{"library":"gin-config","type":"library","category":null,"description":"Gin provides a lightweight configuration framework for Python, based on dependency injection. Functions or classes can be decorated with @gin.configurable, allowing default parameter values to be supplied from a config file (or passed via the command line) using a simple but powerful syntax. This removes the need to define and maintain configuration objects or write boilerplate parameter plumbing and factory code, while often dramatically expanding a project's flexibility and configurability. It is particularly well suited for machine learning experiments. It is currently at version 0.5.0 and is actively maintained by Google.","language":"python","status":"active","version":"0.5.0","tags":["configuration","dependency injection","machine learning","experiment management"],"last_verified":"Sat May 23","install":[{"cmd":"pip install gin-config","imports":["import gin","@gin.configurable","@gin.register","gin.parse_config_file('config.gin')","gin.parse_config_files_and_bindings(gin_files, gin_params)","gin.query_parameter('my_function.param_name')","def my_function(param=gin.REQUIRED):","config_string = gin.operative_config_str()"]}],"homepage":null,"github":"https://github.com/google/gin-config","docs":"https://github.com/google/gin-config/docs","changelog":null,"pypi":"https://pypi.org/project/gin-config/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":100,"avg_install_s":1.6,"avg_import_s":0.07,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/gin-config/compatibility"}}