"""

Helper functions for managing the Matplotlib API.

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

.. warning::

This module and its submodules are for internal use only. Do not use them

in your own code. We may change the API at any time with no warning.

"""

import difflib

import functools

import itertools

import pathlib

import re

import sys

import warnings

from .deprecation import ( # noqa: F401

deprecated, warn_deprecated,

rename_parameter, delete_parameter, make_keyword_only,

deprecate_method_override, deprecate_privatize_attribute,

suppress_matplotlib_deprecation_warning,

MatplotlibDeprecationWarning)

# A sentinel value for optional arguments, when None cannot be used as

# default because we need to distinguish between None passed explicitly

# and parameter not given. Usage: def foo(arg=_api.UNSET):

class _Unset:

def __repr__(self):

return "<UNSET>"

UNSET = _Unset()

class UnsupportedError(RuntimeError):

"""

Raised on inherited methods if the child class does not support the functionality

of the base class.

See `.unsupported_method` for details.

"""

class unsupported_method:

"""

Descriptor that creates a method raising `.UnsupportedError`.

Historically, we have quite a few cases of inheritance hierarchies that do not

fully respect the Liskov Substitution Principle, e.g. Axes and Artist. Some of

the methods of a base class may not be implemented in the child class. In that case,

we override the method in the child class to raise `.UnsupportedError`.

Use in a class body to mark inherited methods as unsupported::

class Axes3D(Axes):

twinx = _api.unsupported_method()

Calling ``Axes3D().twinx()`` will raise

"UnsupportedError: Axes3D does not support 'twinx'."

Parameters

----------

append_message : str

Optional additional text to be appended to the error message.

"""

def __init__(self, *, append_message=None):

self.append_message = append_message

def __set_name__(self, owner, name):

message = f"{owner.__name__} does not support '{name}'."

if self.append_message:

message += ' ' + self.append_message

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

raise UnsupportedError(message)

method.__name__ = name

method.__qualname__ = f"{owner.__qualname__}.{name}"

method.__module__ = owner.__module__

setattr(owner, name, method)

class classproperty:

"""

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"

"""

def __init__(self, fget, fset=None, fdel=None, doc=None):

self._fget = fget

if fset is not None or fdel is not None:

raise ValueError('classproperty only implements fget.')

self.fset = fset

self.fdel = fdel

# docs are ignored for now

self._doc = doc

def __get__(self, instance, owner):

return self._fget(owner)

@property

def fget(self):

return self._fget

# In the following check_foo() functions, the first parameter is positional-only to make

# e.g. `_api.check_isinstance([...], types=foo)` work.

def check_isinstance(types, /, **kwargs):

"""

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)

"""

none_type = type(None)

types = ((types,) if isinstance(types, type) else

(none_type,) if types is None else

tuple(none_type if tp is None else tp for tp in types))

def type_name(tp):

return ("None" if tp is none_type

else tp.__qualname__ if tp.__module__ == "builtins"

else f"{tp.__module__}.{tp.__qualname__}")

for k, v in kwargs.items():

if not isinstance(v, types):

names = [*map(type_name, types)]

if "None" in names: # Move it to the end for better wording.

names.remove("None")

names.append("None")

raise TypeError(

"{!r} must be an instance of {}, not a {}".format(

k,

", ".join(names[:-1]) + " or " + names[-1]

if len(names) > 1 else names[0],

type_name(type(v))))

def list_suggestion_error_msg(name, potential, values):

"""

Generate an error message that a potential setting is not an acceptable value.

If the acceptable values are all strings, and sufficiently large, then add just a

few suggestions to the end of the message. Otherwise list the supported values.

Parameters

----------

name : str

The name of the setting, keyword argument, etc. to generate the message for.

potential

The potential value from the user that is not a valid choice.

values : iterable

Sequence of values to check on.

"""

if len(values) > 5 and all(isinstance(v, str) for v in [potential, *values]):

best = difflib.get_close_matches(potential, values, cutoff=0.5)

match len(best):

case 0:

suggestion = ""

case 1:

suggestion = f" Did you mean: {best[0]!r}?"

case _:

suggestion = f" Did you mean one of: {', '.join(map(repr, best))}?"

else:

suggestion = f" Supported values are {', '.join(map(repr, values))}"

return f"{potential!r} is not a valid value for {name}.{suggestion}"

def check_in_list(values, /, **kwargs):

"""

For each *key, value* pair in *kwargs*, check that *value* is in *values*;

if not, raise an appropriate ValueError.

Parameters

----------

values : iterable

Sequence of values to check on.

Note: All values must support == comparisons.

This means in particular the entries must not be numpy arrays.

**kwargs : dict

*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)

"""

if not kwargs:

raise TypeError("No argument to check!")

for key, val in kwargs.items():

try:

exists = val in values

except ValueError:

# `in` internally uses `val == values[i]`. There are some objects

# that do not support == to arbitrary other objects, in particular

# numpy arrays.

# Since such objects are not allowed in values, we can gracefully

# handle the case that val (typically provided by users) is of such

# type and directly state it's not in the list instead of letting

# the individual `val == values[i]` ValueError surface.

exists = False

if not exists:

raise ValueError(list_suggestion_error_msg(key, val, values))

def check_shape(shape, /, **kwargs):

"""

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)

"""

for k, v in kwargs.items():

data_shape = v.shape

if (len(data_shape) != len(shape)

or any(s != t and t is not None for s, t in zip(data_shape, shape))):

dim_labels = iter(itertools.chain(

'NMLKJIH',

(f"D{i}" for i in itertools.count())))

text_shape = ", ".join([str(n) if n is not None else next(dim_labels)

for n in shape[::-1]][::-1])

if len(shape) == 1:

text_shape += ","

raise ValueError(

f"{k!r} must be {len(shape)}D with shape ({text_shape}), "

f"but your input has shape {v.shape}"

)

def getitem_checked(mapping, /, _error_cls=ValueError, **kwargs):

"""

*kwargs* must consist of a single *key, value* pair. If *key* is in

*mapping*, return ``mapping[value]``; else, raise an appropriate

ValueError.

Parameters

----------

_error_cls :

Class of error to raise.

Examples

--------

>>> _api.getitem_checked({"foo": "bar"}, arg=arg)

"""

if len(kwargs) != 1:

raise ValueError("getitem_checked takes a single keyword argument")

(k, v), = kwargs.items()

try:

return mapping[v]

except KeyError:

raise _error_cls(list_suggestion_error_msg(k, v, mapping.keys())) from None

def caching_module_getattr(cls):

"""

Helper decorator for implementing module-level ``__getattr__`` as a class.

This decorator must be used at the module toplevel as follows::

@caching_module_getattr

class __getattr__: # The class *must* be named ``__getattr__``.

@property # Only properties are taken into account.

def name(self): ...

The ``__getattr__`` class will be replaced by a ``__getattr__``

function such that trying to access ``name`` on the module will

resolve the corresponding property (which may be decorated e.g. with

``_api.deprecated`` for deprecating module globals). The properties are

all implicitly cached. Moreover, a suitable AttributeError is generated

and raised if no property with the given name exists.

"""

assert cls.__name__ == "__getattr__"

# Don't accidentally export cls dunders.

props = {name: prop for name, prop in vars(cls).items()

if isinstance(prop, property)}

instance = cls()

@functools.cache

def __getattr__(name):

if name in props:

return props[name].__get__(instance)

raise AttributeError(

f"module {cls.__module__!r} has no attribute {name!r}")

return __getattr__

def define_aliases(alias_d, cls=None):

"""

Class decorator for defining property aliases.

Use as ::

@_api.define_aliases({"property": ["alias", ...], ...})

class C: ...

For each property, if the corresponding ``get_property`` is defined in the

class so far, an alias named ``get_alias`` will be defined; the same will

be done for setters. If neither the getter nor the setter exists, an

exception will be raised.

The alias map is stored as the ``_alias_to_prop`` attribute under the format

``{"alias": "property", ...}` on the class, and can be used by

`.normalize_kwargs`.

"""

if cls is None: # Return the actual class decorator.

return functools.partial(define_aliases, alias_d)

def make_alias(name): # Enforce a closure over *name*.

@functools.wraps(getattr(cls, name))

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

return getattr(self, name)(*args, **kwargs)

return method

for prop, aliases in alias_d.items():

exists = False

for prefix in ["get_", "set_"]:

if prefix + prop in vars(cls):

exists = True

for alias in aliases:

method = make_alias(prefix + prop)

method.__name__ = prefix + alias

method.__doc__ = f"Alias for `{prefix + prop}`."

setattr(cls, prefix + alias, method)

if not exists:

raise ValueError(

f"Neither getter nor setter exists for {prop!r}")

alias_to_prop = {

alias: prop for prop, aliases in alias_d.items() for alias in aliases}

def get_aliased_and_aliases(d):

return {*d.keys(), *d.values()}

preexisting_aliases = getattr(cls, "_alias_to_prop", {})

conflicting = (get_aliased_and_aliases(preexisting_aliases)

& get_aliased_and_aliases(alias_to_prop))

if conflicting:

# Need to decide on conflict resolution policy.

raise NotImplementedError(

f"Parent class already defines conflicting aliases: {conflicting}")

cls._alias_to_prop = {**preexisting_aliases, **alias_to_prop}

return cls

def select_matching_signature(funcs, *args, **kwargs):

"""

Select and call the function that accepts ``*args, **kwargs``.

*funcs* is a list of functions which should not raise any exception (other

than `TypeError` if the arguments passed do not match their signature).

`select_matching_signature` tries to call each of the functions in *funcs*

with ``*args, **kwargs`` (in the order in which they are given). Calls

that fail with a `TypeError` are silently skipped. As soon as a call

succeeds, `select_matching_signature` returns its return value. If no

function accepts ``*args, **kwargs``, then the `TypeError` raised by the

last failing call is re-raised.

Callers should normally make sure that any ``*args, **kwargs`` can only

bind a single *func* (to avoid any ambiguity), although this is not checked

by `select_matching_signature`.

Notes

-----

`select_matching_signature` is intended to help implementing

signature-overloaded functions. In general, such functions should be

avoided, except for back-compatibility concerns. A typical use pattern is

::

def my_func(*args, **kwargs):

params = select_matching_signature(

[lambda old1, old2: locals(), lambda new: locals()],

*args, **kwargs)

if "old1" in params:

warn_deprecated(...)

old1, old2 = params.values() # note that locals() is ordered.

else:

new, = params.values()

# do things with params

which allows *my_func* to be called either with two parameters (*old1* and

*old2*) or a single one (*new*). Note that the new signature is given

last, so that callers get a `TypeError` corresponding to the new signature

if the arguments they passed in do not match any signature.

"""

# Rather than relying on locals() ordering, one could have just used func's

# signature (``bound = inspect.signature(func).bind(*args, **kwargs);

# bound.apply_defaults(); return bound``) but that is significantly slower.

for i, func in enumerate(funcs):

try:

return func(*args, **kwargs)

except TypeError:

if i == len(funcs) - 1:

raise

def nargs_error(name, takes, given):

"""Generate a TypeError to be raised by function calls with wrong arity."""

return TypeError(f"{name}() takes {takes} positional arguments but "

f"{given} were given")

def kwarg_error(name, kw):

"""

Generate a TypeError to be raised by function calls with wrong kwarg.

Parameters

----------

name : str

The name of the calling function.

kw : str or Iterable[str]

Either the invalid keyword argument name, or an iterable yielding

invalid keyword arguments (e.g., a ``kwargs`` dict).

"""

if not isinstance(kw, str):

kw = next(iter(kw))

return TypeError(f"{name}() got an unexpected keyword argument '{kw}'")

def recursive_subclasses(cls):

"""Yield *cls* and direct and indirect subclasses of *cls*."""

yield cls

for subcls in cls.__subclasses__():

yield from recursive_subclasses(subcls)

def warn_external(message, category=None):

"""

`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.).

"""

kwargs = {}

if sys.version_info[:2] >= (3, 12):

# Go to Python's `site-packages` or `lib` from an editable install.

basedir = pathlib.Path(__file__).parents[2]

kwargs['skip_file_prefixes'] = (str(basedir / 'matplotlib'),

str(basedir / 'mpl_toolkits'))

else:

frame = sys._getframe()

for stacklevel in itertools.count(1):

if frame is None:

# when called in embedded context may hit frame is None

kwargs['stacklevel'] = stacklevel

break

if not re.match(r"\A(matplotlib|mpl_toolkits)(\Z|\.(?!tests\.))",

# Work around sphinx-gallery not setting __name__.

frame.f_globals.get("__name__", "")):

kwargs['stacklevel'] = stacklevel

break

frame = frame.f_back

# preemptively break reference cycle between locals and the frame

del frame

warnings.warn(message, category, **kwargs)