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PEP: 362
Title: Function Signature Object
Version: $Revision$
Last-Modified: $Date$
Author: Brett Cannon <>, Jiwon Seo <>,
Yury Selivanov <>, Larry Hastings <>
Status: Final
Type: Standards Track
Content-Type: text/x-rst
Created: 21-Aug-2006
Python-Version: 3.3
Post-History: 04-Jun-2012
Python has always supported powerful introspection capabilities,
including introspecting functions and methods (for the rest of
this PEP, "function" refers to both functions and methods). By
examining a function object you can fully reconstruct the function's
signature. Unfortunately this information is stored in an inconvenient
manner, and is spread across a half-dozen deeply nested attributes.
This PEP proposes a new representation for function signatures.
The new representation contains all necessary information about a function
and its parameters, and makes introspection easy and straightforward.
However, this object does not replace the existing function
metadata, which is used by Python itself to execute those
functions. The new metadata object is intended solely to make
function introspection easier for Python programmers.
Signature Object
A Signature object represents the call signature of a function and
its return annotation. For each parameter accepted by the function
it stores a `Parameter object`_ in its ``parameters`` collection.
A Signature object has the following public attributes and methods:
* return_annotation : object
The "return" annotation for the function. If the function
has no "return" annotation, this attribute is set to
* parameters : OrderedDict
An ordered mapping of parameters' names to the corresponding
Parameter objects.
* bind(\*args, \*\*kwargs) -> BoundArguments
Creates a mapping from positional and keyword arguments to
parameters. Raises a ``TypeError`` if the passed arguments do
not match the signature.
* bind_partial(\*args, \*\*kwargs) -> BoundArguments
Works the same way as ``bind()``, but allows the omission
of some required arguments (mimics ``functools.partial``
behavior.) Raises a ``TypeError`` if the passed arguments do
not match the signature.
* replace(parameters=<optional>, \*, return_annotation=<optional>) -> Signature
Creates a new Signature instance based on the instance
``replace`` was invoked on. It is possible to pass different
``parameters`` and/or ``return_annotation`` to override the
corresponding properties of the base signature. To remove
``return_annotation`` from the copied ``Signature``, pass in
Note that the '=<optional>' notation, means that the argument is
optional. This notation applies to the rest of this PEP.
Signature objects are immutable. Use ``Signature.replace()`` to
make a modified copy:
>>> def foo() -> None:
... pass
>>> sig = signature(foo)
>>> new_sig = sig.replace(return_annotation="new return annotation")
>>> new_sig is not sig
>>> new_sig.return_annotation != sig.return_annotation
>>> new_sig.parameters == sig.parameters
>>> new_sig = new_sig.replace(return_annotation=new_sig.empty)
>>> new_sig.return_annotation is Signature.empty
There are two ways to instantiate a Signature class:
* Signature(parameters=<optional>, \*, return_annotation=Signature.empty)
Default Signature constructor. Accepts an optional sequence
of ``Parameter`` objects, and an optional ``return_annotation``.
Parameters sequence is validated to check that there are no
parameters with duplicate names, and that the parameters
are in the right order, i.e. positional-only first, then
positional-or-keyword, etc.
* Signature.from_function(function)
Returns a Signature object reflecting the signature of the
function passed in.
It's possible to test Signatures for equality. Two signatures are
equal when their parameters are equal, their positional and
positional-only parameters appear in the same order, and they
have equal return annotations.
Changes to the Signature object, or to any of its data members,
do not affect the function itself.
Signature also implements ``__str__``:
>>> str(Signature.from_function((lambda *args: None)))
>>> str(Signature())
Parameter Object
Python's expressive syntax means functions can accept many different
kinds of parameters with many subtle semantic differences. We
propose a rich Parameter object designed to represent any possible
function parameter.
A Parameter object has the following public attributes and methods:
* name : str
The name of the parameter as a string. Must be a valid
python identifier name (with the exception of ``POSITIONAL_ONLY``
parameters, which can have it set to ``None``.)
* default : object
The default value for the parameter. If the parameter has no
default value, this attribute is set to ``Parameter.empty``.
* annotation : object
The annotation for the parameter. If the parameter has no
annotation, this attribute is set to ``Parameter.empty``.
* kind
Describes how argument values are bound to the parameter.
Possible values:
* ``Parameter.POSITIONAL_ONLY`` - value must be supplied
as a positional argument.
Python has no explicit syntax for defining positional-only
parameters, but many built-in and extension module functions
(especially those that accept only one or two parameters)
accept them.
* ``Parameter.POSITIONAL_OR_KEYWORD`` - value may be
supplied as either a keyword or positional argument
(this is the standard binding behaviour for functions
implemented in Python.)
* ``Parameter.KEYWORD_ONLY`` - value must be supplied
as a keyword argument. Keyword only parameters are those
which appear after a "*" or "\*args" entry in a Python
function definition.
* ``Parameter.VAR_POSITIONAL`` - a tuple of positional
arguments that aren't bound to any other parameter.
This corresponds to a "\*args" parameter in a Python
function definition.
* ``Parameter.VAR_KEYWORD`` - a dict of keyword arguments
that aren't bound to any other parameter. This corresponds
to a "\*\*kwargs" parameter in a Python function definition.
Always use ``Parameter.*`` constants for setting and checking
value of the ``kind`` attribute.
* replace(\*, name=<optional>, kind=<optional>, default=<optional>, annotation=<optional>) -> Parameter
Creates a new Parameter instance based on the instance
``replaced`` was invoked on. To override a Parameter
attribute, pass the corresponding argument. To remove
an attribute from a ``Parameter``, pass ``Parameter.empty``.
Parameter constructor:
* Parameter(name, kind, \*, annotation=Parameter.empty, default=Parameter.empty)
Instantiates a Parameter object. ``name`` and ``kind`` are required,
while ``annotation`` and ``default`` are optional.
Two parameters are equal when they have equal names, kinds, defaults,
and annotations.
Parameter objects are immutable. Instead of modifying a Parameter object,
you can use ``Parameter.replace()`` to create a modified copy like so:
>>> param = Parameter('foo', Parameter.KEYWORD_ONLY, default=42)
>>> str(param)
>>> str(param.replace())
>>> str(param.replace(default=Parameter.empty, annotation='spam'))
BoundArguments Object
Result of a ``Signature.bind`` call. Holds the mapping of arguments
to the function's parameters.
Has the following public attributes:
* arguments : OrderedDict
An ordered, mutable mapping of parameters' names to arguments' values.
Contains only explicitly bound arguments. Arguments for
which ``bind()`` relied on a default value are skipped.
* args : tuple
Tuple of positional arguments values. Dynamically computed from
the 'arguments' attribute.
* kwargs : dict
Dict of keyword arguments values. Dynamically computed from
the 'arguments' attribute.
The ``arguments`` attribute should be used in conjunction with
``Signature.parameters`` for any arguments processing purposes.
``args`` and ``kwargs`` properties can be used to invoke functions:
def test(a, *, b):
sig = signature(test)
ba = sig.bind(10, b=20)
test(*ba.args, **ba.kwargs)
Arguments which could be passed as part of either ``*args`` or ``**kwargs``
will be included only in the ``BoundArguments.args`` attribute. Consider the
following example:
def test(a=1, b=2, c=3):
sig = signature(test)
ba = sig.bind(a=10, c=13)
>>> ba.args
>>> ba.kwargs:
{'c': 13}
The implementation adds a new function ``signature()`` to the ``inspect``
module. The function is the preferred way of getting a ``Signature`` for
a callable object.
The function implements the following algorithm:
- If the object is not callable - raise a TypeError
- If the object has a ``__signature__`` attribute and if it
is not ``None`` - return it
- If it has a ``__wrapped__`` attribute, return
- If the object is an instance of ``FunctionType``, construct
and return a new ``Signature`` for it
- If the object is a bound method, construct and return a new ``Signature``
object, with its first parameter (usually ``self`` or ``cls``)
removed. (``classmethod`` and ``staticmethod`` are supported
too. Since both are descriptors, the former returns a bound method,
and the latter returns its wrapped function.)
- If the object is an instance of ``functools.partial``, construct
a new ``Signature`` from its ``partial.func`` attribute, and
account for already bound ``partial.args`` and ``partial.kwargs``
- If the object is a class or metaclass:
- If the object's type has a ``__call__`` method defined in
its MRO, return a Signature for it
- If the object has a ``__new__`` method defined in its MRO,
return a Signature object for it
- If the object has a ``__init__`` method defined in its MRO,
return a Signature object for it
- Return ``signature(object.__call__)``
Note that the ``Signature`` object is created in a lazy manner, and
is not automatically cached. However, the user can manually cache a
Signature by storing it in the ``__signature__`` attribute.
An implementation for Python 3.3 can be found at [#impl]_.
The python issue tracking the patch is [#issue]_.
Design Considerations
No implicit caching of Signature objects
The first PEP design had a provision for implicit caching of ``Signature``
objects in the ``inspect.signature()`` function. However, this has the
following downsides:
* If the ``Signature`` object is cached then any changes to the function
it describes will not be reflected in it. However, If the caching is
needed, it can be always done manually and explicitly
* It is better to reserve the ``__signature__`` attribute for the cases
when there is a need to explicitly set to a ``Signature`` object that
is different from the actual one
Some functions may not be introspectable
Some functions may not be introspectable in certain implementations of
Python. For example, in CPython, built-in functions defined in C provide
no metadata about their arguments. Adding support for them is out of
scope for this PEP.
Signature and Parameter equivalence
We assume that parameter names have semantic significance--two
signatures are equal only when their corresponding parameters are equal
and have the exact same names. Users who want looser equivalence tests,
perhaps ignoring names of VAR_KEYWORD or VAR_POSITIONAL parameters, will
need to implement those themselves.
Visualizing Callable Objects' Signature
Let's define some classes and functions:
from inspect import signature
from functools import partial, wraps
class FooMeta(type):
def __new__(mcls, name, bases, dct, *, bar:bool=False):
return super().__new__(mcls, name, bases, dct)
def __init__(cls, name, bases, dct, **kwargs):
return super().__init__(name, bases, dct)
class Foo(metaclass=FooMeta):
def __init__(self, spam:int=42):
self.spam = spam
def __call__(self, a, b, *, c) -> tuple:
return a, b, c
def spam(cls, a):
return a
def shared_vars(*shared_args):
"""Decorator factory that defines shared variables that are
passed to every invocation of the function"""
def decorator(f):
def wrapper(*args, **kwargs):
full_args = shared_args + args
return f(*full_args, **kwargs)
# Override signature
sig = signature(f)
sig = sig.replace(tuple(sig.parameters.values())[1:])
wrapper.__signature__ = sig
return wrapper
return decorator
def example(_state, a, b, c):
return _state, a, b, c
def format_signature(obj):
return str(signature(obj))
Now, in the python REPL:
>>> format_signature(FooMeta)
'(name, bases, dct, *, bar:bool=False)'
>>> format_signature(Foo)
>>> format_signature(Foo.__call__)
'(self, a, b, *, c) -> tuple'
>>> format_signature(Foo().__call__)
'(a, b, *, c) -> tuple'
>>> format_signature(Foo.spam)
>>> format_signature(partial(Foo().__call__, 1, c=3))
'(b, *, c=3) -> tuple'
>>> format_signature(partial(partial(Foo().__call__, 1, c=3), 2, c=20))
'(*, c=20) -> tuple'
>>> format_signature(example)
'(a, b, c)'
>>> format_signature(partial(example, 1, 2))
>>> format_signature(partial(partial(example, 1, b=2), c=3))
'(b=2, c=3)'
Annotation Checker
import inspect
import functools
def checktypes(func):
'''Decorator to verify arguments and return types
>>> @checktypes
... def test(a:int, b:str) -> int:
... return int(a * b)
>>> test(10, '1')
>>> test(10, 1)
Traceback (most recent call last):
ValueError: foo: wrong type of 'b' argument, 'str' expected, got 'int'
sig = inspect.signature(func)
types = {}
for param in sig.parameters.values():
# Iterate through function's parameters and build the list of
# arguments types
type_ = param.annotation
if type_ is param.empty or not inspect.isclass(type_):
# Missing annotation or not a type, skip it
types[] = type_
# If the argument has a type specified, let's check that its
# default value (if present) conforms with the type.
if param.default is not param.empty and not isinstance(param.default, type_):
raise ValueError("{func}: wrong type of a default value for {arg!r}". \
def check_type(sig, arg_name, arg_type, arg_value):
# Internal function that encapsulates arguments type checking
if not isinstance(arg_value, arg_type):
raise ValueError("{func}: wrong type of {arg!r} argument, " \
"{exp!r} expected, got {got!r}". \
format(func=func.__qualname__, arg=arg_name,
exp=arg_type.__name__, got=type(arg_value).__name__))
def wrapper(*args, **kwargs):
# Let's bind the arguments
ba = sig.bind(*args, **kwargs)
for arg_name, arg in ba.arguments.items():
# And iterate through the bound arguments
type_ = types[arg_name]
except KeyError:
# OK, we have a type for the argument, lets get the corresponding
# parameter description from the signature object
param = sig.parameters[arg_name]
if param.kind == param.VAR_POSITIONAL:
# If this parameter is a variable-argument parameter,
# then we need to check each of its values
for value in arg:
check_type(sig, arg_name, type_, value)
elif param.kind == param.VAR_KEYWORD:
# If this parameter is a variable-keyword-argument parameter:
for subname, value in arg.items():
check_type(sig, arg_name + ':' + subname, type_, value)
# And, finally, if this parameter a regular one:
check_type(sig, arg_name, type_, arg)
result = func(*ba.args, **ba.kwargs)
# The last bit - let's check that the result is correct
return_type = sig.return_annotation
if (return_type is not sig._empty and
isinstance(return_type, type) and
not isinstance(result, return_type)):
raise ValueError('{func}: wrong return type, {exp} expected, got {got}'. \
format(func=func.__qualname__, exp=return_type.__name__,
return result
return wrapper
PEP 362 was accepted by Guido, Friday, June 22, 2012 [#accepted]_ .
The reference implementation was committed to trunk later that day.
.. [#impl] pep362 branch (
.. [#issue] issue 15008 (
.. [#accepted] "A Desperate Plea For Introspection (aka: BDFAP Needed)" (
This document has been placed in the public domain.
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