looping_performance.py

"""
The results of the script are used in blog article called
"Revisiting the Mechanism Behind the `for` Statement" hosted at
https://mylette.rs/revisiting-the-mechanism-behind-the-for-statement.
Purpose: The script measures the performance of iterating over all
elements in an iterable with two different implementation methods, namely
using Pythonic and non-Pythonic design patterns. See functions
`loop_pythonic` and `loop_with_indexes` for details.
Requirements: Python version >= 3.3
License: MIT License (see https://opensource.org/licenses/MIT)
"""
from functools import wraps
from time import perf_counter

ITERABLE = range(1000000) # <-- change here e.g. ITERABLE = list(range(1000000))


def timeit(func):
    """Minimalistic decorator for timing the performance of `func`"""
    @wraps(func)
    def chronometer(*args):
        t1 = perf_counter()
        rv = func(*args)
        t2 = perf_counter()
        print("{:=^40}".format(func.__qualname__))
        print(f"Elapsed time: {t2 - t1} s")
        return rv
    return chronometer


@timeit
def loop_for(iterable):
    """Retrieve elements of `iterable` with the for-loop

    Demonstrates the Pythonic way of iterating over objects.
    """
    for item in iterable:
        item
    return None


@timeit
def loop_indexes(iterable):
    """Retrieve elements of `iterable` with indexes

    Demonstrates non-Pythonic way of iterating over objects.
    """
    for index in range(len(iterable)):
        iterable[index]
    return None


@timeit
def loop_while(iterable):
    """Retrieve elements of `iterable` with the while-loop

   Demonstrates the mechanism behind the for-loop.
   """
    _i = iter(iterable)
    _loop = True
    while _loop:
        try:
            item = next(_i)
        except StopIteration:
            _loop = False
        else:
            item
    return None


if __name__ == "__main__":
    loop_for(ITERABLE)
    loop_indexes(ITERABLE)
    loop_while(ITERABLE)