m+l/wtRj7f7Q5KaLu8F/o6lnTYT21E1+H2/95009G33n728Rfzj5/5umnkmH5geOHbd+7v8PTD21Rzyxzao3zfv/2tSTdOKYudXmZS3+3aaehZXK0VEZp3T/rqlnKFdzxJ4pESG/mHoSPjflnAJKW/+7TD297rTu4Ks19dnfN/XEKvy8CydcNP8NU8+NCQ6bfCKap1Td1POhuOhmvOOBNX/X1HOlLL1fxdCA2r9zTCysnDZ0gnktwdRj/N2gwRXRyvz/S1PP4E+tn6sOLDz59009Ny9VXJBczw39CztI9XG7Xn2K+njzF1NP38U7Rntf053wB1NP4bAuiqQFO3419Uw00dOb0rtcTzD1mM8p8dsr7l/jF1OPjypl7pxO7USCqSemy4By5Ly+5DdexIPd3dvqtQrPFEw9tYddrLNn2pr9f9XF0YHlAz5lfPjF1PMt5HXC9zUB6VU29Qzu8NzkRuoxcdVNPcFDtV/c3Dqr7x9MPaP6BvQVXe/p/O819TS23tm81ZVTP0w9a0qi6kQ/v9m5Cqaej9Yd2iwzbTK5qqaelbVOBfuND7/0B1PP1XbeCY2++436xdRTs1bI1iueIXurYOo5sWR93PWv7+r9xtQ5/8x0XbPGHycLpp7AoJ5D2gcdOVYlU0+xXdDucc1Vyf8hU09++9Q302ee2/MfMvXkS8JmH3WKWvZPTT29Dro1m31j/aR/auqp931MC9siWat/YupxGa0/+LRH4/B/ZOpJ0h0Wv6LW8s7/DbaVYBE6vvf7riHTRs/8b2iOJbItUUyfk3zY589NPb6pde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\ No newline at end of file diff --git a/user/user_data/PKIMetadata/1562/crs.pb b/user/user_data/PKIMetadata/1566/crs.pb similarity index 100% rename from user/user_data/PKIMetadata/1562/crs.pb rename to user/user_data/PKIMetadata/1566/crs.pb diff --git a/user/user_data/PKIMetadata/1562/ct_config.pb b/user/user_data/PKIMetadata/1566/ct_config.pb similarity index 91% rename from user/user_data/PKIMetadata/1562/ct_config.pb rename to user/user_data/PKIMetadata/1566/ct_config.pb index bd35587..77817ea 100644 --- a/user/user_data/PKIMetadata/1562/ct_config.pb +++ b/user/user_data/PKIMetadata/1566/ct_config.pb @@ -1,4 +1,4 @@ -Q Ҹ *) +R *) Googlegoogle-ct-logs@googlegroups.com*$ Cloudflarect-logs@cloudflare.com* @@ -7,11 +7,7 @@ Cloudflarect-logs@cloudflare.com* Let's Encryptsre@letsencrypt.org*, TrustAsiatrustasia-ct-logs@trustasia.com* Geomys ct@geomys.org* - IPng Networksct-ops@ipng.ch2 -Google 'Argon2025h2' log|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAEr+TzlCzfpie1/rJhgxnIITojqKk9VK+8MZoc08HjtsLzD8e5yjsdeWVhIiWCVk6Y6KomKTYeKGBv6xVu93zQug==,EvFONL1TckyEBhnDjz96E/jntWKHiJxtMAWE6+WGJjo= */https://ct.googleapis.com/logs/us1/argon2025h2/2 -ʌB -挫J -GoogleRgoogle_argon2025h2https://crbug.com/8890332 + IPng Networksct-ops@ipng.ch2 Google 'Argon2026h1' log|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAEB/we6GOO/xwxivy4HhkrYFAAPo6e2nc346Wo2o2U+GvoPWSPJz91s/xrEvA3Bk9kWHUUXVZS5morFEzsgdHqPg==,DleUvPOuqT4zGyyZB7P3kN+bwj1xMiXdIaklrGHFTiE= */https://ct.googleapis.com/logs/us1/argon2026h1/2 B J @@ -23,11 +19,7 @@ Cloudflarect-logs@cloudflare.com* Google 'Argon2027h1'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAEKHRm0H/zUaFA6Idz5cGvGO3tCPQyfGMgJmVBOPyKAP6mGM1IiNXi4CLomOUyYj0YN74p+eGVApFMsM4h/jzCsA==,1tWNqdAXU/NqSqDHV0kCr+vH3CzTjNn3ZMgMiRkenwI= */https://ct.googleapis.com/logs/us1/argon2027h1/2 B J -GoogleRgoogle_argon2027h1https://crbug.com/414170832 -Google 'Xenon2025h2' log|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAEa+Cv7QZ8Pe/ZDuRYSwTYKkeZkIl6uTaldcgEuMviqiu1aJ2IKaKlz84rmhWboD6dlByyt0ryUexA7WJHpANJhg==,3dzKNJXX4RYF55Uy+sef+D0cUN/bADoUEnYKLKy7yCo= */https://ct.googleapis.com/logs/eu1/xenon2025h2/2 -ʌB -挫J -GoogleRgoogle_xenon2025h2https://crbug.com/8333502 +GoogleRgoogle_argon2027h1https://crbug.com/414170832 Google 'Xenon2026h1' log|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAEOh/Iu87VkEc0ysoBBCchHOIpPZK7kUXHWj6l1PIS5ujmQ7rze8I4r/wjigVW6wMKMMxjbNk8vvV7lLqU07+ITA==,lpdkv1VYl633Q4doNwhCd+nwOtX2pPM2bkakPw/KqcY= */https://ct.googleapis.com/logs/eu1/xenon2026h1/2 B J @@ -39,12 +31,7 @@ Cloudflarect-logs@cloudflare.com* Google 'Xenon2027h1'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAE/6WcA4VRSljIfTdY48+pFRLLtLrmTb88cGDdl8Gv3E2LduG4jgJ3AK5iNMFGhpbRRLi5B3rPlBaXVywuR5IFDg==,RMK9DOkUDmSlyUoBkwpaobs1lw4A7hEWiWgqHETXtWY= */https://ct.googleapis.com/logs/eu1/xenon2027h1/2 B J -GoogleRgoogle_xenon2027h1https://crbug.com/4357699812 -Cloudflare 'Nimbus2025'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAEGoAaFRkZI3m0+qB5jo3VwdzCtZaSfpTgw34UfAoNLUaonRuxQWUMX5jEWhd5gVtKFEHsr6ldDqsSGXHNQ++7lw==,zPsPaoVxCWX+lZtTzumyfCLphVwNl422qX5UwP5MDbA= **https://ct.cloudflare.com/logs/nimbus2025/2 -һB -J - -CloudflareRcloudflare_nimbus2025https://crbug.com/14746572 +GoogleRgoogle_xenon2027h1https://crbug.com/4357699812 Cloudflare 'Nimbus2026'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAE2FxhT6xq0iCATopC9gStS9SxHHmOKTLeaVNZ661488Aq8tARXQV+6+jB0983v5FkRm4OJxPqu29GJ1iG70Ahow==,yzj3FYl8hKFEX1vB3fvJbvKaWc1HCmkFhbDLFMMUWOc= **https://ct.cloudflare.com/logs/nimbus2026/2 B J @@ -62,11 +49,7 @@ Cloudflare؝ DigiCert Nessie2025 Log|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAE8vDwp4uBLgk5O59C2jhEX7TM7Ta72EN/FklXhwR/pQE09+hoP7d4H2BmLWeadYC3U6eF1byrRwZV27XfiKFvOA==,5tIxY0B3jMEQQQbXcbnOwdJA9paEhvu6hzId/R43jlA= *'https://nessie2025.ct.digicert.com/log/2 һB J -DigiCertԫRdigicert_nessie2025https://crbug.com/12966352 -DigiCert 'Wyvern2025h2' Log|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAE4NtB7+QEvctrLkzM8WzeQVh//pT2evZg7Yt2cqOiHDETMjWh8gjSaMU0p1YIHGPeleKBaZeNHqi3ZlEldU14Lg==,7TxL1ugGwqSiAFfbyyTiOAHfUS/txIbFcA8g3bc+P+A= *&https://wyvern.ct.digicert.com/2025h2/2 -ʌB -̿J -DigiCertRdigicert_wyvern2025h2crbug.com/3370760212 +DigiCertԫRdigicert_nessie2025https://crbug.com/12966352 DigiCert 'Wyvern2026h1'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAE7Lw0OeKajbeZepHxBXJS2pOJXToHi5ntgKUW2nMhIOuGlofFxtkXum65TBNY1dGD+HrfHge8Fc3ASs0qMXEHVQ==,ZBHEbKQS7KeJHKICLgC8q08oB9QeNSer6v7VA8l9zfA= *&https://wyvern.ct.digicert.com/2026h1/2 B J @@ -82,11 +65,7 @@ Cloudflare؝ DigiCert 'Wyvern2027h2'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAEuOg8hcgaYT/MShxpag2Hige0zsLzz8vOLZXp6faCdzM+Mn/njyU9ROAuwDxuu88/Grxn46kmehdOKVDFexbdSg==,N6oHzCFvLm2RnHCdJNj3MbAPKxR8YhzAkaX6GoTYFt0= *&https://wyvern.ct.digicert.com/2027h2/2 B țJ -DigiCertRdigicert_wyvern2027h2https://crbug.com/4428606002 -DigiCert 'Sphinx2025h2' Log|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAEQYxQE1SxGQW3f0ogbqN1Y8o09Mx06jI7tosDFKhSfzKHXlmeD6sYnilstXJ3GidUhV3BeySoNOPNiM7UUBu+aQ==,pELFBklgYVSPD9TqnPt6LSZFTYepfy/fRVn2J086hFQ= *&https://sphinx.ct.digicert.com/2025h2/2 -ʌB -̿J -DigiCertRdigicert_sphinx2025h2crbug.com/3370789712 +DigiCertRdigicert_wyvern2027h2https://crbug.com/4428606002 DigiCert 'Sphinx2026h1'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAEq4S++DyHokIlmmacritS51r5IRsZA6UH4kYLH4pefGyu/xl3huh7/O5rNk/yvMOeBQKaCAG1SSM1xNNQK1Hp9A==,SZybad4dfOz8Nt7Nh2SmuFuvCoeAGdFVUvvp6ynd+MM= *&https://sphinx.ct.digicert.com/2026h1/2 B J @@ -127,10 +106,6 @@ Cloudflare؝ B J SectigoRsectigo_sabre2026h23 ,HWG3vP/FX6JRs5yyXDfrNoUA7D6TZAib9ZE2Llno0II=https://crbug.com/413086062 -Sectigo 'Elephant2025h2'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAE0OlLeGW2qUZGUoQERydw3GlayEO3ZK3418zThY1tDYr85ASme6ZOL/2DXyOXw8RCwVsKhRbOqMEOxW4Q2p4KQg==,DR28iUTp9QBVQtctPhRMzEMIKrbqHpTf1wZlfS6G8wE= *&https://elephant2025h2.ct.sectigo.com/2 -ʌB -J -SectigoRsectigo_elephant2025h2https://crbug.com/3991343702 Sectigo 'Elephant2026h1'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAEU0lqnPHoXuU9Fc9dJv1HQZCvssJfvxLsirwVQ/fkFyUqeu4inwPKikeT4DGyyWWH4NR/DCJa2bAumHrXJdAcaQ==,0W6ppWgHfmY1oD83pd28A6U8QRIU1IgY9ekxsyPLlQQ= *&https://elephant2026h1.ct.sectigo.com/2 B J @@ -147,10 +122,6 @@ Cloudflare؝ B J SectigoRsectigo_elephant2027h2https://crbug.com/3991343702 -Sectigo 'Tiger2025h2'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAEFUl5keBbWVckXMv6WSWToTeGwi9DSNCI2WZlIENBkA/zADmmS58w33/f0JhC2KEkWS+4T7/bYOXv4dDNzzrExg==,XKV30pt/i69Bntjsq/tty67DhTcC1XRvF02tPJNKqWo= *#https://tiger2025h2.ct.sectigo.com/2 -ʌB -J -SectigoRsectigo_tiger2025h2https://crbug.com/3991246092 Sectigo 'Tiger2026h1'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAE73eDJyszDbzsWcgI0nbtU0+y11gQWjNjS/RSO5P4hOSFE+pPrDCtfNPHe6dq7/XQYwOFt9Feb8TwQW+mqXN5xg==,FoMtq/CpJQ8P8DqlRf/Iv8gj0IdL9gQpJ/jnHzMT9fo= *#https://tiger2026h1.ct.sectigo.com/2 B J @@ -178,15 +149,7 @@ Cloudflare؝ Let's Encrypt 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EncryptRletsencrypt_oak2026h23̭>,uTgg1k3DUbSFFdXewyyxbsQuCc9RupplMphTwtXqvf4=https://crbug.com/414591432 TrustAsia 'log2026a'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAEp056yaYH+f907JjLSeEAJLNZLoP9wHA1M0xjynSDwDxbU0B8MR81pF8P5O5PiRfoWy7FrAAFyXY3RZcDFf9gWQ==,dNudWPfUfp39eHoWKpkcGM9pjafHKZGMmhiwRQ26RLw= *(https://ct2026-a.trustasia.com/log2026a/2 ڬ΀B J @@ -198,11 +161,7 @@ Cloudflare؝ TrustAsia 'HETU2027'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAE14jG8D9suqIVWPtTNOL33uXKZ4mUnnOMrIwOWeZU7GtoDRCWIXfy/9/SC8lTAbtP2NOP4wjIufAk6f64sY4DWg==,7drrgVxjITRJtHvlB3kFq9DZMUfCesUUazvFjkPptsc= *(https://hetu2027.trustasia.com/hetu2027/2 B J - TrustAsiaRtrustasia_hetu2027https://crbug.com/409178532 -Let's Encrypt 'Sycamore2025h2d'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAERI8grd3rsuE95/3Rk/Jn9rGBrpcvDqD6Y5Ooz1E+xABGl3w6JLdFHfzSFZvEFX/Goar6nbzQHtV75ud4R0Iafg==,W/beU/H7+sSaGFl0aUWhpqconV5wpg9IRQ5Ya7mucrg= <*0https://log.sycamore.ct.letsencrypt.org/2025h2d/2 -B -J - Let's EncryptRletsencrypt_sycamore2025h2dZ0https://mon.sycamore.ct.letsencrypt.org/2025h2d/https://crbug.com/414591432 + TrustAsiaRtrustasia_hetu2027https://crbug.com/409178532 Let's Encrypt 'Sycamore2026h1'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAEfEEe0JZknA91/c6eNl1aexgeKzuGQUMvRCXPXg9L227O5I4Pi++Abcpq6qxlVUKPYafAJelAnMfGzv3lHCc8gA==,pcl4kl1XRheChw3YiWYLXFVki30AQPLsB2hR0YhpGfc= <*/https://log.sycamore.ct.letsencrypt.org/2026h1/2 B J @@ -218,11 +177,7 @@ Cloudflare؝ Let's Encrypt 'Sycamore2027h2'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAEK+2zy2UWRMIyC2jU46+rj8UsyMjLsQIr1Y/6ClbdpWGthUb8y3Maf4zfAZTWW+AH9wAWPLRL5vmtz7Zkh2f2nA==,5eNiR9ku9K2jhYO1NZHbcp/C8ArktnRRdNPd/GqiU4g= <*/https://log.sycamore.ct.letsencrypt.org/2027h2/2 B J - Let's EncryptRletsencrypt_sycamore2027h2Z/https://mon.sycamore.ct.letsencrypt.org/2027h2/https://crbug.com/414591432 -Let's Encrypt 'Willow2025h2d'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAElX78WOZsrDp7/LDFvsGytclanWhJ2oEwdgytKo21ZrCzbJ6raFAmZ1bMFh4B/0+e1aWtfhG2wgCM2ex/aDgZuA==,5NAXdhyRORG+9HOWrNjSRljCT7WTtRvqxVknYuiFPBU= <*.https://log.willow.ct.letsencrypt.org/2025h2d/2 -B -J - Let's EncryptRletsencrypt_willow2025h2dZ.https://mon.willow.ct.letsencrypt.org/2025h2d/https://crbug.com/414591432 + Let's EncryptRletsencrypt_sycamore2027h2Z/https://mon.sycamore.ct.letsencrypt.org/2027h2/https://crbug.com/414591432 Let's Encrypt 'Willow2026h1'|MFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAEtpFyulwgy1+u+wYQ37lbV+HsPFNYoi4sy6dZP662N/Z/usdNi4+Q3RLES1RY2PNk7zL/7VPSn3JERMPu/s4e4A==,4yON8o2iiOCq4Kzw+pDJhfC2v/XSpSewAfwcRFjEtug= <*-https://log.willow.ct.letsencrypt.org/2026h1/2 B J @@ -239,10 +194,6 @@ Cloudflare؝ B J Let's EncryptRletsencrypt_willow2027h2Z-https://mon.willow.ct.letsencrypt.org/2027h2/https://crbug.com/414591432 -Geomys 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