GitHub Project on Python: 30 Python Projects You’d Enjoy

Working on the best Python project on GitHub is one of the most effective ways to gain programming experience. Python’s versatility, strong library support, and active community make it a top choice for learners and professionals.  

By exploring GitHub projects on Python, you can apply concepts in data science, AI, automation, and web development while improving problem-solving skills. 

This blog highlights 30 of the best Python projects on GitHub, categorized into beginner, intermediate, and advanced levels. Each project includes complexity, timeline, and practical use cases. These python projects will help you practice hands-on coding and build a portfolio that stands out. 

Want to learn how to use Python as a programming language for actual applications? Join upGrad’s Online Software Development Courses and work on hands-on projects that simulate real industry scenarios. With a focus on trending programming languages and the latest technologies, you’ll be equipped for success. 

Top 30+ Python Projects on GitHub You Can Work On

If you want to improve your coding skills and build a strong portfolio, working on the best Python project on GitHub is the right place to start. These GitHub projects on Python cover a wide range of applications, from beginner-friendly tools to advanced AI systems. In this blog, we’ll explore 30 of the best Python projects on GitHub with timelines and complexity levels to help you choose the right one for your learning journey. 

Want to fast-track your tech career? Our Software Engineering Courses equip you with the skills to innovate, lead, and seize the next big opportunity. 

• Professional Certificate Program in Cloud Computing and DevOps  
• AI-Powered Full Stack Development Course by IIITB  
• Master of Design in User Experience 

Beginner-Level Python Projects on GitHub 

Beginner projects are ideal for those starting with Python. They cover fundamental programming concepts, basic API usage, file handling, and simple visualization techniques. Completing these projects helps you understand Python’s practical applications and prepares you for more complex projects. Most beginner projects take 2–5 weeks to complete. 

1. Basic NLP Chatbot with Context 

Create a chatbot capable of holding simple conversations using Natural Language Processing (NLP). This project introduces you to essential NLP concepts like tokenization, intent recognition, and context management. The chatbot can answer FAQs, maintain context for follow-up questions, and respond appropriately to user inputs. 

Tools: NLTK, spaCy, Flask 

What You’ll Learn: 

• Processing and understanding natural language 
• Handling conversational context and intents 
• Structuring dialogue flows for better UX 
• Deploying a Python-based chatbot as a web app 

Time Required: 2–4 weeks 

Add-On Feature Idea: Integrate with Telegram or Slack for real-time chat interactions 

2. Reddit Comment Analyzer 

Analyze Reddit comments to extract trends, sentiment, and keyword frequency. This project allows you to fetch live data from Reddit using APIs, preprocess text, and visualize patterns to identify trends or community opinions. 

Tools: PRAW (Python Reddit API Wrapper), TextBlob, Matplotlib 

What You’ll Learn: 

• Fetching and handling data from APIs 
• Performing sentiment analysis on text data 
• Visualizing comment trends and insights 
• Basic natural language processing for social media data 

Time Required: 3–5 weeks 

Add-On Feature Idea: Build a dashboard to monitor sentiment across multiple subreddits in real time 

3. Dynamic Portfolio Generator 

Develop a dynamic portfolio website that updates automatically using structured data like JSON or Markdown. This project demonstrates how Python can be used to manage and display content dynamically without manually editing HTML files. 

Tools: Flask, Jinja2, HTML/CSS, JSON 

What You’ll Learn: 

• Dynamic web page generation using Python 
• Using templates to separate design and content 
• Handling structured data inputs for automatic updates 
• Hosting a portfolio using GitHub Pages or Heroku 

Time Required: 3–4 weeks 

Add-On Feature Idea: Include a blog module that generates posts automatically from Markdown files 

4. Dynamic Resume Builder 

Automate resume creation by inputting structured data into predefined templates. Users can generate resumes in PDF format with clean formatting, reducing manual effort while learning Python libraries for document creation. 

Tools: ReportLab, FPDF, Pandas 

What You’ll Learn: 

• Automating document generation in Python 
• Designing flexible templates for different resume styles 
• Working with structured data formats for professional documents 
• Creating user-friendly Python applications for personal use 

Time Required: 2–3 weeks 

Add-On Feature Idea: Offer multiple output formats like PDF, Word, or HTML 

5. 3D Plot Visualizer 

Create a tool to visualize datasets in three dimensions using Python. This project helps beginners understand multidimensional data and practice generating interactive 3D plots that enhance data interpretation. 

Tools: Matplotlib, Plotly, NumPy 

What You’ll Learn: 

• Basics of 3D data visualization 
• Working with NumPy arrays for plotting 
• Customizing 3D plots with labels, colors, and interactivity 
• Presenting complex data in an easily understandable format 

Time Required: 2–4 weeks 

Add-On Feature Idea: Allow users to upload CSV files to automatically generate 3D plots 

6. GitHub Repository Analyzer 

Develop a tool that analyzes GitHub repositories for metrics like commit history, contributor activity, and most-used programming languages. This project is practical for understanding version control data and using APIs effectively. 

Tools: GitHub REST API, Requests, Pandas 

What You’ll Learn: 

• Interacting with REST APIs to fetch repository data 
• Data analysis and visualization of project activity 
• Automating reports for repository metrics 
• Practical experience with GitHub data extraction 

Time Required: 2–3 weeks 

Add-On Feature Idea: Compare multiple repositories to visualize contributors and activity trends 

7. Simple AR App for Learning 

Create an educational AR app that overlays interactive elements on textbooks or flashcards. This project introduces augmented reality concepts and interactive learning tools, making Python applications more engaging. 

Tools: ARToolKit, OpenCV, Kivy 

What You’ll Learn: 

• Fundamentals of computer vision and AR 
• Integrating virtual elements with physical objects 
• Handling user interactions within AR environments 
• Developing cross-platform educational applications 

Time Required: 4–5 weeks 

Add-On Feature Idea: Gamify the learning experience with interactive quizzes triggered by AR elements 

Intermediate-Level Python Projects on GitHub 

Intermediate projects are designed for those with a basic understanding of Python who want to tackle more complex problems. These projects typically involve APIs, automation, data processing, and visualization. They help you gain hands-on experience with real-world applications and generally take 2–6 weeks to complete. 

1. AI-Powered To-Do List 

Develop a to-do list application enhanced with AI features such as task prioritization, reminders, and activity predictions. This project strengthens your understanding of integrating AI with everyday productivity tools. 

Tools: Python, TensorFlow/Keras, Flask, SQLite 

What You’ll Learn: 

• Implementing machine learning for task prediction 
• Building user-friendly Python web applications 
• Storing and retrieving data with SQLite 
• Integrating AI into simple productivity apps 

Time Required: 2–4 weeks 

Add-On Feature Idea: Include voice command support to add or update tasks 

2. API-Based Cryptocurrency Tracker 

Create a dashboard that tracks cryptocurrency prices in real-time using APIs. Learn how to fetch financial data, display trends, and perform basic analysis. 

Tools: Python, Requests, Flask/Django, Plotly 

What You’ll Learn: 

• Working with external APIs to fetch live data 
• Data visualization for financial analysis 
• Building interactive dashboards 
• Real-time monitoring and notifications 

Time Required: 3–4 weeks 

Add-On Feature Idea: Implement price alerts via email or push notifications 

3. Real-Time Weather Dashboard 

Build a Python application that fetches live weather data and visualizes trends for different locations. This project introduces API usage, data parsing, and dynamic UI updates. 

Tools: OpenWeatherMap API, Flask, Plotly, Bootstrap 

What You’ll Learn: 

• Fetching and processing real-time API data 
• Creating dynamic and interactive dashboards 
• Data visualization techniques for weather trends 
• Deploying web applications using Python frameworks 

Time Required: 3–4 weeks 

Add-On Feature Idea: Add a 7-day forecast visualization with customizable location input 

4. Customized PDF Parser 

Develop a Python tool to extract text, tables, and metadata from PDFs. This project is practical for automating document handling and learning about file processing. 

Tools: PyPDF2, PDFMiner, Pandas 

What You’ll Learn: 

• Parsing and extracting data from PDF files 
• Automating repetitive document processing tasks 
• Storing and manipulating extracted data 
• Handling different PDF structures and formats 

Time Required: 3–4 weeks 

Add-On Feature Idea: Enable batch processing for multiple PDFs at once 

5. AI-Powered Content Generator 

Create a Python application that generates textual content automatically using AI models. This project is ideal for learning NLP applications and automating content creation. 

Tools: GPT-based API, Flask, Pandas 

What You’ll Learn: 

• Integrating AI language models in Python 
• Automating content generation tasks 
• Handling API calls and text formatting 
• Building an interactive user interface 

Time Required: 5–6 weeks 

Add-On Feature Idea: Add content summarization or keyword-focused generation 

6. Keyword Extraction Tool 

Develop a Python tool that identifies and extracts key terms from documents or web pages. This project improves your understanding of NLP and text analysis. 

Tools: spaCy, NLTK, Pandas 

What You’ll Learn: 

• Text processing and tokenization 
• Extracting meaningful keywords from large datasets 
• Data cleaning and pre-processing techniques 
• Building Python tools for SEO or research tasks 

Time Required: 3–4 weeks 

Add-On Feature Idea: Add a visualization component to highlight keyword frequency 

7. Advanced Data Scraper with Visual Dashboards 

Create a Python application that scrapes data from websites and presents it on interactive dashboards. This project teaches web scraping, data cleaning, and visualization skills. 

Tools: BeautifulSoup, Selenium, Pandas, Plotly/Dash 

What You’ll Learn: 

• Scraping dynamic websites for structured data 
• Cleaning and analyzing raw data efficiently 
• Presenting insights using dashboards 
• Automating repetitive scraping tasks 

Time Required: 4–6 weeks 

Add-On Feature Idea: Schedule automated scraping and dashboard updates 

8. Code Debugger Helper 

Build a Python tool that assists in identifying and fixing common coding errors. This project is useful for learning debugging automation and improving coding efficiency. 

Tools: Python AST, Regex, PyLint 

What You’ll Learn: 

• Parsing code for syntax and logic errors 
• Automating code checks and suggestions 
• Building a tool that can be integrated into IDEs 
• Understanding common programming pitfalls 

Time Required: 3–4 weeks 

Add-On Feature Idea: Add functionality to suggest optimized code snippets 

9. Mini Video Streaming Service 

Develop a Python-based video streaming application with user authentication and basic playback features. This project helps understand media handling and web application development. 

Tools: Flask/Django, HTML5 Video, SQLite, FFmpeg 

What You’ll Learn: 

• Handling video files in Python applications 
• User authentication and session management 
• Streaming content over web applications 
• Building a basic media server 

Time Required: 5–6 weeks 

Add-On Feature Idea: Enable live streaming or playlist support 

10. Smart Investment Portfolio Tracker 

Create a tool to track investments, calculate returns, and visualize portfolio performance. This project combines data handling, visualization, and financial analysis. 

Tools: Python, Pandas, Matplotlib/Plotly, Yahoo Finance API 

What You’ll Learn: 

• Fetching financial data from APIs 
• Portfolio performance analysis 
• Data visualization and reporting 
• Automating investment tracking 

Time Required: 3–5 weeks 

Add-On Feature Idea: Add alerts for portfolio changes or market fluctuations 

Advanced-Level Python Projects on GitHub 

Advanced Python projects are meant for experienced developers who want to tackle complex problems involving AI, machine learning, automation, and system integration. These projects typically take 5–8 weeks and provide a strong portfolio to demonstrate advanced Python skills. 

1. Custom Machine Learning Framework 

Build your own lightweight machine learning framework from scratch. This project helps you understand the inner workings of ML algorithms, optimization techniques, and model training processes. 

Tools: Python, NumPy, Pandas, Scikit-learn (optional) 

What You’ll Learn: 

• Implementing core ML algorithms manually 
• Understanding gradient descent, optimization, and model evaluation 
• Structuring code for reusable ML modules 
• How frameworks like Scikit-learn are built internally 

Time Required: 6–8 weeks 

Add-On Feature Idea: Add visualization tools to track model performance metrics 

2. AI Model Deployment System 

Create a system to deploy machine learning models as APIs for real-time predictions. This project is ideal for understanding production-ready AI applications. 

Tools: Flask/FastAPI, Docker, Python, AWS/GCP 

What You’ll Learn: 

• Building APIs to serve ML models 
• Containerization using Docker for deployment 
• Scaling applications for multiple users 
• Integrating deployed models with front-end applications 

Time Required: 5–7 weeks 

Add-On Feature Idea: Add a user authentication system for secure model access 

3. Facial Emotion Recognition 

Develop a Python application that detects facial expressions and identifies emotions in real time. This project uses computer vision and deep learning techniques. 

Tools: OpenCV, TensorFlow/Keras, Python 

What You’ll Learn: 

• Detecting faces and facial landmarks 
• Classifying emotions using deep learning models 
• Handling real-time camera input 
• Building interactive visual feedback for users 

Time Required: 5–7 weeks 

Add-On Feature Idea: Include emotion tracking over time to analyze trends 

4. Voice Command Home Automation 

Create a home automation system controlled via voice commands. This project combines speech recognition with IoT devices to control lights, fans, or appliances. 

Tools: Python, SpeechRecognition, Raspberry Pi/Arduino, GPIO libraries 

What You’ll Learn: 

• Processing and interpreting voice commands 
• Controlling hardware devices with Python 
• Integration of IoT devices and Python software 
• Creating a real-time voice-activated system 

Time Required: 5–6 weeks 

Add-On Feature Idea: Add multiple user profiles with personalized commands 

5. Virtual Personal Stylist 

Build an AI-powered stylist that recommends outfits based on user preferences, weather, and occasions. This project uses image recognition and recommendation algorithms. 

Tools: Python, TensorFlow/Keras, OpenCV, Pandas 

What You’ll Learn: 

• Image classification and feature extraction 
• Recommendation systems for personalized suggestions 
• Combining multiple data sources for decision-making 
• Designing AI applications with practical real-life utility 

Time Required: 6–8 weeks 

Add-On Feature Idea: Allow virtual try-on using augmented reality 

6. AI-Powered Resume Screener 

Create a Python tool that evaluates resumes for skills, experience, and suitability for job descriptions. Ideal for learning NLP applications in HR tech. 

Tools: Python, spaCy, NLTK, Flask 

What You’ll Learn: 

• Parsing and analyzing text from resumes 
• Matching skills and experience to job requirements 
• Automating initial HR screening processes 
• Designing a user-friendly interface for HR professionals 

Time Required: 5–6 weeks 

Add-On Feature Idea: Include scoring and ranking of multiple resumes for faster selection 

7. Traffic Flow Prediction System 

Develop a system that predicts traffic flow based on historical data, sensor inputs, or GPS feeds. Useful for urban planning and smart city applications. 

Tools: Python, Pandas, TensorFlow/Keras, Plotly 

What You’ll Learn: 

• Time-series analysis and prediction 
• Building predictive models for real-world datasets 
• Data visualization for traffic trends 
• Integrating predictions into dashboards for users 

Time Required: 5–7 weeks 

Add-On Feature Idea: Add live updates with real-time traffic data integration 

8. AI Stock Price Prediction Dashboard 

Build a dashboard that predicts stock prices using machine learning models. Visualize trends and make predictions based on historical data. 

Tools: Python, Pandas, Scikit-learn, Plotly, Flask 

What You’ll Learn: 

• Financial data preprocessing and analysis 
• Implementing regression and ML models for forecasting 
• Creating interactive dashboards to display predictions 
• Combining predictive analytics with visualization 

Time Required: 5–7 weeks 

Add-On Feature Idea: Include multiple stock tracking and real-time alerts 

9. Reinforcement Learning Game AI 

Create an AI agent capable of learning strategies in games using reinforcement learning. This project is ideal for understanding complex AI behavior and decision-making. 

Tools: Python, TensorFlow/Keras, OpenAI Gym 

What You’ll Learn: 

• Reinforcement learning concepts like Q-learning and policy gradients 
• Training AI agents in simulation environments 
• Optimizing performance for goal-oriented tasks 
• Visualizing AI learning progress and strategies 

Time Required: 6–8 weeks 

Add-On Feature Idea: Expand to multiple game types or multiplayer scenarios 

10. E-commerce Fraud Detection System 

Develop a system to detect fraudulent transactions using machine learning. This project combines data analysis, anomaly detection, and predictive modeling. 

Tools: Python, Pandas, Scikit-learn, Matplotlib/Plotly 

What You’ll Learn: 

• Identifying patterns indicative of fraud 
• Building classification models for anomaly detection 
• Visualizing suspicious activity trends 
• Automating fraud detection in Python applications 

Time Required: 5–6 weeks 

Add-On Feature Idea: Integrate real-time alerts for high-risk transactions 

11. Blockchain-Based Voting System 

Build a secure, transparent voting application using blockchain principles. This project introduces you to cryptography and decentralized systems. 

Tools: Python, Flask, Ethereum (Solidity optional), Web3.py 

What You’ll Learn: 

• Blockchain fundamentals for secure voting 
• Implementing smart contracts for vote recording 
• Handling user authentication and transaction security 
• Building a decentralized web application 

Time Required: 6–8 weeks 

Add-On Feature Idea: Enable verification of votes while maintaining voter anonymity 

12. AI-Powered Document Editor 

Create an intelligent document editor that provides suggestions, auto-corrections, and content enhancements using AI. 

Tools: Python, GPT-based API, Flask, Tkinter 

What You’ll Learn: 

• Integrating AI for text suggestions and corrections 
• Building user interfaces for document editing 
• Automating content improvement tasks 
• Combining NLP with user interaction features 

Time Required: 5–6 weeks 

Add-On Feature Idea: Add real-time collaborative editing features 

13. Advanced Cybersecurity Tool 

Develop a Python tool for penetration testing, vulnerability scanning, or threat detection. This project is ideal for security enthusiasts and advanced Python developers. 

Tools: Python, Nmap, Scapy, Socket programming 

What You’ll Learn: 

• Network scanning and vulnerability assessment 
• Automating cybersecurity tasks 
• Handling network protocols in Python 
• Building real-world security tools for testing and monitoring 

Time Required: 6–8 weeks 

Add-On Feature Idea: Integrate a reporting system that summarizes vulnerabilities with mitigation suggestions 

Benefits of Working on Python Projects from GitHub 

Working on GitHub projects offers practical learning beyond tutorials. It helps you apply Python skills in real-world scenarios and prepares you for professional coding environments. Here are the main benefits: 

• Gain hands-on experience with real-world Python applications. 
• Build a strong portfolio to impress employers or clients. 
• Learn collaboration and version control using GitHub. 
• Explore different coding styles and best practices. 
• Identify the best Python project on GitHub for skill improvement. 

How to Choose the Best Python Project on GitHub 

Choosing the right project is crucial to make your learning effective. Consider your skill level, goals, and project quality to ensure maximum benefit. Key tips include: 

• Match projects to your skill level: Beginner, Intermediate, or Advanced. 
• Check for clear documentation, active contributors, and recent updates. 
• Consider project complexity and timeline before starting. 
• Align projects with career goals or personal interests. 
• Explore GitHub repositories to discover trending Python projects on GitHub. 

Tips to Successfully Complete Python Projects 

Completing a project efficiently requires planning and consistent effort. Follow these practical strategies to stay on track and enhance learning: 

• Break projects into smaller, manageable tasks. 
• Use GitHub for version control and progress tracking. 
• Test and debug code regularly to prevent errors. 
• Document work and challenges for better understanding. 
• Collaborate with the community to improve skills and project quality. 

Conclusion

Working on best Python projects on GitHub is a practical way to strengthen coding skills. Beginner to advanced projects provide hands-on experience with real-world applications. GitHub repositories let you explore, collaborate, and track progress.  

By choosing projects wisely and following structured approaches, you can complete tasks efficiently. Projects help build portfolios and demonstrate expertise to employers. Regular testing, debugging, and documentation enhance learning. Overall, working on these Python projects on GitHub equips you with technical knowledge, practical experience, and confidence to tackle complex coding challenges.

Explore our popular Data Science articles featuring the latest trends, skills, and insights to boost your expertise and career growth.

Read our popular Data Science Articles

Mastering top data science skills like data analysis, machine learning, and Python programming can empower you to excel in the ever-evolving field of data science.

Top Data Science Skills to Learn

Explore Popular GIT Tutorials to master version control, streamline workflows, and enhance your collaboration skills with step-by-step guidance.

Explore Popular GIT Tutorials

 Project Source Codes:

1. Basic NLP Chatbot with Context Project Source Code
2. Reddit Comment Analyzer Project Source Code
3. Dynamic Portfolio Generator Project Source Code
4. Dynamic Resume Builder Project Source Code
5. 3D Plot Visualizer Project Source Code
6. GitHub Repository Analyzer Project Source Code
7. Simple AR App for Learning Project Source Code
8. AI-Powered To-Do List Project Source Code
9. API-Based Cryptocurrency Tracker Project Source Code
10. Real-Time Weather Dashboard Project Source Code
11. Customized PDF Parser Project Source Code
12. AI-Powered Content Generator Project Source Code
13. Keyword Extraction Tool Project Source Code
14. Advanced-Data Scraper with Visual Dashboards Project Source Code
15. Code Debugger Helper Project Source Code
16. Mini Video Streaming Service Project Source Code
17. Smart Investment Portfolio Tracker Project Source Code
18. Custom Machine Learning Framework Project Source Code
19. AI Model Deployment System Project Source Code
20. Facial Emotion Recognition Project Source Code
21. Voice Command Home Automation Project Source Code
22. Virtual Personal Stylist Project Source Code
23. AI-Powered Resume Screener Project Source Code
24. Traffic Flow Prediction System Project Source Code
25. AI Stock Price Prediction Dashboard Project Source Code
26. Reinforcement Learning Game AI Project Source Code
27. E-commerce Fraud Detection System Project Source Code
28. Blockchain-Based Voting System Project Source Code
29. AI-Powered Document Editor Project Source Code
30. Advanced Cybersecurity Tool Project Source Code
31. https://github.blog/news-insights/octoverse/octoverse-2024/
32. https://github.com/anarojoecheburua/RAG-with-Langchain-and-FastAPI 
33. https://github.blog/news-insights/octoverse/octoverse-2024/