Python Clean Code

Python’s philosophy emphasizes readability and simplicity. “Clean code” in Python (often called “Pythonic” code) isn’t just about making it work—it’s about making it expressive and easy for others to maintain.

Here are some essential patterns for writing modern, clean Python.

1. Use iterators instead of index-based for loops

Bad code

items = [1, 3, 5]
for i in range(len(items)):
    print(items[i])

Good code

items = [1, 3, 5]
for item in items:
    print(item)

2. Enumerate if you want the index

Bad code

items = [1, 3, 5]
for i in range(len(items)):
    print(i, items[i])

Good code

items = [1, 3, 5]
for i, item in enumerate(items):
    print(i, item)

3. Use zip for iterating over multiple lists

Bad code

names = ["Vish", "John"]
scores = [95, 88]
for i in range(len(names)):
    print(names[i], scores[i])

Good code

for name, score in zip(names, scores):
    print(name, score)

4. Comprehensions over raw for loops

Bad code

squares = []
for x in range(10):
    squares.append(x * x)

Good code

squares = [x * x for x in range(10)]
# Also works for dictionaries:
sq_dict = {x: x * x for x in range(10)}

5. Use Counter for counting elements

Bad code

items = [1, 2, 1, 3, 2, 1]
d = {}
for item in items:
    d[item] = d.get(item, 0) + 1

Good code

from collections import Counter
counts = Counter([1, 2, 1, 3, 2, 1])

6. Modern String Formatting (F-Strings)

Bad code

name = "Vish"
print("Hello, {}".format(name))

Good code (Python 3.6+)

print(f"Hello, {name}")

7. Type Hinting for Clarity

Bad code

def get_user_ids(users):
    return [u.id for u in users]

Good code (Python 3.5+)

from typing import List

def get_user_ids(users: List[User]) -> List[int]:
    return [u.id for u in users]

8. Use pathlib for File Systems

Bad code

import os
path = os.path.join("data", "results.csv")

Good code (Python 3.4+)

from pathlib import Path
path = Path("data") / "results.csv"

9. The Walrus Operator (Assignment Expressions)

Good code (Python 3.8+)

if (n := len(items)) > 10:
    print(f"Too many items: {n}")

10. dataclasses for Data Containers

Good code (Python 3.7+)

from dataclasses import dataclass

@dataclass
class Profile:
    id: int
    username: str
    email: str

Writing clean code is a continuous journey. These patterns ensure your code is not just functional, but elegant and idiomatic.