matplotlib/lib/matplotlib/_api/deprecation.py at main · matplotlib/matplotlib · GitHub

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"""

Helper functions for deprecating parts of the Matplotlib API.

This documentation is only relevant for Matplotlib developers, not for users.

.. warning::

This module is for internal use only. Do not use it in your own code.

We may change the API at any time with no warning.

"""

import contextlib

import functools

import inspect

import math

import warnings

class MatplotlibDeprecationWarning(DeprecationWarning):

"""A class for issuing deprecation warnings for Matplotlib users."""

def _generate_deprecation_warning(

since, message='', name='', alternative='', pending=False, obj_type='',

addendum='', *, removal=''):

if pending:

if removal:

raise ValueError("A pending deprecation cannot have a scheduled removal")

elif removal == '':

macro, meso, *_ = since.split('.')

removal = f'{macro}.{int(meso) + 2}'

if not message:

message = (

("The %(name)s %(obj_type)s" if obj_type else "%(name)s") +

(" will be deprecated in a future version" if pending else

(" was deprecated in Matplotlib %(since)s" +

(" and will be removed in %(removal)s" if removal else ""))) +

"." +

(" Use %(alternative)s instead." if alternative else "") +

(" %(addendum)s" if addendum else ""))

warning_cls = PendingDeprecationWarning if pending else MatplotlibDeprecationWarning

return warning_cls(message % dict(

func=name, name=name, obj_type=obj_type, since=since, removal=removal,

alternative=alternative, addendum=addendum))

def warn_deprecated(

since, *, message='', name='', alternative='', pending=False,

obj_type='', addendum='', removal=''):

"""

Display a standardized deprecation.

Parameters

----------

since : str

The release at which this API became deprecated.

message : str, optional

Override the default deprecation message. The ``%(since)s``,

``%(name)s``, ``%(alternative)s``, ``%(obj_type)s``, ``%(addendum)s``,

and ``%(removal)s`` format specifiers will be replaced by the values

of the respective arguments passed to this function.

name : str, optional

The name of the deprecated object.

alternative : str, optional

An alternative API that the user may use in place of the deprecated

API. The deprecation warning will tell the user about this alternative

if provided.

pending : bool, optional

If True, uses a PendingDeprecationWarning instead of a

DeprecationWarning. Cannot be used together with *removal*.

obj_type : str, optional

The object type being deprecated.

addendum : str, optional

Additional text appended directly to the final message.

removal : str, optional

The expected removal version. With the default (an empty string), a

removal version is automatically computed from *since*. Set to other

Falsy values to not schedule a removal date. Cannot be used together

with *pending*.

Examples

--------

# To warn of the deprecation of "matplotlib.name_of_module"

warn_deprecated('1.4.0', name='matplotlib.name_of_module',

obj_type='module')

"""

warning = _generate_deprecation_warning(

since, message, name, alternative, pending, obj_type, addendum,

removal=removal)

from . import warn_external

warn_external(warning, category=MatplotlibDeprecationWarning)

def deprecated(since, *, message='', name='', alternative='', pending=False,

obj_type=None, addendum='', removal=''):

"""

Decorator to mark a function, a class, or a property as deprecated.

When deprecating a classmethod, a staticmethod, or a property, the

``@deprecated`` decorator should go *under* ``@classmethod`` and

``@staticmethod`` (i.e., `deprecated` should directly decorate the

underlying callable), but *over* ``@property``.

When deprecating a class ``C`` intended to be used as a base class in a

multiple inheritance hierarchy, ``C`` *must* define an ``__init__`` method

(if ``C`` instead inherited its ``__init__`` from its own base class, then

``@deprecated`` would mess up ``__init__`` inheritance when installing its

own (deprecation-emitting) ``C.__init__``).

Parameters are the same as for `warn_deprecated`, except that *obj_type*

defaults to 'class' if decorating a class, 'attribute' if decorating a

property, and 'function' otherwise.

Examples

--------

@deprecated('1.4.0')

def the_function_to_deprecate():

pass

"""

def deprecate(obj, message=message, name=name, alternative=alternative,

pending=pending, obj_type=obj_type, addendum=addendum):

from matplotlib._api import classproperty

if isinstance(obj, type):

if obj_type is None:

obj_type = "class"

func = obj.__init__

name = name or obj.__name__

old_doc = obj.__doc__

def finalize(wrapper, new_doc):

try:

obj.__doc__ = new_doc

except AttributeError: # Can't set on some extension objects.

pass

obj.__init__ = functools.wraps(obj.__init__)(wrapper)

return obj

elif isinstance(obj, (property, classproperty)):

if obj_type is None:

obj_type = "attribute"

func = None

name = name or obj.fget.__name__

old_doc = obj.__doc__

class _deprecated_property(type(obj)):

def __get__(self, instance, owner=None):

if instance is not None or owner is not None \

and isinstance(self, classproperty):

emit_warning()

return super().__get__(instance, owner)

def __set__(self, instance, value):

if instance is not None:

emit_warning()

return super().__set__(instance, value)

def __delete__(self, instance):

if instance is not None:

emit_warning()

return super().__delete__(instance)

def __set_name__(self, owner, set_name):

nonlocal name

if name == "<lambda>":

name = set_name

def finalize(_, new_doc):

return _deprecated_property(

fget=obj.fget, fset=obj.fset, fdel=obj.fdel, doc=new_doc)

else:

if obj_type is None:

obj_type = "function"

func = obj

name = name or obj.__name__

old_doc = func.__doc__

def finalize(wrapper, new_doc):

wrapper = functools.wraps(func)(wrapper)

wrapper.__doc__ = new_doc

return wrapper

def emit_warning():

warn_deprecated(

since, message=message, name=name, alternative=alternative,

pending=pending, obj_type=obj_type, addendum=addendum,

removal=removal)

def wrapper(*args, **kwargs):

__tracebackhide__ = True

emit_warning()

return func(*args, **kwargs)

old_doc = inspect.cleandoc(old_doc or '').strip('\n')

notes_header = '\nNotes\n-----'

second_arg = ' '.join([t.strip() for t in

(message, f"Use {alternative} instead."

if alternative else "", addendum) if t])

new_doc = (f"[*Deprecated*] {old_doc}\n"

f"{notes_header if notes_header not in old_doc else ''}\n"

f".. deprecated:: {since}\n"

f" {second_arg}")

if not old_doc:

# This is to prevent a spurious 'unexpected unindent' warning from

# docutils when the original docstring was blank.

new_doc += r'\ '

return finalize(wrapper, new_doc)

return deprecate

class deprecate_privatize_attribute:

"""

Helper to deprecate public access to an attribute (or method).

This helper should only be used at class scope, as follows::

class Foo:

attr = _deprecate_privatize_attribute(*args, **kwargs)

where *all* parameters are forwarded to `deprecated`. This form makes

``attr`` a property which forwards read and write access to ``self._attr``

(same name but with a leading underscore), with a deprecation warning.

Note that the attribute name is derived from *the name this helper is

assigned to*. This helper also works for deprecating methods.

"""

def __init__(self, *args, **kwargs):

self.deprecator = deprecated(*args, **kwargs)

def __set_name__(self, owner, name):

setattr(owner, name, self.deprecator(

property(lambda self: getattr(self, f"_{name}"),

lambda self, value: setattr(self, f"_{name}", value)),

name=name))

# Used by _copy_docstring_and_deprecators to redecorate pyplot wrappers and

# boilerplate.py to retrieve original signatures. It may seem natural to store

# this information as an attribute on the wrapper, but if the wrapper gets

# itself functools.wraps()ed, then such attributes are silently propagated to

# the outer wrapper, which is not desired.

DECORATORS = {}

def rename_parameter(since, old, new, func=None):

"""

Decorator indicating that parameter *old* of *func* is renamed to *new*.

The actual implementation of *func* should use *new*, not *old*. If *old*

is passed to *func*, a DeprecationWarning is emitted, and its value is

used, even if *new* is also passed by keyword (this is to simplify pyplot

wrapper functions, which always pass *new* explicitly to the Axes method).

If *new* is also passed but positionally, a TypeError will be raised by the

underlying function during argument binding.

Examples

--------

@_api.rename_parameter("3.1", "bad_name", "good_name")

def func(good_name): ...

"""

decorator = functools.partial(rename_parameter, since, old, new)

if func is None:

return decorator

signature = inspect.signature(func)

assert old not in signature.parameters, (

f"Matplotlib internal error: {old!r} cannot be a parameter for "

f"{func.__name__}()")

assert new in signature.parameters, (

f"Matplotlib internal error: {new!r} must be a parameter for "

f"{func.__name__}()")

@functools.wraps(func)

def wrapper(*args, **kwargs):

__tracebackhide__ = True

if old in kwargs:

warn_deprecated(

since, message=f"The {old!r} parameter of {func.__name__}() "

f"has been renamed {new!r} since Matplotlib {since}; support "

f"for the old name will be dropped in %(removal)s.")

kwargs[new] = kwargs.pop(old)

return func(*args, **kwargs)

# wrapper() must keep the same documented signature as func(): if we

# instead made both *old* and *new* appear in wrapper()'s signature, they

# would both show up in the pyplot function for an Axes method as well and

# pyplot would explicitly pass both arguments to the Axes method.

DECORATORS[wrapper] = decorator

return wrapper

class _deprecated_parameter_class:

def __repr__(self):

return "<deprecated parameter>"

_deprecated_parameter = _deprecated_parameter_class()

def delete_parameter(since, name, func=None, **kwargs):

"""

Decorator indicating that parameter *name* of *func* is being deprecated.

The actual implementation of *func* should keep the *name* parameter in its

signature, or accept a ``**kwargs`` argument (through which *name* would be

passed).

Parameters that come after the deprecated parameter effectively become

keyword-only (as they cannot be passed positionally without triggering the

DeprecationWarning on the deprecated parameter), and should be marked as

such after the deprecation period has passed and the deprecated parameter

is removed.

Parameters other than *since*, *name*, and *func* are keyword-only and

forwarded to `.warn_deprecated`.

Examples

--------

@_api.delete_parameter("3.1", "unused")

def func(used_arg, other_arg, unused, more_args): ...

"""

decorator = functools.partial(delete_parameter, since, name, **kwargs)

if func is None:

return decorator

signature = inspect.signature(func)

# Name of `**kwargs` parameter of the decorated function, typically

# "kwargs" if such a parameter exists, or None if the decorated function

# doesn't accept `**kwargs`.

kwargs_name = next((param.name for param in signature.parameters.values()

if param.kind == inspect.Parameter.VAR_KEYWORD), None)

if name in signature.parameters:

kind = signature.parameters[name].kind

is_varargs = kind is inspect.Parameter.VAR_POSITIONAL

is_varkwargs = kind is inspect.Parameter.VAR_KEYWORD

if not is_varargs and not is_varkwargs:

name_idx = (

# Deprecated parameter can't be passed positionally.

math.inf if kind is inspect.Parameter.KEYWORD_ONLY

# If call site has no more than this number of parameters, the

# deprecated parameter can't have been passed positionally.

else [*signature.parameters].index(name))

func.__signature__ = signature = signature.replace(parameters=[

param.replace(default=_deprecated_parameter)

if param.name == name else param

for param in signature.parameters.values()])

else:

name_idx = -1 # Deprecated parameter can always have been passed.

else:

is_varargs = is_varkwargs = False

# Deprecated parameter can't be passed positionally.

name_idx = math.inf

assert kwargs_name, (

f"Matplotlib internal error: {name!r} must be a parameter for "

f"{func.__name__}()")

addendum = kwargs.pop('addendum', None)

@functools.wraps(func)

def wrapper(*inner_args, **inner_kwargs):

__tracebackhide__ = True

if len(inner_args) <= name_idx and name not in inner_kwargs:

# Early return in the simple, non-deprecated case (much faster than

# calling bind()).

return func(*inner_args, **inner_kwargs)

arguments = signature.bind(*inner_args, **inner_kwargs).arguments

if is_varargs and arguments.get(name):

warn_deprecated(

since, message=f"Additional positional arguments to "

f"{func.__name__}() are deprecated since %(since)s and "

f"support for them will be removed in %(removal)s.")

elif is_varkwargs and arguments.get(name):

warn_deprecated(

since, message=f"Additional keyword arguments to "

f"{func.__name__}() are deprecated since %(since)s and "

f"support for them will be removed in %(removal)s.")

# We cannot just check `name not in arguments` because the pyplot

# wrappers always pass all arguments explicitly.

elif any(name in d and d[name] != _deprecated_parameter

for d in [arguments, arguments.get(kwargs_name, {})]):

deprecation_addendum = (

f"If any parameter follows {name!r}, they should be passed as "

f"keyword, not positionally.")

warn_deprecated(

since,

name=repr(name),

obj_type=f"parameter of {func.__name__}()",

addendum=(addendum + " " + deprecation_addendum) if addendum

else deprecation_addendum,

**kwargs)

return func(*inner_args, **inner_kwargs)

DECORATORS[wrapper] = decorator

return wrapper

def make_keyword_only(since, name, func=None):

"""

Decorator indicating that passing parameter *name* (or any of the following

ones) positionally to *func* is being deprecated.

When used on a method that has a pyplot wrapper, this should be the

outermost decorator, so that :file:`boilerplate.py` can access the original

signature.

Examples

--------

Assume we want to only allow *dataset* and *positions* as positional

parameters on the method ::

def violinplot(self, dataset, positions=None, vert=None, ...)

Introduce the deprecation by adding the decorator ::

@_api.make_keyword_only("3.10", "vert")

def violinplot(self, dataset, positions=None, vert=None, ...)

When the deprecation expires, switch to ::

def violinplot(self, dataset, positions=None, *, vert=None, ...)

"""

decorator = functools.partial(make_keyword_only, since, name)

if func is None:

return decorator

signature = inspect.signature(func)

POK = inspect.Parameter.POSITIONAL_OR_KEYWORD

KWO = inspect.Parameter.KEYWORD_ONLY

assert (name in signature.parameters

and signature.parameters[name].kind == POK), (

f"Matplotlib internal error: {name!r} must be a positional-or-keyword "

f"parameter for {func.__name__}(). If this error happens on a function with a "

f"pyplot wrapper, make sure make_keyword_only() is the outermost decorator.")

names = [*signature.parameters]

name_idx = names.index(name)

kwonly = [name for name in names[name_idx:]

if signature.parameters[name].kind == POK]

@functools.wraps(func)

def wrapper(*args, **kwargs):

__tracebackhide__ = True

# Don't use signature.bind here, as it would fail when stacked with

# rename_parameter and an "old" argument name is passed in

# (signature.bind would fail, but the actual call would succeed).

if len(args) > name_idx:

warn_deprecated(

since, message="Passing the %(name)s %(obj_type)s "

"positionally is deprecated since Matplotlib %(since)s; the "

"parameter will become keyword-only in %(removal)s.",

name=name, obj_type=f"parameter of {func.__name__}()")

return func(*args, **kwargs)

# Don't modify *func*'s signature, as boilerplate.py needs it.

wrapper.__signature__ = signature.replace(parameters=[

param.replace(kind=KWO) if param.name in kwonly else param

for param in signature.parameters.values()])

DECORATORS[wrapper] = decorator

return wrapper

def deprecate_method_override(method, obj, *, allow_empty=False, **kwargs):

"""

Return ``obj.method`` with a deprecation if it was overridden, else None.

Parameters

----------

method

An unbound method, i.e. an expression of the form

``Class.method_name``. Remember that within the body of a method, one

can always use ``__class__`` to refer to the class that is currently

being defined.

obj

Either an object of the class where *method* is defined, or a subclass

of that class.

allow_empty : bool, default: False

Whether to allow overrides by "empty" methods without emitting a

warning.

**kwargs

Additional parameters passed to `warn_deprecated` to generate the

deprecation warning; must at least include the "since" key.

"""

def empty(): pass

def empty_with_docstring(): """doc"""

name = method.__name__

bound_child = getattr(obj, name)

bound_base = (

method # If obj is a class, then we need to use unbound methods.

if isinstance(bound_child, type(empty)) and isinstance(obj, type)

else method.__get__(obj))

if (bound_child != bound_base

and (not allow_empty

or (getattr(getattr(bound_child, "__code__", None),

"co_code", None)

not in [empty.__code__.co_code,

empty_with_docstring.__code__.co_code]))):

warn_deprecated(**{"name": name, "obj_type": "method", **kwargs})

return bound_child

return None

@contextlib.contextmanager

def suppress_matplotlib_deprecation_warning():

with warnings.catch_warnings():

warnings.simplefilter("ignore", MatplotlibDeprecationWarning)

yield

matplotlib/lib/matplotlib/_api/deprecation.py at main · matplotlib/matplotlib · GitHub

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