You might need to check out numpy.flatten and numpy.ravel, both return a 1-d array from an n-d array.

Furthermore, if you're not going to modify the returned 1-d array, I suggest you use numpy.ravel, since it doesn't make a copy of the array, but just return a view of the array, which is much faster than numpy.flatten.

>>>a = np.arange(10000).reshape((100,100))

>>>%timeit a.flatten()
100000 loops, best of 3: 4.02 µs per loop

>>>%timeit a.ravel()
1000000 loops, best of 3: 412 ns per loop

Also check out this post.

A list of lists named xss can be flattened using a nested list comprehension:

flat_list = [
    x
    for xs in xss
    for x in xs
]

The above is equivalent to:

flat_list = []

for xs in xss:
    for x in xs:
        flat_list.append(x)

Here is the corresponding function:

def flatten(xss):
    return [x for xs in xss for x in xs]

This is the fastest method. As evidence, using the timeit module in the standard library, we see:

$ python -mtimeit -s'xss=[[1,2,3],[4,5,6],[7],[8,9]]*99' '[x for xs in xss for x in xs]'
10000 loops, best of 3: 143 usec per loop

$ python -mtimeit -s'xss=[[1,2,3],[4,5,6],[7],[8,9]]*99' 'sum(xss, [])'
1000 loops, best of 3: 969 usec per loop

$ python -mtimeit -s'xss=[[1,2,3],[4,5,6],[7],[8,9]]*99' 'reduce(lambda xs, ys: xs + ys, xss)'
1000 loops, best of 3: 1.1 msec per loop

Explanation: the methods based on + (including the implied use in sum) are, of necessity, O(L**2) when there are L 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 L sublists of M items each: the first M items are copied back and forth L-1 times, the second M items L-2 times, and so on; total number of copies is M times the sum of x for x from 1 to L excluded, i.e., M * (L**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.