mchart 0.2.1

A unified Python library for fetching music chart data from multiple sources

MChart

一个统一的 Python 音乐排行榜数据获取库，支持从多个来源（Billboard、Spotify 等）获取排行榜数据。

English | 中文

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中文

✨ 特性

• 🎵 多数据源支持 - 统一接口访问多个音乐排行榜平台
• 🔧 灵活配置 - TypedDict 配置系统，支持按需定制
• 📊 双重返回格式 - 支持字典（JSON）和 Pydantic 模型两种返回格式
• 🚀 易于使用 - 简洁的 API 设计，开箱即用
• 🛡️ 类型安全 - 完整的类型提示支持
• ⚡ 可扩展 - 标准化的 Provider 接口，易于添加新数据源

🎯 支持的平台

平台	状态	功能
Billboard	✅ 已实现	最新排行榜、列出排行榜
Spotify	📋 计划中	等待实现
Apple Music	📋 计划中	未来支持
YouTube Music	📋 计划中	未来支持

📦 安装

使用 pip

pip install mchart

使用 uv（推荐）

uv add mchart

可选依赖

为获得更快的 HTML 解析速度，建议安装 lxml：

pip install mchart[lxml]
# 或
uv add mchart[lxml]

🚀 快速开始

基础使用

from mchart import MChart

# 创建客户端
client = MChart()

# 获取 Billboard Hot 100（返回字典）
chart = client.get_chart("billboard", "hot-100")

print(f"排行榜: {chart['metadata']['title']}")
print(f"发布日期: {chart['published_date']}")
print(f"总条目数: {len(chart['entries'])}")

# 显示前 5 名
for entry in chart['entries'][:5]:
    song = entry['song']
    print(f"#{entry['rank']} - {song['title']} by {song['artist']}")

使用 Pydantic 模型

from mchart import MChart

client = MChart()

# 返回 Pydantic 模型，支持类型提示和便捷方法
chart = client.get_chart("billboard", "hot-100", return_type="model")

# 使用模型的便捷方法
print(f"总条目数: {chart.total_entries}")

# 查找特定艺术家
taylor_songs = chart.find_by_artist("Taylor Swift")
for entry in taylor_songs:
    print(f"#{entry.rank} - {entry.song.title}")

# 获取前 10 名
top_10 = chart.get_top(10)

自定义配置

from mchart import MChart

# 配置 Billboard provider
config = {
    "billboard": {
        "timeout": 60,              # 请求超时（秒）
        "max_retries": 5,           # 最大重试次数
        "parser": "html.parser",    # HTML 解析器
        "max_chart_entries": 50,    # 限制返回条目数
    }
}

client = MChart(config)
chart = client.get_chart("billboard", "hot-100")

📚 示例

查看 examples/ 目录获取更多示例：

• fetch_billboard_hot100.py - 获取并保存 Billboard Hot 100
• list_all_charts.py - 列出所有可用排行榜
• compare_charts.py - 比较多个排行榜
• search_artist.py - 搜索特定艺术家

运行示例：

# 使用 uv
uv run python examples/fetch_billboard_hot100.py

# 或使用 python
python examples/fetch_billboard_hot100.py

🎵 支持的排行榜

Billboard

• hot-100 - Billboard Hot 100（美国最热门 100 首歌曲）
• billboard-200 - Billboard 200（最热门 200 张专辑）
• global-200 - Global 200（全球最热门 200 首歌曲）
• artist-100 - Artist 100（最热门 100 位艺术家）
• streaming-songs - Streaming Songs（流媒体最热歌曲）
• radio-songs - Radio Songs（电台最热播放歌曲）
• digital-song-sales - Digital Song Sales（数字单曲销量榜）

📖 文档

完整的 API 文档请查看 docs/API.md

🛠️ 开发

克隆仓库

git clone https://github.com/yourusername/mchart.git
cd mchart

安装开发依赖

# 使用 uv
uv sync --all-extras

# 或使用 pip
pip install -e ".[dev,lxml]"

运行测试

pytest

🤝 贡献

欢迎贡献！请查看 CONTRIBUTING.md 了解详细信息。

特别欢迎以下贡献：

• 新的 provider 实现（Spotify、Apple Music 等）
• Bug 修复和功能增强
• 文档改进
• 测试用例

📄 许可证

本项目采用 MIT 许可证 - 查看 LICENSE 文件了解详情。

🙏 致谢

• Billboard - 排行榜数据源
• BeautifulSoup - HTML 解析
• Pydantic - 数据验证
• Requests - HTTP 库

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English

✨ Features

• 🎵 Multiple Data Sources - Unified interface for accessing multiple music chart platforms
• 🔧 Flexible Configuration - TypedDict-based configuration system with customization support
• 📊 Dual Return Formats - Support for both dict (JSON) and Pydantic model return types
• 🚀 Easy to Use - Clean API design, works out of the box
• 🛡️ Type Safe - Full type hints support
• ⚡ Extensible - Standardized Provider interface for easy addition of new data sources

🎯 Supported Platforms

Platform	Status	Features
Billboard	✅ Implemented	Latest charts, List charts
Spotify	📋 Planned	Coming soon
Apple Music	📋 Planned	Future support
YouTube Music	📋 Planned	Future support

📦 Installation

Using pip

pip install mchart

Using uv (Recommended)

uv add mchart

Optional Dependencies

For faster HTML parsing, install lxml:

pip install mchart[lxml]
# or
uv add mchart[lxml]

🚀 Quick Start

Basic Usage

from mchart import MChart

# Create client
client = MChart()

# Get Billboard Hot 100 (returns dict)
chart = client.get_chart("billboard", "hot-100")

print(f"Chart: {chart['metadata']['title']}")
print(f"Date: {chart['published_date']}")
print(f"Total entries: {len(chart['entries'])}")

# Show top 5
for entry in chart['entries'][:5]:
    song = entry['song']
    print(f"#{entry['rank']} - {song['title']} by {song['artist']}")

Using Pydantic Models

from mchart import MChart

client = MChart()

# Return Pydantic model with type hints and convenient methods
chart = client.get_chart("billboard", "hot-100", return_type="model")

# Use model's convenient methods
print(f"Total entries: {chart.total_entries}")

# Find specific artist
taylor_songs = chart.find_by_artist("Taylor Swift")
for entry in taylor_songs:
    print(f"#{entry.rank} - {entry.song.title}")

# Get top 10
top_10 = chart.get_top(10)

Custom Configuration

from mchart import MChart

# Configure Billboard provider
config = {
    "billboard": {
        "timeout": 60,              # Request timeout (seconds)
        "max_retries": 5,           # Max retry attempts
        "parser": "html.parser",    # HTML parser
        "max_chart_entries": 50,    # Limit returned entries
    }
}

client = MChart(config)
chart = client.get_chart("billboard", "hot-100")

📚 Examples

See the examples/ directory for more examples:

• fetch_billboard_hot100.py - Fetch and save Billboard Hot 100
• list_all_charts.py - List all available charts
• compare_charts.py - Compare multiple charts
• search_artist.py - Search for specific artist

Run examples:

# Using uv
uv run python examples/fetch_billboard_hot100.py

# Or using python
python examples/fetch_billboard_hot100.py

🎵 Supported Charts

Billboard

• hot-100 - Billboard Hot 100 (Top 100 songs in the US)
• billboard-200 - Billboard 200 (Top 200 albums)
• global-200 - Global 200 (Top 200 songs globally)
• artist-100 - Artist 100 (Top 100 artists)
• streaming-songs - Streaming Songs (Most-streamed songs)
• radio-songs - Radio Songs (Most-played on radio)
• digital-song-sales - Digital Song Sales (Best-selling digital songs)

📖 Documentation

For complete API documentation, see docs/API.md

🛠️ Development

Clone Repository

git clone https://github.com/yourusername/mchart.git
cd mchart

Install Development Dependencies

# Using uv
uv sync --all-extras

# Or using pip
pip install -e ".[dev,lxml]"

Run Tests

pytest

🤝 Contributing

Contributions are welcome! Please see CONTRIBUTING.md for details.

We especially welcome:

• New provider implementations (Spotify, Apple Music, etc.)
• Bug fixes and feature enhancements
• Documentation improvements
• Test cases

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Billboard - Chart data source
• BeautifulSoup - HTML parsing
• Pydantic - Data validation
• Requests - HTTP library

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Made with ❤️ for music lovers and developers