hub/venv/lib/python3.7/site-packages/matplotlib/cbook/deprecation.py
2020-06-26 10:06:43 -04:00

410 lines
15 KiB
Python

import contextlib
import functools
import inspect
import warnings
class MatplotlibDeprecationWarning(UserWarning):
"""
A class for issuing deprecation warnings for Matplotlib users.
In light of the fact that Python builtin DeprecationWarnings are ignored
by default as of Python 2.7 (see link below), this class was put in to
allow for the signaling of deprecation, but via UserWarnings which are not
ignored by default.
https://docs.python.org/dev/whatsnew/2.7.html#the-future-for-python-2-x
"""
mplDeprecation = MatplotlibDeprecationWarning
"""mplDeprecation is deprecated. Use MatplotlibDeprecationWarning instead."""
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")
else:
if removal:
removal = "in {}".format(removal)
else:
removal = {"2.2": "in 3.1", "3.0": "in 3.2", "3.1": "in 3.3"}.get(
since, "two minor releases later")
if not message:
message = (
"\nThe %(name)s %(obj_type)s"
+ (" will be deprecated in a future version"
if pending else
(" was deprecated in Matplotlib %(since)s"
+ (" and will be removed %(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=''):
"""
Used to display deprecation in a standard way.
Parameters
----------
since : str
The release at which this API became deprecated.
message : str, optional
Override the default deprecation message. The format
specifier `%(name)s` may be used for the name of the function,
and `%(alternative)s` may be used in the deprecation message
to insert the name of an alternative to the deprecated
function. `%(obj_type)s` may be used to insert a friendly name
for the type of object being deprecated.
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
--------
Basic example::
# 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)
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* the ``@classmethod``, etc.
decorator (i.e., `deprecated` should directly decorate the underlying
callable).
Parameters
----------
since : str
The release at which this API became deprecated. This is
required.
message : str, optional
Override the default deprecation message. The format
specifier `%(name)s` may be used for the name of the object,
and `%(alternative)s` may be used in the deprecation message
to insert the name of an alternative to the deprecated
object.
name : str, optional
The name used in the deprecation message; if not provided, the name
is automatically determined from 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; by default, 'class' if decorating
a class, 'attribute' if decorating a property, 'function' otherwise.
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
--------
Basic example::
@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):
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):
obj_type = "attribute"
func = None
name = name or obj.fget.__name__
old_doc = obj.__doc__
class _deprecated_property(property):
def __get__(self, instance, owner):
if instance is not None:
from . import _warn_external
_warn_external(warning)
return super().__get__(instance, owner)
def __set__(self, instance, value):
if instance is not None:
from . import _warn_external
_warn_external(warning)
return super().__set__(instance, value)
def __delete__(self, instance):
if instance is not None:
from . import _warn_external
_warn_external(warning)
return super().__delete__(instance)
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
warning = _generate_deprecation_warning(
since, message, name, alternative, pending, obj_type, addendum,
removal=removal)
def wrapper(*args, **kwargs):
from . import _warn_external
_warn_external(warning)
return func(*args, **kwargs)
old_doc = inspect.cleandoc(old_doc or '').strip('\n')
notes_header = '\nNotes\n-----'
new_doc = (f"[*Deprecated*] {old_doc}\n"
f"{notes_header if notes_header not in old_doc else ''}\n"
f".. deprecated:: {since}\n"
f" {message.strip()}")
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
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
--------
::
@_rename_parameter("3.1", "bad_name", "good_name")
def func(good_name): ...
"""
if func is None:
return functools.partial(_rename_parameter, since, old, new)
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):
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 %(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.
return wrapper
class _deprecated_parameter_class:
def __repr__(self):
return "<deprecated parameter>"
_deprecated_parameter = _deprecated_parameter_class()
def _delete_parameter(since, name, func=None):
"""
Decorator indicating that parameter *name* of *func* is being deprecated.
The actual implementation of *func* should keep the *name* parameter in its
signature.
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.
Examples
--------
::
@_delete_parameter("3.1", "unused")
def func(used_arg, other_arg, unused, more_args): ...
"""
if func is None:
return functools.partial(_delete_parameter, since, name)
signature = inspect.signature(func)
assert name in signature.parameters, (
f"Matplotlib internal error: {name!r} must be a parameter for "
f"{func.__name__}()")
func.__signature__ = signature.replace(parameters=[
param.replace(default=_deprecated_parameter) if param.name == name
else param
for param in signature.parameters.values()])
@functools.wraps(func)
def wrapper(*args, **kwargs):
arguments = func.__signature__.bind(*args, **kwargs).arguments
# We cannot just check `name not in arguments` because the pyplot
# wrappers always pass all arguments explicitly.
if name in arguments and arguments[name] != _deprecated_parameter:
warn_deprecated(
since, message=f"The {name!r} parameter of {func.__name__}() "
f"is deprecated since Matplotlib {since} and will be removed "
f"%(removal)s. If any parameter follows {name!r}, they "
f"should be pass as keyword, not positionally.")
return func(*args, **kwargs)
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.
Note that this decorator **cannot** be applied to a function that has a
pyplot-level wrapper, as the wrapper always pass all arguments by keyword.
If it is used, users will see spurious DeprecationWarnings every time they
call the pyplot wrapper.
"""
if func is None:
return functools.partial(_make_keyword_only, since, name)
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__}()")
names = [*signature.parameters]
kwonly = [name for name in names[names.index(name):]
if signature.parameters[name].kind == POK]
func.__signature__ = signature.replace(parameters=[
param.replace(kind=KWO) if param.name in kwonly else param
for param in signature.parameters.values()])
@functools.wraps(func)
def wrapper(*args, **kwargs):
bound = signature.bind(*args, **kwargs)
if name in bound.arguments and name not in kwargs:
warn_deprecated(
since, message="Passing the %(name)s %(obj_type)s "
"positionally is deprecated since Matplotlib %(since)s; the "
"parameter will become keyword-only %(removal)s.",
name=name, obj_type=f"parameter of {func.__name__}()")
return func(*args, **kwargs)
return wrapper
@contextlib.contextmanager
def _suppress_matplotlib_deprecation_warning():
with warnings.catch_warnings():
warnings.simplefilter("ignore", MatplotlibDeprecationWarning)
yield