Hello,
The new revision of PEP 362 has been posted:
http://www.python.org/dev/peps/pep-0362/
Summary:
1. What was 'Signature.__deepcopy__' is now 'Signature.__copy__'.
__copy__ creates a shallow copy of Signature, shallow copying its
Parameters as well.
2. 'Signature.format()' was removed. I think we'll add something
to customize formatting later, in 3.4. Although, Signature still has
its __str__ method.
3. Built-in ('C') functions no longer have mutable '__signature__'
attribute, that patch was reverted. In the "Design Considerations"
section we stated clear that we don't support some callables.
4. Positions of keyword-only parameters now longer affect equality
testing of Signatures, i.e. 'foo(*, a, b)' is equal to 'foo(*, b, a)'
(Thanks to Jim Jewett for pointing that out)
The only question we have now is: when we do equality test between
Signatures, should we account for positional-only, var_positional
and var_keyword arguments names? So that: 'foo(*args)' will
be equal to 'bar(*arguments)', but not to 'spam(*coordinates:int)'
(Again, I think that's a Jim's idea)
Thank you!
--
PEP: 362
Title: Function Signature Object
Version: $Revision$
Last-Modified: $Date$
Author: Brett Cannon <br...@python.org>, Jiwon Seo <seoji...@gmail.com>,
Yury Selivanov <yseliva...@sprymix.com>, Larry Hastings
<la...@hastings.org>
Status: Draft
Type: Standards Track
Content-Type: text/x-rst
Created: 21-Aug-2006
Python-Version: 3.3
Post-History: 04-Jun-2012
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_annotation : object
The annotation for the return type of the function if specified.
If the function has no annotation for its return type, this
attribute is not set.
* parameters : OrderedDict
An ordered mapping of parameters' names to the corresponding
Parameter objects (keyword-only arguments are in the same order
as listed in ``code.co_varnames``).
* 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.
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__`` and ``__copy__`` methods.
The latter creates a shallow copy of Signature, with all Parameter
objects copied as well.
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.
The structure of the Parameter object is:
* name : str
The name of the parameter as a string.
* default : object
The default value for the parameter, if specified. If the
parameter has no default value, this attribute is not set.
* annotation : object
The annotation for the parameter if specified. If the
parameter has no annotation, this attribute is not set.
* kind : str
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 builtin 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 "\*\*kwds" parameter in a Python function definition.
Two parameters are equal when they have equal names, kinds, defaults,
and annotations.
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.
Does not contain arguments' default values.
* 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)
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 not ``None`` - return a shallow copy of it
- If it has a ``__wrapped__`` attribute, return
``signature(object.__wrapped__)``
- If the object is a an instance of ``FunctionType`` construct
and return a new ``Signature`` for it
- If the object is a method or a classmethod, construct and return
a new ``Signature`` object, with its first parameter (usually
``self`` or ``cls``) removed
- If the object is a staticmethod, construct and return
a new ``Signature`` object
- 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 class,
return a Signature object for it
- If the object has a ``__init__`` method defined in its class,
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. If, however, the Signature object was
explicitly cached by the user, ``signature()`` returns a new shallow copy
of it on each invocation.
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, builtin functions defined in C provide
no metadata about their arguments. Adding support for them is out of
scope for this PEP.
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
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, **kwds):
full_args = shared_args + args
return f(*full_args, **kwds)
# Override signature
sig = wrapper.__signature__ = signature(f)
for __ in shared_args:
sig.parameters.popitem(last=False)
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(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
try:
type_ = param.annotation
except AttributeError:
continue
else:
if not inspect.isclass(type_):
# 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.
try:
default = param.default
except AttributeError:
continue
else:
if not isinstance(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
try:
return_type = sig.return_annotation
except AttributeError:
# Looks like we don't have any restriction on the return type
pass
else:
if 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
References
==========
.. [#impl] pep362 branch (https://bitbucket.org/1st1/cpython/overview)
.. [#issue] issue 15008 (http://bugs.python.org/issue15008)
Copyright
=========
This document has been placed in the public domain.
..
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