The functional module hasn't been maintained since 2006 and doesn't work with Python 3.
Remove section about it from the functional programming FAQ.
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Antoine Pitrou
commit
b53e2c4900
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@ -1010,135 +1010,6 @@ Some of the functions in this module are:
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Consult the operator module's documentation for a complete list.
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The functional module
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---------------------
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Collin Winter's `functional module <http://oakwinter.com/code/functional/>`__
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provides a number of more advanced tools for functional programming. It also
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reimplements several Python built-ins, trying to make them more intuitive to
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those used to functional programming in other languages.
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This section contains an introduction to some of the most important functions in
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``functional``; full documentation can be found at `the project's website
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<http://oakwinter.com/code/functional/documentation/>`__.
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``compose(outer, inner, unpack=False)``
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The ``compose()`` function implements function composition. In other words, it
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returns a wrapper around the ``outer`` and ``inner`` callables, such that the
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return value from ``inner`` is fed directly to ``outer``. That is, ::
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>>> def add(a, b):
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... return a + b
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...
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>>> def double(a):
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... return 2 * a
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...
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>>> compose(double, add)(5, 6)
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22
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is equivalent to ::
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>>> double(add(5, 6))
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22
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The ``unpack`` keyword is provided to work around the fact that Python functions
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are not always `fully curried <http://en.wikipedia.org/wiki/Currying>`__. By
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default, it is expected that the ``inner`` function will return a single object
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and that the ``outer`` function will take a single argument. Setting the
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``unpack`` argument causes ``compose`` to expect a tuple from ``inner`` which
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will be expanded before being passed to ``outer``. Put simply, ::
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compose(f, g)(5, 6)
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is equivalent to::
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f(g(5, 6))
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while ::
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compose(f, g, unpack=True)(5, 6)
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is equivalent to::
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f(*g(5, 6))
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Even though ``compose()`` only accepts two functions, it's trivial to build up a
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version that will compose any number of functions. We'll use
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:func:`functools.reduce`, ``compose()`` and ``partial()`` (the last of which is
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provided by both ``functional`` and ``functools``). ::
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from functional import compose, partial
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import functools
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multi_compose = partial(functools.reduce, compose)
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We can also use ``map()``, ``compose()`` and ``partial()`` to craft a version of
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``"".join(...)`` that converts its arguments to string::
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from functional import compose, partial
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join = compose("".join, partial(map, str))
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``flip(func)``
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``flip()`` wraps the callable in ``func`` and causes it to receive its
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non-keyword arguments in reverse order. ::
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>>> def triple(a, b, c):
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... return (a, b, c)
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...
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>>> triple(5, 6, 7)
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(5, 6, 7)
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>>>
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>>> flipped_triple = flip(triple)
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>>> flipped_triple(5, 6, 7)
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(7, 6, 5)
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``foldl(func, start, iterable)``
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``foldl()`` takes a binary function, a starting value (usually some kind of
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'zero'), and an iterable. The function is applied to the starting value and the
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first element of the list, then the result of that and the second element of the
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list, then the result of that and the third element of the list, and so on.
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This means that a call such as::
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foldl(f, 0, [1, 2, 3])
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is equivalent to::
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f(f(f(0, 1), 2), 3)
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``foldl()`` is roughly equivalent to the following recursive function::
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def foldl(func, start, seq):
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if len(seq) == 0:
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return start
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return foldl(func, func(start, seq[0]), seq[1:])
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Speaking of equivalence, the above ``foldl`` call can be expressed in terms of
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the built-in :func:`functools.reduce` like so::
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import functools
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functools.reduce(f, [1, 2, 3], 0)
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We can use ``foldl()``, ``operator.concat()`` and ``partial()`` to write a
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cleaner, more aesthetically-pleasing version of Python's ``"".join(...)``
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idiom::
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from functional import foldl, partial from operator import concat
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join = partial(foldl, concat, "")
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Small functions and the lambda expression
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=========================================
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