Problem Statement
I would like to apply a list of functions fs = [ f, g, h ]
sequentially to a string text=' abCdEf '
Something like f( g( h( text) ) )
where f,g,h in fs
This could easily be accomplished with the following code:
# initial text
text = ' abCDef '
# list of functions to apply sequentially
fs = [str.rstrip, str.lstrip, str.lower]
for f in fs:
text = f(text)
# expected result is 'abcdef' with spaces stripped, and all lowercase
print(text)
Using list comprehension
I tried using list comprehension, but it simply creates a list of every function call:
[ f(text) for f in fs ]
[' abCDef', 'abCDef ', ' abcdef ']
Using functools.reduce
It seems that functools.reduce
should do the job here, since it "consumes" the list of functions at each iteration.
from functools import reduce
reduce(f(text), fs)
# first interaction should call
y = str.rstrip(' abCDef ') --> ' abCDef'
# next iterations fails, because tries to call ' abCDef'() -- as a function
Unfortunately, this code doesn't work, since each iteration returns a string istead of a function, and fails with TypeError: 'str' object is not callable
.
QUESTION: Is there any solution using map, reduce
or list comprehension
to this problem?
CodePudding user response:
reduce
can take three arguments:
reduce(function, iterable, initializer)
What are these three arguments in general?
function
is a function of two arguments. Let's call these two argumentst
andf
.- the first argument,
t
, will start asinitializer
; then will continue as the return value of the previous call offunction
. - the second argument,
f
, is taken fromiterable
.
What are these three arguments in our case?
- the iterable is your list of function;
- the second argument
f
is going to be one of the functions; - the first argument
t
must be the text; - the initializer must be the initial text;
- the return of
function
must be the resulting text; function(t, f)
must bef(t)
.
Finally:
from functools import reduce
# initial text
text = ' abCDef '
# list of functions to apply sequentially
fs = [str.rstrip, str.lstrip, str.lower]
result = reduce(lambda t,f: f(t), fs, text)
print(result)
# abcdef
CodePudding user response:
You can try this:
import functools
text = ' abCDef '
fs = [str.rstrip, str.lstrip, str.lower]
text = functools.reduce(lambda store, func: func(store), fs, text)
print(text)
I think you have misunderstood how reduce works. Reduce reduces an iterable into a single value. The callback function can take two arguments, a store and a element.
The reduce function first creates a store variable. Then, looping through the iterable, it calls the function with the store variable and the current element, and updating the store to the returned value. Finally, the function returns the store value. The final argument is what the store variable starts with.
So in the snippet, it loops through the function array, and calls the respective function on it. The lambda will then return the processed value, updating the store.
CodePudding user response:
Here's an alternative solution, which allows you to compose any number of functions and save the composed function for reuse:
import functools as ft
def compose(*funcs):
return ft.reduce(lambda f, g: lambda x: f(g(x)), funcs)
Usage:
In [4]: strip_and_lower = compose(str.rstrip, str.lstrip, str.lower)
In [5]: strip_and_lower(' abCDef ')
Out[5]: 'abcdef'
In [6]: strip_and_lower(" AJWEGIAJWGIAWJWGIWAJ ")
Out[6]: 'ajwegiajwgiawjwgiwaj'
In [7]: strip_lower_title = compose(str.title, str.lower, str.strip)
In [8]: strip_lower_title(" hello world ")
Out[8]: 'Hello World'
Note that the order of functions matters; this works just like mathematical function composition, i.e., (f . g . h)(x) = f(g(h(x))
so the functions are applied from right to left.
CodePudding user response:
Since you also asked for a map
solution, here is one. My values
contains single-element iterables, values[0]
has the original value and values[i]
has the value after applying the first i
functions.
text = ' abCDef '
fs = [str.rstrip, str.lstrip, str.lower]
values = [[text]]
values = map(map, fs, values)
result = next(values[-1])
print(repr(result)) # prints 'abcdef'
But I wouldn't recommend this. I was mostly curious whether I can do it. And now I'll try to think of how to avoid building that auxiliary list.