HiveBrain v1.2.0
Get Started
← Back to all entries
snippetpythonModerate

Make this implementation of counting sort Pythonic

Submitted by: @import:stackexchange-codereview··
0
Viewed 0 times
thispythoniccountingmakesortimplementation

Problem

This is my crude attempt at implementing a counting sort algorithm. My goal is to be able to sort lists of ints, negative and positive. As you can see I've employed such hacks as return res[1:] to get by. I'd appreciate any feedback I can get to make this a more pythonic implementation.

def find_min(a_list):
    min = a_list[0]
    for item in a_list:
        if item  max:
            max = item
    return max

def counting_sort(a_list):
    min = find_min(a_list)
    max = find_max(a_list)

    counts = [0] * (abs(max) + abs(min) + 1)

    for i in range(0, len(a_list), 1):
        counts[a_list[i] - min] += 1

    sum = 0
    for j in range(0, len(counts), 1):
        sum += counts[j]
        counts[j] = sum

    res = [0] * (len(a_list)+1)
    for k in range(0, len(a_list), 1):
        res_index = counts[a_list[k]-min]
        res[res_index] = a_list[k]
        counts[a_list[k]-min] -= 1

    return res[1:]

Solution

My two cents:

You can get rid of def find_min(a_list): and def find_max(a_list):. Instead, use python's built-ins min() and max():

min(iterable[, key])


Return the smallest item in an iterable
or the smallest of two or more arguments.


If one positional argument is provided, iterable must be a non-empty
iterable (such as a non-empty string, tuple or list). The smallest
item in the iterable is returned. If two or more positional arguments
are provided, the smallest of the positional arguments is returned.

max(iterable[, key])


Return the largest item in an iterable or the
largest of two or more arguments.


If one positional argument is provided, iterable must be a non-empty
iterable (such as a non-empty string, tuple or list). The largest item
in the iterable is returned. If two or more positional arguments are
provided, the largest of the positional arguments is returned.

So you'll have:

...
min_element, max_element = min(a_list), max(a_list)
...


Now, regarding you algorithm, you can avoid those hacks you were talking about by rewriting your function as:

def count_sort(array):
    min_element, max_element = min(array), max(array)
    count_array = [0] * (max_element - min_element + 1)

    for val in array:
        count_array[val - min_element] += 1

    sorted_array = []
    for i in range(min_element, max_element + 1):
        if count_array[i - min_element] > 0:
            for j in range(0, count_array[i - min_element]):
                sorted_array.append(i)

    return sorted_array


More, as @ChatterOne mentioned, instead of the final for loop with append, you could do:

sorted_array.extend([i] * count_array[i - min_element])


So, your final code would look like this:

def count_sort(array):
    min_element, max_element = min(array), max(array)
    count_array = [0] * (max_element - min_element + 1)

    for val in array:
        count_array[val - min_element] += 1

    sorted_array = []
    for i in range(min_element, max_element + 1):
        if count_array[i - min_element] > 0:
            for j in range(0, count_array[i - min_element]):
                sorted_array.append(i)

    return sorted_array

if __name__ == '__main__':
    my_array = [3, 2, -1, 1, 5, 0, 10, 18, 25, 25]
    print(count_sort(my_array))


or

def count_sort(array):
    min_element, max_element = min(array), max(array)
    count_array = [0] * (max_element - min_element + 1)

    for val in array:
        count_array[val - min_element] += 1

    sorted_array = []
    for i in range(min_element, max_element + 1):
        if count_array[i - min_element] > 0:
            sorted_array.extend([i] * count_array[i - min_element])

    return sorted_array

if __name__ == '__main__':
    my_array = [3, 2, -1, 1, 5, 0, 10, 18, 25, 25]
    print(count_sort(my_array))


Extras:

You can see that I also added if __name__ == '__main__'. By doing the main check, you can have that code execute only when you want to run the module as a program, and not have it execute when someone just wants to import your module and call your functions themselves.

I also changed the names min and max(which are already built-ins in Python) to min_element and max_element, respectively.

And the result:

[-1, 0, 1, 2, 3, 5, 10, 18, 25, 25]

Code Snippets

...
min_element, max_element = min(a_list), max(a_list)
...
def count_sort(array):
    min_element, max_element = min(array), max(array)
    count_array = [0] * (max_element - min_element + 1)

    for val in array:
        count_array[val - min_element] += 1

    sorted_array = []
    for i in range(min_element, max_element + 1):
        if count_array[i - min_element] > 0:
            for j in range(0, count_array[i - min_element]):
                sorted_array.append(i)

    return sorted_array
sorted_array.extend([i] * count_array[i - min_element])
def count_sort(array):
    min_element, max_element = min(array), max(array)
    count_array = [0] * (max_element - min_element + 1)

    for val in array:
        count_array[val - min_element] += 1

    sorted_array = []
    for i in range(min_element, max_element + 1):
        if count_array[i - min_element] > 0:
            for j in range(0, count_array[i - min_element]):
                sorted_array.append(i)

    return sorted_array


if __name__ == '__main__':
    my_array = [3, 2, -1, 1, 5, 0, 10, 18, 25, 25]
    print(count_sort(my_array))
def count_sort(array):
    min_element, max_element = min(array), max(array)
    count_array = [0] * (max_element - min_element + 1)

    for val in array:
        count_array[val - min_element] += 1

    sorted_array = []
    for i in range(min_element, max_element + 1):
        if count_array[i - min_element] > 0:
            sorted_array.extend([i] * count_array[i - min_element])

    return sorted_array


if __name__ == '__main__':
    my_array = [3, 2, -1, 1, 5, 0, 10, 18, 25, 25]
    print(count_sort(my_array))

Context

StackExchange Code Review Q#149069, answer score: 10

Revisions (0)

No revisions yet.