# Given a list of lists `t`,
#
# ```python
# flat_list = [item for sublist in t for item in sublist]
# ```
#
# which means:
flat_list = []
for sublist in t:
for item in sublist:
flat_list.append(item)
# is faster than the shortcuts posted so far. (`t` is the list to
# flatten.)
#
# Here is the corresponding function:
flatten = lambda t: [item for sublist in t for item in sublist]
# As evidence, you can use the `timeit` module in the standard library:
$ python -mtimeit -s't=[[1,2,3],[4,5,6], [7], [8,9]]*99' '[item for sublist in t for item in sublist]'
10000 loops, best of 3: 143 usec per loop
$ python -mtimeit -s't=[[1,2,3],[4,5,6], [7], [8,9]]*99' 'sum(t, [])'
1000 loops, best of 3: 969 usec per loop
$ python -mtimeit -s't=[[1,2,3],[4,5,6], [7], [8,9]]*99' 'reduce(lambda x,y: x+y,t)'
1000 loops, best of 3: 1.1 msec per loop
# Explanation: the shortcuts based on `+` (including the implied use in
# `sum`) are, of necessity, `O(T**2)` when there are T sublists -- as
# the intermediate result list keeps getting longer, at each step a new
# intermediate result list object gets allocated, and all the items in
# the previous intermediate result must be copied over (as well as a few
# new ones added at the end). So, for simplicity and without actual loss
# of generality, say you have T sublists of k items each: the first k
# items are copied back and forth T-1 times, the second k items T-2
# times, and so on; total number of copies is k times the sum of x for x
# from 1 to T excluded, i.e., `k * (T**2)/2`.
#
# The list comprehension just generates one list, once, and copies each
# item over (from its original place of residence to the result list)
# also exactly once.
#
# [Alex Martelli] [so/q/952914] [cc by-sa 3.0]
$
cheat.sh