Step up your coding game with AI-powered Code Explainer. Get insights like never before!
As a developer, contributing to open-source projects can provide a rewarding way to learn, teach, and gain experience in almost any skill. You can contribute to an open-source project by integrating a pull request into your local version and testing it, commenting on it, and adding additional information to existing issues.
While open-source database contribution offers plenty of opportunities to progress your coding skills, it also exposes you to gain new programming languages, libraries, SDKs, and more. Apart from assisting you in your technical prowess, participating in open-source projects also expands your network, potentially enhancing your career prospects and professional goals.
Here are nine Python projects where you can offer your contribution.
Requests is one of the most popular libraries around the world, and it allows Python users to make HTTP requests. Your application can focus on interacting with the services and consuming the data instead of worrying about the complexities of making requests. With the library, you can create, customize, inspect and configure your requests, and Python would not exist without it.
TensorFlow is an advanced Python neural network, machine learning, and deep learning library with more than 160k stars on GitHub. TensorFlow has many ways for you to contribute, and you can write code, update the TensorFlow library documentation, or submit a Jupyter notebook to the TensorFlow examples repository.
Django is one of the most common web development frameworks for Python, with over 60k stars on GitHub and millions of developers worldwide using it. Among the things you can do is fix a bug, write code or new features, translate Django, and write documentation. The Django project is for you if you're a Python website developer and looking for an open-source project.
A popular Python neural network library, Keras has over 50k stars on Github. Contribute to this repository by working on a single issue, such as making changes to the source code, developing new features, fixing a bug, or pulling requests.
If you're interested in contributing to the future of web development using Python, Flask is the best open project for you. With the library having more than 50k stars on Github, you can report issues, submit patches, or create translation documents.
Data visualization in Python is most commonly carried out using Matplotlib. If you specialize in Python-based data visualization and are interested in contributing to one of the widely used and versatile data visualization libraries in Python, you should consider contributing to Matplotlib.
Contributing to Matplotlib involves cloning the GitHub central repository and submitting a pull request. GitHub's best practices for making PRs to Matplotlib are documented in the Development workflow section.
This library is probably familiar to anyone who has worked with Python machine learning. Start contributing to Scikit-Learn if you are familiar with machine learning and data visualization in Python. Contribute by reporting a bug, downloading new code, and writing code.
Scrapy has over 40k stars on GitHub, making it the most popular web scraping library. Suppose you're using Python to scrape websites, and you're interested in working on improving the web scraping library. In that case, you can start by reporting bugs and requesting features, submitting patches for new functionalities, and contributing to the Stack Overflow Scrapy question board.
Pandas is the most popular Python library for data analysis and manipulation. If you know how to analyze or manipulate data in Python and are interested in building the future of data analysis in Python, consider contributing to pandas. The best way to contribute to pandas is to review the list of open good first issues and pick one by commenting on it.
Contributing to open-source projects is an excellent way to gain knowledge, teach others, and share experiences. These nine open-source projects offer you a chance to contribute and help the future of python. Not only will you be contributing to one of the most significant projects, but you'll also become part of a vibrant community.
Finished reading? Keep the learning going with our AI-powered Code Explainer. Try it now!
Got a coding query or need some guidance before you comment? Check out this Python Code Assistant for expert advice and handy tips. It's like having a coding tutor right in your fingertips!