And here I was thinking arrays were for JavaScript and lists were for Python

Python has arrays. Python even has an entirely special module that lets you build arrays. Like arrays in Java and C++, arrays from the arrays module must all be of a certain type of data. I assume these things must be wicked fast, but I wonder how large the array would have to be before there would be a noticeable difference.

Having nothing further to say about single-type arrays, let us proceed with the code!

import array

a = array.array('c', 'check out my sick array')

print "As array:", a

In our first little snippet here, we’re turning a string into an array to start conducting experiments. The first parameter - 'c' - specifies that this array will be full of characters.

a.extend(', it has so many bytes')

print a

print a[10:23]

We continue fiddling with our array by extending it. We can also slice arrays into smaller arrays, as we see here.

output_data = open('array-ex', 'wb')



Arrays built using array.array() have a built-in function to save the data to a file. By opening a file object, calling tofile(file_name) on the array, and flushing the file object, we write our array to disk.

input_data = open('array-ex', 'rb')

raw_data =

print 'Raw data:', raw_data

We’ve extracted our raw data from the file as binary information. To read it into a new array we’ll do the following:

second_array = array.array('c')

second_array.fromfile(input_data, len(a))

print second_array

And that’s about it for arrays. Super easy on memory, super fast, and useful in situations where performance is critical.

  • special thanks to PYMOTW for some inspiration on stuff to do with arrays as examples