Mailman 3 June 2012 - Python-Dev

Re: [Python-Dev] [Python-checkins] cpython: Issue #14769: test_capi now has SkipitemTest, which cleverly checks
by Terry Reedy June 22, 2012

June 22, 2012

On 6/22/2012 6:57 AM, larry.hastings wrote: > http://hg.python.org/cpython/rev/ace45d23628a > changeset: 77567:ace45d23628a > user: Larry Hastings <larry(a)hastings.org> > date: Fri Jun 22 03:56:29 2012 -0700 > summary: > Issue #14769: test_capi now has SkipitemTest, which cleverly checks > for "parity" between PyArg_ParseTuple() and the Python/getargs.c static > function skipitem() for all possible "format units". You sensibly only test … [View More]

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A Desperate Plea For Introspection (aka: BDFAP Needed)
by Larry Hastings June 22, 2012

June 22, 2012

Here's PEP 362: http://www.python.org/dev/peps/pep-0362/ It adds easy introspection abilities to Python callables. After a whirlwind of activity over the past several weeks we think it's ready. All it needs now is an official pronouncement from some seasoned veteran of the Python community. But that's where it's hit an impasse. Nick Coghlan has recused himself because he was heavily involved in shaping it. And obviously the authors (including myself, in a small way) are … [View More]

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Feature Freeze
by Ethan Furman June 22, 2012

June 22, 2012

Does the feature freeze affect documentation enhancements? If it does, can somebody review (and commit! :) issues: http://bugs.python.org/issue14954 http://bugs.python.org/issue14617 Thanks! (And if not necessary before the feature freeze, sorry for the noise.) ~Ethan~

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A reference leak with PyType_FromSpec
by Antoine Pitrou June 22, 2012

June 22, 2012

Hi, As mentioned in the commit message for 96513d71e650, creating a type using PyType_FromSpec seems to leak references when the type is instantiated. This happens with SSLError: >>> e = ssl.SSLError() >>> sys.getrefcount(ssl.SSLError) 35 >>> e = ssl.SSLError() >>> sys.getrefcount(ssl.SSLError) 36 >>> e = ssl.SSLError() >>> sys.getrefcount(ssl.SSLError) 37 (the SSLError definition is quite simple; it only uses the Py_tp_base, … [View More]

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Summary of Python tracker Issues
by Python tracker June 22, 2012

June 22, 2012

ACTIVITY SUMMARY (2012-06-15 - 2012-06-22) Python tracker at http://bugs.python.org/ To view or respond to any of the issues listed below, click on the issue. Do NOT respond to this message. Issues counts and deltas: open 3482 (+10) closed 23435 (+51) total 26917 (+61) Open issues with patches: 1460 Issues opened (46) ================== #15079: pickle: Possibly misplaced test http://bugs.python.org/issue15079 opened by mstefanro #15080: Cookie library doesn't parse date … [View More]

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PEP 362 - request for pronouncement
by Yury Selivanov June 22, 2012

June 22, 2012

Hello, On behalf of Brett, Larry, and myself, I'm requesting for PEP 362 pronouncement. The PEP, has been updated with all feedback from python-dev list discussions. I'm posting the latest version of it with this message. The PEP is also available here: http://www.python.org/dev/peps/pep-0362/ The python issue tracking the patch: http://bugs.python.org/issue15008 The reception of the PEP was very positive, the API is minimalistic and future-proof; the implementation is stable, well tested,… [View More] reviewed and should be ready to merge. Thank you, Yury PEP: 362 Title: Function Signature Object Version: $Revision$ Last-Modified: $Date$ Author: Brett Cannon <brett(a)python.org>, Jiwon Seo <seojiwon(a)gmail.com>, Yury Selivanov <yselivanov(a)sprymix.com>, Larry Hastings <larry(a)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 "return" annotation for the function. If the function has no "return" annotation, this attribute is not set. * 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, \*, return_annotation) -> 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 ``Signature.empty``. 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) >>> hasattr(new_sig, "return_annotation") False There are two ways to instantiate a Signature class: * Signature(parameters, \*, return_annotation) 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))) '(*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: * 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 not set. * annotation : object The annotation for the parameter. If the parameter has no annotation, this attribute is not set. * 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 "\*\*kwds" parameter in a Python function definition. Always use ``Parameter.*`` constants for setting and checking value of the ``kind`` attribute. * replace(\*, name, kind, default, annotation) -> 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, default) 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) '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: * 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): 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 not ``None`` - return 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 bound method, construct and return a new ``Signature`` object, with its first parameter (usually ``self`` or ``cls``) removed - 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. 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, **kwds): full_args = shared_args + args return f(*full_args, **kwds) # 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 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. .. Local Variables: mode: indented-text indent-tabs-mode: nil sentence-end-double-space: t fill-column: 70 coding: utf-8 End: [View Less]

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Accepting PEP 397
by Brian Curtin June 21, 2012

June 21, 2012

As the PEP czar for 397, after Martin's final updates, I hereby pronounce this PEP "accepted"! Thanks to Mark Hammond for kicking it off, Vinay Sajip for writing up the code, Martin von Loewis for recent updates, and everyone in the community who contributed to the discussions. I will begin integration work this evening.

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import too slow on NFS based systems
by Daniel Braniss June 21, 2012

June 21, 2012

Hi, when lib/python/site-packages/ is accessed via NFS, open/stat/access is very expensive/slow. A simple solution is to use an in memory directory search/hash, so I was wondering if this has been concidered in the past, if not, and I come with a working solution for Unix (at least Linux/Freebsd) will it be concidered. thanks, danny

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Re: [Python-Dev] [Python-checkins] peps: The latest changes from Yury Selivanov. I can almost taste the acceptance!
by Eric Snow June 21, 2012

June 21, 2012

On Thu, Jun 21, 2012 at 2:44 AM, larry.hastings <python-checkins(a)python.org> wrote: > http://hg.python.org/peps/rev/1edf1cecae7d > changeset: 4472:1edf1cecae7d > user: Larry Hastings <larry(a)hastings.org> > date: Thu Jun 21 01:44:15 2012 -0700 > summary: > The latest changes from Yury Selivanov. I can almost taste the acceptance! > > files: > pep-0362.txt | 159 +++++++++… [View More]++++++++++++++++++++++------- > 1 files changed, 128 insertions(+), 31 deletions(-) > > > diff --git a/pep-0362.txt b/pep-0362.txt > --- a/pep-0362.txt > +++ b/pep-0362.txt > @@ -42,23 +42,58 @@ > 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. > + The "return" annotation for the function. If the function > + has no "return" annotation, 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``). > + 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, \*, return_annotation) -> Signature Shouldn't it be something like this: * replace_(*parameters, [return_annotation]) -> Signature Or is parameters supposed to be a dict/OrderedDict of replacements/additions? > + 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 > + ``Signature.empty``. Can you likewise remove parameters this way? > + > +Signature objects are immutable. Use ``Signature.replace()`` to > +make a modified copy: > +:: > + > + >>> 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 Should be False here, right? > + >>> new_sig.parameters == sig.parameters > + True An example of replacing parameters would also be good here. > + > +There are two ways to instantiate a Signature class: > + > +* Signature(parameters, *, return_annotation) Same here as with Signature.replace(). > + 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 > @@ -67,9 +102,14 @@ > 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. > +Signature also implements ``__str__``: > +:: > + > + >>> str(Signature.from_function((lambda *args: None))) > + '(*args)' > + > + >>> str(Signature()) > + '()' > > > Parameter Object > @@ -80,20 +120,22 @@ > propose a rich Parameter object designed to represent any possible > function parameter. > > -The structure of the Parameter object is: > +A Parameter object has the following public attributes and methods: > > * name : str > - The name of the parameter as a string. > + 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 specified. If the > - parameter has no default value, this attribute is not set. > + The default value for the parameter. 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. > + The annotation for the parameter. If the parameter has no > + annotation, this attribute is not set. > > -* kind : str > +* kind > Describes how argument values are bound to the parameter. > Possible values: > > @@ -101,7 +143,7 @@ > as a positional argument. > > Python has no explicit syntax for defining positional-only > - parameters, but many builtin and extension module functions > + parameters, but many built-in and extension module functions > (especially those that accept only one or two parameters) > accept them. > > @@ -124,9 +166,30 @@ > that aren't bound to any other parameter. This corresponds > to a "\*\*kwds" parameter in a Python function definition. > > +* replace(\*, name, kind, default, annotation) -> 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``. > + > + > 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 > ===================== > @@ -138,7 +201,8 @@ > > * arguments : OrderedDict > An ordered, mutable mapping of parameters' names to arguments' values. > - Does not contain arguments' default 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. > @@ -159,6 +223,23 @@ > 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 Why wouldn't the kwargs go into BoundArguments.kwargs? > +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 > ============== > @@ -172,7 +253,7 @@ > - 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 > + is not ``None`` - return it > > - If it has a ``__wrapped__`` attribute, return > ``signature(object.__wrapped__)`` > @@ -180,12 +261,9 @@ > - If the object is a an instance of ``FunctionType`` construct s/``FunctionType`` construct/``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 a method, construct and return a new ``Signature`` > + object, with its first parameter (usually ``self`` or ``cls``) > + removed It may be worth explicitly clarify that it refers to bound methods (and classmethods) here. Also, inspect.getfullargspec() doesn't strip out the self/cls. Would it be okay to store that implicit first argument (self/cls) on the Signature object somehow? Explicit is better than implicit. It's certainly a very special case: the only implicit (and unavoidable) arguments of any kind of callable. If the self were stored on the Signature, I'd also expect that Signature.replace() would leave it out (as would any other copy mechanism). > > - If the object is an instance of ``functools.partial``, construct > a new ``Signature`` from its ``partial.func`` attribute, and > @@ -196,15 +274,15 @@ > - 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, > + - 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 class, > + - 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 > +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. > @@ -236,11 +314,21 @@ > ---------------------------------------- > > Some functions may not be introspectable in certain implementations of > -Python. For example, in CPython, builtin functions defined in C provide > +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 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 > ======== > > @@ -270,6 +358,10 @@ > 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 > @@ -280,10 +372,12 @@ > 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) > + sig = signature(f) > + sig = sig.replace(tuple(sig.parameters.values())[1:]) > + wrapper.__signature__ = sig > + > return wrapper > return decorator > > @@ -313,6 +407,9 @@ > >>> 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' I'm really impressed by the great work on this and how well the PEP process has been working here. This is a great addition to Python! -eric [View Less]

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PEP 362 6th edition
by Yury Selivanov June 21, 2012

June 21, 2012

Hello, The new revision of PEP 362 has been posted: http://www.python.org/dev/peps/pep-0362/ Summary: 1. Signature & Parameter objects are now immutable 2. Signature.replace() and Parameter.replace() 3. Signature has a new default constructor, which accepts parameters list and a return_annotation. Parameters list is checked for the correct order (i.e. keyword-only before var-keyword, not vice-versa) The second way to instantiate Signatures is to use 'from_function', which creates a … [View More]Signature object for the passed function. 4. Parameter.__str__ 5. Positional-only arguments are rendered in '<>' 6. PEP was updated to include new documentation & small examples. The implementation is updated and 100% test covered. Please see the issue: http://bugs.python.org/issue15008 Open questions: Just one - Should we rename 'replace()' to 'new()'? I like 'new()' a bit better - it suggests that we'll get a new object. - Yury PEP: 362 Title: Function Signature Object Version: $Revision$ Last-Modified: $Date$ Author: Brett Cannon <brett(a)python.org>, Jiwon Seo <seojiwon(a)gmail.com>, Yury Selivanov <yselivanov(a)sprymix.com>, Larry Hastings <larry(a)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 "return" annotation for the function. If the function has no "return" annotation, this attribute is not set. * 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, \*, return_annotation) -> 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 ``Signature.empty``. 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) >>> hasattr(new_sig, "return_annotation") False There are two ways to instantiate a Signature class: * Signature(parameters, \*, return_annotation) 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))) '(*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: * 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 not set. * annotation : object The annotation for the parameter. If the parameter has no annotation, this attribute is not set. * 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 "\*\*kwds" parameter in a Python function definition. Always use ``Parameter.*`` constants for setting and checking value of the ``kind`` attribute. * replace(\*, name, kind, default, annotation) -> 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, default) 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) '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: * 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): 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 not ``None`` - return 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, construct and return a new ``Signature`` object, with its first parameter (usually ``self`` or ``cls``) removed - 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. 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, **kwds): full_args = shared_args + args return f(*full_args, **kwds) # 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 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. .. Local Variables: mode: indented-text indent-tabs-mode: nil sentence-end-double-space: t fill-column: 70 coding: utf-8 End: [View Less]

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