{"categories":[{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/9"},{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/19"}],"enrichment":{"capability":"Provides an `@override` decorator that lets you pass function parameters as a dictionary via a `kwargs` argument, ignoring extra keys and allowing parameter overrides without raising errors.","skillfed_tags":["decorator","parameter-handling"],"use_cases":["Load function parameters from a config file that may contain extra keys you don't need","Overlay multiple parameter dictionaries with explicit overrides (e.g., base config + user overrides)","Accept parameter bundles from external APIs without manually extracting each field","Collect all parameters passed to a function in a single dict for logging or inspection","Simplify function calls when parameters come from a dynamic source with unknown keys"],"what_it_does":"mo-kwargs is a decorator library that brings JavaScript-style object destructuring to Python function parameters. It provides an `@override` decorator that adds a `kwargs` parameter to decorated functions, allowing you to pass a dictionary of parameters that will be unpacked and merged with explicit arguments. Unlike `**kwargs`, this approach ignores extra keys in the dictionary instead of raising a TypeError, and allows explicit parameters to override values from the dictionary.\n\nThe primary use case is handling parameter sets from external sources\u2014configuration files, APIs, or dynamic data structures\u2014where you cannot control whether extra keys are present. The decorator ensures required parameters are still enforced, optional parameters get their defaults, and all parameters (used or not) are available in the `kwargs` dict if the function accepts it. It works with regular Python functions, instance methods, and class methods.","worth_installing":"Yes, if you frequently work with parameter dictionaries from external sources and want to avoid boilerplate extraction or TypeError handling. The low install friction, active maintenance, and lack of security issues make it a safe choice. The MPL 2.0 copyleft license is a minor consideration only if you plan to modify and redistribute the package itself."},"id":"mo-kwargs","links":{"html":"https://skillfed.io/packages/mo-kwargs","md":"https://skillfed.io/packages/mo-kwargs.md","pypi":"https://pypi.org/project/mo-kwargs/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-03-02","license_spdx":null,"license_treatment":"copyleft","name":"mo-kwargs","python_support":"unspecified","summary":"Object destructuring of function parameters for Python!"},"popularity":{"monthly_downloads":118992,"position":12093,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"8.703.26061"}