5 Python Idioms to Write Faster, More Memory‑Efficient Code

Python is praised for its simplicity and versatility, but writing idiomatic code that balances readability with execution speed and memory efficiency is essential for professional developers.

a. range() – Instead of manually listing numbers, use the built‑in range() function. It generates the sequence lazily and supports start, stop, and step arguments, making loops scalable from a few items to millions.

for i in [2,3,4,5,6,7,8,9,10]:
    print(i)

for i in range(2, 11):
    print(i)

for i in range(2, 11, 2):
    print(i)  # 2 4 6 8 10

When iterating over a list, range(len(list)) can be replaced by direct iteration.

cloths = ['shirt', 'hat', 'socks', 'shorts']
for i in range(len(cloths)):
    print(cloths[i])

for cloth in cloths:
    print(cloth)

b. zip() – Combine multiple iterables element‑wise. The built‑in zip() works with any number of sequences.

colours = ['pink', 'red', 'green']
cloths = ['shirt', 'hat', 'socks', 'shorts']
for colour, cloth in zip(colours, cloths):
    print(colour, cloth)
# Output: pink shirt, red hat, green socks

c. reversed() – Iterate a sequence backwards without manual index calculations.

cloths = ['shirt', 'hat', 'socks', 'shorts']
for cloth in reversed(cloths):
    print(cloth)
# Output: shorts, socks, hat, shirt

d. enumerate() – Access both index and element in a loop cleanly.

cloths = ['shirt', 'hat', 'socks', 'shorts']
for i, cloth in enumerate(cloths):
    print(i, cloth)
# Output: 0 shirt, 1 hat, 2 socks, 3 shorts

e. sorted() – Iterate over a collection in sorted order without mutating the original. It uses TimSort (average O(n·log n)). The key argument allows custom sorting criteria, and reverse=True yields descending order.

nums = [2, 3, 1, 5, 2]
for i in sorted(nums):
    print(i)
# Output: 1 2 2 3 5

cloths = ['shirt', 'hat', 'socks', 'shorts']
for cloth in sorted(cloths, key=len):
    print(cloth)
# Output by length: hat, shirt, socks, shorts

Applying these five built‑in functions helps you write Python code that is both idiomatic and performant.