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.
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:
Signature.empty.TypeError if the passed arguments do
not match the signature.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 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
Signature.empty.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 True >>> new_sig.return_annotation != sig.return_annotation True >>> new_sig.parameters == sig.parameters True >>> new_sig = new_sig.replace(return_annotation=new_sig.empty) >>> new_sig.return_annotation is Signature.empty True
There are two ways to instantiate a Signature class:
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.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))) '(*args)' >>> str(Signature()) '()'
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:
POSITIONAL_ONLY
parameters, which can have it set to None.)Parameter.empty.Parameter.empty.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.
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:
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) 'foo=42' >>> str(param.replace()) 'foo=42' >>> str(param.replace(default=Parameter.empty, annotation='spam')) "foo:'spam'"
Result of a Signature.bind call. Holds the mapping of arguments
to the function’s parameters.
Has the following public attributes:
bind() relied on a default value are skipped.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): pass sig = signature(test) ba = sig.bind(a=10, c=13) >>> ba.args (10,) >>> 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:
__signature__ attribute and if it
is not None - return it__wrapped__ attribute, return
signature(object.__wrapped__)FunctionType, construct
and return a new Signature for itSignature
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.)functools.partial, construct
a new Signature from its partial.func attribute, and
account for already bound partial.args and partial.kwargs__call__ method defined in
its MRO, return a Signature for it__new__ method defined in its MRO,
return a Signature object for it__init__ method defined in its MRO,
return a Signature object for itsignature(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 [1]. The python issue tracking the patch is [2].
The first PEP design had a provision for implicit caching of Signature
objects in the inspect.signature() function. However, this has the
following downsides:
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__signature__ attribute for the cases
when there is a need to explicitly set to a Signature object that
is different from the actual oneSome 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.
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.
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 @classmethod 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): @wraps(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 @shared_vars({}) 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) '(spam:int=42)' >>> format_signature(Foo.__call__) '(self, a, b, *, c) -> tuple' >>> format_signature(Foo().__call__) '(a, b, *, c) -> tuple' >>> format_signature(Foo.spam) '(a)' >>> 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)) '(c)' >>> format_signature(partial(partial(example, 1, b=2), c=3)) '(b=2, c=3)'
import inspect import functools def checktypes(func): '''Decorator to verify arguments and return types Example: >>> @checktypes ... def test(a:int, b:str) -> int: ... return int(a * b) >>> test(10, '1') 1111111111 >>> 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 continue types[param.name] = 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}". \ format(func=func.__qualname__, arg=param.name)) 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__)) @functools.wraps(func) 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 try: type_ = types[arg_name] except KeyError: continue else: # 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) else: # 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__, got=type(result).__name__)) return result return wrapper
PEP 362 was accepted by Guido, Friday, June 22, 2012 [3] . The reference implementation was committed to trunk later that day.
This document has been placed in the public domain.