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    "info": {
        "author": "Dustin Wyatt",
        "author_email": "dustin.wyatt@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3.7"
        ],
        "description": "# argupdate\n\nThis package is used for updating values in the args/kwargs destined to\na function. This is particularly useful for decorators that want to\nmodify the values passed into the decorated function.\n\nBy introspecting the function the args/kwargs are destined for, it knows\nthe names of all arguments in your args (and of course your kwargs since\nthat is a dict). Because of this, you are able to provide updated values\nby name of the argument.\n\nBy accepting a special callable, we also provide a way to dynamically\nupdate the value of an argument at runtime.\n\n## simple example\n\n### The function we want to modify a value for\n\n```python\nfrom typing import Optional\n\ndef foo(arg_1: int, arg_2: bool, arg_3: Optional[str] = None) -> None:\n    print(arg_1, arg_2, arg_3)\n```\n\nLet's say for some reason we always want `arg_2` to be `False`, no\nmatter what the caller passes in.\n\n```python\nimport functools\nfrom argupdate import update_parameter_value\nfrom typing import Optional\n\ndef arg_2_always_false(func):\n    # This is the new value for `arg_2`\n    updated_values = {\n        'arg_2': False\n    }\n    @functools.wraps(func)\n    def wrapper(*args, **kwargs):\n        # Here we update the value.\n        updated_args, updated_kwargs = update_parameter_value(func, updated_values, args, kwargs)\n        return func(*updated_args, **updated_kwargs)\n    return wrapper\n\n@arg_2_always_false\ndef foo(arg_1: int, arg_2: bool, arg_3: Optional[str] = None) -> None:\n    print(arg_1, arg_2, arg_3)\n```\n\nAdmittedly, this is a contrived example. You could've just set set the\nsecond parameter in `args` to `False` without using this library. But,\neven in this small, contrived example, you've gained some decoupling by\nusing `argupdate`. As long as the name of the parameter stays the same,\nyou do not have to count on it being the second parameter in the\nargument list.\n\n## more advanced example\nYou can also use a special callable as the new value. This allows you to\nset the new value based upon the signature of the function and other\nargument's values.\n\nHere is an example taken from a real project. This project wrapped\nmultiple other backend libraries. These libraries all had methods that\ntook a `handle` argument as an `int`. Except one. This one library\nrequired the `handle` argument as a string that looked like\n`[HANDLE:0x0000001]`.\n\nInstead of repeating code everywhere checking which type of handle we\nshould pass in, we created a decorator that did it for us.\n\n```python\nimport functools\nimport inspect\nfrom typing import Any, Mapping, Sequence\n\nfrom argupdate import update_parameter_value, ValueUpdater\nfrom utils import stringify_int\n\n\ndef handle_stringifier(func):\n    class update_handle(ValueUpdater):\n        def __call__(self,\n                     original_value: Any,\n                     signature: inspect.Signature,\n                     orig_args: Sequence[Any],\n                     orig_kwargs: Mapping[str, Any]) -> Any:\n            if isinstance(original_value, int):\n                return stringify_int(int)\n\n            return original_value\n\n\n    updated_values = {\n        # update_handle will be used to create the value for the argument\n        # called `handle`\n        'handle': update_handle\n    }\n\n    @functools.wraps(func)\n    def wrapper(*args, **kwargs):\n        updated_args, updated_kwargs = update_parameter_value(func, updated_values, args, kwargs)\n        return func(*updated_args, **updated_kwargs)\n\n    return wrapper\n\n\n@handle_stringifier\ndef weird_handle_taker(handle: int) -> None:\n    ...\n```\n\n\n",
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