Why do I need itertools.count?

Sometimes you need an endless stream of numbers or an infinite iterator. Writing loops or generator functions for such simple tasks can become cumbersome or unclear. Thankfully, Python's built-in itertools module provides a neat and readable solution with count.

Let's see an example.

Example without itertools.count

A common example is when you need continuous incremental indices. Without count, you might write something like this:

def index_generator(start=0, step=1):
    n = start
    while True:
        yield n
        n += step

counter = index_generator(5, 2)

for _ in range(5):
    print(next(counter))

Output:

5
7
9
11
13

This works, but Python gives us a better built-in way.

Example with itertools.count

itertools.count makes this significantly simpler and cleaner.

from itertools import count

counter = count(start=5, step=2)

for _ in range(5):
    print(next(counter))

Output:

5
7
9
11
13

Practical use-case

count is also very handy when pairing with other tools like zip() to effortlessly create indexed lists:

from itertools import count

fruits = ['apple', 'banana', 'orange']
indexed_fruits = list(zip(count(1), fruits))

print(indexed_fruits)

Output:

[(1, 'apple'), (2, 'banana'), (3, 'orange')]

Compared to manually managing counters, this approach is concise, readable, and reliable.

Conclusion

While creating a manual counter is straightforward, using itertools.count makes your code more expressive and reduces potential bugs or inconsistencies in managing loop indices or incremental counts. As a general rule, whenever you find yourself creating a custom incremental generator or manually incrementing a variable repeatedly, consider using count from itertools instead.