{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering"}],"enrichment":{"capability":"Confection is a configuration system for Python that parses INI-style `.cfg` files into nested dictionaries, with support for JSON values, cross-section references, and registry-based function instantiation.","skillfed_tags":["configuration-management","machine-learning","registry-pattern"],"use_cases":["Define machine-learning training pipelines with shared hyperparameters across multiple components using cross-section references.","Manage optimizer, model, and data-loader configurations for deep-learning projects without hardcoding parameters.","Build CLI or REST API applications where configuration needs to flow through many intermediate functions without modifying their signatures.","Version function implementations in a registry so improvements can be deployed without breaking existing configuration files.","Parse and validate complex nested object hierarchies from configuration files with automatic type checking against function signatures."],"what_it_does":"Confection solves the problem of managing complex, nested configurations in Python applications\u2014especially machine-learning projects where hyperparameters and component settings need to be exposed without breaking intermediate function interfaces. It parses `.cfg` files using an INI-like format enhanced with JSON-typed values, dot-notation for nested sections, and cross-section variable references using `${section.key}` syntax. The package also integrates with function registries (via decorators) to instantiate configured objects with type validation.\n\nYou define configuration blocks in a `.cfg` file, load them with `Config().from_disk()`, resolve them through a registry, and receive a dictionary of initialized objects or plain settings. The system is designed to let you version functions and change defaults without breaking backward compatibility\u2014a key concern when configuration becomes part of your API surface.","worth_installing":"Yes. Confection is actively maintained, has no known vulnerabilities, and installs with minimal friction. It is well-suited for machine-learning and complex application configuration where you need to avoid tight coupling between configuration and function signatures. The MIT license imposes no restrictions. Install it if you are building systems where configuration complexity and versioning matter; skip it for simple flat-file or environment-variable configuration."},"id":"confection","links":{"html":"https://skillfed.io/packages/confection","md":"https://skillfed.io/packages/confection.md","pypi":"https://pypi.org/project/confection/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-03-24","license_spdx":null,"license_treatment":"permissive","name":"confection","python_support":"supports_current","summary":"The sweetest config system for Python"},"popularity":{"monthly_downloads":20544828,"position":1033,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"1.3.3"}