""" This is a module for defining private helpers which do not depend on the rest of NumPy. Everything in here must be self-contained so that it can be imported anywhere else without creating circular imports. If a utility requires the import of NumPy, it probably belongs in ``numpy._core``. """ import functools import warnings from ._convertions import asunicode, asbytes def set_module(module): """Private decorator for overriding __module__ on a function or class. Example usage:: @set_module('numpy') def example(): pass assert example.__module__ == 'numpy' """ def decorator(func): if module is not None: func.__module__ = module return func return decorator def _rename_parameter(old_names, new_names, dep_version=None): """ Generate decorator for backward-compatible keyword renaming. Apply the decorator generated by `_rename_parameter` to functions with a renamed parameter to maintain backward-compatibility. After decoration, the function behaves as follows: If only the new parameter is passed into the function, behave as usual. If only the old parameter is passed into the function (as a keyword), raise a DeprecationWarning if `dep_version` is provided, and behave as usual otherwise. If both old and new parameters are passed into the function, raise a DeprecationWarning if `dep_version` is provided, and raise the appropriate TypeError (function got multiple values for argument). Parameters ---------- old_names : list of str Old names of parameters new_name : list of str New names of parameters dep_version : str, optional Version of NumPy in which old parameter was deprecated in the format 'X.Y.Z'. If supplied, the deprecation message will indicate that support for the old parameter will be removed in version 'X.Y+2.Z' Notes ----- Untested with functions that accept *args. Probably won't work as written. """ def decorator(fun): @functools.wraps(fun) def wrapper(*args, **kwargs): for old_name, new_name in zip(old_names, new_names): if old_name in kwargs: if dep_version: end_version = dep_version.split('.') end_version[1] = str(int(end_version[1]) + 2) end_version = '.'.join(end_version) msg = (f"Use of keyword argument `{old_name}` is " f"deprecated and replaced by `{new_name}`. " f"Support for `{old_name}` will be removed " f"in NumPy {end_version}.") warnings.warn(msg, DeprecationWarning, stacklevel=2) if new_name in kwargs: msg = (f"{fun.__name__}() got multiple values for " f"argument now known as `{new_name}`") raise TypeError(msg) kwargs[new_name] = kwargs.pop(old_name) return fun(*args, **kwargs) return wrapper return decorator