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Clean Code in Python

Simplifying Code through Iterators

Explore how Python iterators and the itertools module can simplify your code by reducing repeated loops and flattening nested iterations. Learn to create cleaner, more maintainable code by leveraging generator functions and idiomatic iteration patterns, improving efficiency and readability.

We'll cover the following...

Now, let's briefly discuss some situations that can be improved with the help of iterators and occasionally the itertools module. After discussing each case, and its proposed optimization, we'll close each point with a corollary.

Repeated iterations

Now that we have seen more about iterators and introduced the itertools module, we can show you how one of the first examples of this chapter (the one for computing statistics about some purchases) can be dramatically simplified:

Python 3.8
import logging
from itertools import tee
from statistics import median
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
def produce_values(how_many):
    for i in range(1, how_many + 1):
        logger.debug("producing purchase %i", i)
        yield i
def process_purchases(purchases):
    min_, max_, avg = tee(purchases, 3)
    return min(min_), max(max_), median(avg)
def main():
    data = produce_values(7)
    obtained = process_purchases(data)
    logger.info("Obtained: %s", obtained)
    assert obtained == (1, 7, 4)
if __name__ == "__main__":
    main()

In this example, itertools.tee will split the original iterable into three new ones. We will use each of these for the different kinds of iterations that we require, without needing to repeat three different loops over purchases. ...