PEP 362 – Function Signature Object
- PEP
- 362
- Title
- Function Signature Object
- Author
- Brett Cannon <brett at python.org>, Jiwon Seo <seojiwon at gmail.com>, Yury Selivanov <yury at edgedb.com>, Larry Hastings <larry at hastings.org>
- Status
- Final
- Type
- Standards Track
- Created
- 21-Aug-2006
- Python-Version
- 3.3
- Post-History
- 04-Jun-2012
- Resolution
- Python-Dev
Abstract
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_annotationobject
- The “return” annotation for the function. If the function
has no “return” annotation, this attribute is set to
Signature.empty
.
- parametersOrderedDict
- 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 (mimicsfunctools.partial
behavior.) Raises aTypeError
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 differentparameters
and/orreturn_annotation
to override the corresponding properties of the base signature. To removereturn_annotation
from the copiedSignature
, pass inSignature.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:
- Signature(parameters=<optional>, *, return_annotation=Signature.empty)
- Default Signature constructor. Accepts an optional sequence
of
Parameter
objects, and an optionalreturn_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)))
'(*args)'
>>> 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:
- namestr
- 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 toNone
.)
- defaultobject
- The default value for the parameter. If the parameter has no
default value, this attribute is set to
Parameter.empty
.
- annotationobject
- 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 thekind
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 aParameter
, passParameter.empty
.
Parameter constructor:
- Parameter(name, kind, *, annotation=Parameter.empty, default=Parameter.empty)
- Instantiates a Parameter object.
name
andkind
are required, whileannotation
anddefault
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'"
BoundArguments Object
Result of a Signature.bind
call. Holds the mapping of arguments
to the function’s parameters.
Has the following public attributes:
- argumentsOrderedDict
- 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.
- argstuple
- Tuple of positional arguments values. Dynamically computed from the ‘arguments’ attribute.
- kwargsdict
- 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):
pass
sig = signature(test)
ba = sig.bind(a=10, c=13)
>>> ba.args
(10,)
>>> ba.kwargs:
{'c': 13}
Implementation
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 notNone
- return it - If it has a
__wrapped__
attribute, returnsignature(object.__wrapped__)
- If the object is an instance of
FunctionType
, construct and return a newSignature
for it - If the object is a bound method, construct and return a new
Signature
object, with its first parameter (usuallyself
orcls
) removed. (classmethod
andstaticmethod
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 newSignature
from itspartial.func
attribute, and account for already boundpartial.args
andpartial.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
- If the object’s type has a
- 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 [1]. The python issue tracking the patch is [2].
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 aSignature
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.
Examples
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
@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)'
Annotation Checker
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
Acceptance
PEP 362 was accepted by Guido, Friday, June 22, 2012 [3] . The reference implementation was committed to trunk later that day.
References
- [1]
- pep362 branch (https://bitbucket.org/1st1/cpython/overview)
- [2]
- issue 15008 (http://bugs.python.org/issue15008)
- [3]
- “A Desperate Plea For Introspection (aka: BDFAP Needed)” (https://mail.python.org/pipermail/python-dev/2012-June/120682.html)
Copyright
This document has been placed in the public domain.
Source: https://github.com/python-discord/peps/blob/main/pep-0362.txt
Last modified: 2022-01-21 11:03:51 GMT