Python Hands-on Projects

1. Introduction

From Theory to Practice

You have already learned the fundamental syntax of Python, as well as core knowledge in web development, data processing, and more. Now, it's time to apply this knowledge to real-world projects. Through hands-on practice, you will gain a deeper understanding of Python's power and acquire valuable development experience.

This module will provide several hands-on projects in different areas. Each project will comprehensively use the skills learned in previous modules and provide a comparative thinking process with JavaScript/Node.js implementations.

💡 Learning Strategy: Choose a project that interests you the most and start with it. Try to complete it independently. When you encounter problems, review the previous modules or consult the official documentation. The key is to "do" rather than just "watch."

2. Project 1: URL Shortener Service

Project Description

Build a fully functional URL shortener service, similar to bit.ly. Users can submit a long URL, and the service will return a short URL. When the short URL is accessed, it should redirect to the original long URL.

Core Features

• Build API endpoints using FastAPI.
• Use Pydantic for data validation.
• Use SQLite or another database to store URL mappings.
• Generate unique short URL identifiers.
• Implement redirection logic.

3. Project 2: Command-Line Weather App

Project Description

Create a command-line tool where a user can enter a city name, and the program will fetch and display the current weather information from a weather API (e.g., OpenWeatherMap).

Core Features

• Use argparse or typer to parse command-line arguments.
• Use httpx or requests to call a third-party API.
• Handle the API response (JSON).
• Format and display the weather information in the terminal.

4. Project 3: Data Analysis and Visualization Report

Project Description

Extract and analyze data from a CSV dataset (e.g., on sales, movies, or any topic you are interested in), and generate a simple HTML report containing key metrics and charts.

Core Features

• Use pandas to read and clean the CSV data.
• Perform data aggregation and analysis (e.g., calculate averages, sums, groupings).
• Use matplotlib or seaborn to create charts (e.g., bar charts, line charts).
• Save the charts as images.
• Use the jinja2 template engine to generate an HTML report.

5. Summary

After completing these projects, you will not just be someone who "knows" Python, but someone who can "use" Python to solve real problems. Your skills will be greatly enhanced, and you will have a deeper understanding of the Python ecosystem.

Don't stop here! Try to expand these projects, add new features, or find your own project ideas. The best way to learn programming is to constantly create and practice.