[Python-Dev] PEP 362: Signature objects

Brett Cannon brett at python.org
Fri Sep 7 04:34:42 CEST 2007

Neal Becker over on python-3000 said that the Boost people could use
this.  Figured it was time to present it officially to the list to see
if I can get it added for 2.6/3.0.

The implementation in the sandbox works in both 2.6 and 3.0 out of the
box (no 2to3 necessary) so feel free to play with it.



Python has always supported powerful introspection capabilities,
including that for functions and methods (for the rest of this PEP the
word "function" refers to both functions and methods).  Taking a
function object, you can fully reconstruct the function's signature.
Unfortunately it is a little unruly having to look at all the
different attributes to pull together complete information for a
function's signature.

This PEP proposes an object representation for function signatures.
This should help facilitate introspection on functions for various
uses (e.g., decorators).  The introspection information contains all
possible information about the parameters in a signature (including
Python 3.0 features).

This object, though, is not meant to replace existing ways of
introspection on a function's signature.  The current solutions are
there to make Python's execution work in an efficient manner.  The
proposed object representation is only meant to help make application
code have an easier time to query a function on its signature.

Signature Object

The overall signature of an object is represented by the Signature
object.  This object is to store a `Parameter object`_ for each
parameter in the signature.  It is also to store any information
about the function itself that is pertinent to the signature.

A Signature object has the following structure attributes:

* name : str
    Name of the function.  This is not fully qualified because
    function objects for methods do not know the class they are
    contained within.  This makes functions and methods
    indistinguishable from one another when passed to decorators,
    preventing proper creation of a fully qualified name.
* var_args : str
    Name of the variable positional parameter (i.e., ``*args``), if
    present, or the empty string.
* var_kw_args : str
    Name of the variable keyword parameter (i.e., ``**kwargs``), if
    present, or the empty string.
* var_annotations: dict(str, object)
    Dict that contains the annotations for the variable parameters.
    The keys are of the variable parameter with values of the
    annotation.  If an annotation does not exist for a variable
    parameter then the key does not exist in the dict.
* parameters : list(Parameter)
    List of the parameters of the function as represented by
    Parameter objects in the order of its definition (keyword-only
    arguments are in the order listed by ``code.co_varnames``).
* bind(\*args, \*\*kwargs) -> dict(str, Parameter)
    Create a mapping from arguments to parameters.  The keys are the
    names of the parameter that an argument maps to with the value
    being the value the parameter would have if this function was
    called with the given arguments.

The Signature object is stored in the ``__signature__`` attribute of
a function.  When it is to be created is discussed in
`Open Issues`_.

Parameter Object

A function's signature is made up of several parameters.  Python's
different kinds of parameters is quite large and rich and continues to
grow.  Parameter objects represent any possible parameter.

Originally the plan was to represent parameters using a list of
parameter names on the Signature object along with various dicts keyed
on parameter names to disseminate the various pieces of information
one can know about a parameter.  But the decision was made to
incorporate all information about a parameter in a single object so
as to make extending the information easier.  This was originally put
forth by Talin and the preferred form of Guido (as discussed at the
2006 Google Sprint).

The structure of the Parameter object is:

* name : (str | tuple(str))
    The name of the parameter as a string if it is not a tuple.  If
    the argument is a tuple then a tuple of strings is used.
* position : int
    The position of the parameter within the signature of the
    function (zero-indexed).  For keyword-only parameters the position
    value is arbitrary while not conflicting with positional
    parameters.  The suggestion of setting the attribute to None or -1
    to represent keyword-only parameters was rejected to prevent
    variable type usage and as a possible point of errors,
* has_default : bool
    True if the parameter has a default value, else False.
* default_value : object
    The default value for the parameter, if present, else the
    attribute does not exist.  This is done so that the attribute is
    not accidentally used if no default value is set as any default
    value could be a legitimate default value itself.
* keyword_only : bool
    True if the parameter is keyword-only, else False.
* has_annotation : bool
    True if the parameter has an annotation, else False.
* annotation
    Set to the annotation for the parameter.  If ``has_annotation`` is
    False then the attribute does not exist to prevent accidental use.


An implementation can be found in Python's sandbox [#impl]_.
There is a function named ``signature()`` which
returns the value stored on the ``__signature__`` attribute if it
exists, else it creates the Signature object for the
function and sets ``__signature__``.  For methods this is stored
directly on the im_func function object since that is what decorators
work with.

Open Issues

When to construct the Signature object?

The Signature object can either be created in an eager or lazy
fashion.  In the eager situation, the object can be created during
creation of the function object.  In the lazy situation, one would
pass a function object to a function and that would generate the
Signature object and store it to ``__signature__`` if
needed, and then return the value of ``__signature__``.

Should ``Signature.bind`` return Parameter objects as keys?

Instead of returning a dict with keys consisting of the name of the
parameters, would it be more useful to instead use Parameter
objects?  The name of the argument can easily be retrieved from the
key (and the name would be used as the hash for a Parameter object).

Provide a mapping of parameter name to Parameter object?

While providing access to the parameters in order is handy, it might
also be beneficial to provide a way to retrieve Parameter objects from
a Signature object based on the parameter's name.  Which style of
access (sequential/iteration or mapping) will influence how the
parameters are stored internally and whether __getitem__ accepts
strings or integers.

One possible compromise is to have ``__getitem__`` provide mapping
support and have ``__iter__`` return Parameter objects based on their
``position`` attribute.  This allows for getting the sequence of
Parameter objects easily by using the ``__iter__`` method on Signature
object along with the sequence constructor (e.g., ``list`` or

Remove ``has_*`` attributes?

If an EAFP approach to the API is taken, both ``has_annotation`` and
``has_default`` are unneeded as the respective ``annotation`` and
``default_value`` attributes are simply not set.  It's simply a
question of whether to have a EAFP or LBYL interface.

Have ``var_args`` and ``_var_kw_args`` default to ``None``?

It has been suggested by Fred Drake that these two attributes have a
value of ``None`` instead of empty strings when they do not exist.

Deprecate ``inspect.getargspec()`` and ``.formatargspec()``?

Since the Signature object replicates the use of ``getargspec()``
from the ``inspect`` module it might make sense to deprecate it in
2.6.  ``formatargspec()`` could also go if Signature objects gained a
__str__ representation.

Issue with that is types such as ``int``, when used as annotations,
do not lend themselves for output (e.g., ``"type 'int'>"`` is the
string represenation for ``int``).  The repr representation of types
would need to change in order to make this reasonable.


.. [#impl] pep362 directory in Python's sandbox


This document has been placed in the public domain.

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