Convert a nested for loop to a map equivalent

Question

Example:

for x in iterable1:
    expression

The map form would be:

map(lambda x: expression, iterable1)

How do I extend this to a nested for loop using only map and without list comprehensions?

Example:

for x in itr1:
    for y in itr2:
        expr

Answer 1

You could use itertools.product to build the cartesian product of your two nested sequences, and map your expression to the that list of 2-tuples:

from itertools import product

map(lambda (x, y): expression, product(itr1, itr2))

Example with some actual values:

seq = map(lambda (x, y): '%s:%s' % (x, y), product(itr1, itr2))
for item in seq:
    print item

Note that the lambda (x, y) is necessary to unpack each 2-tuple from the sequence to the separate x and y arguments used in the expression.

Answer 2

Bear with me on this one. Not an explanation but this worked after 2 days. Using only map and list. It's bad code. Suggestions to shorten the code are welcome. Python 3 solution

Example using list comprehension:

>>> a=[x+y for x in [0,1,2] for y in [100,200,300]]
>>> a
[100,200,300,101,201,301,102,202,302]

Example using for:

>>>a=[]
>>>for x in [0,1,2]:
...    for y in [100,200,300]:
...        a.append(x+y)
...
>>>a
[100,200,300,101,201,301,102,202,302]

Now example using only map:

>>>n=[]
>>>list(map(lambda x:n.extend(map(x,[100,200,300])),map(lambda x:lambda y:x+y,[0,1,2])))
>>>n
[100,200,300,101,201,301,102,202,302]

Much smaller python2.7 solution:

>>>m=[]
>>>map(lambda x:m.extend(x),map(lambda x:map(x,[100,200,300]),map(lambda x:lambda y:x+y,[0,1,2])))
>>>m
[100,200,300,101,201,301,102,202,302]

Another variation : I emailed to Mark Lutz and this was his solution. This doesn't use closures and is the closest to nested for loops functionality.

>>> X = [0, 1, 2]               
>>> Y = [100, 200, 300]
>>> n = []
>>> t = list(map(lambda x: list(map(lambda y: n.append(x + y), Y)),X))
>>> n
[100,200,300,101,201,301,102,202,302]