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Code Editor : _globals.py
""" Module defining global singleton classes. This module raises a RuntimeError if an attempt to reload it is made. In that way the identities of the classes defined here are fixed and will remain so even if numpy itself is reloaded. In particular, a function like the following will still work correctly after numpy is reloaded:: def foo(arg=np._NoValue): if arg is np._NoValue: ... That was not the case when the singleton classes were defined in the numpy ``__init__.py`` file. See gh-7844 for a discussion of the reload problem that motivated this module. """ from __future__ import division, absolute_import, print_function __ALL__ = [ 'ModuleDeprecationWarning', 'VisibleDeprecationWarning', '_NoValue' ] # Disallow reloading this module so as to preserve the identities of the # classes defined here. if '_is_loaded' in globals(): raise RuntimeError('Reloading numpy._globals is not allowed') _is_loaded = True class ModuleDeprecationWarning(DeprecationWarning): """Module deprecation warning. The nose tester turns ordinary Deprecation warnings into test failures. That makes it hard to deprecate whole modules, because they get imported by default. So this is a special Deprecation warning that the nose tester will let pass without making tests fail. """ ModuleDeprecationWarning.__module__ = 'numpy' class VisibleDeprecationWarning(UserWarning): """Visible deprecation warning. By default, python will not show deprecation warnings, so this class can be used when a very visible warning is helpful, for example because the usage is most likely a user bug. """ VisibleDeprecationWarning.__module__ = 'numpy' class _NoValueType(object): """Special keyword value. The instance of this class may be used as the default value assigned to a deprecated keyword in order to check if it has been given a user defined value. """ __instance = None def __new__(cls): # ensure that only one instance exists if not cls.__instance: cls.__instance = super(_NoValueType, cls).__new__(cls) return cls.__instance # needed for python 2 to preserve identity through a pickle def __reduce__(self): return (self.__class__, ()) def __repr__(self): return "<no value>" _NoValue = _NoValueType()
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