mirror of https://github.com/python/cpython
404 lines
15 KiB
ReStructuredText
404 lines
15 KiB
ReStructuredText
:mod:`functools` --- Higher-order functions and operations on callable objects
|
|
==============================================================================
|
|
|
|
.. module:: functools
|
|
:synopsis: Higher-order functions and operations on callable objects.
|
|
.. moduleauthor:: Peter Harris <scav@blueyonder.co.uk>
|
|
.. moduleauthor:: Raymond Hettinger <python@rcn.com>
|
|
.. moduleauthor:: Nick Coghlan <ncoghlan@gmail.com>
|
|
.. moduleauthor:: Łukasz Langa <lukasz@langa.pl>
|
|
.. sectionauthor:: Peter Harris <scav@blueyonder.co.uk>
|
|
|
|
**Source code:** :source:`Lib/functools.py`
|
|
|
|
--------------
|
|
|
|
The :mod:`functools` module is for higher-order functions: functions that act on
|
|
or return other functions. In general, any callable object can be treated as a
|
|
function for the purposes of this module.
|
|
|
|
The :mod:`functools` module defines the following functions:
|
|
|
|
.. function:: cmp_to_key(func)
|
|
|
|
Transform an old-style comparison function to a key function. Used with
|
|
tools that accept key functions (such as :func:`sorted`, :func:`min`,
|
|
:func:`max`, :func:`heapq.nlargest`, :func:`heapq.nsmallest`,
|
|
:func:`itertools.groupby`). This function is primarily used as a transition
|
|
tool for programs being converted from Python 2 which supported the use of
|
|
comparison functions.
|
|
|
|
A comparison function is any callable that accept two arguments, compares them,
|
|
and returns a negative number for less-than, zero for equality, or a positive
|
|
number for greater-than. A key function is a callable that accepts one
|
|
argument and returns another value indicating the position in the desired
|
|
collation sequence.
|
|
|
|
Example::
|
|
|
|
sorted(iterable, key=cmp_to_key(locale.strcoll)) # locale-aware sort order
|
|
|
|
.. versionadded:: 3.2
|
|
|
|
|
|
.. decorator:: lru_cache(maxsize=128, typed=False)
|
|
|
|
Decorator to wrap a function with a memoizing callable that saves up to the
|
|
*maxsize* most recent calls. It can save time when an expensive or I/O bound
|
|
function is periodically called with the same arguments.
|
|
|
|
Since a dictionary is used to cache results, the positional and keyword
|
|
arguments to the function must be hashable.
|
|
|
|
If *maxsize* is set to None, the LRU feature is disabled and the cache can
|
|
grow without bound. The LRU feature performs best when *maxsize* is a
|
|
power-of-two.
|
|
|
|
If *typed* is set to True, function arguments of different types will be
|
|
cached separately. For example, ``f(3)`` and ``f(3.0)`` will be treated
|
|
as distinct calls with distinct results.
|
|
|
|
To help measure the effectiveness of the cache and tune the *maxsize*
|
|
parameter, the wrapped function is instrumented with a :func:`cache_info`
|
|
function that returns a :term:`named tuple` showing *hits*, *misses*,
|
|
*maxsize* and *currsize*. In a multi-threaded environment, the hits
|
|
and misses are approximate.
|
|
|
|
The decorator also provides a :func:`cache_clear` function for clearing or
|
|
invalidating the cache.
|
|
|
|
The original underlying function is accessible through the
|
|
:attr:`__wrapped__` attribute. This is useful for introspection, for
|
|
bypassing the cache, or for rewrapping the function with a different cache.
|
|
|
|
An `LRU (least recently used) cache
|
|
<http://en.wikipedia.org/wiki/Cache_algorithms#Least_Recently_Used>`_ works
|
|
best when the most recent calls are the best predictors of upcoming calls (for
|
|
example, the most popular articles on a news server tend to change each day).
|
|
The cache's size limit assures that the cache does not grow without bound on
|
|
long-running processes such as web servers.
|
|
|
|
Example of an LRU cache for static web content::
|
|
|
|
@lru_cache(maxsize=32)
|
|
def get_pep(num):
|
|
'Retrieve text of a Python Enhancement Proposal'
|
|
resource = 'http://www.python.org/dev/peps/pep-%04d/' % num
|
|
try:
|
|
with urllib.request.urlopen(resource) as s:
|
|
return s.read()
|
|
except urllib.error.HTTPError:
|
|
return 'Not Found'
|
|
|
|
>>> for n in 8, 290, 308, 320, 8, 218, 320, 279, 289, 320, 9991:
|
|
... pep = get_pep(n)
|
|
... print(n, len(pep))
|
|
|
|
>>> get_pep.cache_info()
|
|
CacheInfo(hits=3, misses=8, maxsize=32, currsize=8)
|
|
|
|
Example of efficiently computing
|
|
`Fibonacci numbers <http://en.wikipedia.org/wiki/Fibonacci_number>`_
|
|
using a cache to implement a
|
|
`dynamic programming <http://en.wikipedia.org/wiki/Dynamic_programming>`_
|
|
technique::
|
|
|
|
@lru_cache(maxsize=None)
|
|
def fib(n):
|
|
if n < 2:
|
|
return n
|
|
return fib(n-1) + fib(n-2)
|
|
|
|
>>> [fib(n) for n in range(16)]
|
|
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610]
|
|
|
|
>>> fib.cache_info()
|
|
CacheInfo(hits=28, misses=16, maxsize=None, currsize=16)
|
|
|
|
.. versionadded:: 3.2
|
|
|
|
.. versionchanged:: 3.3
|
|
Added the *typed* option.
|
|
|
|
.. decorator:: total_ordering
|
|
|
|
Given a class defining one or more rich comparison ordering methods, this
|
|
class decorator supplies the rest. This simplifies the effort involved
|
|
in specifying all of the possible rich comparison operations:
|
|
|
|
The class must define one of :meth:`__lt__`, :meth:`__le__`,
|
|
:meth:`__gt__`, or :meth:`__ge__`.
|
|
In addition, the class should supply an :meth:`__eq__` method.
|
|
|
|
For example::
|
|
|
|
@total_ordering
|
|
class Student:
|
|
def __eq__(self, other):
|
|
return ((self.lastname.lower(), self.firstname.lower()) ==
|
|
(other.lastname.lower(), other.firstname.lower()))
|
|
def __lt__(self, other):
|
|
return ((self.lastname.lower(), self.firstname.lower()) <
|
|
(other.lastname.lower(), other.firstname.lower()))
|
|
|
|
.. versionadded:: 3.2
|
|
|
|
|
|
.. function:: partial(func, *args, **keywords)
|
|
|
|
Return a new :class:`partial` object which when called will behave like *func*
|
|
called with the positional arguments *args* and keyword arguments *keywords*. If
|
|
more arguments are supplied to the call, they are appended to *args*. If
|
|
additional keyword arguments are supplied, they extend and override *keywords*.
|
|
Roughly equivalent to::
|
|
|
|
def partial(func, *args, **keywords):
|
|
def newfunc(*fargs, **fkeywords):
|
|
newkeywords = keywords.copy()
|
|
newkeywords.update(fkeywords)
|
|
return func(*(args + fargs), **newkeywords)
|
|
newfunc.func = func
|
|
newfunc.args = args
|
|
newfunc.keywords = keywords
|
|
return newfunc
|
|
|
|
The :func:`partial` is used for partial function application which "freezes"
|
|
some portion of a function's arguments and/or keywords resulting in a new object
|
|
with a simplified signature. For example, :func:`partial` can be used to create
|
|
a callable that behaves like the :func:`int` function where the *base* argument
|
|
defaults to two:
|
|
|
|
>>> from functools import partial
|
|
>>> basetwo = partial(int, base=2)
|
|
>>> basetwo.__doc__ = 'Convert base 2 string to an int.'
|
|
>>> basetwo('10010')
|
|
18
|
|
|
|
|
|
.. function:: reduce(function, iterable[, initializer])
|
|
|
|
Apply *function* of two arguments cumulatively to the items of *sequence*, from
|
|
left to right, so as to reduce the sequence to a single value. For example,
|
|
``reduce(lambda x, y: x+y, [1, 2, 3, 4, 5])`` calculates ``((((1+2)+3)+4)+5)``.
|
|
The left argument, *x*, is the accumulated value and the right argument, *y*, is
|
|
the update value from the *sequence*. If the optional *initializer* is present,
|
|
it is placed before the items of the sequence in the calculation, and serves as
|
|
a default when the sequence is empty. If *initializer* is not given and
|
|
*sequence* contains only one item, the first item is returned.
|
|
|
|
|
|
.. decorator:: singledispatch(default)
|
|
|
|
Transforms a function into a :term:`single-dispatch <single
|
|
dispatch>` :term:`generic function`.
|
|
|
|
To define a generic function, decorate it with the ``@singledispatch``
|
|
decorator. Note that the dispatch happens on the type of the first argument,
|
|
create your function accordingly::
|
|
|
|
>>> from functools import singledispatch
|
|
>>> @singledispatch
|
|
... def fun(arg, verbose=False):
|
|
... if verbose:
|
|
... print("Let me just say,", end=" ")
|
|
... print(arg)
|
|
|
|
To add overloaded implementations to the function, use the :func:`register`
|
|
attribute of the generic function. It is a decorator, taking a type
|
|
parameter and decorating a function implementing the operation for that
|
|
type::
|
|
|
|
>>> @fun.register(int)
|
|
... def _(arg, verbose=False):
|
|
... if verbose:
|
|
... print("Strength in numbers, eh?", end=" ")
|
|
... print(arg)
|
|
...
|
|
>>> @fun.register(list)
|
|
... def _(arg, verbose=False):
|
|
... if verbose:
|
|
... print("Enumerate this:")
|
|
... for i, elem in enumerate(arg):
|
|
... print(i, elem)
|
|
|
|
To enable registering lambdas and pre-existing functions, the
|
|
:func:`register` attribute can be used in a functional form::
|
|
|
|
>>> def nothing(arg, verbose=False):
|
|
... print("Nothing.")
|
|
...
|
|
>>> fun.register(type(None), nothing)
|
|
|
|
The :func:`register` attribute returns the undecorated function which
|
|
enables decorator stacking, pickling, as well as creating unit tests for
|
|
each variant independently::
|
|
|
|
>>> @fun.register(float)
|
|
... @fun.register(Decimal)
|
|
... def fun_num(arg, verbose=False):
|
|
... if verbose:
|
|
... print("Half of your number:", end=" ")
|
|
... print(arg / 2)
|
|
...
|
|
>>> fun_num is fun
|
|
False
|
|
|
|
When called, the generic function dispatches on the type of the first
|
|
argument::
|
|
|
|
>>> fun("Hello, world.")
|
|
Hello, world.
|
|
>>> fun("test.", verbose=True)
|
|
Let me just say, test.
|
|
>>> fun(42, verbose=True)
|
|
Strength in numbers, eh? 42
|
|
>>> fun(['spam', 'spam', 'eggs', 'spam'], verbose=True)
|
|
Enumerate this:
|
|
0 spam
|
|
1 spam
|
|
2 eggs
|
|
3 spam
|
|
>>> fun(None)
|
|
Nothing.
|
|
>>> fun(1.23)
|
|
0.615
|
|
|
|
Where there is no registered implementation for a specific type, its
|
|
method resolution order is used to find a more generic implementation.
|
|
The original function decorated with ``@singledispatch`` is registered
|
|
for the base ``object`` type, which means it is used if no better
|
|
implementation is found.
|
|
|
|
To check which implementation will the generic function choose for
|
|
a given type, use the ``dispatch()`` attribute::
|
|
|
|
>>> fun.dispatch(float)
|
|
<function fun_num at 0x1035a2840>
|
|
>>> fun.dispatch(dict) # note: default implementation
|
|
<function fun at 0x103fe0000>
|
|
|
|
To access all registered implementations, use the read-only ``registry``
|
|
attribute::
|
|
|
|
>>> fun.registry.keys()
|
|
dict_keys([<class 'NoneType'>, <class 'int'>, <class 'object'>,
|
|
<class 'decimal.Decimal'>, <class 'list'>,
|
|
<class 'float'>])
|
|
>>> fun.registry[float]
|
|
<function fun_num at 0x1035a2840>
|
|
>>> fun.registry[object]
|
|
<function fun at 0x103fe0000>
|
|
|
|
.. versionadded:: 3.4
|
|
|
|
|
|
.. function:: update_wrapper(wrapper, wrapped, assigned=WRAPPER_ASSIGNMENTS, updated=WRAPPER_UPDATES)
|
|
|
|
Update a *wrapper* function to look like the *wrapped* function. The optional
|
|
arguments are tuples to specify which attributes of the original function are
|
|
assigned directly to the matching attributes on the wrapper function and which
|
|
attributes of the wrapper function are updated with the corresponding attributes
|
|
from the original function. The default values for these arguments are the
|
|
module level constants *WRAPPER_ASSIGNMENTS* (which assigns to the wrapper
|
|
function's *__name__*, *__module__*, *__annotations__* and *__doc__*, the
|
|
documentation string) and *WRAPPER_UPDATES* (which updates the wrapper
|
|
function's *__dict__*, i.e. the instance dictionary).
|
|
|
|
To allow access to the original function for introspection and other purposes
|
|
(e.g. bypassing a caching decorator such as :func:`lru_cache`), this function
|
|
automatically adds a ``__wrapped__`` attribute to the wrapper that refers to
|
|
the function being wrapped.
|
|
|
|
The main intended use for this function is in :term:`decorator` functions which
|
|
wrap the decorated function and return the wrapper. If the wrapper function is
|
|
not updated, the metadata of the returned function will reflect the wrapper
|
|
definition rather than the original function definition, which is typically less
|
|
than helpful.
|
|
|
|
:func:`update_wrapper` may be used with callables other than functions. Any
|
|
attributes named in *assigned* or *updated* that are missing from the object
|
|
being wrapped are ignored (i.e. this function will not attempt to set them
|
|
on the wrapper function). :exc:`AttributeError` is still raised if the
|
|
wrapper function itself is missing any attributes named in *updated*.
|
|
|
|
.. versionadded:: 3.2
|
|
Automatic addition of the ``__wrapped__`` attribute.
|
|
|
|
.. versionadded:: 3.2
|
|
Copying of the ``__annotations__`` attribute by default.
|
|
|
|
.. versionchanged:: 3.2
|
|
Missing attributes no longer trigger an :exc:`AttributeError`.
|
|
|
|
.. versionchanged:: 3.4
|
|
The ``__wrapped__`` attribute now always refers to the wrapped
|
|
function, even if that function defined a ``__wrapped__`` attribute.
|
|
(see :issue:`17482`)
|
|
|
|
|
|
.. decorator:: wraps(wrapped, assigned=WRAPPER_ASSIGNMENTS, updated=WRAPPER_UPDATES)
|
|
|
|
This is a convenience function for invoking ``partial(update_wrapper,
|
|
wrapped=wrapped, assigned=assigned, updated=updated)`` as a function decorator
|
|
when defining a wrapper function. For example:
|
|
|
|
>>> from functools import wraps
|
|
>>> def my_decorator(f):
|
|
... @wraps(f)
|
|
... def wrapper(*args, **kwds):
|
|
... print('Calling decorated function')
|
|
... return f(*args, **kwds)
|
|
... return wrapper
|
|
...
|
|
>>> @my_decorator
|
|
... def example():
|
|
... """Docstring"""
|
|
... print('Called example function')
|
|
...
|
|
>>> example()
|
|
Calling decorated function
|
|
Called example function
|
|
>>> example.__name__
|
|
'example'
|
|
>>> example.__doc__
|
|
'Docstring'
|
|
|
|
Without the use of this decorator factory, the name of the example function
|
|
would have been ``'wrapper'``, and the docstring of the original :func:`example`
|
|
would have been lost.
|
|
|
|
|
|
.. _partial-objects:
|
|
|
|
:class:`partial` Objects
|
|
------------------------
|
|
|
|
:class:`partial` objects are callable objects created by :func:`partial`. They
|
|
have three read-only attributes:
|
|
|
|
|
|
.. attribute:: partial.func
|
|
|
|
A callable object or function. Calls to the :class:`partial` object will be
|
|
forwarded to :attr:`func` with new arguments and keywords.
|
|
|
|
|
|
.. attribute:: partial.args
|
|
|
|
The leftmost positional arguments that will be prepended to the positional
|
|
arguments provided to a :class:`partial` object call.
|
|
|
|
|
|
.. attribute:: partial.keywords
|
|
|
|
The keyword arguments that will be supplied when the :class:`partial` object is
|
|
called.
|
|
|
|
:class:`partial` objects are like :class:`function` objects in that they are
|
|
callable, weak referencable, and can have attributes. There are some important
|
|
differences. For instance, the :attr:`__name__` and :attr:`__doc__` attributes
|
|
are not created automatically. Also, :class:`partial` objects defined in
|
|
classes behave like static methods and do not transform into bound methods
|
|
during instance attribute look-up.
|
|
|