Comments

Good code communicates its intent. Comments let you explain why your code works the way it does, making it easier for others (and your future self) to understand. Single-Line Comments Notice how Python completely ignores the comment lines. They exist only for humans reading the code. Writing clear comments is a skill that separates professional code from amateur code. Knowing when and how to comment is just as important as knowing the syntax. Here are some patterns to follow and avoid. Multiline comments in Python are typically written as multiple consecutive single-line comments. Triple-quoted strings are sometimes used but are technically string literals, not true comments. Good comments document intent, edge cases, and the reasoning behind non-obvious decisions. They are written for the

About This Interactive Section

This section is part of the Python Foundations: Beginner lesson on DataDriven, a free data engineering interview prep platform. Each section includes explanations, worked examples, and hands-on code challenges that execute in real time. SQL queries run against a live PostgreSQL database. Python runs in a sandboxed Docker container. Data modeling problems validate against interactive schema canvases. All content is framed around what data engineering interviewers actually test at companies like Meta, Google, Amazon, Netflix, Stripe, and Databricks.

How DataDriven Lessons Work

DataDriven combines four interview rounds (SQL, Python, Data Modeling, Pipeline Architecture) with adaptive difficulty and spaced repetition. Easy problems get harder as you improve. Weak concepts resurface until you master them. Your readiness score tracks progress across every topic interviewers test. Every lesson section ends with problems you solve by writing and running real code, not by picking multiple-choice answers.