imported by:
gui_app.py
+ •
gui_worker
•
loguru
•
loguru._asyncio_loop
•
loguru._better_exceptions
@@ -17300,6 +17366,7 @@ imports:
@@ -30286,6 +30353,8 @@ imported by:
•
gettext
•
glob
•
gui_app.py
+ •
gui_constants
+ •
gui_worker
•
gzip
•
http.cookiejar
•
http.server
@@ -43422,6 +43491,7 @@ imported by:
•
filelock._util
•
filelock._windows
•
gui_app.py
+ •
gui_worker
•
importlib.metadata
•
importlib.resources._common
•
importlib.resources.abc
@@ -54168,6 +54238,7 @@ imported by:
•
filelock.asyncio
•
gc
•
gui_app.py
+ •
gui_worker
•
gzip
•
http.cookiejar
•
http.cookies
@@ -54547,6 +54618,7 @@ imported by:
•
concurrent.futures.process
•
doctest
•
gui_app.py
+ •
gui_worker
•
http.cookiejar
•
logging
•
loguru._better_exceptions
diff --git a/dist/多多自动发文助手.exe b/dist/多多发文助手.exe
similarity index 99%
rename from dist/多多自动发文助手.exe
rename to dist/多多发文助手.exe
index ae1b67b..8852c6f 100644
Binary files a/dist/多多自动发文助手.exe and b/dist/多多发文助手.exe differ
diff --git a/gui_app.py b/gui_app.py
index 640b182..ba1c2b6 100644
--- a/gui_app.py
+++ b/gui_app.py
@@ -17,7 +17,7 @@ from PyQt5.QtWidgets import (
QStyleOptionProgressBar, QStyleOptionButton, QHeaderView,
QTabWidget, QSplitter, QSizePolicy, QCheckBox
)
-from PyQt5.QtCore import Qt, QThread, pyqtSignal, QDateTime, QSize, QAbstractTableModel, QModelIndex, \
+from PyQt5.QtCore import Qt, QDateTime, QSize, QAbstractTableModel, QModelIndex, \
QSortFilterProxyModel, QRegularExpression, QSettings, QTimer, QEvent
from PyQt5.QtGui import QFont, QTextDocument, QTextCursor, QKeySequence, QColor, QPainter
@@ -30,689 +30,14 @@ from qfluentwidgets import (
from main import Pdd
from loguru import logger
+from gui_constants import get_default_folder_path, TABLE_HEADERS, MODEL_VIEW_HEADERS
+from gui_worker import WorkerThread
+from gui_models import ConfigTableModel, TableActionDelegate
-def get_default_folder_path():
- """获取默认文件夹路径（桌面/多多自动化发文）"""
- desktop = os.path.join(os.path.expanduser("~"), "Desktop")
- default_path = os.path.join(desktop, "多多自动化发文")
- return default_path
-
-
-class WorkerThread(QThread):
- """工作线程，用于执行自动化任务"""
- finished = pyqtSignal(bool, str)
- log_message = pyqtSignal(str)
- progress = pyqtSignal(int)
- item_result = pyqtSignal(object) # 单条发布结果（dict）
-
- def __init__(self, config_data, is_batch_mode, prepared_files=None, parent=None):
- super().__init__(parent)
- self.config_data = config_data
- self.is_batch_mode = is_batch_mode
- self.prepared_files = prepared_files # 预查找的文件列表
- self.is_running = True
-
- def run(self):
- sink_id = None
- start_ts = time.time()
- try:
- # 将日志转发到 GUI（不要 remove 全局 sink，避免影响主线程/其他模块日志）
- sink_id = logger.add(lambda msg: self.log_message.emit(str(msg).strip()))
-
- if self.is_batch_mode:
- self.run_batch_mode()
- else:
- self.run_single_mode()
- except Exception as e:
- error_msg = f"执行失败: {str(e)}"
- self.finished.emit(False, error_msg)
- self.log_message.emit(error_msg)
- logger.error(f"执行失败: {e}")
- import traceback
- traceback_str = traceback.format_exc()
- logger.error(traceback_str)
- self.log_message.emit(f"错误详情: {traceback_str}")
- finally:
- try:
- cost = time.time() - start_ts
- self.log_message.emit(f"[线程] 任务结束，耗时 {cost:.2f}s")
- except Exception:
- pass
- if sink_id is not None:
- try:
- logger.remove(sink_id)
- except Exception:
- pass
-
- def run_single_mode(self):
- """执行单个上传模式（action方法）"""
- try:
- config = self.config_data
- self.log_message.emit(f"开始处理单个任务（逐个上传模式）...")
-
- pdd = Pdd(
- url=config.get('达人链接', ''),
- user_id=config.get('多多id', ''),
- time_start=config.get('定时发布', '') if config.get('定时发布') else None,
- ht=config.get('话题', ''),
- index=config.get('序号', ''),
- title=config.get('标题', None)
- )
-
- # 如果已经预查找了文件，直接使用
- if self.prepared_files:
- self.log_message.emit(f"使用预查找的文件列表，共 {len(self.prepared_files)} 个文件")
- self.progress.emit(30)
-
- # 单个上传模式，使用action方法
- # 从预查找的文件中提取文件夹路径（取第一个文件的父目录的父目录，回到最外层文件夹）
- first_file = self.prepared_files[0]
- if first_file['path'].is_file():
- # 文件路径：最外层文件夹/多多ID文件夹/文件名
- # 需要回到最外层文件夹
- folder_path = str(first_file['path'].parent.parent)
- else:
- # 文件夹路径：最外层文件夹/多多ID文件夹/文件夹名
- folder_path = str(first_file['path'].parent.parent)
-
- self.log_message.emit(f"使用文件夹路径: {folder_path}")
- try:
- 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 ''}")
- # 单条回传结果
- if isinstance(result, dict):
- self.item_result.emit({
- "user_id": config.get("多多id", ""),
- "index": config.get("序号", ""),
- "name": config.get("标题", "") or "",
- "ok": ok,
- "reason": result.get("reason", ""),
- })
- self.progress.emit(100)
- self.finished.emit(ok, f"单个任务执行完成（ok={ok}）")
- except Exception as e:
- error_msg = f"执行action方法失败: {str(e)}"
- self.log_message.emit(error_msg)
- logger.error(error_msg)
- import traceback
- traceback_str = traceback.format_exc()
- logger.error(traceback_str)
- self.log_message.emit(f"错误详情: {traceback_str}")
- self.finished.emit(False, error_msg)
- return
- else:
- # 未预查找文件，使用原来的逻辑
- folder_path = config.get('文件夹路径', '').strip()
- if not folder_path:
- folder_path = get_default_folder_path()
-
- if not os.path.exists(folder_path):
- error_msg = f"文件夹路径不存在: {folder_path}"
- self.finished.emit(False, error_msg)
- self.log_message.emit(error_msg)
- return
-
- self.log_message.emit(f"使用文件夹路径: {folder_path}")
- self.progress.emit(30)
-
- # 检查是否勾选了批量上传
- is_batch_mode = self.is_batch_mode
-
- # 调用action方法
- try:
- 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 ''}")
- if isinstance(result, dict):
- self.item_result.emit({
- "user_id": config.get("多多id", ""),
- "index": config.get("序号", ""),
- "name": config.get("标题", "") or "",
- "ok": ok,
- "reason": result.get("reason", ""),
- })
- except Exception as e:
- error_msg = f"执行action方法失败: {str(e)}"
- self.log_message.emit(error_msg)
- logger.error(error_msg)
- import traceback
- traceback_str = traceback.format_exc()
- logger.error(traceback_str)
- self.log_message.emit(f"错误详情: {traceback_str}")
- self.finished.emit(False, error_msg)
- return
-
- self.progress.emit(100)
- self.finished.emit(ok, f"单个任务执行完成（ok={ok}）")
- except Exception as e:
- error_msg = f"执行失败: {str(e)}"
- self.finished.emit(False, error_msg)
- self.log_message.emit(error_msg)
- logger.error(f"执行失败: {e}")
- import traceback
- traceback_str = traceback.format_exc()
- logger.error(traceback_str)
- self.log_message.emit(f"错误详情: {traceback_str}")
-
- def run_batch_mode(self):
- """执行批量上传模式：先批量上传所有视频，然后逐个上传图片"""
- try:
- config = self.config_data
- self.log_message.emit(f"开始处理批量上传任务...")
-
- index = config.get('序号', '')
-
- # 创建Pdd实例
- pdd = Pdd(
- url=config.get('达人链接', ''),
- user_id=config.get('多多id', ''),
- time_start=config.get('定时发布', '') if config.get('定时发布') else None,
- ht=config.get('话题', ''),
- index=index,
- title=config.get('标题', None)
- )
-
- # 如果已经预查找了文件，直接使用
- if self.prepared_files:
- self.log_message.emit(f"使用预查找的文件列表，共 {len(self.prepared_files)} 个文件")
- self.progress.emit(30)
-
- # 分离视频文件和图片文件夹
- video_extensions = ['.mp4', '.avi', '.mov', '.mkv', '.flv', '.wmv', '.webm']
- video_file_paths = [f for f in self.prepared_files if f['path'].is_file() and any(
- f['path'].suffix.lower() == ext for ext in video_extensions)]
- image_folders = [f for f in self.prepared_files if f['path'].is_dir()]
-
- # 如果有视频，批量上传所有视频
- if video_file_paths:
- self.log_message.emit(f"找到 {len(video_file_paths)} 个视频文件，开始批量上传...")
- self.progress.emit(30)
-
- # 定义实时回调函数：每处理完一个视频就立即通知 GUI 更新状态
- def on_video_done(result_item):
- try:
- payload = dict(result_item)
- payload["user_id"] = config.get("多多id", "")
- # 确保index字段正确传递
- if "index" not in payload or not payload.get("index"):
- for vid_file in video_file_paths:
- if str(vid_file.get('path')) == str(payload.get('path')):
- payload["index"] = vid_file.get("index", config.get("序号", ""))
- break
- if "index" not in payload or not payload.get("index"):
- payload["index"] = config.get("序号", "")
- # 立即通知 GUI 更新状态
- self.item_result.emit(payload)
- self.log_message.emit(f" {'✓' if payload.get('ok') else '✗'} {payload.get('name', '')} 已更新状态")
- except Exception as e:
- self.log_message.emit(f" 回调处理异常: {e}")
-
- result = pdd.action1(folder_path=video_file_paths, on_item_done=on_video_done)
- ok = bool(result.get("ok")) if isinstance(result, dict) else True
- if not ok:
- fails = [r for r in (result.get("results") or []) if not r.get("ok")]
- self.log_message.emit(f"发布校验失败条数: {len(fails)}")
- for r in fails[:20]:
- self.log_message.emit(f" ✗ {r.get('name')} | {r.get('reason')}")
- self.log_message.emit(f"批量上传视频完成，共处理 {len(video_file_paths)} 个视频")
- else:
- self.log_message.emit("未找到视频文件，跳过视频上传")
- ok = True
-
- # 如果有图片文件夹，逐个上传图片
- if image_folders:
- self.log_message.emit(f"找到 {len(image_folders)} 个图片文件夹，开始逐个上传...")
- self.progress.emit(70)
-
- for idx, image_folder_info in enumerate(image_folders):
- if not self.is_running:
- break
-
- image_folder = str(image_folder_info['path'])
- self.log_message.emit(f"处理第 {idx + 1}/{len(image_folders)} 个图片文件夹: {image_folder}")
- # 使用action方法处理图片文件夹
- pdd.action(folder_path=image_folder)
- self.log_message.emit(f"图片文件夹 {idx + 1} 上传完成")
-
- self.log_message.emit(f"所有图片文件夹上传完成，共处理 {len(image_folders)} 个文件夹")
- else:
- self.log_message.emit("未找到图片文件夹，跳过图片上传")
-
- self.progress.emit(100)
- total_count = len(video_file_paths) + len(image_folders)
- self.finished.emit(ok,
- f"批量任务执行完成，共处理 {len(video_file_paths)} 个视频和 {len(image_folders)} 个图片文件夹（ok={ok}）")
- else:
- # 未预查找文件，使用原来的逻辑
- folder_path = config.get('文件夹路径', '').strip()
- if not folder_path:
- folder_path = get_default_folder_path()
-
- if not os.path.exists(folder_path):
- self.finished.emit(False, f"文件夹路径不存在: {folder_path}")
- return
-
- # 第一步：收集所有视频文件
- self.log_message.emit("第一步：收集所有视频文件...")
- video_file_paths = self.prepare_batch_files(folder_path, config)
-
- # 第二步：收集所有图片文件夹
- self.log_message.emit("第二步：收集所有图片文件夹...")
- image_folders = self.prepare_image_folders(folder_path, index)
-
- # 第三步：如果有视频，批量上传所有视频
- if video_file_paths:
- self.log_message.emit(f"找到 {len(video_file_paths)} 个视频文件，开始批量上传...")
- self.progress.emit(30)
- pdd.action1(folder_path=video_file_paths)
- self.log_message.emit(f"批量上传视频完成，共处理 {len(video_file_paths)} 个视频")
- else:
- self.log_message.emit("未找到视频文件，跳过视频上传")
-
- # 第四步：如果有图片文件夹，逐个上传图片
- if image_folders:
- self.log_message.emit(f"找到 {len(image_folders)} 个图片文件夹，开始逐个上传...")
- self.progress.emit(70)
-
- for idx, image_folder in enumerate(image_folders):
- if not self.is_running:
- break
-
- self.log_message.emit(f"处理第 {idx + 1}/{len(image_folders)} 个图片文件夹: {image_folder}")
- # 使用action方法处理图片文件夹
- pdd.action(folder_path=image_folder)
- self.log_message.emit(f"图片文件夹 {idx + 1} 上传完成")
-
- self.log_message.emit(f"所有图片文件夹上传完成，共处理 {len(image_folders)} 个文件夹")
- else:
- self.log_message.emit("未找到图片文件夹，跳过图片上传")
-
- self.progress.emit(100)
- total_count = len(video_file_paths) + len(image_folders)
- self.finished.emit(True,
- f"批量任务执行完成，共处理 {len(video_file_paths)} 个视频和 {len(image_folders)} 个图片文件夹")
-
- except Exception as e:
- self.finished.emit(False, f"批量执行失败: {str(e)}")
- logger.error(f"批量执行失败: {e}")
-
- def prepare_image_folders(self, folder_path, index):
- """收集所有匹配序号的图片文件夹（与main.py中action方法的逻辑一致）"""
- image_folders = []
-
- try:
- # 参数验证
- if not folder_path or not os.path.exists(folder_path):
- logger.warning(f"文件夹路径无效或不存在: {folder_path}")
- return image_folders
-
- if not os.access(folder_path, os.R_OK):
- logger.error(f"没有权限读取文件夹: {folder_path}")
- return image_folders
-
- # 遍历最外层文件夹下的所有子文件夹（与main.py逻辑一致）
- try:
- subdirs = os.listdir(folder_path)
- except PermissionError:
- logger.error(f"没有权限访问文件夹: {folder_path}")
- return image_folders
- except Exception as e:
- logger.error(f"读取文件夹失败: {e}")
- return image_folders
-
- for file in subdirs:
- try:
- file_path = os.path.join(folder_path, file) # 拼接文件夹
- # 检查是否为目录，跳过文件（如.lnk快捷方式）
- if not os.path.isdir(file_path):
- continue
-
- # 获取用户id下的文件
- try:
- files = os.listdir(file_path)
- except PermissionError:
- logger.warning(f"没有权限访问子文件夹: {file_path}")
- continue
- except Exception as e:
- logger.warning(f"读取子文件夹失败: {file_path}, 错误: {e}")
- continue
-
- for file_name in files:
- try:
- # 跳过隐藏文件
- if file_name.startswith('.'):
- continue
-
- # 用"-"分割文件名，检查第一部分是否等于序号
- file_names = file_name.split("-")
- if len(file_names) > 0 and file_names[0] == str(index):
- path = Path(os.path.join(file_path, file_name))
- # 确保路径存在
- if path.exists() and path.is_dir():
- # 这是一个图片文件夹
- image_folders.append(str(path))
- except Exception as e:
- logger.warning(f"处理文件 {file_name} 时出错: {e}")
- continue
- except Exception as e:
- logger.warning(f"处理子文件夹 {file} 时出错: {e}")
- continue
- except Exception as e:
- logger.error(f"收集图片文件夹失败: {e}", exc_info=True)
-
- return image_folders
-
- def count_videos_in_folder(self, folder_path, index):
- """统计文件夹中匹配序号的视频文件数量（与main.py逻辑一致）"""
- count = 0
- try:
- # 遍历最外层文件夹下的所有子文件夹（与main.py逻辑一致）
- for file in os.listdir(folder_path): # 获取文件夹下所有的文件夹
- file_path = os.path.join(folder_path, file) # 拼接文件夹
- # 检查是否为目录，跳过文件（如.lnk快捷方式）
- if not os.path.isdir(file_path):
- continue
-
- files = os.listdir(file_path) # 获取用户id下的文件
- for file_name in files:
- # 检查是否是视频文件（.mp4）
- if ".mp4" in file_name:
- # 用"-"分割文件名，检查第一部分是否等于序号
- # 文件名格式：4-茶叶蛋大冒险-.mp4 -> ['4', '茶叶蛋大冒险', '', 'mp4']
- file_names = file_name.split("-")
- if len(file_names) > 0 and file_names[0] == str(index):
- path = Path(os.path.join(file_path, file_name))
- # 判断是否为文件
- if path.is_file():
- count += 1
- else:
- # 如果是文件夹，统计其中的文件
- for sub_file in os.listdir(path):
- sub_path = Path(os.path.join(path, sub_file))
- if sub_path.is_file():
- count += 1
- except Exception as e:
- logger.error(f"统计视频文件失败: {e}")
-
- return count
-
- def prepare_batch_files(self, folder_path, config):
- """准备批量上传的文件列表（与main.py中的action1方法逻辑一致）"""
- file_paths = []
-
- # 参数验证
- if not config:
- logger.error("配置为空，无法准备批量上传文件")
- return file_paths
-
- index = str(config.get('序号', '')).strip()
- if not index:
- logger.warning("序号为空，无法准备批量上传文件")
- return file_paths
-
- if not folder_path or not os.path.exists(folder_path):
- logger.error(f"文件夹路径无效或不存在: {folder_path}")
- return file_paths
-
- if not os.access(folder_path, os.R_OK):
- logger.error(f"没有权限读取文件夹: {folder_path}")
- return file_paths
-
- logger.info("=" * 50)
- logger.info("开始准备批量上传文件列表...")
- logger.info(f"文件夹路径: {folder_path}")
- logger.info(f"查找序号: {index}")
-
- try:
- # 遍历最外层文件夹下的所有子文件夹（与main.py逻辑一致）
- try:
- all_items = os.listdir(folder_path)
- subdirs = [f for f in all_items if os.path.isdir(os.path.join(folder_path, f))]
- except PermissionError:
- logger.error(f"没有权限访问文件夹: {folder_path}")
- return file_paths
- except Exception as e:
- logger.error(f"读取文件夹失败: {e}")
- return file_paths
-
- logger.info(f"在最外层文件夹下找到 {len(subdirs)} 个子文件夹（多多ID文件夹）")
-
- for subdir_name in subdirs:
- file_path = os.path.join(folder_path, subdir_name) # 拼接文件夹
- logger.info(f" 正在扫描子文件夹: {subdir_name}")
-
- # 检查是否为目录，跳过文件（如.lnk快捷方式）
- if not os.path.isdir(file_path):
- logger.info(f" 跳过（不是文件夹）")
- continue
-
- files = os.listdir(file_path) # 获取用户id下的文件
- logger.info(f" 该文件夹下有 {len(files)} 个项目")
-
- for file_name in files:
- logger.info(f" 检查项目: {file_name}")
-
- # 检查是否是视频文件（.mp4）
- if ".mp4" in file_name:
- logger.info(f" ✓ 是视频文件（包含.mp4）")
- # 用"-"分割文件名，检查第一部分是否等于序号
- # 文件名格式：4-茶叶蛋大冒险-.mp4 -> ['4', '茶叶蛋大冒险', '', 'mp4']
- file_names = file_name.split("-")
- logger.info(f" 文件名分割结果: {file_names}")
-
- if len(file_names) > 0 and file_names[0] == str(index):
- logger.info(f" ✓ 序号匹配！序号: {file_names[0]}, 目标序号: {index}")
- path = Path(os.path.join(file_path, file_name))
-
- # 判断是否为文件
- if path.is_file():
- logger.info(f" ✓ 是文件，添加到列表: {path.name}")
- file_paths.append({
- "url": config.get('达人链接', ''),
- "user_id": config.get('多多id', ''),
- "time_start": config.get('定时发布', '') if config.get('定时发布') else None,
- "ht": config.get('话题', ''),
- "index": str(index),
- "path": path
- })
- logger.info(f" 当前视频总数: {len(file_paths)}")
- # 注意：这里不break，因为可能有多个匹配的文件
- else:
- logger.info(f" 是文件夹，扫描其中的文件...")
- # 如果是文件夹，添加其中的所有文件
- try:
- sub_files = os.listdir(path)
- logger.info(f" 文件夹中有 {len(sub_files)} 个文件")
- for sub_file in sub_files:
- sub_path = Path(os.path.join(path, sub_file))
- if sub_path.is_file():
- logger.info(f" ✓ 添加文件: {sub_file}")
- file_paths.append({
- "url": config.get('达人链接', ''),
- "user_id": config.get('多多id', ''),
- "time_start": config.get('定时发布', '') if config.get(
- '定时发布') else None,
- "ht": config.get('话题', ''),
- "index": str(index),
- "path": sub_path
- })
- logger.info(f" 当前视频总数: {len(file_paths)}")
- except Exception as e:
- logger.error(f" 扫描子文件夹失败: {e}")
- else:
- if len(file_names) > 0:
- logger.info(f" ✗ 序号不匹配: {file_names[0]} != {index}")
- else:
- logger.info(f" ✗ 文件名格式不正确，无法提取序号")
- else:
- logger.info(f" ✗ 不是视频文件（不包含.mp4），跳过")
- except Exception as e:
- logger.error(f"准备批量文件失败: {e}")
- import traceback
- traceback.print_exc()
-
- logger.info("=" * 50)
- logger.info(f"文件收集完成！共找到 {len(file_paths)} 个视频文件")
- if file_paths:
- logger.info("视频文件列表:")
- for idx, video_info in enumerate(file_paths, 1):
- logger.info(f" {idx}. {video_info['path'].name} ({video_info['path']})")
-
- return file_paths
-
- def stop(self):
- """停止执行"""
- self.is_running = False
-
- def requestInterruption(self):
- """请求中断线程（重写QThread方法）"""
- super().requestInterruption()
- self.is_running = False
-
-
-class ConfigTableModel(QAbstractTableModel):
- """大数据量表格模型"""
-
- def __init__(self, configs, headers, parent=None):
- super().__init__(parent)
- self._configs = configs
- self._headers = headers
-
- def rowCount(self, parent=QModelIndex()):
- return len(self._configs)
-
- def columnCount(self, parent=QModelIndex()):
- return len(self._headers)
-
- def data(self, index, role=Qt.DisplayRole):
- if not index.isValid():
- return None
- row = index.row()
- col = index.column()
- config = self._configs[row]
- mapping = {
- 0: "多多id",
- 1: "序号",
- 2: "话题",
- 3: "定时发布",
- 4: "间隔时间",
- 5: "达人链接",
- 6: "执行人",
- 7: "情况",
- 8: "文件路径",
- 9: "",
- 10: "",
- }
- key = mapping.get(col, "")
- if role == Qt.DisplayRole:
- return str(config.get(key, "")) if key else ""
- elif role == Qt.TextAlignmentRole:
- # 所有单元格居中对齐
- return Qt.AlignCenter
- elif role == Qt.ToolTipRole:
- # 为达人链接和文件路径列提供 tooltip 显示完整内容
- if col in (5, 8) and key:
- return str(config.get(key, ""))
- return None
-
- def headerData(self, section, orientation, role=Qt.DisplayRole):
- if role != Qt.DisplayRole:
- return None
- if orientation == Qt.Horizontal:
- return self._headers[section]
- return section + 1
-
- def flags(self, index):
- if not index.isValid():
- return Qt.NoItemFlags
- return Qt.ItemIsEnabled | Qt.ItemIsSelectable | Qt.ItemIsEditable
-
- def setData(self, index, value, role=Qt.EditRole):
- if role != Qt.EditRole or not index.isValid():
- return False
- row = index.row()
- col = index.column()
- mapping = {
- 0: "多多id",
- 1: "序号",
- 2: "话题",
- 3: "定时发布",
- 4: "间隔时间",
- 5: "达人链接",
- 6: "执行人",
- 7: "情况",
- 8: "文件路径",
- }
- key = mapping.get(col, "")
- if not key:
- return False
- self._configs[row][key] = str(value)
- self.dataChanged.emit(index, index, [Qt.DisplayRole])
- return True
-
- def removeRows(self, row, count, parent=QModelIndex()):
- if row < 0 or row + count > len(self._configs):
- return False
- self.beginRemoveRows(parent, row, row + count - 1)
- del self._configs[row:row + count]
- self.endRemoveRows()
- return True
-
-
-class TableActionDelegate(QStyledItemDelegate):
- """Model/View 操作列 + 进度列 delegate"""
-
- def __init__(self, parent, on_delete):
- super().__init__(parent)
- self.on_delete = on_delete
-
- def paint(self, painter, option, index):
- if index.column() == 9:
- status_text = index.sibling(index.row(), 7).data() or ""
- value = 0
- if "完成" in status_text or "成功" in status_text:
- value = 100
- elif "执行中" in status_text or "进行" in status_text:
- value = 60
- elif "待" in status_text:
- value = 10
- bar = QStyleOptionProgressBar()
- bar.rect = option.rect.adjusted(6, option.rect.height() // 3, -6, -option.rect.height() // 3)
- bar.minimum = 0
- bar.maximum = 100
- bar.progress = value
- bar.textVisible = False
- QApplication.style().drawControl(QStyle.CE_ProgressBar, bar, painter)
- return
- if index.column() == 10:
- rect = option.rect
- delete_rect = rect.adjusted(6, 4, -6, -4)
- delete_btn = QStyleOptionButton()
- delete_btn.rect = delete_rect
- delete_btn.text = "删除"
- QApplication.style().drawControl(QStyle.CE_PushButton, delete_btn, painter)
- return
- super().paint(painter, option, index)
-
- def editorEvent(self, event, model, option, index):
- if index.column() != 10:
- return super().editorEvent(event, model, option, index)
- if event.type() == event.MouseButtonRelease:
- rect = option.rect
- delete_rect = rect.adjusted(6, 4, -6, -4)
- if delete_rect.contains(event.pos()):
- self.on_delete(index)
- return True
- return False
-
- def update_data(self, configs):
- self.beginResetModel()
- self._configs = configs
- self.endResetModel()
+# ---------------------------------------------------------------------------
+# 主窗口
+# ---------------------------------------------------------------------------
class MainWindow(QMainWindow):
"""主窗口"""
@@ -1149,10 +474,7 @@ class MainWindow(QMainWindow):
}
""")
self.config_table.setColumnCount(12)
- self.config_table.setHorizontalHeaderLabels([
- '☑', '多多ID', '序号', '话题', '定时发布', '间隔时间', '达人链接',
- '执行人', '情况', '文件路径', '进度', '操作'
- ])
+ self.config_table.setHorizontalHeaderLabels(TABLE_HEADERS)
self.table_column_filter.addItem("全部列")
# 第0列为勾选框；记录下拉项对应的表格列索引及 Model 列索引
self._filter_table_columns = []
@@ -1502,10 +824,12 @@ class MainWindow(QMainWindow):
# 确保标志被重置
self.is_updating_table = False
- def _set_checkbox_item(self, row, config_index):
- """设置勾选框列（第0列），使用嵌套布局确保真正水平+垂直居中"""
+ def _set_checkbox_item(self, row, config_index, row_height=None):
+ """设置勾选框列（第0列）。row_height 传入时使用固定高度+居中对齐，避免第二行起勾选框往下错位。"""
checkbox = QCheckBox()
+ checkbox.blockSignals(True)
checkbox.setChecked(self.configs[config_index].get('勾选', False)) # 默认不勾选
+ checkbox.blockSignals(False)
checkbox.stateChanged.connect(lambda state, idx=config_index: self._on_checkbox_changed(idx, state))
checkbox.setStyleSheet(
"QCheckBox { margin: 0px; padding: 0px; }"
@@ -1513,24 +837,15 @@ class MainWindow(QMainWindow):
)
wrapper = QWidget()
- wrapper.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Expanding)
+ h = row_height if (row_height is not None and row_height > 0) else 42
+ wrapper.setFixedHeight(h)
+ wrapper.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Fixed)
- # 外层垂直布局：通过上下 stretch 实现垂直居中
- v_layout = QVBoxLayout(wrapper)
- v_layout.setContentsMargins(0, 0, 0, 0)
- v_layout.setSpacing(0)
- v_layout.addStretch()
-
- # 内层水平布局：通过左右 stretch 实现水平居中
- h_layout = QHBoxLayout()
- h_layout.setContentsMargins(0, 0, 0, 0)
- h_layout.setSpacing(0)
- h_layout.addStretch()
- h_layout.addWidget(checkbox)
- h_layout.addStretch()
-
- v_layout.addLayout(h_layout)
- v_layout.addStretch()
+ layout = QVBoxLayout(wrapper)
+ layout.setContentsMargins(0, 0, 0, 0)
+ layout.setSpacing(0)
+ layout.setAlignment(Qt.AlignCenter)
+ layout.addWidget(checkbox)
self.config_table.setCellWidget(row, 0, wrapper)
@@ -3430,44 +2745,52 @@ class MainWindow(QMainWindow):
# 计算实际显示行数：数据行数和最小行数取最大值
display_rows = max(len(self.page_row_indices), min_display_rows)
self.config_table.setRowCount(display_rows)
-
- # 填充数据行
- for table_row, config_index in enumerate(self.page_row_indices):
- config = self.configs[config_index]
- # 第0列：勾选框
- self._set_checkbox_item(table_row, config_index)
- # 其他列的索引均+1
- self.config_table.setItem(table_row, 1, self._create_centered_item(str(config.get('多多id', ''))))
- self.config_table.setItem(table_row, 2, self._create_centered_item(str(config.get('序号', ''))))
- self.config_table.setItem(table_row, 3, self._create_centered_item(str(config.get('话题', ''))))
- self.config_table.setItem(table_row, 4, self._create_centered_item(str(config.get('定时发布', ''))))
- # 间隔时间：保持原始状态，空值显示为空
- interval_val = config.get('间隔时间', '')
- # 如果是数字类型（0或其他数字），显示数字；如果是空字符串，保持为空
- if interval_val == '' or interval_val is None:
- interval_display = ''
- else:
- interval_display = str(interval_val)
- self.config_table.setItem(table_row, 5, self._create_centered_item(interval_display))
- # 达人链接列：设置 tooltip 显示完整内容
- url_text = str(config.get('达人链接', ''))
- url_item = self._create_centered_item(url_text)
- url_item.setToolTip(url_text) # 悬停显示完整链接
- self.config_table.setItem(table_row, 6, url_item)
- self.config_table.setItem(table_row, 7, self._create_centered_item(str(config.get('执行人', ''))))
- self._set_status_item(table_row, str(config.get('情况', '待执行')))
- # 文件路径列（第9列，索引为9），如果配置中没有则显示空，设置 tooltip
- file_path = str(config.get('文件路径', ''))
- file_path_item = self._create_centered_item(file_path)
- file_path_item.setToolTip(file_path) # 悬停显示完整路径
- self.config_table.setItem(table_row, 9, file_path_item)
- self._set_progress_item(table_row, str(config.get('情况', '待执行')))
- self._set_action_buttons(table_row, config_index)
-
- # 确保所有行使用一致的行高
+
+ # 先统一设置行高，再填数据，避免后设行高导致勾选框列布局重算、出现“除第一行外往下移”
default_row_height = self.config_table.verticalHeader().defaultSectionSize()
- for row in range(self.config_table.rowCount()):
+ for row in range(display_rows):
self.config_table.setRowHeight(row, default_row_height)
+
+ # 先清除第 0 列所有单元格控件，避免连续刷新时旧勾选框残留导致错位
+ for row in range(display_rows):
+ self.config_table.removeCellWidget(row, 0)
+
+ # 填充期间禁止表格重绘，避免中间布局导致勾选框错位
+ self.config_table.setUpdatesEnabled(False)
+ try:
+ # 填充数据行
+ for table_row, config_index in enumerate(self.page_row_indices):
+ config = self.configs[config_index]
+ # 第0列：勾选框（传入行高，固定高度+居中对齐，避免第一页第二行等错位）
+ self._set_checkbox_item(table_row, config_index, default_row_height)
+ # 其他列的索引均+1
+ self.config_table.setItem(table_row, 1, self._create_centered_item(str(config.get('多多id', ''))))
+ self.config_table.setItem(table_row, 2, self._create_centered_item(str(config.get('序号', ''))))
+ self.config_table.setItem(table_row, 3, self._create_centered_item(str(config.get('话题', ''))))
+ self.config_table.setItem(table_row, 4, self._create_centered_item(str(config.get('定时发布', ''))))
+ # 间隔时间：保持原始状态，空值显示为空
+ interval_val = config.get('间隔时间', '')
+ if interval_val == '' or interval_val is None:
+ interval_display = ''
+ else:
+ interval_display = str(interval_val)
+ self.config_table.setItem(table_row, 5, self._create_centered_item(interval_display))
+ url_text = str(config.get('达人链接', ''))
+ url_item = self._create_centered_item(url_text)
+ url_item.setToolTip(url_text)
+ self.config_table.setItem(table_row, 6, url_item)
+ self.config_table.setItem(table_row, 7, self._create_centered_item(str(config.get('执行人', ''))))
+ self._set_status_item(table_row, str(config.get('情况', '待执行')))
+ file_path = str(config.get('文件路径', ''))
+ file_path_item = self._create_centered_item(file_path)
+ file_path_item.setToolTip(file_path)
+ self.config_table.setItem(table_row, 9, file_path_item)
+ self._set_progress_item(table_row, str(config.get('情况', '待执行')))
+ self._set_action_buttons(table_row, config_index)
+ finally:
+ self.config_table.setUpdatesEnabled(True)
+ # 强制表格立即完成布局，避免第一页第二行等勾选框错位
+ self.config_table.doItemsLayout()
# 重新启用排序功能（但不会自动排序已填充的数据）
self.config_table.setSortingEnabled(True)
@@ -3486,8 +2809,7 @@ class MainWindow(QMainWindow):
def _setup_model_view(self):
"""切换到大数据量 Model/View 模式"""
- headers = ['多多ID', '序号', '话题', '定时发布', '间隔时间', '达人链接', '执行人', '情况', '文件路径', '进度',
- '操作']
+ headers = MODEL_VIEW_HEADERS
if self.table_model is None:
self.table_model = ConfigTableModel(self.configs, headers, self)
self.table_proxy = QSortFilterProxyModel(self)
@@ -3578,7 +2900,14 @@ class MainWindow(QMainWindow):
def update_data(self):
"""更新数据：找出文件并保存到各行的文件路径列"""
+ # 防止连续点击导致重入，避免勾选框错位
+ if getattr(self, '_update_data_running', False):
+ return
try:
+ self._update_data_running = True
+ if hasattr(self, 'update_data_btn'):
+ self.update_data_btn.setEnabled(False)
+
if not self.configs:
self._show_infobar("warning", "提示", "请先导入Excel配置文件")
return
@@ -3681,6 +3010,10 @@ class MainWindow(QMainWindow):
logger.error(f"更新数据失败: {e}")
import traceback
traceback.print_exc()
+ finally:
+ self._update_data_running = False
+ if hasattr(self, 'update_data_btn'):
+ self.update_data_btn.setEnabled(True)
def _index_matches_name(self, index, name_or_stem):
"""序号与文件名/文件夹名是否匹配。支持：序号、序号.mp4、序号-xxx、01 与 1 数字等价。"""
@@ -4590,4 +3923,3 @@ def main():
if __name__ == '__main__':
main()
-# docker run honeygain/honeygain -tou-accept -email ddrwode1@gmail.com -pass 040828cjj -device DEVICE_NAME
diff --git a/gui_constants.py b/gui_constants.py
new file mode 100644
index 0000000..2b63bea
--- /dev/null
+++ b/gui_constants.py
@@ -0,0 +1,56 @@
+# -*- coding: utf-8 -*-
+"""GUI 常量与配置：路径、表头、列映射、视频扩展名等。"""
+
+import os
+
+# 默认资料文件夹名（相对桌面）
+DEFAULT_FOLDER_NAME = "多多自动化发文"
+
+# 表格列与配置键的映射（Model 列索引 -> config 键）
+COLUMN_KEY_MAPPING = {
+ 0: "多多id",
+ 1: "序号",
+ 2: "话题",
+ 3: "定时发布",
+ 4: "间隔时间",
+ 5: "达人链接",
+ 6: "执行人",
+ 7: "情况",
+ 8: "文件路径",
+ 9: "",
+ 10: "",
+}
+
+# 表格列与配置键的映射（仅可编辑列，用于 setData）
+COLUMN_KEY_MAPPING_EDIT = {
+ 0: "多多id",
+ 1: "序号",
+ 2: "话题",
+ 3: "定时发布",
+ 4: "间隔时间",
+ 5: "达人链接",
+ 6: "执行人",
+ 7: "情况",
+ 8: "文件路径",
+}
+
+# 配置表格表头（12 列：勾选 + 9 数据 + 进度 + 操作）
+TABLE_HEADERS = [
+ '☑', '多多ID', '序号', '话题', '定时发布', '间隔时间', '达人链接',
+ '执行人', '情况', '文件路径', '进度', '操作'
+]
+
+# Model/View 模式表头（11 列：无勾选列）
+MODEL_VIEW_HEADERS = [
+ '多多ID', '序号', '话题', '定时发布', '间隔时间', '达人链接',
+ '执行人', '情况', '文件路径', '进度', '操作'
+]
+
+# 视频文件扩展名
+VIDEO_EXTENSIONS = ['.mp4', '.avi', '.mov', '.mkv', '.flv', '.wmv', '.webm']
+
+
+def get_default_folder_path():
+ """获取默认文件夹路径（桌面/多多自动化发文）"""
+ desktop = os.path.join(os.path.expanduser("~"), "Desktop")
+ return os.path.join(desktop, DEFAULT_FOLDER_NAME)
diff --git a/gui_models.py b/gui_models.py
new file mode 100644
index 0000000..789b973
--- /dev/null
+++ b/gui_models.py
@@ -0,0 +1,129 @@
+# -*- coding: utf-8 -*-
+"""表格数据模型与代理：ConfigTableModel、TableActionDelegate。"""
+
+from PyQt5.QtWidgets import (
+ QApplication,
+ QStyle,
+ QStyledItemDelegate,
+ QStyleOptionProgressBar,
+ QStyleOptionButton,
+)
+from PyQt5.QtCore import Qt, QAbstractTableModel, QModelIndex
+
+from gui_constants import COLUMN_KEY_MAPPING, COLUMN_KEY_MAPPING_EDIT, MODEL_VIEW_HEADERS
+
+
+class ConfigTableModel(QAbstractTableModel):
+ """大数据量表格模型"""
+
+ def __init__(self, configs, headers, parent=None):
+ super().__init__(parent)
+ self._configs = configs
+ self._headers = headers if headers is not None else MODEL_VIEW_HEADERS
+
+ def rowCount(self, parent=QModelIndex()):
+ return len(self._configs)
+
+ def columnCount(self, parent=QModelIndex()):
+ return len(self._headers)
+
+ def data(self, index, role=Qt.DisplayRole):
+ if not index.isValid():
+ return None
+ row = index.row()
+ col = index.column()
+ config = self._configs[row]
+ key = COLUMN_KEY_MAPPING.get(col, "")
+ if role == Qt.DisplayRole:
+ return str(config.get(key, "")) if key else ""
+ elif role == Qt.TextAlignmentRole:
+ return Qt.AlignCenter
+ elif role == Qt.ToolTipRole:
+ if col in (5, 8) and key:
+ return str(config.get(key, ""))
+ return None
+
+ def headerData(self, section, orientation, role=Qt.DisplayRole):
+ if role != Qt.DisplayRole:
+ return None
+ if orientation == Qt.Horizontal:
+ return self._headers[section]
+ return section + 1
+
+ def flags(self, index):
+ if not index.isValid():
+ return Qt.NoItemFlags
+ return Qt.ItemIsEnabled | Qt.ItemIsSelectable | Qt.ItemIsEditable
+
+ def setData(self, index, value, role=Qt.EditRole):
+ if role != Qt.EditRole or not index.isValid():
+ return False
+ row = index.row()
+ col = index.column()
+ key = COLUMN_KEY_MAPPING_EDIT.get(col, "")
+ if not key:
+ return False
+ self._configs[row][key] = str(value)
+ self.dataChanged.emit(index, index, [Qt.DisplayRole])
+ return True
+
+ def removeRows(self, row, count, parent=QModelIndex()):
+ if row < 0 or row + count > len(self._configs):
+ return False
+ self.beginRemoveRows(parent, row, row + count - 1)
+ del self._configs[row:row + count]
+ self.endRemoveRows()
+ return True
+
+ def update_data(self, configs):
+ """更新内部数据并刷新视图"""
+ self.beginResetModel()
+ self._configs = configs
+ self.endResetModel()
+
+
+class TableActionDelegate(QStyledItemDelegate):
+ """Model/View 操作列 + 进度列 delegate"""
+
+ def __init__(self, parent, on_delete):
+ super().__init__(parent)
+ self.on_delete = on_delete
+
+ def paint(self, painter, option, index):
+ if index.column() == 9:
+ status_text = index.sibling(index.row(), 7).data() or ""
+ value = 0
+ if "完成" in status_text or "成功" in status_text:
+ value = 100
+ elif "执行中" in status_text or "进行" in status_text:
+ value = 60
+ elif "待" in status_text:
+ value = 10
+ bar = QStyleOptionProgressBar()
+ bar.rect = option.rect.adjusted(6, option.rect.height() // 3, -6, -option.rect.height() // 3)
+ bar.minimum = 0
+ bar.maximum = 100
+ bar.progress = value
+ bar.textVisible = False
+ QApplication.style().drawControl(QStyle.CE_ProgressBar, bar, painter)
+ return
+ if index.column() == 10:
+ rect = option.rect
+ delete_rect = rect.adjusted(6, 4, -6, -4)
+ delete_btn = QStyleOptionButton()
+ delete_btn.rect = delete_rect
+ delete_btn.text = "删除"
+ QApplication.style().drawControl(QStyle.CE_PushButton, delete_btn, painter)
+ return
+ super().paint(painter, option, index)
+
+ def editorEvent(self, event, model, option, index):
+ if index.column() != 10:
+ return super().editorEvent(event, model, option, index)
+ if event.type() == event.MouseButtonRelease:
+ rect = option.rect
+ delete_rect = rect.adjusted(6, 4, -6, -4)
+ if delete_rect.contains(event.pos()):
+ self.on_delete(index)
+ return True
+ return False
diff --git a/gui_worker.py b/gui_worker.py
new file mode 100644
index 0000000..b65e6e6
--- /dev/null
+++ b/gui_worker.py
@@ -0,0 +1,470 @@
+# -*- coding: utf-8 -*-
+"""后台工作线程：执行单个/批量上传任务，与 main.Pdd 交互。"""
+
+import os
+import time
+from pathlib import Path
+
+from PyQt5.QtCore import QThread, pyqtSignal
+
+from main import Pdd
+from loguru import logger
+
+from gui_constants import get_default_folder_path, VIDEO_EXTENSIONS
+
+
+class WorkerThread(QThread):
+ """工作线程，用于执行自动化任务"""
+ finished = pyqtSignal(bool, str)
+ log_message = pyqtSignal(str)
+ progress = pyqtSignal(int)
+ item_result = pyqtSignal(object) # 单条发布结果（dict）
+
+ def __init__(self, config_data, is_batch_mode, prepared_files=None, parent=None):
+ super().__init__(parent)
+ self.config_data = config_data
+ self.is_batch_mode = is_batch_mode
+ self.prepared_files = prepared_files # 预查找的文件列表
+ self.is_running = True
+
+ def run(self):
+ sink_id = None
+ start_ts = time.time()
+ try:
+ sink_id = logger.add(lambda msg: self.log_message.emit(str(msg).strip()))
+ if self.is_batch_mode:
+ self.run_batch_mode()
+ else:
+ self.run_single_mode()
+ except Exception as e:
+ error_msg = f"执行失败: {str(e)}"
+ self.finished.emit(False, error_msg)
+ self.log_message.emit(error_msg)
+ logger.error(f"执行失败: {e}")
+ import traceback
+ traceback_str = traceback.format_exc()
+ logger.error(traceback_str)
+ self.log_message.emit(f"错误详情: {traceback_str}")
+ finally:
+ try:
+ cost = time.time() - start_ts
+ self.log_message.emit(f"[线程] 任务结束，耗时 {cost:.2f}s")
+ except Exception:
+ pass
+ if sink_id is not None:
+ try:
+ logger.remove(sink_id)
+ except Exception:
+ pass
+
+ def run_single_mode(self):
+ """执行单个上传模式（action方法）"""
+ try:
+ config = self.config_data
+ self.log_message.emit(f"开始处理单个任务（逐个上传模式）...")
+
+ pdd = Pdd(
+ url=config.get('达人链接', ''),
+ user_id=config.get('多多id', ''),
+ time_start=config.get('定时发布', '') if config.get('定时发布') else None,
+ ht=config.get('话题', ''),
+ index=config.get('序号', ''),
+ title=config.get('标题', None)
+ )
+
+ if self.prepared_files:
+ self.log_message.emit(f"使用预查找的文件列表，共 {len(self.prepared_files)} 个文件")
+ self.progress.emit(30)
+
+ first_file = self.prepared_files[0]
+ if first_file['path'].is_file():
+ folder_path = str(first_file['path'].parent.parent)
+ else:
+ folder_path = str(first_file['path'].parent.parent)
+
+ self.log_message.emit(f"使用文件夹路径: {folder_path}")
+ try:
+ 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 ''}")
+ if isinstance(result, dict):
+ self.item_result.emit({
+ "user_id": config.get("多多id", ""),
+ "index": config.get("序号", ""),
+ "name": config.get("标题", "") or "",
+ "ok": ok,
+ "reason": result.get("reason", ""),
+ })
+ self.progress.emit(100)
+ self.finished.emit(ok, f"单个任务执行完成（ok={ok}）")
+ except Exception as e:
+ error_msg = f"执行action方法失败: {str(e)}"
+ self.log_message.emit(error_msg)
+ logger.error(error_msg)
+ import traceback
+ traceback_str = traceback.format_exc()
+ logger.error(traceback_str)
+ self.log_message.emit(f"错误详情: {traceback_str}")
+ self.finished.emit(False, error_msg)
+ return
+ else:
+ folder_path = config.get('文件夹路径', '').strip()
+ if not folder_path:
+ folder_path = get_default_folder_path()
+
+ if not os.path.exists(folder_path):
+ error_msg = f"文件夹路径不存在: {folder_path}"
+ self.finished.emit(False, error_msg)
+ self.log_message.emit(error_msg)
+ return
+
+ self.log_message.emit(f"使用文件夹路径: {folder_path}")
+ self.progress.emit(30)
+ is_batch_mode = self.is_batch_mode
+
+ try:
+ 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 ''}")
+ if isinstance(result, dict):
+ self.item_result.emit({
+ "user_id": config.get("多多id", ""),
+ "index": config.get("序号", ""),
+ "name": config.get("标题", "") or "",
+ "ok": ok,
+ "reason": result.get("reason", ""),
+ })
+ except Exception as e:
+ error_msg = f"执行action方法失败: {str(e)}"
+ self.log_message.emit(error_msg)
+ logger.error(error_msg)
+ import traceback
+ traceback_str = traceback.format_exc()
+ logger.error(traceback_str)
+ self.log_message.emit(f"错误详情: {traceback_str}")
+ self.finished.emit(False, error_msg)
+ return
+
+ self.progress.emit(100)
+ self.finished.emit(ok, f"单个任务执行完成（ok={ok}）")
+ except Exception as e:
+ error_msg = f"执行失败: {str(e)}"
+ self.finished.emit(False, error_msg)
+ self.log_message.emit(error_msg)
+ logger.error(f"执行失败: {e}")
+ import traceback
+ traceback_str = traceback.format_exc()
+ logger.error(traceback_str)
+ self.log_message.emit(f"错误详情: {traceback_str}")
+
+ def run_batch_mode(self):
+ """执行批量上传模式：先批量上传所有视频，然后逐个上传图片"""
+ try:
+ config = self.config_data
+ self.log_message.emit(f"开始处理批量上传任务...")
+ index = config.get('序号', '')
+
+ pdd = Pdd(
+ url=config.get('达人链接', ''),
+ user_id=config.get('多多id', ''),
+ time_start=config.get('定时发布', '') if config.get('定时发布') else None,
+ ht=config.get('话题', ''),
+ index=index,
+ title=config.get('标题', None)
+ )
+
+ if self.prepared_files:
+ self.log_message.emit(f"使用预查找的文件列表，共 {len(self.prepared_files)} 个文件")
+ self.progress.emit(30)
+
+ video_file_paths = [f for f in self.prepared_files if f['path'].is_file() and any(
+ f['path'].suffix.lower() == ext for ext in VIDEO_EXTENSIONS)]
+ image_folders = [f for f in self.prepared_files if f['path'].is_dir()]
+
+ if video_file_paths:
+ self.log_message.emit(f"找到 {len(video_file_paths)} 个视频文件，开始批量上传...")
+ self.progress.emit(30)
+
+ def on_video_done(result_item):
+ try:
+ payload = dict(result_item)
+ payload["user_id"] = config.get("多多id", "")
+ if "index" not in payload or not payload.get("index"):
+ for vid_file in video_file_paths:
+ if str(vid_file.get('path')) == str(payload.get('path')):
+ payload["index"] = vid_file.get("index", config.get("序号", ""))
+ break
+ if "index" not in payload or not payload.get("index"):
+ payload["index"] = config.get("序号", "")
+ self.item_result.emit(payload)
+ self.log_message.emit(f" {'✓' if payload.get('ok') else '✗'} {payload.get('name', '')} 已更新状态")
+ except Exception as e:
+ self.log_message.emit(f" 回调处理异常: {e}")
+
+ result = pdd.action1(folder_path=video_file_paths, on_item_done=on_video_done)
+ ok = bool(result.get("ok")) if isinstance(result, dict) else True
+ if not ok:
+ fails = [r for r in (result.get("results") or []) if not r.get("ok")]
+ self.log_message.emit(f"发布校验失败条数: {len(fails)}")
+ for r in fails[:20]:
+ self.log_message.emit(f" ✗ {r.get('name')} | {r.get('reason')}")
+ self.log_message.emit(f"批量上传视频完成，共处理 {len(video_file_paths)} 个视频")
+ else:
+ self.log_message.emit("未找到视频文件，跳过视频上传")
+ ok = True
+
+ if image_folders:
+ self.log_message.emit(f"找到 {len(image_folders)} 个图片文件夹，开始逐个上传...")
+ self.progress.emit(70)
+
+ for idx, image_folder_info in enumerate(image_folders):
+ if not self.is_running:
+ break
+ image_folder = str(image_folder_info['path'])
+ self.log_message.emit(f"处理第 {idx + 1}/{len(image_folders)} 个图片文件夹: {image_folder}")
+ pdd.action(folder_path=image_folder)
+ self.log_message.emit(f"图片文件夹 {idx + 1} 上传完成")
+
+ self.log_message.emit(f"所有图片文件夹上传完成，共处理 {len(image_folders)} 个文件夹")
+ else:
+ self.log_message.emit("未找到图片文件夹，跳过图片上传")
+
+ self.progress.emit(100)
+ self.finished.emit(ok,
+ f"批量任务执行完成，共处理 {len(video_file_paths)} 个视频和 {len(image_folders)} 个图片文件夹（ok={ok}）")
+ else:
+ folder_path = config.get('文件夹路径', '').strip()
+ if not folder_path:
+ folder_path = get_default_folder_path()
+
+ if not os.path.exists(folder_path):
+ self.finished.emit(False, f"文件夹路径不存在: {folder_path}")
+ return
+
+ self.log_message.emit("第一步：收集所有视频文件...")
+ video_file_paths = self.prepare_batch_files(folder_path, config)
+ self.log_message.emit("第二步：收集所有图片文件夹...")
+ image_folders = self.prepare_image_folders(folder_path, index)
+
+ if video_file_paths:
+ self.log_message.emit(f"找到 {len(video_file_paths)} 个视频文件，开始批量上传...")
+ self.progress.emit(30)
+ pdd.action1(folder_path=video_file_paths)
+ self.log_message.emit(f"批量上传视频完成，共处理 {len(video_file_paths)} 个视频")
+ else:
+ self.log_message.emit("未找到视频文件，跳过视频上传")
+
+ if image_folders:
+ self.log_message.emit(f"找到 {len(image_folders)} 个图片文件夹，开始逐个上传...")
+ self.progress.emit(70)
+
+ for idx, image_folder in enumerate(image_folders):
+ if not self.is_running:
+ break
+ self.log_message.emit(f"处理第 {idx + 1}/{len(image_folders)} 个图片文件夹: {image_folder}")
+ pdd.action(folder_path=image_folder)
+ self.log_message.emit(f"图片文件夹 {idx + 1} 上传完成")
+
+ self.log_message.emit(f"所有图片文件夹上传完成，共处理 {len(image_folders)} 个文件夹")
+ else:
+ self.log_message.emit("未找到图片文件夹，跳过图片上传")
+
+ self.progress.emit(100)
+ total_count = len(video_file_paths) + len(image_folders)
+ self.finished.emit(True,
+ f"批量任务执行完成，共处理 {len(video_file_paths)} 个视频和 {len(image_folders)} 个图片文件夹")
+
+ except Exception as e:
+ self.finished.emit(False, f"批量执行失败: {str(e)}")
+ logger.error(f"批量执行失败: {e}")
+
+ def prepare_image_folders(self, folder_path, index):
+ """收集所有匹配序号的图片文件夹（与main.py中action方法的逻辑一致）"""
+ image_folders = []
+ try:
+ if not folder_path or not os.path.exists(folder_path):
+ logger.warning(f"文件夹路径无效或不存在: {folder_path}")
+ return image_folders
+ if not os.access(folder_path, os.R_OK):
+ logger.error(f"没有权限读取文件夹: {folder_path}")
+ return image_folders
+ try:
+ subdirs = os.listdir(folder_path)
+ except PermissionError:
+ logger.error(f"没有权限访问文件夹: {folder_path}")
+ return image_folders
+ except Exception as e:
+ logger.error(f"读取文件夹失败: {e}")
+ return image_folders
+
+ for file in subdirs:
+ try:
+ file_path = os.path.join(folder_path, file)
+ if not os.path.isdir(file_path):
+ continue
+ try:
+ files = os.listdir(file_path)
+ except (PermissionError, Exception) as e:
+ logger.warning(f"读取子文件夹失败: {file_path}, 错误: {e}")
+ continue
+
+ for file_name in files:
+ try:
+ if file_name.startswith('.'):
+ continue
+ file_names = file_name.split("-")
+ if len(file_names) > 0 and file_names[0] == str(index):
+ path = Path(os.path.join(file_path, file_name))
+ if path.exists() and path.is_dir():
+ image_folders.append(str(path))
+ except Exception as e:
+ logger.warning(f"处理文件 {file_name} 时出错: {e}")
+ continue
+ except Exception as e:
+ logger.warning(f"处理子文件夹 {file} 时出错: {e}")
+ continue
+ except Exception as e:
+ logger.error(f"收集图片文件夹失败: {e}", exc_info=True)
+ return image_folders
+
+ def count_videos_in_folder(self, folder_path, index):
+ """统计文件夹中匹配序号的视频文件数量（与main.py逻辑一致）"""
+ count = 0
+ try:
+ for file in os.listdir(folder_path):
+ file_path = os.path.join(folder_path, file)
+ if not os.path.isdir(file_path):
+ continue
+ files = os.listdir(file_path)
+ for file_name in files:
+ if ".mp4" in file_name:
+ file_names = file_name.split("-")
+ if len(file_names) > 0 and file_names[0] == str(index):
+ path = Path(os.path.join(file_path, file_name))
+ if path.is_file():
+ count += 1
+ else:
+ for sub_file in os.listdir(path):
+ sub_path = Path(os.path.join(path, sub_file))
+ if sub_path.is_file():
+ count += 1
+ except Exception as e:
+ logger.error(f"统计视频文件失败: {e}")
+ return count
+
+ def prepare_batch_files(self, folder_path, config):
+ """准备批量上传的文件列表（与main.py中的action1方法逻辑一致）"""
+ file_paths = []
+ if not config:
+ logger.error("配置为空，无法准备批量上传文件")
+ return file_paths
+ index = str(config.get('序号', '')).strip()
+ if not index:
+ logger.warning("序号为空，无法准备批量上传文件")
+ return file_paths
+ if not folder_path or not os.path.exists(folder_path):
+ logger.error(f"文件夹路径无效或不存在: {folder_path}")
+ return file_paths
+ if not os.access(folder_path, os.R_OK):
+ logger.error(f"没有权限读取文件夹: {folder_path}")
+ return file_paths
+
+ logger.info("=" * 50)
+ logger.info("开始准备批量上传文件列表...")
+ logger.info(f"文件夹路径: {folder_path}")
+ logger.info(f"查找序号: {index}")
+
+ try:
+ try:
+ all_items = os.listdir(folder_path)
+ subdirs = [f for f in all_items if os.path.isdir(os.path.join(folder_path, f))]
+ except PermissionError:
+ logger.error(f"没有权限访问文件夹: {folder_path}")
+ return file_paths
+ except Exception as e:
+ logger.error(f"读取文件夹失败: {e}")
+ return file_paths
+
+ logger.info(f"在最外层文件夹下找到 {len(subdirs)} 个子文件夹（多多ID文件夹）")
+
+ for subdir_name in subdirs:
+ file_path = os.path.join(folder_path, subdir_name)
+ logger.info(f" 正在扫描子文件夹: {subdir_name}")
+ if not os.path.isdir(file_path):
+ logger.info(f" 跳过（不是文件夹）")
+ continue
+ files = os.listdir(file_path)
+ logger.info(f" 该文件夹下有 {len(files)} 个项目")
+
+ for file_name in files:
+ logger.info(f" 检查项目: {file_name}")
+ if ".mp4" in file_name:
+ logger.info(f" ✓ 是视频文件（包含.mp4）")
+ file_names = file_name.split("-")
+ logger.info(f" 文件名分割结果: {file_names}")
+
+ if len(file_names) > 0 and file_names[0] == str(index):
+ logger.info(f" ✓ 序号匹配！序号: {file_names[0]}, 目标序号: {index}")
+ path = Path(os.path.join(file_path, file_name))
+
+ if path.is_file():
+ logger.info(f" ✓ 是文件，添加到列表: {path.name}")
+ file_paths.append({
+ "url": config.get('达人链接', ''),
+ "user_id": config.get('多多id', ''),
+ "time_start": config.get('定时发布', '') if config.get('定时发布') else None,
+ "ht": config.get('话题', ''),
+ "index": str(index),
+ "path": path
+ })
+ logger.info(f" 当前视频总数: {len(file_paths)}")
+ else:
+ logger.info(f" 是文件夹，扫描其中的文件...")
+ try:
+ sub_files = os.listdir(path)
+ logger.info(f" 文件夹中有 {len(sub_files)} 个文件")
+ for sub_file in sub_files:
+ sub_path = Path(os.path.join(path, sub_file))
+ if sub_path.is_file():
+ logger.info(f" ✓ 添加文件: {sub_file}")
+ file_paths.append({
+ "url": config.get('达人链接', ''),
+ "user_id": config.get('多多id', ''),
+ "time_start": config.get('定时发布', '') if config.get('定时发布') else None,
+ "ht": config.get('话题', ''),
+ "index": str(index),
+ "path": sub_path
+ })
+ logger.info(f" 当前视频总数: {len(file_paths)}")
+ except Exception as e:
+ logger.error(f" 扫描子文件夹失败: {e}")
+ else:
+ if len(file_names) > 0:
+ logger.info(f" ✗ 序号不匹配: {file_names[0]} != {index}")
+ else:
+ logger.info(f" ✗ 文件名格式不正确，无法提取序号")
+ else:
+ logger.info(f" ✗ 不是视频文件（不包含.mp4），跳过")
+ except Exception as e:
+ logger.error(f"准备批量文件失败: {e}")
+ import traceback
+ traceback.print_exc()
+
+ logger.info("=" * 50)
+ logger.info(f"文件收集完成！共找到 {len(file_paths)} 个视频文件")
+ if file_paths:
+ logger.info("视频文件列表:")
+ for idx, video_info in enumerate(file_paths, 1):
+ logger.info(f" {idx}. {video_info['path'].name} ({video_info['path']})")
+ return file_paths
+
+ def stop(self):
+ """停止执行"""
+ self.is_running = False
+
+ def requestInterruption(self):
+ """请求中断线程（重写QThread方法）"""
+ super().requestInterruption()
+ self.is_running = False
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diff --git a/user/user_data/BrowserMetrics/BrowserMetrics-69779642-8EF8.pma b/user/user_data/BrowserMetrics/BrowserMetrics-697CC4B6-2F80.pma
similarity index 83%
rename from user/user_data/BrowserMetrics/BrowserMetrics-69779642-8EF8.pma
rename to user/user_data/BrowserMetrics/BrowserMetrics-697CC4B6-2F80.pma
index 6825839..d08bb39 100644
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diff --git a/user/user_data/CrashpadMetrics-active.pma b/user/user_data/CrashpadMetrics-active.pma
index a8bcdc4..7c1abb0 100644
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diff --git a/user/user_data/Default/BrowsingTopicsState b/user/user_data/Default/BrowsingTopicsState
index a63fb53..ea27ec5 100644
--- a/user/user_data/Default/BrowsingTopicsState
+++ b/user/user_data/Default/BrowsingTopicsState
@@ -13,7 +13,14 @@
"padded_top_topics_start_index": 0,
"taxonomy_version": 0,
"top_topics_and_observing_domains": [ ]
+ }, {
+ "calculation_time": "13414257993246306",
+ "config_version": 0,
+ "model_version": "0",
+ "padded_top_topics_start_index": 0,
+ "taxonomy_version": 0,
+ "top_topics_and_observing_domains": [ ]
} ],
"hex_encoded_hmac_key": "434BF7DBD7DA573B45E0A11AD9045A61B6221D14AE2F9A341E2FEF659AF071F6",
- "next_scheduled_calculation_time": "13414055093389664"
+ "next_scheduled_calculation_time": "13414862793246352"
}
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diff --git a/user/user_data/Default/DIPS b/user/user_data/Default/DIPS
index 785cf6a..7d35107 100644
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diff --git a/user/user_data/Default/DawnGraphiteCache/data_1 b/user/user_data/Default/DawnGraphiteCache/data_1
index 3356aaa..74a807b 100644
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diff --git a/user/user_data/Default/DawnWebGPUCache/data_1 b/user/user_data/Default/DawnWebGPUCache/data_1
index 29b1df9..b44de73 100644
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diff --git a/user/user_data/Default/Favicons b/user/user_data/Default/Favicons
index e3f5c59..5176dde 100644
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diff --git a/user/user_data/Default/File System/Origins/LOG b/user/user_data/Default/File System/Origins/LOG
index 6604f80..35412dc 100644
--- a/user/user_data/Default/File System/Origins/LOG
+++ b/user/user_data/Default/File System/Origins/LOG
@@ -1,3 +1,3 @@
-2026/01/27-00:28:51.452 37b0 Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\File System\Origins/MANIFEST-000001
-2026/01/27-00:28:51.452 37b0 Recovering log #6
-2026/01/27-00:28:51.452 37b0 Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\File System\Origins/000006.log
+2026/01/30-22:48:23.361 4e48 Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\File System\Origins/MANIFEST-000001
+2026/01/30-22:48:23.361 4e48 Recovering log #6
+2026/01/30-22:48:23.362 4e48 Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\File System\Origins/000006.log
diff --git a/user/user_data/Default/File System/Origins/LOG.old b/user/user_data/Default/File System/Origins/LOG.old
index 7eff1f8..72b947c 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 @@
-2026/01/27-00:28:49.803 7ddc Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\File System\Origins/MANIFEST-000001
-2026/01/27-00:28:49.804 7ddc Recovering log #6
-2026/01/27-00:28:49.804 7ddc Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\File System\Origins/000006.log
+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
diff --git a/user/user_data/Default/GCM Store/LOG b/user/user_data/Default/GCM Store/LOG
index 31f631d..9a54e38 100644
--- a/user/user_data/Default/GCM Store/LOG
+++ b/user/user_data/Default/GCM Store/LOG
@@ -1,3 +1,3 @@
-2026/01/27-00:27:47.374 12ac Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\GCM Store/MANIFEST-000001
-2026/01/27-00:27:47.374 12ac Recovering log #3
-2026/01/27-00:27:47.398 12ac Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\GCM Store/000003.log
+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
diff --git a/user/user_data/Default/GCM Store/LOG.old b/user/user_data/Default/GCM Store/LOG.old
index 7779e8e..b084370 100644
--- a/user/user_data/Default/GCM Store/LOG.old
+++ b/user/user_data/Default/GCM Store/LOG.old
@@ -1,3 +1,3 @@
-2026/01/27-00:15:07.342 9b40 Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\GCM Store/MANIFEST-000001
-2026/01/27-00:15:07.342 9b40 Recovering log #3
-2026/01/27-00:15:07.377 9b40 Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\GCM Store/000003.log
+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
diff --git a/user/user_data/Default/GPUCache/data_0 b/user/user_data/Default/GPUCache/data_0
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index 1b36309..edbb8ed 100644
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index 3fe8d5b..97e8984 100644
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diff --git a/user/user_data/Default/History b/user/user_data/Default/History
index e53b15f..69e8545 100644
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diff --git a/user/user_data/Default/Local Storage/leveldb/000011.log b/user/user_data/Default/Local Storage/leveldb/000011.log
index b85a578..4d0d8ee 100644
Binary files a/user/user_data/Default/Local Storage/leveldb/000011.log and b/user/user_data/Default/Local Storage/leveldb/000011.log differ
diff --git a/user/user_data/Default/Local Storage/leveldb/LOG b/user/user_data/Default/Local Storage/leveldb/LOG
index 698d340..0713f30 100644
--- a/user/user_data/Default/Local Storage/leveldb/LOG
+++ b/user/user_data/Default/Local Storage/leveldb/LOG
@@ -1,3 +1,3 @@
-2026/01/27-00:28:50.976 17f4 Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\Local Storage\leveldb/MANIFEST-000001
-2026/01/27-00:28:50.979 17f4 Recovering log #11
-2026/01/27-00:28:50.982 17f4 Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\Local Storage\leveldb/000011.log
+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
diff --git a/user/user_data/Default/Local Storage/leveldb/LOG.old b/user/user_data/Default/Local Storage/leveldb/LOG.old
index 241dac0..444645b 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 @@
-2026/01/27-00:28:49.356 42fc Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\Local Storage\leveldb/MANIFEST-000001
-2026/01/27-00:28:49.359 42fc Recovering log #11
-2026/01/27-00:28:49.362 42fc Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\Local Storage\leveldb/000011.log
+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
diff --git a/user/user_data/Default/Network Action Predictor b/user/user_data/Default/Network Action Predictor
index 1350ab3..d3db51b 100644
Binary files a/user/user_data/Default/Network Action Predictor and b/user/user_data/Default/Network Action Predictor differ
diff --git a/user/user_data/Default/Network/Cookies b/user/user_data/Default/Network/Cookies
index 582e8ab..4382ac6 100644
Binary files a/user/user_data/Default/Network/Cookies and b/user/user_data/Default/Network/Cookies differ
diff --git a/user/user_data/Default/Network/Network Persistent State b/user/user_data/Default/Network/Network Persistent State
index 86a72e5..0ff04f5 100644
--- a/user/user_data/Default/Network/Network Persistent State
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diff --git a/user/user_data/Default/Preferences b/user/user_data/Default/Preferences
index 60e65b5..c331d50 100644
--- a/user/user_data/Default/Preferences
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Binary files /dev/null and b/user/user_data/Default/Service Worker/CacheStorage/987935aee542b816248034eca833fe60a4d902b0/a43f1e9f-240e-4972-857c-1e091121eae4/9947208164d0f2f0_0 differ
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diff --git a/user/user_data/Default/Service Worker/CacheStorage/987935aee542b816248034eca833fe60a4d902b0/a43f1e9f-240e-4972-857c-1e091121eae4/caf4bb6cc4138264_0 b/user/user_data/Default/Service Worker/CacheStorage/987935aee542b816248034eca833fe60a4d902b0/a43f1e9f-240e-4972-857c-1e091121eae4/caf4bb6cc4138264_0
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diff --git a/user/user_data/Default/Service Worker/CacheStorage/987935aee542b816248034eca833fe60a4d902b0/a43f1e9f-240e-4972-857c-1e091121eae4/index-dir/the-real-index b/user/user_data/Default/Service Worker/CacheStorage/987935aee542b816248034eca833fe60a4d902b0/a43f1e9f-240e-4972-857c-1e091121eae4/index-dir/the-real-index
index 3bb2353..b598db4 100644
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diff --git a/user/user_data/Default/Service Worker/CacheStorage/987935aee542b816248034eca833fe60a4d902b0/index.txt b/user/user_data/Default/Service Worker/CacheStorage/987935aee542b816248034eca833fe60a4d902b0/index.txt
index 00d63a7..88290a9 100644
Binary files a/user/user_data/Default/Service Worker/CacheStorage/987935aee542b816248034eca833fe60a4d902b0/index.txt and b/user/user_data/Default/Service Worker/CacheStorage/987935aee542b816248034eca833fe60a4d902b0/index.txt differ
diff --git a/user/user_data/Default/Service Worker/Database/000003.log b/user/user_data/Default/Service Worker/Database/000003.log
index ea40c82..e7aa2ca 100644
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diff --git a/user/user_data/Default/Service Worker/Database/LOG b/user/user_data/Default/Service Worker/Database/LOG
index 13e8425..9349f65 100644
--- a/user/user_data/Default/Service Worker/Database/LOG
+++ b/user/user_data/Default/Service Worker/Database/LOG
@@ -1,3 +1,3 @@
-2026/01/27-00:28:50.902 928c Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\Service Worker\Database/MANIFEST-000001
-2026/01/27-00:28:50.903 928c Recovering log #3
-2026/01/27-00:28:50.904 928c Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\Service Worker\Database/000003.log
+2026/01/30-22:48:22.344 7d20 Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\Service Worker\Database/MANIFEST-000001
+2026/01/30-22:48:22.345 7d20 Recovering log #3
+2026/01/30-22:48:22.345 7d20 Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\Service Worker\Database/000003.log
diff --git a/user/user_data/Default/Service Worker/Database/LOG.old b/user/user_data/Default/Service Worker/Database/LOG.old
index c1eeda9..ee23549 100644
--- a/user/user_data/Default/Service Worker/Database/LOG.old
+++ b/user/user_data/Default/Service Worker/Database/LOG.old
@@ -1,3 +1,3 @@
-2026/01/27-00:28:49.276 6cc Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\Service Worker\Database/MANIFEST-000001
-2026/01/27-00:28:49.277 6cc Recovering log #3
-2026/01/27-00:28:49.278 6cc Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\Service Worker\Database/000003.log
+2026/01/30-22:46:21.502 e18 Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\Service Worker\Database/MANIFEST-000001
+2026/01/30-22:46:21.503 e18 Recovering log #3
+2026/01/30-22:46:21.505 e18 Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\Service Worker\Database/000003.log
diff --git a/user/user_data/Default/Service Worker/ScriptCache/653e56b4b6556a9e_0 b/user/user_data/Default/Service Worker/ScriptCache/f13a76bbf6c7f0b3_0
similarity index 95%
rename from user/user_data/Default/Service Worker/ScriptCache/653e56b4b6556a9e_0
rename to user/user_data/Default/Service Worker/ScriptCache/f13a76bbf6c7f0b3_0
index 3e1369b..216e587 100644
Binary files a/user/user_data/Default/Service Worker/ScriptCache/653e56b4b6556a9e_0 and b/user/user_data/Default/Service Worker/ScriptCache/f13a76bbf6c7f0b3_0 differ
diff --git a/user/user_data/Default/Service Worker/ScriptCache/653e56b4b6556a9e_1 b/user/user_data/Default/Service Worker/ScriptCache/f13a76bbf6c7f0b3_1
similarity index 94%
rename from user/user_data/Default/Service Worker/ScriptCache/653e56b4b6556a9e_1
rename to user/user_data/Default/Service Worker/ScriptCache/f13a76bbf6c7f0b3_1
index 9cfc53c..00fc5d9 100644
Binary files a/user/user_data/Default/Service Worker/ScriptCache/653e56b4b6556a9e_1 and b/user/user_data/Default/Service Worker/ScriptCache/f13a76bbf6c7f0b3_1 differ
diff --git a/user/user_data/Default/Service Worker/ScriptCache/index-dir/the-real-index b/user/user_data/Default/Service Worker/ScriptCache/index-dir/the-real-index
index 193db1a..db44ad9 100644
Binary files a/user/user_data/Default/Service Worker/ScriptCache/index-dir/the-real-index and b/user/user_data/Default/Service Worker/ScriptCache/index-dir/the-real-index differ
diff --git a/user/user_data/Default/Session Storage/000033.log b/user/user_data/Default/Session Storage/000033.log
index 8b66452..6218ce9 100644
Binary files a/user/user_data/Default/Session Storage/000033.log and b/user/user_data/Default/Session Storage/000033.log differ
diff --git a/user/user_data/Default/Session Storage/LOG b/user/user_data/Default/Session Storage/LOG
index 98c4f41..0bd0277 100644
--- a/user/user_data/Default/Session Storage/LOG
+++ b/user/user_data/Default/Session Storage/LOG
@@ -1,3 +1,3 @@
-2026/01/27-00:28:51.065 17f4 Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\Session Storage/MANIFEST-000001
-2026/01/27-00:28:51.066 17f4 Recovering log #33
-2026/01/27-00:28:51.069 17f4 Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\Session Storage/000033.log
+2026/01/30-22:48:22.495 2eb0 Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\Session Storage/MANIFEST-000001
+2026/01/30-22:48:22.496 2eb0 Recovering log #33
+2026/01/30-22:48:22.499 2eb0 Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\Session Storage/000033.log
diff --git a/user/user_data/Default/Session Storage/LOG.old b/user/user_data/Default/Session Storage/LOG.old
index 3918ddb..670e1cb 100644
--- a/user/user_data/Default/Session Storage/LOG.old
+++ b/user/user_data/Default/Session Storage/LOG.old
@@ -1,3 +1,3 @@
-2026/01/27-00:28:49.444 42fc Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\Session Storage/MANIFEST-000001
-2026/01/27-00:28:49.446 42fc Recovering log #33
-2026/01/27-00:28:49.449 42fc Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\Session Storage/000033.log
+2026/01/30-22:46:21.683 5448 Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\Session Storage/MANIFEST-000001
+2026/01/30-22:46:21.684 5448 Recovering log #33
+2026/01/30-22:46:21.688 5448 Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\Session Storage/000033.log
diff --git a/user/user_data/Default/Sessions/Tabs_13413918533568702 b/user/user_data/Default/Sessions/Tabs_13414257984198305
similarity index 82%
rename from user/user_data/Default/Sessions/Tabs_13413918533568702
rename to user/user_data/Default/Sessions/Tabs_13414257984198305
index b8e0236..193792e 100644
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diff --git a/user/user_data/Default/Sessions/Tabs_13413918530255076 b/user/user_data/Default/Sessions/Tabs_13414258104998859
similarity index 76%
rename from user/user_data/Default/Sessions/Tabs_13413918530255076
rename to user/user_data/Default/Sessions/Tabs_13414258104998859
index 87e4e0f..514019e 100644
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diff --git a/user/user_data/Default/Site Characteristics Database/000006.log b/user/user_data/Default/Site Characteristics Database/000006.log
index 590c374..853ec9d 100644
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diff --git a/user/user_data/Default/Site Characteristics Database/LOG b/user/user_data/Default/Site Characteristics Database/LOG
index 900d153..1c31f4e 100644
--- a/user/user_data/Default/Site Characteristics Database/LOG
+++ b/user/user_data/Default/Site Characteristics Database/LOG
@@ -1,3 +1,3 @@
-2026/01/27-00:28:50.908 5598 Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\Site Characteristics Database/MANIFEST-000001
-2026/01/27-00:28:50.908 5598 Recovering log #6
-2026/01/27-00:28:50.909 5598 Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\Site Characteristics Database/000006.log
+2026/01/30-22:48:22.352 83cc Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\Site Characteristics Database/MANIFEST-000001
+2026/01/30-22:48:22.352 83cc Recovering log #6
+2026/01/30-22:48:22.353 83cc Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\Site Characteristics Database/000006.log
diff --git a/user/user_data/Default/Site Characteristics Database/LOG.old b/user/user_data/Default/Site Characteristics Database/LOG.old
index ad26e33..d2bf5cf 100644
--- a/user/user_data/Default/Site Characteristics Database/LOG.old
+++ b/user/user_data/Default/Site Characteristics Database/LOG.old
@@ -1,3 +1,3 @@
-2026/01/27-00:28:49.280 2604 Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\Site Characteristics Database/MANIFEST-000001
-2026/01/27-00:28:49.281 2604 Recovering log #6
-2026/01/27-00:28:49.281 2604 Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\Site Characteristics Database/000006.log
+2026/01/30-22:46:21.510 23b0 Reusing MANIFEST C:\Users\27942\Desktop\haha\user\user_data\Default\Site Characteristics Database/MANIFEST-000001
+2026/01/30-22:46:21.512 23b0 Recovering log #6
+2026/01/30-22:46:21.513 23b0 Reusing old log C:\Users\27942\Desktop\haha\user\user_data\Default\Site Characteristics Database/000006.log
diff --git a/user/user_data/Default/Web Data b/user/user_data/Default/Web Data
index 0c9f599..76ca59b 100644
Binary files a/user/user_data/Default/Web Data and b/user/user_data/Default/Web Data differ
diff --git a/user/user_data/Default/WebStorage/QuotaManager b/user/user_data/Default/WebStorage/QuotaManager
index 6f49f6a..67322fc 100644
Binary files a/user/user_data/Default/WebStorage/QuotaManager and b/user/user_data/Default/WebStorage/QuotaManager differ
diff --git a/user/user_data/GrShaderCache/data_0 b/user/user_data/GrShaderCache/data_0
index 4db6cc6..f09c8eb 100644
Binary files a/user/user_data/GrShaderCache/data_0 and b/user/user_data/GrShaderCache/data_0 differ
diff --git a/user/user_data/GrShaderCache/data_1 b/user/user_data/GrShaderCache/data_1
index edfaa62..b03afcb 100644
Binary files a/user/user_data/GrShaderCache/data_1 and b/user/user_data/GrShaderCache/data_1 differ
diff --git a/user/user_data/GrShaderCache/data_3 b/user/user_data/GrShaderCache/data_3
index 06a66f2..6279a6b 100644
Binary files a/user/user_data/GrShaderCache/data_3 and b/user/user_data/GrShaderCache/data_3 differ
diff --git a/user/user_data/GrShaderCache/f_000022 b/user/user_data/GrShaderCache/f_000022
new file mode 100644
index 0000000..605fa09
Binary files /dev/null and b/user/user_data/GrShaderCache/f_000022 differ
diff --git a/user/user_data/GrShaderCache/f_000023 b/user/user_data/GrShaderCache/f_000023
new file mode 100644
index 0000000..c84037c
Binary files /dev/null and b/user/user_data/GrShaderCache/f_000023 differ
diff --git a/user/user_data/GrShaderCache/f_000024 b/user/user_data/GrShaderCache/f_000024
new file mode 100644
index 0000000..1d14c76
Binary files /dev/null and b/user/user_data/GrShaderCache/f_000024 differ
diff --git a/user/user_data/GrShaderCache/f_000025 b/user/user_data/GrShaderCache/f_000025
new file mode 100644
index 0000000..2e85696
Binary files /dev/null and b/user/user_data/GrShaderCache/f_000025 differ
diff --git a/user/user_data/GrShaderCache/f_000026 b/user/user_data/GrShaderCache/f_000026
new file mode 100644
index 0000000..800155a
Binary files /dev/null and b/user/user_data/GrShaderCache/f_000026 differ
diff --git a/user/user_data/GrShaderCache/f_000027 b/user/user_data/GrShaderCache/f_000027
new file mode 100644
index 0000000..5d42e6e
Binary files /dev/null and b/user/user_data/GrShaderCache/f_000027 differ
diff --git a/user/user_data/GrShaderCache/f_000028 b/user/user_data/GrShaderCache/f_000028
new file mode 100644
index 0000000..27d9828
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diff --git a/user/user_data/GrShaderCache/f_000029 b/user/user_data/GrShaderCache/f_000029
new file mode 100644
index 0000000..ef5c2b1
Binary files /dev/null and b/user/user_data/GrShaderCache/f_000029 differ
diff --git a/user/user_data/GrShaderCache/f_00002a b/user/user_data/GrShaderCache/f_00002a
new file mode 100644
index 0000000..ff42e0c
Binary files /dev/null and b/user/user_data/GrShaderCache/f_00002a differ
diff --git a/user/user_data/GrShaderCache/f_00002b b/user/user_data/GrShaderCache/f_00002b
new file mode 100644
index 0000000..4bb5cfd
Binary files /dev/null and b/user/user_data/GrShaderCache/f_00002b differ
diff --git a/user/user_data/GrShaderCache/f_00002c b/user/user_data/GrShaderCache/f_00002c
new file mode 100644
index 0000000..5c9d69b
Binary files /dev/null and b/user/user_data/GrShaderCache/f_00002c differ
diff --git a/user/user_data/GrShaderCache/f_00002d b/user/user_data/GrShaderCache/f_00002d
new file mode 100644
index 0000000..a89548a
Binary files /dev/null and b/user/user_data/GrShaderCache/f_00002d differ
diff --git a/user/user_data/GrShaderCache/f_00002e b/user/user_data/GrShaderCache/f_00002e
new file mode 100644
index 0000000..79cabd8
Binary files /dev/null and b/user/user_data/GrShaderCache/f_00002e differ
diff --git a/user/user_data/GrShaderCache/f_00002f b/user/user_data/GrShaderCache/f_00002f
new file mode 100644
index 0000000..398c61a
Binary files /dev/null and b/user/user_data/GrShaderCache/f_00002f differ
diff --git a/user/user_data/GrShaderCache/f_000030 b/user/user_data/GrShaderCache/f_000030
new file mode 100644
index 0000000..fdc8437
Binary files /dev/null and b/user/user_data/GrShaderCache/f_000030 differ
diff --git a/user/user_data/GrShaderCache/f_000031 b/user/user_data/GrShaderCache/f_000031
new file mode 100644
index 0000000..1b61b37
Binary files /dev/null and b/user/user_data/GrShaderCache/f_000031 differ
diff --git a/user/user_data/GrShaderCache/f_000032 b/user/user_data/GrShaderCache/f_000032
new file mode 100644
index 0000000..04dc042
Binary files /dev/null and b/user/user_data/GrShaderCache/f_000032 differ
diff --git a/user/user_data/GrShaderCache/f_000033 b/user/user_data/GrShaderCache/f_000033
new file mode 100644
index 0000000..e65b50d
Binary files /dev/null and b/user/user_data/GrShaderCache/f_000033 differ
diff --git a/user/user_data/GrShaderCache/f_000034 b/user/user_data/GrShaderCache/f_000034
new file mode 100644
index 0000000..e9da66a
Binary files /dev/null and b/user/user_data/GrShaderCache/f_000034 differ
diff --git a/user/user_data/GraphiteDawnCache/data_1 b/user/user_data/GraphiteDawnCache/data_1
index 7d7a124..5277cb8 100644
Binary files a/user/user_data/GraphiteDawnCache/data_1 and b/user/user_data/GraphiteDawnCache/data_1 differ
diff --git a/user/user_data/Last Version b/user/user_data/Last Version
index cf29a91..6c77d08 100644
--- a/user/user_data/Last Version
+++ b/user/user_data/Last Version
@@ -1 +1 @@
-144.0.7559.97
\ No newline at end of file
+144.0.7559.110
\ No newline at end of file
diff --git a/user/user_data/Local State b/user/user_data/Local State
index 2ef1254..04008d8 100644
--- a/user/user_data/Local State
+++ b/user/user_data/Local State
@@ -1 +1 @@
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","variations_safe_seed_date":"13413918529000000","variations_safe_seed_fetch_time":"13413918531390449","variations_safe_seed_locale":"zh-CN","variations_safe_seed_milestone":144,"variations_safe_seed_permanent_consistency_country":"us","variations_safe_seed_session_consistency_country":"cn","variations_safe_seed_signature":"MEYCIQCfivSvAYiDVJ3/O3i4tRgewxm0XwuALaZtzktQsaIeDgIhAO5yC6mDWaL0kcOHlwnairR8fIoqrb/CTSh9pR4CaB5f","variations_seed_date":"13413918530000000","variations_seed_milestone":144,"variations_seed_serial_number":"SMChYyMDI2MDEyNi0wMTAwMjAuNzYwMDAwEgkIABADGJABIAA=#0jdOGaLszeI=","variations_seed_signature":"MEYCIQCfivSvAYiDVJ3/O3i4tRgewxm0XwuALaZtzktQsaIeDgIhAO5yC6mDWaL0k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","hash":"tA+TGTqmOnqzcuikk/ZeDDQ6JWc=","signature":"mLVIYMbhgAF9GYIYnF9Tdo91enWMgEinbHXEQHp5PGg=","timestamp":"1769784565"},{"data":"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","variations_safe_seed_date":"13414257982000000","variations_safe_seed_fetch_time":"13414258102846685","variations_safe_seed_locale":"zh-CN","variations_safe_seed_milestone":144,"variations_safe_seed_permanent_consistency_country":"cn","variations_safe_seed_session_consistency_country":"cn","variations_safe_seed_signature":"MEUCIEuo+BGI0YtxjD6BXJ3W+Bg/cN/E4tMMlH2XTbJC/9ykAiEA4+5TY0WfpFoHdTIobDCMkZ1P7VutPL2W+IcVnZu15h0=","variations_seed_date":"13414258103000000","variations_seed_milestone":144,"variations_seed_serial_number":"SMChYyMDI2MDEzMC0wMTAwMTEuMzU0MDAwEgkIABADGJABIAA=#9Xgb/RrQCHA=","variations_seed_signature":"MEUCIEuo+BGI0YtxjD6BXJ3W+Bg/cN/E4tMMlH2XTbJC/9ykAiEA4+5TY0WfpFoHdTIobDCMkZ1P7VutPL2W+IcVnZu15h0=","variations_sticky_studies":"RollBackModeB/EnabledLaunch","was":{"restarted":false}}
\ No newline at end of file
diff --git a/user/user_data/ShaderCache/data_1 b/user/user_data/ShaderCache/data_1
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diff --git a/user/user_data/first_party_sets.db b/user/user_data/first_party_sets.db
index 5004ce5..154a4a0 100644
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diff --git a/user/user_data/segmentation_platform/ukm_db b/user/user_data/segmentation_platform/ukm_db
index 1e316de..8eefacc 100644
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