Composing functions in python
Solution 1
It doesn't work because all the anonymous functions you create in the loop refer to the same loop variable and therefore share its final value.
As a quick fix, you can replace the assignment with:
final = lambda x, f=f, final=final: f(final(x))
Or, you can return the lambda from a function:
def wrap(accum, f):
return lambda x: f(accum(x))
...
final = wrap(final, f)
To understand what's going on, try this experiment:
>>> l = [lambda: n for n in xrange(10)]
>>> [f() for f in l]
[9, 9, 9, 9, 9, 9, 9, 9, 9, 9]
This result surprises many people, who expect the result to be [0, 1, 2, ...]
. However, all the lambdas point to the same n
variable, and all refer to its final value, which is 9. In your case, all the versions of final
which are supposed to nest end up referring to the same f
and, even worse, to the same final
.
The topic of lambdas and for loops in Python has been already covered on SO.
Solution 2
The easiest approach would be first to write a composition of 2 functions:
def compose2(f, g):
return lambda *a, **kw: f(g(*a, **kw))
And then use reduce
to compose more functions:
import functools
def compose(*fs):
return functools.reduce(compose2, fs)
Or you can use some library, which already contains compose function.
Solution 3
def compose (*functions):
def inner(arg):
for f in reversed(functions):
arg = f(arg)
return arg
return inner
Example:
>>> def square (x):
return x ** 2
>>> def increment (x):
return x + 1
>>> def half (x):
return x / 2
>>> composed = compose(square, increment, half) # square(increment(half(x)))
>>> composed(5) # square(increment(half(5))) = square(increment(2.5)) = square(3.5) = 12,25
12.25
Solution 4
Recursive implementation
Here's a fairly elegant recursive implementation, which uses features of Python 3 for clarity:
def strict_compose(*funcs):
*funcs, penultimate, last = funcs
if funcs:
penultimate = strict_compose(*funcs, penultimate)
return lambda *args, **kwargs: penultimate(last(*args, **kwargs))
Python 2 compatible version:
def strict_compose2(*funcs):
if len(funcs) > 2:
penultimate = strict_compose2(*funcs[:-1])
else:
penultimate = funcs[-2]
return lambda *args, **kwargs: penultimate(funcs[-1](*args, **kwargs))
This is an earlier version which uses lazy evaluation of the recursion:
def lazy_recursive_compose(*funcs):
def inner(*args, _funcs=funcs, **kwargs):
if len(_funcs) > 1:
return inner(_funcs[-1](*args, **kwargs), _funcs=_funcs[:-1])
else:
return _funcs[0](*args, **kwargs)
return inner
Both would seem to make a new tuple and dict of arguments each recursive call.
Comparison of all suggestions:
Let's test some of these implementations and determine which is most performant, first some single argument functions (Thank you poke):
def square(x):
return x ** 2
def increment(x):
return x + 1
def half(x):
return x / 2
Here's our implementations, I suspect my iterative version is the second most efficient (manual compose will naturally be fastest), but that may be in part due to it sidestepping the difficulty of passing any number of arguments or keyword arguments between functions - in most cases we'll only see the trivial one argument being passed.
from functools import reduce
def strict_recursive_compose(*funcs):
*funcs, penultimate, last = funcs
if funcs:
penultimate = strict_recursive_compose(*funcs, penultimate)
return lambda *args, **kwargs: penultimate(last(*args, **kwargs))
def strict_recursive_compose2(*funcs):
if len(funcs) > 2:
penultimate = strict_recursive_compose2(*funcs[:-1])
else:
penultimate = funcs[-2]
return lambda *args, **kwargs: penultimate(funcs[-1](*args, **kwargs))
def lazy_recursive_compose(*funcs):
def inner(*args, _funcs=funcs, **kwargs):
if len(_funcs) > 1:
return inner(_funcs[-1](*args, **kwargs), _funcs=_funcs[:-1])
else:
return _funcs[0](*args, **kwargs)
return inner
def iterative_compose(*functions):
"""my implementation, only accepts one argument."""
def inner(arg):
for f in reversed(functions):
arg = f(arg)
return arg
return inner
def _compose2(f, g):
return lambda *a, **kw: f(g(*a, **kw))
def reduce_compose1(*fs):
return reduce(_compose2, fs)
def reduce_compose2(*funcs):
"""bug fixed - added reversed()"""
return lambda x: reduce(lambda acc, f: f(acc), reversed(funcs), x)
And to test these:
import timeit
def manual_compose(n):
return square(increment(half(n)))
composes = (strict_recursive_compose, strict_recursive_compose2,
lazy_recursive_compose, iterative_compose,
reduce_compose1, reduce_compose2)
print('manual compose', min(timeit.repeat(lambda: manual_compose(5))), manual_compose(5))
for compose in composes:
fn = compose(square, increment, half)
result = min(timeit.repeat(lambda: fn(5)))
print(compose.__name__, result, fn(5))
Results
And we get the following output (same magnitude and proportion in Python 2 and 3):
manual compose 0.4963762479601428 12.25
strict_recursive_compose 0.6564744340721518 12.25
strict_recursive_compose2 0.7216697579715401 12.25
lazy_recursive_compose 1.260614730999805 12.25
iterative_compose 0.614982972969301 12.25
reduce_compose1 0.6768529079854488 12.25
reduce_compose2 0.9890829260693863 12.25
And my expectations were confirmed: the fastest is of course, manual function composition followed by the iterative implementation. The lazy recursive version is much slower - likely since a new stack frame is created by each function call and a new tuple of functions is created for each function.
For a better and perhaps more realistic comparison, if you remove **kwargs
and change *args
to arg
in the functions, the ones that used them will be more performant, and we can better compare apples to apples - here, aside from manual composition, reduce_compose1 wins followed by the strict_recursive_compose:
manual compose 0.443808660027571 12.25
strict_recursive_compose 0.5409777010791004 12.25
strict_recursive_compose2 0.5698030130006373 12.25
lazy_recursive_compose 1.0381018499610946 12.25
iterative_compose 0.619289995986037 12.25
reduce_compose1 0.49532539502251893 12.25
reduce_compose2 0.9633988010464236 12.25
Functions with just one arg:
def strict_recursive_compose(*funcs):
*funcs, penultimate, last = funcs
if funcs:
penultimate = strict_recursive_compose(*funcs, penultimate)
return lambda arg: penultimate(last(arg))
def strict_recursive_compose2(*funcs):
if len(funcs) > 2:
penultimate = strict_recursive_compose2(*funcs[:-1])
else:
penultimate = funcs[-2]
return lambda arg: penultimate(funcs[-1](arg))
def lazy_recursive_compose(*funcs):
def inner(arg, _funcs=funcs):
if len(_funcs) > 1:
return inner(_funcs[-1](arg), _funcs=_funcs[:-1])
else:
return _funcs[0](arg)
return inner
def iterative_compose(*functions):
"""my implementation, only accepts one argument."""
def inner(arg):
for f in reversed(functions):
arg = f(arg)
return arg
return inner
def _compose2(f, g):
return lambda arg: f(g(arg))
def reduce_compose1(*fs):
return reduce(_compose2, fs)
def reduce_compose2(*funcs):
"""bug fixed - added reversed()"""
return lambda x: reduce(lambda acc, f: f(acc), reversed(funcs), x)
Solution 5
One liner:
compose = lambda *F: reduce(lambda f, g: lambda x: f(g(x)), F)
Example usage:
f1 = lambda x: x+3
f2 = lambda x: x*2
f3 = lambda x: x-1
g = compose(f1, f2, f3)
assert(g(7) == 15)
Starless
Updated on December 02, 2021Comments
-
Starless over 2 years
I have an array of functions and I'm trying to produce one function which consists of the composition of the elements in my array. My approach is:
def compose(list): if len(list) == 1: return lambda x:list[0](x) list.reverse() final=lambda x:x for f in list: final=lambda x:f(final(x)) return final
This method doesn't seems to be working, help will be appreciated.
(I'm reversing the list because this is the order of composition I want the functions to be)
-
Starless about 11 yearsThanks for the answer, it indeed worked for me. I used the second method. Can you explain what do you mean by "final closures refer to the same f cell", and also can you please explain the first method.
-
WestCoastProjects over 5 yearsCan you show how (/is it even possible) to add an aggregation step - presuming the chained functions are operating on collections?
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WestCoastProjects over 5 yearsCan you show how (/is it even possible) to add an aggregation step - presuming the chained functions are operating on collections?
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poke over 5 years@javadba I’m not sure what you mean. Can you give an example for what you would like to do?
-
WestCoastProjects over 5 yearsConsider the functions might be :
(add 5 to x, mult by 3, *find top 3*, *sum*)
. the "top3" and "sum" are aggregations that I don't know how to insert into the composition. -
poke over 5 years@javadba You could surely do that, although I would say that it looks a bit complicated then:
compose(sum, lambda x: sorted(x, reverse=True)[:3], lambda x: map(lambda y: y * 3, x), lambda x: map(lambda y: y + 5, x))
– You could also justmap
once with a composed function:compose(sum, lambda x: sorted(x, reverse=True)[:3], lambda x: map(compose(lambda y: y * 3, lambda y: y + 5), x))
. So if you named them nicely, it could look like this:compose(sum, top3, lambda x: map(compose(times3, plus5), x))
. You could also get rid of thatlambda
by usingfunctools.partial
. -
Amir over 5 yearsThis is going to create a shadow function for every function in
fs
. I don’t know how much functions in Python are resource intensive, but that seems wasteful. Instead, see other solution by Imanol Luengo:def compose(*funcs): return lambda x: reduce(lambda acc, f: f(acc), funcs, x)
(stackoverflow.com/a/16739663/216138) -
Suor over 5 yearsYou can bench it, but your solution will be probably slower. For most common case of 2 functions mine is zero cost.
-
RussAbbott over 5 yearsHere's an interesting alternative. Replace
l
withl = [lambda x=n: x for n in range(10)]
This produces[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
as one might expect. -
user4815162342 over 5 years@RussAbbott That's the gist of the "quick fix" proposed near the beginning of the answer. In that pattern the convention is to name the keyword the same as the variable you are capturing, e.g.
lambda n=n: ...
. -
Rexcirus over 4 yearsreduce is functools.reduce in python3
-
0-_-0 almost 4 yearsMind that
compose(a,b,c)
will result in the following ordera(b(c(input)))
-
Relative0 over 3 yearsThis is interesting to me because of the procedural execution - however (in python 3) on print(compose(10)) I get: <function compose.<locals>.<lambda>.<locals>.<lambda> at 0x000002E51BF3FDC0> I'm not sure what I need to do to get the value.
-
mmj about 2 yearsIf you want no dependencies the 2 functions solution can be generalized with recursion: stackoverflow.com/a/71713702/694360
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philosofool about 2 yearsThis is going to throw an error if
arg
evaluates to false. For example, if0
is the value of arg. -
philosofool about 2 yearsThis solution cannot be adapted to cases for arbitrary arguments (i.e., *args, **kwargs) because
return *args
is a syntax error.