pixi-to-conda-lock 🔄🔒

pixi-to-conda-lock is a Python utility designed to bridge the gap between the lightning-fast pixi lock and the traditionally slow generation of conda-lock files. By converting your fast-generated pixi.lock file into a fully functional conda-lock.yml, you can enjoy rapid lock file creation without sacrificing the reproducibility of your conda environments. 🚀

[ToC] 📚

• 🌟 Features
• 📚 Usage
• 🛠️ Installation
• 💡 Examples
  • Basic Conversion
  • Converting a Specific Environment
  • Specifying an Output Directory
  • Enable Verbose Logging
• 📄 How It Works
• ❤️ Support and Contributions

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🌟 Features

• Speed Boost: Generate a conda-lock.yml file quickly by leveraging the performance of pixi lock.
• Accurate Conversion: Uses repodata to extract detailed package metadata from your pixi.lock file.
• Multi-Environment Support: Convert all environments in your pixi.lock file or select specific ones.
• Multi-Manager Support: Handles both conda and PyPI packages, ensuring comprehensive environment reproduction.
• Fully Tested: Comprehensive tests ensure robust and reliable behavior.
• Typed & Readable: Written in Python with full type annotations for clarity and maintainability.

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📚 Usage

Transform your fast-generated pixi.lock file into reproducible conda lock files with a single command:

pixi-to-conda-lock --help

This will display the help message:

usage: pixi-to-conda-lock [-h] [--output OUTPUT] [--environment ENVIRONMENT]
                          [--verbose]
                          pixi_lock

Convert pixi.lock to conda-lock.yml

positional arguments:
  pixi_lock             Path to pixi.lock file

options:
  -h, --help            show this help message and exit
  --output, -o OUTPUT   Output directory for conda-lock files (default:
                        current directory)
  --environment, -e ENVIRONMENT
                        Specific environment to convert (default: convert all
                        environments)
  --verbose, -v         Enable verbose logging

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🛠️ Installation

Install pixi-to-conda-lock via PyPI:

pip install pixi-to-conda-lock

Or clone the repository and install locally:

git clone https://github.com/basnijholt/pixi-to-conda-lock.git
cd pixi-to-conda-lock
pip install .

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💡 Examples

Basic Conversion

Convert all environments in your pixi.lock file to conda-lock files:

pixi-to-conda-lock /path/to/pixi.lock

This will generate:

• conda-lock.yml for the default environment
• <env_name>.conda-lock.yml for each additional environment

Converting a Specific Environment

Convert only a specific environment from your pixi.lock file:

pixi-to-conda-lock /path/to/pixi.lock --environment dev

This will generate only dev.conda-lock.yml (or conda-lock.yml if the environment is "default").

Specifying an Output Directory

Save the generated conda-lock files to a specific directory:

pixi-to-conda-lock /path/to/pixi.lock --output /path/to/output/dir

Enable Verbose Logging

To see detailed logs during the conversion process:

pixi-to-conda-lock /path/to/pixi.lock --verbose

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📄 How It Works

1. Fast pixi.lock Parsing: Reads the fast-generated pixi.lock file, which is created quickly compared to generating a conda lock file directly.
2. Environment Detection: Identifies all environments defined in the pixi.lock file or processes only the specified environment.
3. Repodata Loading: Retrieves detailed package metadata from repodata files (either automatically discovered or from a user-specified directory).
4. Package Processing: Processes both conda and PyPI packages for each environment. For conda packages, if repodata information isn't available, the tool falls back on URL parsing.
5. Generating conda-lock.yml: Combines the gathered information to generate fully reproducible conda-lock files that mirror your original environments.

This approach ensures you get the speed benefits of pixi lock without compromising on the quality and reproducibility of your conda environments.

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❤️ Support and Contributions

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

Happy converting! 🔄🔒