Practical habits that make your code easy to read, test, and maintain
Code reviews are not about showing how smart you are. They are about making your future self (and your teammates) able to understand, trust, and extend your code with minimal cognitive load.
After reviewing and being reviewed in data science, analytics engineering, and ML systems teams, I noticed the same friction patterns over and over. The difference between a blocked PR and a clean approval rarely comes down to “advanced Python tricks.” It comes down to clarity, structure, and intent.
Below are 5 practical, repeatable habits I apply to pass code reviews consistently.
1. Make Functions Do One Thing Well
If a function is hard to name, it is doing too much.
The fastest way to reduce review friction is to ensure each function has:
- A single responsibility
- A clear input and clear output
- No hidden side effects unless explicitly documented
Bad: Too many responsibilities
def process_books(path):
import json
from datetime import datetime
with open(path) as f:
data =…
Learn more about 5 Ways to Pass Any Python Code Review