Lesson 14: Capstone — Build a Real Tool

⏱ ~60 min Lesson 14 of 14 💚 Free

What You'll Learn

Combine OOP, file I/O, API calls, and CLI argument parsing in one project
Plan and structure a multi-file Python project
Write tests for the capstone and run with pytest
Reflect on all 14 lessons and identify next steps

The Capstone Project

Your capstone is a GitHub Repository Analyzer — a CLI tool that searches GitHub's API for repositories by language, filters by stars, and exports the results to JSON. It uses every major concept from this course.

Skills Applied

Lesson 2–3: OOP — a RepoAnalyzer class with methods for fetch, filter, and export

Lesson 4: File I/O — JSON export with json.dump()

Lesson 5: Error handling — try/except around all API calls

Lesson 6–7: requests + JSON parsing from the GitHub API

Lesson 8: List comprehensions for filtering and transforming results

Lesson 11: argparse CLI with --language, --min-stars, --output flags

Lesson 12: venv + requirements.txt (requests, tabulate)

Lesson 13: pytest tests for the filter and export logic

You Are an Advanced Python Developer

Over 14 lessons you've gone from Python review to building production-quality tools: OOP hierarchies, file pipelines, REST APIs, generators, decorators, regex, CLI tools, dependency management, and automated testing. These skills are used every day at companies like Google, Spotify, and NASA.

Next steps: Django or FastAPI (web), pandas + matplotlib (data science), asyncio (async Python), Docker (deployment).

Quick Check

1. When designing a multi-module Python project, where should you put the entry point that calls argparse?

In the first file Python alphabetically finds

In a main() function, guarded by if __name__ == "__main__":

At the top level of every module file

In a __init__.py file

2. Which of these is NOT a good reason to add a class to a project?

The data and behavior are naturally related

You need multiple instances with different state

You want your code to look more professional

You need to encapsulate complex internal logic

3. What is the purpose of requirements.txt in a project you share on GitHub?

It describes what the project does

It lets anyone recreate the exact same virtual environment with pip install -r requirements.txt

It lists which Python version to use

It is required by GitHub Pages

4. What is the best next course after Advanced Python?

Learn C++ to get closer to the hardware

Restart from lesson 1 to reinforce fundamentals

Choose a specialization: web (Django/FastAPI), data (pandas/ML), or automation/scripting

Stop coding — you know everything now