Melodic

Melodic is a Python client for fetching artist lyrical discographies. This library provides an asynchronous interface to retrieve complete artist discographies, including album and track metadata including lyrics, with built-in database storage, proxy support, and great error handling.

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Features

• Complete Discography Fetching: Retrieves full discography metadata and lyrics for any given artist.
• Asynchronous Interface: Built with modern async with patterns for efficient, safe I/O operations.
• Database Storage: Optional built-in storage system for organizing artist, album, and track data.
• Proxy Support: Easily pass a list of HTTP or SOCKS proxies to route requests through.
• Robust Error Handling: Comprehensive error handling and logging for reliable operations.
• Modern Development Tools: Includes ruff, mypy, pre-commit, and commitizen for high-quality code.

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Installation

From PyPI (Recommended)

pip install melodic

From Source

You can install melodic by cloning the repository directly or using pre-built wheel files.

Prerequisites: This project requires uv for dependency management.

Option 1: Clone and Build

1. Clone the repository:

   git clone https://github.com/filming/melodic.git
   cd melodic

2. Install the project and its dependencies:

   uv sync

Option 2: Install from Pre-built Wheels

Pre-built wheel files are automatically generated and attached to each GitHub release. You can download and install them directly:

1. Go to the GitHub releases page
2. Download the .whl file from the latest release
3. Install using pip:

   pip install path/to/downloaded/melodic-*.whl
   

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Usage

Here's a basic example of how to use melodic to fetch the discography of an artist:

import asyncio
from melodic import Melodic

async def main():
    async with Melodic(storage_path="lyrics.db") as melodic:
        discography = await melodic.get_discography("Taylor Swift")

if __name__ == "__main__":
    asyncio.run(main())

This script will fetch the entire lyrical discography for Taylor Swift and will return it directly to the calling line in the form of a list of Track objects. It will also store the discography into a lyrics.db SQLite database if storage_path is provided.

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Configuration

Configuration is managed through the Melodic client during initialization.

• storage_path: str | Path | None (Default: None)

  • The file path where the SQLite database will be stored. If None, the database will be created in memory and will not be saved to disk.

• proxies: list[str] | None (Default: None)

  • A list of proxy strings (e.g., ["http://user:pass@host:port"]). If provided, all network requests will be rotated through these proxies.

• max_concurrent_requests: int (Default: 10)

  • The maximum number of concurrent aiohttp requests to make at one time.

• max_retry_attempts: int (Default: 10)

  • The maximum amount of times to retry a failed fetch.

• request_delay: float (Default: 3.5)

  • The cooldown period (in seconds) for a proxy after it has been used. This helps prevent rate-limiting.

• user_agent: str | None (Default: None)

  • A custom User-Agent string for network requests. If None, a default aiohttp User-Agent is used.

• batch_save_size: int (Default: 20)

  • The number of tracks to accumulate in memory before saving them to the database in a single transaction.

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Development

This project uses modern Python development tools:

• uv for dependency management
• ruff for linting and formatting
• mypy for type checking
• pre-commit for git hooks
• commitizen for conventional commits

Setting up for development:

1. Clone the repository:

   git clone https://github.com/filming/melodic.git
   cd melodic

2. Install dependencies (including dev tools):

   uv sync --extra dev

3. Set up pre-commit hooks:

   uv run pre-commit install

4. Start developing!

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Dependencies

All project dependencies are managed via pyproject.toml and use Python 3.10+.

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License

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

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Contributing

Contributions, bug reports, and feature requests are welcome! Please open an issue or submit a pull request on GitHub.