Python Scenario Practice 🐍 Overview

Python Scenario Practice

A collection of scenario-based Python problems that simulate real-world tasks and interview-style challenges. Each scenario emphasizes practical problem-solving, clean code, and industry-relevant logic.

Why this repo

• Bridge the gap between algorithmic exercises and production-focused problems.
• Practice data processing, automation, and robust error handling.
• Build readable, well-structured solutions suitable for interviews and portfolios.

Topics covered

• Problem-solving & logical thinking
• File handling & data processing
• ETL-style transformations
• API and JSON handling
• Error handling and edge cases
• Automation & scripting
• Basic data analysis

Repository layout

• 1_Netflix - Timebucket Watch Stats/ — Example scenario computing hourly watch-time totals.
• (Other scenario folders will appear here as added.)

Getting started

1. Clone the repository.
2. Inspect a scenario folder (e.g., 1_Netflix - Timebucket Watch Stats) and read its README.md for specific instructions.
3. Install common dependencies (examples below) if a scenario requires them.

Common dependency install:

python -m pip install --upgrade pip
pip install pandas

How to use a scenario

1. Open the scenario folder and read its README for the problem statement and assumptions.
2. Run solution.py in that folder. Some solutions expect an injected data DataFrame in evaluation environments.
3. For local testing, create a small CSV matching the required schema and add a short data = pd.read_csv('data.csv') helper in the script.

Contributing

• Add new scenarios as numbered folders with a README.md and solution.py.
• Keep solutions focused, well-documented, and easy to run locally.

License & Notes

This repo is intended for learning and interview practice. Feel free to adapt scenarios for your own use.