{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/17"}],"enrichment":{"capability":"Coqpit provides configuration management through Python dataclasses with JSON serialization, type checking, and command-line argument parsing, designed for machine learning projects that need portable, schema-driven configs.","skillfed_tags":["config-management","dataclass-based","ml-workflow"],"use_cases":["Define and validate ML training configs with typed fields, default values, and range constraints for hyperparameter experiments.","Save and load experiment configurations to JSON, then share or version-control them independently of code.","Override config values from the command line during training runs without modifying the source code or config files.","Organize large configs into nested dataclasses for dataset, preprocessing, and model parameters, keeping them maintainable.","Enforce that certain config fields are explicitly set before use, catching missing required values early."],"what_it_does":"Coqpit is a lightweight configuration library built on Python dataclasses that lets you define structured configs with type hints, default values, and validation. It handles serialization to and from JSON, supports nested and inherited configurations, and can parse values from command-line arguments\u2014useful for machine learning workflows where you need to swap parameters without changing code.\n\nThe package intentionally avoids external dependencies, relying only on the standard library's dataclasses module. It's designed for scenarios where you want a schema-driven config file that can be read by other programming languages via JSON, with built-in type checking and the ability to mark fields as mandatory or provide dynamic defaults. The library also supports pretty-printing configs and exporting them to dictionaries for programmatic access.","worth_installing":"Yes, if you need a minimal, dependency-free config system for ML projects and can tolerate dormant maintenance. The package is stable for its current scope\u2014JSON serialization, nested configs, and CLI parsing work as documented. However, do not use it if you require active maintenance, ongoing Python version support, or a clear license statement. Verify the license in the repository before production use."},"id":"coqpit","links":{"html":"https://skillfed.io/packages/coqpit","md":"https://skillfed.io/packages/coqpit.md","pypi":"https://pypi.org/project/coqpit/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2022-12-21","license_spdx":null,"license_treatment":"unclear","name":"coqpit","python_support":"supports_current","summary":"Simple (maybe too simple), light-weight config management through python data-classes."},"popularity":{"monthly_downloads":101226,"position":12952,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.0.17"}