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== Usage == == Function Composition ==
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The module provides `partial` and `partialmethod` functions for function composition.
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Try:
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=== @Cache === {{{
from functools import partial

basetwo = partial(int, base=2)
basetwo('10010') # 18
}}}

`partialmethod` is used in exactly the same way, and just manages the `self`.

{{{
class Cat:
    def say(self, message):
        print(message)

    meow = partialmethod(say, "Meow!")
}}}

The module also exposes two objects (`functools.Placeholder` and `functools.partial`) which are implementation details of these functions.
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=== @Cached_Property === == Function Overloading ==

The module provides `singledispatch` and `singledispatchmethod` decorators for function overloading.

Try:

{{{
from functools import singledispatch

@singledispatch
def makebigger(arg):
    print(arg + 1)

@makebigger.register
def _(arg: string):
    print(arg + "s")

@makebigger.register
def _(list: string):
    print(arg.append(0))
}}}

`singledispatchmethod` is used in exactly the same way, and just dispatches on the second argument (i.e., does not dispatch on the `self`).
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=== Cmp_To_Key === == Memoization ==

The module provides the `lru_cache` and `cache` decorators for memoization.

{{{
@lru_cache(maxsize=None)
def fib(n):
    if n < 2:
        return n
    return fib(n-1) + fib(n-2)
}}}

Note that `cache` is the same as `lru_cache(maxsize=None)`.

`cached_property` can be made to work in a similar way.
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=== @Lru_Cache === == Others ==
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---- ||'''Function Names''' ||'''Description'''||
||`functools.cmp_to_key` || ||
||`functools.reduce` || ||
||`functools.update_wrapper`|| ||
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=== Partial ===

----



=== PartialMethod ===

----



=== Reduce ===

----



=== @SingleDispatch ===

----



=== @SingleDispatchMethod ===

----



=== Update_Wrapper ===

----



=== @Total_Ordering ===

----



=== @Wraps ===		 ||'''Decorator Names''' ||'''Description'''||
||`functools.total_ordering`|| ||
||`functools.wraps` || ||
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[[https://pymotw.com/3/functools/|Python Module of the Day article for functools]]

Python Functools

functools is a module supporting the construction of efficient functions.

Contents

  1. Python Functools
    1. Function Composition
    2. Function Overloading
    3. Memoization
    4. Others
    5. See also

Function Composition

The module provides partial and partialmethod functions for function composition.

Try: 

from functools import partial

basetwo = partial(int, base=2)
basetwo('10010')               # 18

partialmethod is used in exactly the same way, and just manages the self. 

class Cat:
    def say(self, message):
        print(message)

    meow = partialmethod(say, "Meow!")

The module also exposes two objects (functools.Placeholder and functools.partial) which are implementation details of these functions.

Function Overloading

The module provides singledispatch and singledispatchmethod decorators for function overloading.

Try: 

from functools import singledispatch

@singledispatch
def makebigger(arg):
    print(arg + 1)

@makebigger.register
def _(arg: string):
    print(arg + "s")

@makebigger.register
def _(list: string):
    print(arg.append(0))

singledispatchmethod is used in exactly the same way, and just dispatches on the second argument (i.e., does not dispatch on the self).

Memoization

The module provides the lru_cache and cache decorators for memoization. 

@lru_cache(maxsize=None)
def fib(n):
    if n < 2:
        return n
    return fib(n-1) + fib(n-2)

Note that cache is the same as lru_cache(maxsize=None).

cached_property can be made to work in a similar way.

Others

Function Names

Description

functools.cmp_to_key

functools.reduce

functools.update_wrapper

Decorator Names

Description

functools.total_ordering

functools.wraps

See also

Python functools module documentation

Python Module of the Day article for functools

CategoryRicottone

Python/FuncTools (last edited 2025-12-23 04:34:48 by DominicRicottone)