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 <section id="module-functools">
<h1><a class="reference internal" href="#module-functools" title="functools: Higher-order functions and operations on callable objects."><code class="xref py py-mod docutils literal notranslate">functools</code></a> — Higher-order functions and operations on callable objects<a class="headerlink" href="#module-functools" title="Permalink to this headline">¶</a></h1>
Source code: <a class="reference external" href="https://github.com/python/cpython/tree/3.10/Lib/functools.py">Lib/functools.py</a>
<hr class="docutils" />
The <a class="reference internal" href="#module-functools" title="functools: Higher-order functions and operations on callable objects."><code class="xref py py-mod docutils literal notranslate">functools</code></a> 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 <a class="reference internal" href="#module-functools" title="functools: Higher-order functions and operations on callable objects."><code class="xref py py-mod docutils literal notranslate">functools</code></a> module defines the following functions:
<dl class="py function">
<dt class="sig sig-object py" id="functools.cache">
&#64;functools.cache(user_function)<a class="headerlink" href="#functools.cache" title="Permalink to this definition">¶</a></dt>
<dd>Simple lightweight unbounded function cache. Sometimes called
<a class="reference external" href="https://en.wikipedia.org/wiki/Memoization">“memoize”</a>.
Returns the same as <code class="docutils literal notranslate">lru_cache(maxsize=None)</code>, creating a thin
wrapper around a dictionary lookup for the function arguments. Because it
never needs to evict old values, this is smaller and faster than
<a class="reference internal" href="#functools.lru_cache" title="functools.lru_cache"><code class="xref py py-func docutils literal notranslate">lru_cache()</code></a> with a size limit.
For example:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>@cache
def factorial(n):
 return n * factorial(n-1) if n else 1

&gt;&gt;&gt; factorial(10) # no previously cached result, makes 11 recursive calls
3628800
&gt;&gt;&gt; factorial(5) # just looks up cached value result
120
&gt;&gt;&gt; factorial(12) # makes two new recursive calls, the other 10 are cached
479001600
</pre></div>
</div>
<div class="versionadded">
New in version 3.9.
</div>
</dd></dl>

<dl class="py function">
<dt class="sig sig-object py" id="functools.cached_property">
&#64;functools.cached_property(func)<a class="headerlink" href="#functools.cached_property" title="Permalink to this definition">¶</a></dt>
<dd>Transform a method of a class into a property whose value is computed once
and then cached as a normal attribute for the life of the instance. Similar
to <a class="reference internal" href="functions.html#property" title="property"><code class="xref py py-func docutils literal notranslate">property()</code></a>, with the addition of caching. Useful for expensive
computed properties of instances that are otherwise effectively immutable.
Example:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>class DataSet:

def __init__(self, sequence_of_numbers):
 self._data = tuple(sequence_of_numbers)

@cached_property
 def stdev(self):
 return statistics.stdev(self._data)
</pre></div>
</div>
The mechanics of <a class="reference internal" href="#functools.cached_property" title="functools.cached_property"><code class="xref py py-func docutils literal notranslate">cached_property()</code></a> are somewhat different from
<a class="reference internal" href="functions.html#property" title="property"><code class="xref py py-func docutils literal notranslate">property()</code></a>. A regular property blocks attribute writes unless a
setter is defined. In contrast, a cached_property allows writes.
The cached_property decorator only runs on lookups and only when an
attribute of the same name doesn’t exist. When it does run, the
cached_property writes to the attribute with the same name. Subsequent
attribute reads and writes take precedence over the cached_property
method and it works like a normal attribute.
The cached value can be cleared by deleting the attribute. This
allows the cached_property method to run again.
Note, this decorator interferes with the operation of <a class="pep reference external" href="https://www.python.org/dev/peps/pep-0412">PEP 412</a>
key-sharing dictionaries. This means that instance dictionaries
can take more space than usual.
Also, this decorator requires that the <code class="docutils literal notranslate">__dict__</code> attribute on each instance
be a mutable mapping. This means it will not work with some types, such as
metaclasses (since the <code class="docutils literal notranslate">__dict__</code> attributes on type instances are
read-only proxies for the class namespace), and those that specify
<code class="docutils literal notranslate">__slots__</code> without including <code class="docutils literal notranslate">__dict__</code> as one of the defined slots
(as such classes don’t provide a <code class="docutils literal notranslate">__dict__</code> attribute at all).
If a mutable mapping is not available or if space-efficient key sharing
is desired, an effect similar to <a class="reference internal" href="#functools.cached_property" title="functools.cached_property"><code class="xref py py-func docutils literal notranslate">cached_property()</code></a> can be achieved
by a stacking <a class="reference internal" href="functions.html#property" title="property"><code class="xref py py-func docutils literal notranslate">property()</code></a> on top of <a class="reference internal" href="#functools.cache" title="functools.cache"><code class="xref py py-func docutils literal notranslate">cache()</code></a>:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>class DataSet:
 def __init__(self, sequence_of_numbers):
 self._data = sequence_of_numbers

@property
 @cache
 def stdev(self):
 return statistics.stdev(self._data)
</pre></div>
</div>
<div class="versionadded">
New in version 3.8.
</div>
</dd></dl>

<dl class="py function">
<dt class="sig sig-object py" id="functools.cmp_to_key">
functools.cmp_to_key(func)<a class="headerlink" href="#functools.cmp_to_key" title="Permalink to this definition">¶</a></dt>
<dd>Transform an old-style comparison function to a <a class="reference internal" href="../glossary.html#term-key-function">key function</a>. Used
with tools that accept key functions (such as <a class="reference internal" href="functions.html#sorted" title="sorted"><code class="xref py py-func docutils literal notranslate">sorted()</code></a>, <a class="reference internal" href="functions.html#min" title="min"><code class="xref py py-func docutils literal notranslate">min()</code></a>,
<a class="reference internal" href="functions.html#max" title="max"><code class="xref py py-func docutils literal notranslate">max()</code></a>, <a class="reference internal" href="heapq.html#heapq.nlargest" title="heapq.nlargest"><code class="xref py py-func docutils literal notranslate">heapq.nlargest()</code></a>, <a class="reference internal" href="heapq.html#heapq.nsmallest" title="heapq.nsmallest"><code class="xref py py-func docutils literal notranslate">heapq.nsmallest()</code></a>,
<a class="reference internal" href="itertools.html#itertools.groupby" title="itertools.groupby"><code class="xref py py-func docutils literal notranslate">itertools.groupby()</code></a>). 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 accepts 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 to be used as the sort key.
Example:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>sorted(iterable, key=cmp_to_key(locale.strcoll)) # locale-aware sort order
</pre></div>
</div>
For sorting examples and a brief sorting tutorial, see <a class="reference internal" href="../howto/sorting.html#sortinghowto">Sorting HOW TO</a>.
<div class="versionadded">
New in version 3.2.
</div>
</dd></dl>

<dl class="py function">
<dt class="sig sig-object py" id="functools.lru_cache">
&#64;functools.lru_cache(user_function)<a class="headerlink" href="#functools.lru_cache" title="Permalink to this definition">¶</a></dt>
<dt class="sig sig-object py">
&#64;functools.lru_cache(maxsize=128, typed=False)</dt>
<dd>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 <a class="reference internal" href="../glossary.html#term-hashable">hashable</a>.
Distinct argument patterns may be considered to be distinct calls with
separate cache entries. For example, <cite>f(a=1, b=2)</cite> and <cite>f(b=2, a=1)</cite>
differ in their keyword argument order and may have two separate cache
entries.
If user_function is specified, it must be a callable. This allows the
lru_cache decorator to be applied directly to a user function, leaving
the maxsize at its default value of 128:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>@lru_cache
def count_vowels(sentence):
 return sum(sentence.count(vowel) for vowel in &#39;AEIOUaeiou&#39;)
</pre></div>
</div>
If maxsize is set to <code class="docutils literal notranslate">None</code>, the LRU feature is disabled and the cache can
grow without bound.
If typed is set to true, function arguments of different types will be
cached separately. If typed is false, the implementation will usually
regard them as equivalent calls and only cache a single result. (Some
types such as str and int may be cached separately even when typed
is false.)
Note, type specificity applies only to the function’s immediate arguments
rather than their contents. The scalar arguments, <code class="docutils literal notranslate">Decimal(42)</code> and
<code class="docutils literal notranslate">Fraction(42)</code> are be treated as distinct calls with distinct results.
In contrast, the tuple arguments <code class="docutils literal notranslate">('answer', Decimal(42))</code> and
<code class="docutils literal notranslate">('answer', Fraction(42))</code> are treated as equivalent.
The wrapped function is instrumented with a <code class="xref py py-func docutils literal notranslate">cache_parameters()</code>
function that returns a new <a class="reference internal" href="stdtypes.html#dict" title="dict"><code class="xref py py-class docutils literal notranslate">dict</code></a> showing the values for maxsize
and typed. This is for information purposes only. Mutating the values
has no effect.
To help measure the effectiveness of the cache and tune the maxsize
parameter, the wrapped function is instrumented with a <code class="xref py py-func docutils literal notranslate">cache_info()</code>
function that returns a <a class="reference internal" href="../glossary.html#term-named-tuple">named tuple</a> showing hits, misses,
maxsize and currsize.
The decorator also provides a <code class="xref py py-func docutils literal notranslate">cache_clear()</code> function for clearing or
invalidating the cache.
The original underlying function is accessible through the
<code class="xref py py-attr docutils literal notranslate">__wrapped__</code> attribute. This is useful for introspection, for
bypassing the cache, or for rewrapping the function with a different cache.
The cache keeps references to the arguments and return values until they age
out of the cache or until the cache is cleared.
An <a class="reference external" href="https://en.wikipedia.org/wiki/Cache_replacement_policies#Least_recently_used_(LRU)">LRU (least recently used) cache</a>
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.
In general, the LRU cache should only be used when you want to reuse
previously computed values. Accordingly, it doesn’t make sense to cache
functions with side-effects, functions that need to create distinct mutable
objects on each call, or impure functions such as time() or random().
Example of an LRU cache for static web content:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>@lru_cache(maxsize=32)
def get_pep(num):
 &#39;Retrieve text of a Python Enhancement Proposal&#39;
 resource = &#39;https://www.python.org/dev/peps/pep-%04d/&#39; % num
 try:
 with urllib.request.urlopen(resource) as s:
 return s.read()
 except urllib.error.HTTPError:
 return &#39;Not Found&#39;

&gt;&gt;&gt; for n in 8, 290, 308, 320, 8, 218, 320, 279, 289, 320, 9991:
... pep = get_pep(n)
... print(n, len(pep))

&gt;&gt;&gt; get_pep.cache_info()
CacheInfo(hits=3, misses=8, maxsize=32, currsize=8)
</pre></div>
</div>
Example of efficiently computing
<a class="reference external" href="https://en.wikipedia.org/wiki/Fibonacci_number">Fibonacci numbers</a>
using a cache to implement a
<a class="reference external" href="https://en.wikipedia.org/wiki/Dynamic_programming">dynamic programming</a>
technique:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>@lru_cache(maxsize=None)
def fib(n):
 if n &lt; 2:
 return n
 return fib(n-1) + fib(n-2)

&gt;&gt;&gt; [fib(n) for n in range(16)]
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610]

&gt;&gt;&gt; fib.cache_info()
CacheInfo(hits=28, misses=16, maxsize=None, currsize=16)
</pre></div>
</div>
<div class="versionadded">
New in version 3.2.
</div>
<div class="versionchanged">
Changed in version 3.3: Added the typed option.
</div>
<div class="versionchanged">
Changed in version 3.8: Added the user_function option.
</div>
<div class="versionadded">
New in version 3.9: Added the function <code class="xref py py-func docutils literal notranslate">cache_parameters()</code>
</div>
</dd></dl>

<dl class="py function">
<dt class="sig sig-object py" id="functools.total_ordering">
&#64;functools.total_ordering<a class="headerlink" href="#functools.total_ordering" title="Permalink to this definition">¶</a></dt>
<dd>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 <code class="xref py py-meth docutils literal notranslate">__lt__()</code>, <code class="xref py py-meth docutils literal notranslate">__le__()</code>,
<code class="xref py py-meth docutils literal notranslate">__gt__()</code>, or <code class="xref py py-meth docutils literal notranslate">__ge__()</code>.
In addition, the class should supply an <code class="xref py py-meth docutils literal notranslate">__eq__()</code> method.
For example:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>@total_ordering
class Student:
 def _is_valid_operand(self, other):
 return (hasattr(other, &quot;lastname&quot;) and
 hasattr(other, &quot;firstname&quot;))
 def __eq__(self, other):
 if not self._is_valid_operand(other):
 return NotImplemented
 return ((self.lastname.lower(), self.firstname.lower()) ==
 (other.lastname.lower(), other.firstname.lower()))
 def __lt__(self, other):
 if not self._is_valid_operand(other):
 return NotImplemented
 return ((self.lastname.lower(), self.firstname.lower()) &lt;
 (other.lastname.lower(), other.firstname.lower()))
</pre></div>
</div>
<div class="admonition note">
Note
While this decorator makes it easy to create well behaved totally
ordered types, it does come at the cost of slower execution and
more complex stack traces for the derived comparison methods. If
performance benchmarking indicates this is a bottleneck for a given
application, implementing all six rich comparison methods instead is
likely to provide an easy speed boost.
</div>
<div class="admonition note">
Note
This decorator makes no attempt to override methods that have been
declared in the class or its superclasses. Meaning that if a
superclass defines a comparison operator, total_ordering will not
implement it again, even if the original method is abstract.
</div>
<div class="versionadded">
New in version 3.2.
</div>
<div class="versionchanged">
Changed in version 3.4: Returning NotImplemented from the underlying comparison function for
unrecognised types is now supported.
</div>
</dd></dl>

<dl class="py function">
<dt class="sig sig-object py" id="functools.partial">
functools.partial(func, /, *args, **keywords)<a class="headerlink" href="#functools.partial" title="Permalink to this definition">¶</a></dt>
<dd>Return a new <a class="reference internal" href="#partial-objects">partial object</a> 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:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>def partial(func, /, *args, **keywords):
 def newfunc(*fargs, **fkeywords):
 newkeywords = {**keywords, **fkeywords}
 return func(*args, *fargs, **newkeywords)
 newfunc.func = func
 newfunc.args = args
 newfunc.keywords = keywords
 return newfunc
</pre></div>
</div>
The <a class="reference internal" href="#functools.partial" title="functools.partial"><code class="xref py py-func docutils literal notranslate">partial()</code></a> 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, <a class="reference internal" href="#functools.partial" title="functools.partial"><code class="xref py py-func docutils literal notranslate">partial()</code></a> can be used to create
a callable that behaves like the <a class="reference internal" href="functions.html#int" title="int"><code class="xref py py-func docutils literal notranslate">int()</code></a> function where the base argument
defaults to two:
<div class="doctest highlight-default notranslate"><div class="highlight"><pre>&gt;&gt;&gt; from functools import partial
&gt;&gt;&gt; basetwo = partial(int, base=2)
&gt;&gt;&gt; basetwo.__doc__ = &#39;Convert base 2 string to an int.&#39;
&gt;&gt;&gt; basetwo(&#39;10010&#39;)
18
</pre></div>
</div>
</dd></dl>

<dl class="py class">
<dt class="sig sig-object py" id="functools.partialmethod">
class functools.partialmethod(func, /, *args, **keywords)<a class="headerlink" href="#functools.partialmethod" title="Permalink to this definition">¶</a></dt>
<dd>Return a new <a class="reference internal" href="#functools.partialmethod" title="functools.partialmethod"><code class="xref py py-class docutils literal notranslate">partialmethod</code></a> descriptor which behaves
like <a class="reference internal" href="#functools.partial" title="functools.partial"><code class="xref py py-class docutils literal notranslate">partial</code></a> except that it is designed to be used as a method
definition rather than being directly callable.
func must be a <a class="reference internal" href="../glossary.html#term-descriptor">descriptor</a> or a callable (objects which are both,
like normal functions, are handled as descriptors).
When func is a descriptor (such as a normal Python function,
<a class="reference internal" href="functions.html#classmethod" title="classmethod"><code class="xref py py-func docutils literal notranslate">classmethod()</code></a>, <a class="reference internal" href="functions.html#staticmethod" title="staticmethod"><code class="xref py py-func docutils literal notranslate">staticmethod()</code></a>, <code class="xref py py-func docutils literal notranslate">abstractmethod()</code> or
another instance of <a class="reference internal" href="#functools.partialmethod" title="functools.partialmethod"><code class="xref py py-class docutils literal notranslate">partialmethod</code></a>), calls to <code class="docutils literal notranslate">__get__</code> are
delegated to the underlying descriptor, and an appropriate
<a class="reference internal" href="#partial-objects">partial object</a> returned as the result.
When func is a non-descriptor callable, an appropriate bound method is
created dynamically. This behaves like a normal Python function when
used as a method: the self argument will be inserted as the first
positional argument, even before the args and keywords supplied to
the <a class="reference internal" href="#functools.partialmethod" title="functools.partialmethod"><code class="xref py py-class docutils literal notranslate">partialmethod</code></a> constructor.
Example:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>&gt;&gt;&gt; class Cell:
... def __init__(self):
... self._alive = False
... @property
... def alive(self):
... return self._alive
... def set_state(self, state):
... self._alive = bool(state)
... set_alive = partialmethod(set_state, True)
... set_dead = partialmethod(set_state, False)
...
&gt;&gt;&gt; c = Cell()
&gt;&gt;&gt; c.alive
False
&gt;&gt;&gt; c.set_alive()
&gt;&gt;&gt; c.alive
True
</pre></div>
</div>
<div class="versionadded">
New in version 3.4.
</div>
</dd></dl>

<dl class="py function">
<dt class="sig sig-object py" id="functools.reduce">
functools.reduce(function, iterable[, initializer])<a class="headerlink" href="#functools.reduce" title="Permalink to this definition">¶</a></dt>
<dd>Apply function of two arguments cumulatively to the items of iterable, from
left to right, so as to reduce the iterable to a single value. For example,
<code class="docutils literal notranslate">reduce(lambda x, y: x+y, [1, 2, 3, 4, 5])</code> calculates <code class="docutils literal notranslate">((((1+2)+3)+4)+5)</code>.
The left argument, x, is the accumulated value and the right argument, y, is
the update value from the iterable. If the optional initializer is present,
it is placed before the items of the iterable in the calculation, and serves as
a default when the iterable is empty. If initializer is not given and
iterable contains only one item, the first item is returned.
Roughly equivalent to:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>def reduce(function, iterable, initializer=None):
 it = iter(iterable)
 if initializer is None:
 value = next(it)
 else:
 value = initializer
 for element in it:
 value = function(value, element)
 return value
</pre></div>
</div>
See <a class="reference internal" href="itertools.html#itertools.accumulate" title="itertools.accumulate"><code class="xref py py-func docutils literal notranslate">itertools.accumulate()</code></a> for an iterator that yields all intermediate
values.
</dd></dl>

<dl class="py function">
<dt class="sig sig-object py" id="functools.singledispatch">
&#64;functools.singledispatch<a class="headerlink" href="#functools.singledispatch" title="Permalink to this definition">¶</a></dt>
<dd>Transform a function into a <a class="reference internal" href="../glossary.html#term-single-dispatch">single-dispatch</a> <a class="reference internal" href="../glossary.html#term-generic-function">generic function</a>.
To define a generic function, decorate it with the <code class="docutils literal notranslate">&#64;singledispatch</code>
decorator. When defining a function using <code class="docutils literal notranslate">&#64;singledispatch</code>, note that the
dispatch happens on the type of the first argument:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>&gt;&gt;&gt; from functools import singledispatch
&gt;&gt;&gt; @singledispatch
... def fun(arg, verbose=False):
... if verbose:
... print(&quot;Let me just say,&quot;, end=&quot; &quot;)
... print(arg)
</pre></div>
</div>
To add overloaded implementations to the function, use the <code class="xref py py-func docutils literal notranslate">register()</code>
attribute of the generic function, which can be used as a decorator. For
functions annotated with types, the decorator will infer the type of the
first argument automatically:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>&gt;&gt;&gt; @fun.register
... def _(arg: int, verbose=False):
... if verbose:
... print(&quot;Strength in numbers, eh?&quot;, end=&quot; &quot;)
... print(arg)
...
&gt;&gt;&gt; @fun.register
... def _(arg: list, verbose=False):
... if verbose:
... print(&quot;Enumerate this:&quot;)
... for i, elem in enumerate(arg):
... print(i, elem)
</pre></div>
</div>
For code which doesn’t use type annotations, the appropriate type
argument can be passed explicitly to the decorator itself:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>&gt;&gt;&gt; @fun.register(complex)
... def _(arg, verbose=False):
... if verbose:
... print(&quot;Better than complicated.&quot;, end=&quot; &quot;)
... print(arg.real, arg.imag)
...
</pre></div>
</div>
To enable registering <a class="reference internal" href="../glossary.html#term-lambda">lambdas</a> and pre-existing functions,
the <code class="xref py py-func docutils literal notranslate">register()</code> attribute can also be used in a functional form:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>&gt;&gt;&gt; def nothing(arg, verbose=False):
... print(&quot;Nothing.&quot;)
...
&gt;&gt;&gt; fun.register(type(None), nothing)
</pre></div>
</div>
The <code class="xref py py-func docutils literal notranslate">register()</code> attribute returns the undecorated function. This
enables decorator stacking, <a class="reference internal" href="pickle.html#module-pickle" title="pickle: Convert Python objects to streams of bytes and back."><code class="xref py py-mod docutils literal notranslate">pickling</code></a>, and the creation
of unit tests for each variant independently:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>&gt;&gt;&gt; @fun.register(float)
... @fun.register(Decimal)
... def fun_num(arg, verbose=False):
... if verbose:
... print(&quot;Half of your number:&quot;, end=&quot; &quot;)
... print(arg / 2)
...
&gt;&gt;&gt; fun_num is fun
False
</pre></div>
</div>
When called, the generic function dispatches on the type of the first
argument:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>&gt;&gt;&gt; fun(&quot;Hello, world.&quot;)
Hello, world.
&gt;&gt;&gt; fun(&quot;test.&quot;, verbose=True)
Let me just say, test.
&gt;&gt;&gt; fun(42, verbose=True)
Strength in numbers, eh? 42
&gt;&gt;&gt; fun([&#39;spam&#39;, &#39;spam&#39;, &#39;eggs&#39;, &#39;spam&#39;], verbose=True)
Enumerate this:
0 spam
1 spam
2 eggs
3 spam
&gt;&gt;&gt; fun(None)
Nothing.
&gt;&gt;&gt; fun(1.23)
0.615
</pre></div>
</div>
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 <code class="docutils literal notranslate">&#64;singledispatch</code> is registered
for the base <a class="reference internal" href="functions.html#object" title="object"><code class="xref py py-class docutils literal notranslate">object</code></a> type, which means it is used if no better
implementation is found.
If an implementation is registered to an <a class="reference internal" href="../glossary.html#term-abstract-base-class">abstract base class</a>,
virtual subclasses of the base class will be dispatched to that
implementation:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>&gt;&gt;&gt; from collections.abc import Mapping
&gt;&gt;&gt; @fun.register
... def _(arg: Mapping, verbose=False):
... if verbose:
... print(&quot;Keys &amp; Values&quot;)
... for key, value in arg.items():
... print(key, &quot;=&gt;&quot;, value)
...
&gt;&gt;&gt; fun({&quot;a&quot;: &quot;b&quot;})
a =&gt; b
</pre></div>
</div>
To check which implementation the generic function will choose for
a given type, use the <code class="docutils literal notranslate">dispatch()</code> attribute:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>&gt;&gt;&gt; fun.dispatch(float)
&lt;function fun_num at 0x1035a2840&gt;
&gt;&gt;&gt; fun.dispatch(dict) # note: default implementation
&lt;function fun at 0x103fe0000&gt;
</pre></div>
</div>
To access all registered implementations, use the read-only <code class="docutils literal notranslate">registry</code>
attribute:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>&gt;&gt;&gt; fun.registry.keys()
dict_keys([&lt;class &#39;NoneType&#39;&gt;, &lt;class &#39;int&#39;&gt;, &lt;class &#39;object&#39;&gt;,
 &lt;class &#39;decimal.Decimal&#39;&gt;, &lt;class &#39;list&#39;&gt;,
 &lt;class &#39;float&#39;&gt;])
&gt;&gt;&gt; fun.registry[float]
&lt;function fun_num at 0x1035a2840&gt;
&gt;&gt;&gt; fun.registry[object]
&lt;function fun at 0x103fe0000&gt;
</pre></div>
</div>
<div class="versionadded">
New in version 3.4.
</div>
<div class="versionchanged">
Changed in version 3.7: The <code class="xref py py-func docutils literal notranslate">register()</code> attribute now supports using type annotations.
</div>
</dd></dl>

<dl class="py class">
<dt class="sig sig-object py" id="functools.singledispatchmethod">
class functools.singledispatchmethod(func)<a class="headerlink" href="#functools.singledispatchmethod" title="Permalink to this definition">¶</a></dt>
<dd>Transform a method into a <a class="reference internal" href="../glossary.html#term-single-dispatch">single-dispatch</a> <a class="reference internal" href="../glossary.html#term-generic-function">generic function</a>.
To define a generic method, decorate it with the <code class="docutils literal notranslate">&#64;singledispatchmethod</code>
decorator. When defining a function using <code class="docutils literal notranslate">&#64;singledispatchmethod</code>, note
that the dispatch happens on the type of the first non-self or non-cls
argument:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>class Negator:
 @singledispatchmethod
 def neg(self, arg):
 raise NotImplementedError(&quot;Cannot negate a&quot;)

@neg.register
 def _(self, arg: bool):
 return not arg
</pre></div>
</div>
<code class="docutils literal notranslate">&#64;singledispatchmethod</code> supports nesting with other decorators such as
<a class="reference internal" href="functions.html#classmethod" title="classmethod"><code class="xref py py-func docutils literal notranslate">&#64;classmethod</code></a>. Note that to allow for
<code class="docutils literal notranslate">dispatcher.register</code>, <code class="docutils literal notranslate">singledispatchmethod</code> must be the outer most
decorator. Here is the <code class="docutils literal notranslate">Negator</code> class with the <code class="docutils literal notranslate">neg</code> methods bound to
the class, rather than an instance of the class:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>class Negator:
 @singledispatchmethod
 @classmethod
 def neg(cls, arg):
 raise NotImplementedError(&quot;Cannot negate a&quot;)

@neg.register
 @classmethod
 def _(cls, arg: bool):
 return not arg
</pre></div>
</div>
The same pattern can be used for other similar decorators:
<a class="reference internal" href="functions.html#staticmethod" title="staticmethod"><code class="xref py py-func docutils literal notranslate">&#64;staticmethod</code></a>,
<a class="reference internal" href="abc.html#abc.abstractmethod" title="abc.abstractmethod"><code class="xref py py-func docutils literal notranslate">&#64;abstractmethod</code></a>, and others.
<div class="versionadded">
New in version 3.8.
</div>
</dd></dl>

<dl class="py function">
<dt class="sig sig-object py" id="functools.update_wrapper">
functools.update_wrapper(wrapper, wrapped, assigned=WRAPPER_ASSIGNMENTS, updated=WRAPPER_UPDATES)<a class="headerlink" href="#functools.update_wrapper" title="Permalink to this definition">¶</a></dt>
<dd>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 <code class="docutils literal notranslate">WRAPPER_ASSIGNMENTS</code> (which assigns to the wrapper
function’s <code class="docutils literal notranslate">__module__</code>, <code class="docutils literal notranslate">__name__</code>, <code class="docutils literal notranslate">__qualname__</code>, <code class="docutils literal notranslate">__annotations__</code>
and <code class="docutils literal notranslate">__doc__</code>, the documentation string) and <code class="docutils literal notranslate">WRAPPER_UPDATES</code> (which
updates the wrapper function’s <code class="docutils literal notranslate">__dict__</code>, 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 <a class="reference internal" href="#functools.lru_cache" title="functools.lru_cache"><code class="xref py py-func docutils literal notranslate">lru_cache()</code></a>), this function
automatically adds a <code class="docutils literal notranslate">__wrapped__</code> attribute to the wrapper that refers to
the function being wrapped.
The main intended use for this function is in <a class="reference internal" href="../glossary.html#term-decorator">decorator</a> 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.
<a class="reference internal" href="#functools.update_wrapper" title="functools.update_wrapper"><code class="xref py py-func docutils literal notranslate">update_wrapper()</code></a> 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). <a class="reference internal" href="exceptions.html#AttributeError" title="AttributeError"><code class="xref py py-exc docutils literal notranslate">AttributeError</code></a> is still raised if the
wrapper function itself is missing any attributes named in updated.
<div class="versionadded">
New in version 3.2: Automatic addition of the <code class="docutils literal notranslate">__wrapped__</code> attribute.
</div>
<div class="versionadded">
New in version 3.2: Copying of the <code class="docutils literal notranslate">__annotations__</code> attribute by default.
</div>
<div class="versionchanged">
Changed in version 3.2: Missing attributes no longer trigger an <a class="reference internal" href="exceptions.html#AttributeError" title="AttributeError"><code class="xref py py-exc docutils literal notranslate">AttributeError</code></a>.
</div>
<div class="versionchanged">
Changed in version 3.4: The <code class="docutils literal notranslate">__wrapped__</code> attribute now always refers to the wrapped
function, even if that function defined a <code class="docutils literal notranslate">__wrapped__</code> attribute.
(see <a class="reference external" href="https://bugs.python.org/issue?&#64;action=redirect&amp;bpo=17482">bpo-17482</a>)
</div>
</dd></dl>

<dl class="py function">
<dt class="sig sig-object py" id="functools.wraps">
&#64;functools.wraps(wrapped, assigned=WRAPPER_ASSIGNMENTS, updated=WRAPPER_UPDATES)<a class="headerlink" href="#functools.wraps" title="Permalink to this definition">¶</a></dt>
<dd>This is a convenience function for invoking <a class="reference internal" href="#functools.update_wrapper" title="functools.update_wrapper"><code class="xref py py-func docutils literal notranslate">update_wrapper()</code></a> as a
function decorator when defining a wrapper function. It is equivalent to
<code class="docutils literal notranslate">partial(update_wrapper, wrapped=wrapped, assigned=assigned, updated=updated)</code>.
For example:
<div class="highlight-python3 notranslate"><div class="highlight"><pre>&gt;&gt;&gt; from functools import wraps
&gt;&gt;&gt; def my_decorator(f):
... @wraps(f)
... def wrapper(*args, **kwds):
... print(&#39;Calling decorated function&#39;)
... return f(*args, **kwds)
... return wrapper
...
&gt;&gt;&gt; @my_decorator
... def example():
... &quot;&quot;&quot;Docstring&quot;&quot;&quot;
... print(&#39;Called example function&#39;)
...
&gt;&gt;&gt; example()
Calling decorated function
Called example function
&gt;&gt;&gt; example.__name__
&#39;example&#39;
&gt;&gt;&gt; example.__doc__
&#39;Docstring&#39;
</pre></div>
</div>
Without the use of this decorator factory, the name of the example function
would have been <code class="docutils literal notranslate">'wrapper'</code>, and the docstring of the original <code class="xref py py-func docutils literal notranslate">example()</code>
would have been lost.
</dd></dl>

<section id="partial-objects">
<h2><a class="reference internal" href="#functools.partial" title="functools.partial"><code class="xref py py-class docutils literal notranslate">partial</code></a> Objects<a class="headerlink" href="#partial-objects" title="Permalink to this headline">¶</a></h2>
<a class="reference internal" href="#functools.partial" title="functools.partial"><code class="xref py py-class docutils literal notranslate">partial</code></a> objects are callable objects created by <a class="reference internal" href="#functools.partial" title="functools.partial"><code class="xref py py-func docutils literal notranslate">partial()</code></a>. They
have three read-only attributes:
<dl class="py attribute">
<dt class="sig sig-object py" id="functools.partial.func">
partial.func<a class="headerlink" href="#functools.partial.func" title="Permalink to this definition">¶</a></dt>
<dd>A callable object or function. Calls to the <a class="reference internal" href="#functools.partial" title="functools.partial"><code class="xref py py-class docutils literal notranslate">partial</code></a> object will be
forwarded to <a class="reference internal" href="#functools.partial.func" title="functools.partial.func"><code class="xref py py-attr docutils literal notranslate">func</code></a> with new arguments and keywords.
</dd></dl>

<dl class="py attribute">
<dt class="sig sig-object py" id="functools.partial.args">
partial.args<a class="headerlink" href="#functools.partial.args" title="Permalink to this definition">¶</a></dt>
<dd>The leftmost positional arguments that will be prepended to the positional
arguments provided to a <a class="reference internal" href="#functools.partial" title="functools.partial"><code class="xref py py-class docutils literal notranslate">partial</code></a> object call.
</dd></dl>

<dl class="py attribute">
<dt class="sig sig-object py" id="functools.partial.keywords">
partial.keywords<a class="headerlink" href="#functools.partial.keywords" title="Permalink to this definition">¶</a></dt>
<dd>The keyword arguments that will be supplied when the <a class="reference internal" href="#functools.partial" title="functools.partial"><code class="xref py py-class docutils literal notranslate">partial</code></a> object is
called.
</dd></dl>

<a class="reference internal" href="#functools.partial" title="functools.partial"><code class="xref py py-class docutils literal notranslate">partial</code></a> objects are like <code class="xref py py-class docutils literal notranslate">function</code> objects in that they are
callable, weak referencable, and can have attributes. There are some important
differences. For instance, the <a class="reference internal" href="stdtypes.html#definition.__name__" title="definition.__name__"><code class="xref py py-attr docutils literal notranslate">__name__</code></a> and <code class="xref py py-attr docutils literal notranslate">__doc__</code> attributes
are not created automatically. Also, <a class="reference internal" href="#functools.partial" title="functools.partial"><code class="xref py py-class docutils literal notranslate">partial</code></a> objects defined in
classes behave like static methods and do not transform into bound methods
during instance attribute look-up.
</section>
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