2024/09/28 –, 4F Track4
The open source community is all about giving back and learning from one another. No matter how small, every contribution is valuable. And everyone can contribute something with a little bit of help. The hardest part is finding something to work on that fits your interests and skills.
In this talk, I will provide five ways that I used to get started contributing to different open source projects. I also share some guidance on selecting projects to contribute to and how to set yourself up for success. Get ready to start your open source journey!
I have contributed to several Python open source projects (e.g., NumPy, pandas, Matplotlib, Scikit-learn, numpydoc) using a variety of strategies to find my entry point. Many people have asked me how they can do the same, so I created this talk to spread that knowledge.
オーディエンスが持って帰れる具体的な知識やノウハウ:- Learn how people of all levels can contribute to open source projects.
- Learn how you can contribute to open source projects.
- Learn how to find a project to work on.
- Learn how to find a particular task to work on within a project.
- Learn about sprints, contributing to documentation, navigating an issue tracker, the process for identifying and fixing a bug, and the process for implementing a new feature, using examples from the author's personal experiences contributing to various Python open source projects.
- Learn tips for making a successful contribution.
Audience members should have an interest in contributing to open source, and ideally, should have used at least one open source library before.
オーディエンスの経験レベル:Beginner
発表の言語:English
発表資料の言語:English
Stefanie Molin is a software engineer at Bloomberg in New York City, where she tackles tough problems in information security, particularly those revolving around data wrangling/visualization, building tools for gathering data, and knowledge sharing. She is also the author of “Hands-On Data Analysis with Pandas: A Python data science handbook for data collection, wrangling, analysis, and visualization,” which is currently in its second edition and has been translated into Korean and Chinese. She holds a bachelor’s of science degree in operations research from Columbia University's Fu Foundation School of Engineering and Applied Science, as well as a master’s degree in computer science, with a specialization in machine learning, from Georgia Tech. In her free time, she enjoys traveling the world, inventing new recipes, and learning new languages spoken among both people and computers.