423 lines
15 KiB
Python
423 lines
15 KiB
Python
import contextlib
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import functools
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import inspect
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import warnings
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class MatplotlibDeprecationWarning(UserWarning):
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"""
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A class for issuing deprecation warnings for Matplotlib users.
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In light of the fact that Python builtin DeprecationWarnings are ignored
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by default as of Python 2.7 (see link below), this class was put in to
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allow for the signaling of deprecation, but via UserWarnings which are not
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ignored by default.
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https://docs.python.org/dev/whatsnew/2.7.html#the-future-for-python-2-x
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"""
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mplDeprecation = MatplotlibDeprecationWarning
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"""mplDeprecation is deprecated. Use MatplotlibDeprecationWarning instead."""
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def _generate_deprecation_warning(
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since, message='', name='', alternative='', pending=False,
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obj_type='attribute', addendum='', *, removal=''):
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if removal == "":
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removal = {"2.2": "in 3.1", "3.0": "in 3.2", "3.1": "in 3.3"}.get(
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since, "two minor releases later")
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elif removal:
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if pending:
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raise ValueError(
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"A pending deprecation cannot have a scheduled removal")
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removal = "in {}".format(removal)
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if not message:
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message = (
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"\nThe %(name)s %(obj_type)s"
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+ (" will be deprecated in a future version"
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if pending else
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(" was deprecated in Matplotlib %(since)s"
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+ (" and will be removed %(removal)s"
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if removal else
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"")))
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+ "."
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+ (" Use %(alternative)s instead." if alternative else "")
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+ (" %(addendum)s" if addendum else ""))
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warning_cls = (PendingDeprecationWarning if pending
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else MatplotlibDeprecationWarning)
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return warning_cls(message % dict(
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func=name, name=name, obj_type=obj_type, since=since, removal=removal,
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alternative=alternative, addendum=addendum))
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def warn_deprecated(
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since, *, message='', name='', alternative='', pending=False,
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obj_type='attribute', addendum='', removal=''):
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"""
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Used to display deprecation in a standard way.
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Parameters
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----------
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since : str
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The release at which this API became deprecated.
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message : str, optional
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Override the default deprecation message. The format
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specifier `%(name)s` may be used for the name of the function,
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and `%(alternative)s` may be used in the deprecation message
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to insert the name of an alternative to the deprecated
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function. `%(obj_type)s` may be used to insert a friendly name
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for the type of object being deprecated.
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name : str, optional
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The name of the deprecated object.
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alternative : str, optional
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An alternative API that the user may use in place of the deprecated
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API. The deprecation warning will tell the user about this alternative
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if provided.
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pending : bool, optional
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If True, uses a PendingDeprecationWarning instead of a
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DeprecationWarning. Cannot be used together with *removal*.
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obj_type : str, optional
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The object type being deprecated.
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addendum : str, optional
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Additional text appended directly to the final message.
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removal : str, optional
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The expected removal version. With the default (an empty string), a
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removal version is automatically computed from *since*. Set to other
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Falsy values to not schedule a removal date. Cannot be used together
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with *pending*.
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Examples
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--------
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Basic example::
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# To warn of the deprecation of "matplotlib.name_of_module"
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warn_deprecated('1.4.0', name='matplotlib.name_of_module',
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obj_type='module')
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"""
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warning = _generate_deprecation_warning(
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since, message, name, alternative, pending, obj_type, addendum,
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removal=removal)
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from . import _warn_external
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_warn_external(warning)
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def deprecated(since, *, message='', name='', alternative='', pending=False,
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obj_type=None, addendum='', removal=''):
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"""
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Decorator to mark a function, a class, or a property as deprecated.
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When deprecating a classmethod, a staticmethod, or a property, the
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``@deprecated`` decorator should go *under* the ``@classmethod``, etc.
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decorator (i.e., `deprecated` should directly decorate the underlying
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callable).
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Parameters
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----------
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since : str
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The release at which this API became deprecated. This is
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required.
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message : str, optional
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Override the default deprecation message. The format
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specifier `%(name)s` may be used for the name of the object,
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and `%(alternative)s` may be used in the deprecation message
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to insert the name of an alternative to the deprecated
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object.
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name : str, optional
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The name of the deprecated object; if not provided the name
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is automatically determined from the passed in object,
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though this is useful in the case of renamed functions, where
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the new function is just assigned to the name of the
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deprecated function. For example::
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def new_function():
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...
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old_function = new_function
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alternative : str, optional
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An alternative API that the user may use in place of the deprecated
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API. The deprecation warning will tell the user about this alternative
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if provided.
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pending : bool, optional
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If True, uses a PendingDeprecationWarning instead of a
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DeprecationWarning. Cannot be used together with *removal*.
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obj_type : str, optional
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The object type being deprecated; by default, 'function' if decorating
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a function and 'class' if decorating a class.
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addendum : str, optional
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Additional text appended directly to the final message.
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removal : str, optional
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The expected removal version. With the default (an empty string), a
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removal version is automatically computed from *since*. Set to other
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Falsy values to not schedule a removal date. Cannot be used together
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with *pending*.
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Examples
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--------
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Basic example::
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@deprecated('1.4.0')
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def the_function_to_deprecate():
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pass
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"""
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def deprecate(obj, message=message, name=name, alternative=alternative,
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pending=pending, obj_type=obj_type, addendum=addendum):
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if isinstance(obj, type):
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if obj_type is None:
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obj_type = "class"
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func = obj.__init__
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name = name or obj.__name__
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old_doc = obj.__doc__
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def finalize(wrapper, new_doc):
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try:
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obj.__doc__ = new_doc
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except AttributeError: # Can't set on some extension objects.
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pass
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obj.__init__ = wrapper
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return obj
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elif isinstance(obj, property):
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obj_type = "attribute"
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func = None
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name = name or obj.fget.__name__
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old_doc = obj.__doc__
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class _deprecated_property(property):
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def __get__(self, instance, owner):
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if instance is not None:
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from . import _warn_external
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_warn_external(warning)
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return super().__get__(instance, owner)
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def __set__(self, instance, value):
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if instance is not None:
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from . import _warn_external
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_warn_external(warning)
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return super().__set__(instance, value)
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def __delete__(self, instance):
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if instance is not None:
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from . import _warn_external
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_warn_external(warning)
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return super().__delete__(instance)
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def finalize(_, new_doc):
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return _deprecated_property(
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fget=obj.fget, fset=obj.fset, fdel=obj.fdel, doc=new_doc)
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else:
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if obj_type is None:
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obj_type = "function"
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func = obj
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name = name or obj.__name__
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old_doc = func.__doc__
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def finalize(wrapper, new_doc):
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wrapper = functools.wraps(func)(wrapper)
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wrapper.__doc__ = new_doc
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return wrapper
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warning = _generate_deprecation_warning(
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since, message, name, alternative, pending, obj_type, addendum,
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removal=removal)
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def wrapper(*args, **kwargs):
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from . import _warn_external
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_warn_external(warning)
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return func(*args, **kwargs)
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old_doc = inspect.cleandoc(old_doc or '').strip('\n')
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notes_header = '\nNotes\n-----'
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new_doc = (f"[*Deprecated*] {old_doc}\n"
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f"{notes_header if notes_header not in old_doc else ''}\n"
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f".. deprecated:: {since}\n"
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f" {message.strip()}")
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if not old_doc:
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# This is to prevent a spurious 'unexpected unindent' warning from
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# docutils when the original docstring was blank.
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new_doc += r'\ '
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return finalize(wrapper, new_doc)
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return deprecate
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def _rename_parameter(since, old, new, func=None):
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"""
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Decorator indicating that parameter *old* of *func* is renamed to *new*.
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The actual implementation of *func* should use *new*, not *old*. If *old*
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is passed to *func*, a DeprecationWarning is emitted, and its value is
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used, even if *new* is also passed by keyword (this is to simplify pyplot
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wrapper functions, which always pass *new* explicitly to the Axes method).
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If *new* is also passed but positionally, a TypeError will be raised by the
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underlying function during argument binding.
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Examples
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--------
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::
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@_rename_parameter("3.1", "bad_name", "good_name")
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def func(good_name): ...
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"""
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if func is None:
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return functools.partial(_rename_parameter, since, old, new)
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signature = inspect.signature(func)
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assert old not in signature.parameters, (
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f"Matplotlib internal error: {old!r} cannot be a parameter for "
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f"{func.__name__}()")
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assert new in signature.parameters, (
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f"Matplotlib internal error: {new!r} must be a parameter for "
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f"{func.__name__}()")
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@functools.wraps(func)
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def wrapper(*args, **kwargs):
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if old in kwargs:
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warn_deprecated(
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since, message=f"The {old!r} parameter of {func.__name__}() "
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f"has been renamed {new!r} since Matplotlib {since}; support "
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f"for the old name will be dropped %(removal)s.")
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kwargs[new] = kwargs.pop(old)
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return func(*args, **kwargs)
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# wrapper() must keep the same documented signature as func(): if we
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# instead made both *old* and *new* appear in wrapper()'s signature, they
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# would both show up in the pyplot function for an Axes method as well and
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# pyplot would explicitly pass both arguments to the Axes method.
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return wrapper
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class _deprecated_parameter_class:
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def __repr__(self):
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return "<deprecated parameter>"
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_deprecated_parameter = _deprecated_parameter_class()
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def _delete_parameter(since, name, func=None):
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"""
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Decorator indicating that parameter *name* of *func* is being deprecated.
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The actual implementation of *func* should keep the *name* parameter in its
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signature.
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Parameters that come after the deprecated parameter effectively become
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keyword-only (as they cannot be passed positionally without triggering the
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DeprecationWarning on the deprecated parameter), and should be marked as
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such after the deprecation period has passed and the deprecated parameter
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is removed.
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Examples
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--------
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::
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@_delete_parameter("3.1", "unused")
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def func(used_arg, other_arg, unused, more_args): ...
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"""
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if func is None:
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return functools.partial(_delete_parameter, since, name)
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signature = inspect.signature(func)
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assert name in signature.parameters, (
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f"Matplotlib internal error: {name!r} must be a parameter for "
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f"{func.__name__}()")
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func.__signature__ = signature.replace(parameters=[
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param.replace(default=_deprecated_parameter) if param.name == name
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else param
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for param in signature.parameters.values()])
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@functools.wraps(func)
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def wrapper(*args, **kwargs):
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arguments = func.__signature__.bind(*args, **kwargs).arguments
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# We cannot just check `name not in arguments` because the pyplot
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# wrappers always pass all arguments explicitly.
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if name in arguments and arguments[name] != _deprecated_parameter:
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warn_deprecated(
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since, message=f"The {name!r} parameter of {func.__name__}() "
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f"is deprecated since Matplotlib {since} and will be removed "
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f"%(removal)s. If any parameter follows {name!r}, they "
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f"should be pass as keyword, not positionally.")
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return func(*args, **kwargs)
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return wrapper
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def _make_keyword_only(since, name, func=None):
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"""
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Decorator indicating that passing parameter *name* (or any of the following
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ones) positionally to *func* is being deprecated.
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Note that this decorator **cannot** be applied to a function that has a
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pyplot-level wrapper, as the wrapper always pass all arguments by keyword.
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If it is used, users will see spurious DeprecationWarnings every time they
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call the pyplot wrapper.
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"""
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if func is None:
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return functools.partial(_make_keyword_only, since, name)
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signature = inspect.signature(func)
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POK = inspect.Parameter.POSITIONAL_OR_KEYWORD
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KWO = inspect.Parameter.KEYWORD_ONLY
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assert (name in signature.parameters
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and signature.parameters[name].kind == POK), (
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f"Matplotlib internal error: {name!r} must be a positional-or-keyword "
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f"parameter for {func.__name__}()")
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names = [*signature.parameters]
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kwonly = [name for name in names[names.index(name):]
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if signature.parameters[name].kind == POK]
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func.__signature__ = signature.replace(parameters=[
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param.replace(kind=inspect.Parameter.KEYWORD_ONLY)
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if param.name in kwonly
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else param
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for param in signature.parameters.values()])
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@functools.wraps(func)
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def wrapper(*args, **kwargs):
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bound = signature.bind(*args, **kwargs)
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if name in bound.arguments and name not in kwargs:
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warn_deprecated(
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since, message="Passing the %(name)s %(obj_type)s "
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"positionally is deprecated since Matplotlib %(since)s; the "
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"parameter will become keyword-only %(removal)s.",
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name=name, obj_type=f"parameter of {func.__name__}()")
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return func(*args, **kwargs)
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return wrapper
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@contextlib.contextmanager
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def _suppress_matplotlib_deprecation_warning():
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with warnings.catch_warnings():
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warnings.simplefilter("ignore", MatplotlibDeprecationWarning)
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yield
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