venera-parser-bangumi 0.1.1

Parse Venera exports and sync selected favorites to Bangumi.

Venera Parser for Bangumi

A script to parse the data exported from Bangumi's Venera app, which includes users' watching history, ratings, collections, and more. The parsed data can be used for various purposes such as data analysis, visualization, or migration to other platforms.

Quick Start

1. Install from frok

git clone --branch 2026/05/venera-parser-bangumi-sync https://github.com/bGZo/playground.git
cd playground
pipx install . 

2. Install from PyPI

pipx install venera-parser-bangumi

Usage

[!NOTE] Use venera-sync-bangumi replace python3 src/parser.py after installation from PyPI.

❯ venera-sync-bangumi --help
Usage: venera-sync-bangumi [OPTIONS] COMMAND [ARGS]...

  Parse Venera exported archives and sync selected
  favorites to Bangumi.

Options:
  --help  Show this message and exit.

Commands:
  dump
  summary
  sync-bangumi

Parser

# 查看摘要
python3 src/parser.py summary 20575-2273.venera

# 导出完整 JSON
python3 src/parser.py dump 20575-2273.venera --include-rows --pretty -o venera_dump.json

# 连 cookie.db 一起解析
# 在上面的命令后追加 --include-cookie-db

Bangumi Sync

# 安装运行依赖
python3 -m pip install -e .

# dry-run，同步本地 DONE 表到 Bangumi done
export ACCESS_TOKEN="your-token"
python3 src/parser.py sync-bangumi 20575-2273.venera --sync DONE=done --dry-run

# 同步多个表，并输出审计报告
python3 src/parser.py sync-bangumi 20575-2273.venera \
  --sync Doing=doing \
  --sync DONE=done \
  --dry-run \
  --report-output reports/dry-run.json

说明：

1. ACCESS_TOKEN 只从环境变量读取。
2. --dry-run 会执行解析、搜索、匹配和当前收藏读取，但不会发写请求。
3. 当前项目已切换为 click CLI，所有自动验收以 pytest 为准。

Tests

python3 -m pytest

Contributing

Any contributions made are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'feat(module):add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Top contributors:

License

All code is licensed under the AGPL-3.0 license. See LICENSE for more information.