python-peps/pep-0362.txt

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PEP: 362
Title: Function Signature Object
Version: $Revision$
Last-Modified: $Date$
Author: Brett Cannon <brett@python.org>, Jiwon Seo <seojiwon@gmail.com>,
Yury Selivanov <yselivanov@sprymix.com>, Larry Hastings <larry@hastings.org>
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Status: Draft
Type: Standards Track
Content-Type: text/x-rst
Created: 21-Aug-2006
Python-Version: 3.3
Post-History: 04-Jun-2012
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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.
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Signature Object
================
A Signature object represents the overall signature of a function.
It stores a `Parameter object`_ for each parameter accepted by the
function, as well as information specific to the function itself.
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A Signature object has the following public attributes and methods:
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* name : str
Name of the function.
* qualname : str
Fully qualified name of the function.
* 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
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parameters. Raises a ``BindError`` if the passed arguments
do not match the signature.
Changes to the Signature object, or to any of its data members,
do not affect the function itself.
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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.
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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.
* is_keyword_only : bool
True if the parameter is keyword-only, else False.
* is_args : bool
True if the parameter accepts variable number of arguments
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(``*args``-like), else False.
* is_kwargs : bool
True if the parameter accepts variable number of keyword
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arguments (``**kwargs``-like), else False.
* is_implemented : bool
True if the parameter is implemented for use. Some platforms
implement functions but can't support specific parameters
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(e.g. "mode" for ``os.mkdir``). Passing in an unimplemented
parameter may result in the parameter being ignored,
or in NotImplementedError being raised. It is intended that
all conditions where ``is_implemented`` may be False be
thoroughly documented.
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Parameter objects support testing for equality. Two Parameter
objects are equal, when all their properties are equal. Those
who need to test if one signature has the same parameters as
another, can do a direct comparison of ``Signature.parameters``
collections: ``signature(foo).parameters == signature(bar).parameters``.
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 should be used to invoke functions:
::
def test(a, *, b):
...
sig = signature(test)
ba = sig.bind(10, b=20)
test(*ba.args, **ba.kwargs)
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Implementation
==============
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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 is ``None`` and the object is an instance of
``BuiltinFunction``, raise a ``ValueError``
- If the object is a an instance of ``FunctionType``:
- If it has a ``__wrapped__`` attribute, return
``signature(object.__wrapped__)``
- Or else construct a new ``Signature`` object and return it
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- 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
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- If the object is a class return ``signature(object.__init__)``
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- 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``
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- Return ``signature(object.__call__)``
Note, that the ``Signature`` object is created in a lazy manner, and
is not automatically cached.
An implementation for Python 3.3 can be found here: [#impl]_.
A python issue was also created: [#issue]_.
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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
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Examples
========
Function Signature Renderer
---------------------------
::
def render_signature(signature):
'''Renders function definition by its signature.
Example:
>>> def test(a:'foo', *, b:'bar', c=True, **kwargs:None) -> 'spam':
... pass
>>> render_signature(inspect.signature(test))
test(a:'foo', *, b:'bar', c=True, **kwargs:None) -> 'spam'
'''
result = []
render_kw_only_separator = True
for param in signature.parameters.values():
formatted = param.name
# Add annotation and default value
if hasattr(param, 'annotation'):
formatted = '{}:{!r}'.format(formatted, param.annotation)
if hasattr(param, 'default'):
formatted = '{}={!r}'.format(formatted, param.default)
# Handle *args and **kwargs -like parameters
if param.is_args:
formatted = '*' + formatted
elif param.is_kwargs:
formatted = '**' + formatted
if param.is_args:
# OK, we have an '*args'-like parameter, so we won't need
# a '*' to separate keyword-only arguments
render_kw_only_separator = False
elif param.is_keyword_only and render_kw_only_separator:
# We have a keyword-only parameter to render and we haven't
# rendered an '*args'-like parameter before, so add a '*'
# separator to the parameters list ("foo(arg1, *, arg2)" case)
result.append('*')
# This condition should be only triggered once, so
# reset the flag
render_kw_only_separator = False
result.append(formatted)
rendered = '{}({})'.format(signature.name, ', '.join(result))
if hasattr(signature, 'return_annotation'):
rendered += ' -> {!r}'.format(signature.return_annotation)
return rendered
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=sig.qualname, arg=param.name))
def check_type(sig, arg_name, arg_type, arg_value):
# Internal function that incapsulates 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=sig.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.is_args:
# 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.is_kwargs:
# 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=sig.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)
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Copyright
=========
This document has been placed in the public domain.
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