matplotlib._api

Helper functions for managing the Matplotlib API.

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

matplotlib._api.check_getitem(_mapping, **kwargs)[source]

kwargs must consist of a single key, value pair. If key is in _mapping, return _mapping[value]; else, raise an appropriate ValueError.

Examples

>>> _api.check_getitem({"foo": "bar"}, arg=arg)
matplotlib._api.check_in_list(_values, *, _print_supported_values=True, **kwargs)[source]

For each key, value pair in kwargs, check that value is in _values.

Parameters:
_valuesiterable

Sequence of values to check on.

_print_supported_valuesbool, default: True

Whether to print _values when raising ValueError.

**kwargsdict

key, value pairs as keyword arguments to find in _values.

Raises:
ValueError

If any value in kwargs is not found in _values.

Examples

>>> _api.check_in_list(["foo", "bar"], arg=arg, other_arg=other_arg)
matplotlib._api.check_isinstance(_types, **kwargs)[source]

For each key, value pair in kwargs, check that value is an instance of one of _types; if not, raise an appropriate TypeError.

As a special case, a None entry in _types is treated as NoneType.

Examples

>>> _api.check_isinstance((SomeClass, None), arg=arg)
matplotlib._api.check_shape(_shape, **kwargs)[source]

For each key, value pair in kwargs, check that value has the shape _shape, if not, raise an appropriate ValueError.

None in the shape is treated as a "free" size that can have any length. e.g. (None, 2) -> (N, 2)

The values checked must be numpy arrays.

Examples

To check for (N, 2) shaped arrays

>>> _api.check_shape((None, 2), arg=arg, other_arg=other_arg)
class matplotlib._api.classproperty(fget, fset=None, fdel=None, doc=None)[source]

Bases: object

Like property, but also triggers on access via the class, and it is the class that's passed as argument.

Examples

class C:
    @classproperty
    def foo(cls):
        return cls.__name__

assert C.foo == "C"
property fget
matplotlib._api.warn_external(message, category=None)[source]

warnings.warn wrapper that sets stacklevel to "outside Matplotlib".

The original emitter of the warning can be obtained by patching this function back to warnings.warn, i.e. _api.warn_external = warnings.warn (or functools.partial(warnings.warn, stacklevel=2), etc.).

Helper functions for deprecating parts of the Matplotlib API.

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

exception matplotlib._api.deprecation.MatplotlibDeprecationWarning[source]

Bases: DeprecationWarning

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

matplotlib._api.deprecation.delete_parameter(since, name, func=None, **kwargs)[source]

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): ...
matplotlib._api.deprecation.deprecate_method_override(method, obj, *, allow_empty=False, **kwargs)[source]

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_emptybool, 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.

class matplotlib._api.deprecation.deprecate_privatize_attribute(*args, **kwargs)[source]

Bases: object

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.

matplotlib._api.deprecation.deprecated(since, *, message='', name='', alternative='', pending=False, obj_type=None, addendum='', removal='')[source]

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:
sincestr

The release at which this API became deprecated.

messagestr, 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.

namestr, optional

The name used in the deprecation message; if not provided, the name is automatically determined from the deprecated object.

alternativestr, 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.

pendingbool, optional

If True, uses a PendingDeprecationWarning instead of a DeprecationWarning. Cannot be used together with removal.

obj_typestr, optional

The object type being deprecated; by default, 'class' if decorating a class, 'attribute' if decorating a property, 'function' otherwise.

addendumstr, optional

Additional text appended directly to the final message.

removalstr, 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
matplotlib._api.deprecation.make_keyword_only(since, name, func=None)[source]

Decorator indicating that passing parameter name (or any of the following ones) positionally to func is being deprecated.

matplotlib._api.deprecation.mplDeprecation

alias of matplotlib._api.deprecation.MatplotlibDeprecationWarning

matplotlib._api.deprecation.rename_parameter(since, old, new, func=None)[source]

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): ...
matplotlib._api.deprecation.suppress_matplotlib_deprecation_warning()[source]
matplotlib._api.deprecation.warn_deprecated(since, *, message='', name='', alternative='', pending=False, obj_type='', addendum='', removal='')[source]

Display a standardized deprecation.

Parameters:
sincestr

The release at which this API became deprecated.

messagestr, 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.

namestr, optional

The name of the deprecated object.

alternativestr, 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.

pendingbool, optional

If True, uses a PendingDeprecationWarning instead of a DeprecationWarning. Cannot be used together with removal.

obj_typestr, optional

The object type being deprecated.

addendumstr, optional

Additional text appended directly to the final message.

removalstr, 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')