PyCon APAC 2025

Most beginners think that contributing to Open Source is hard and time-consuming, but it's actually quite the opposite. It kind of looks complicated but is actually simple and straight forward once you do it.

In this talk, I’ll share my personal journey contributing to open-source projects like Pandas, providing practical insights into how to get started, how open-source collaboration works, and the tangible benefits and challenges involved. Through real examples of issues and pull requests I’ve worked on, as well as stories of both successes and struggles, I’ll offer an honest look at the open-source contribution process and what it takes to make a meaningful impact.

I'll showcase one PR I submitted where it looks complicated at first glance. The implementation was simple, yet the performance yielded 10x results. I improved df.to_csv's performance when Index=False by 90%. Just by a simple change: I just used an np.empty as the dataframe's index when Index=False since originally, it still builds the index and drops it at the last time.

One of the best benefits of Open source contribution is being able to navigate, understand and trace large multi-file projects, get hands-on experience on code reviews and PRs, learn how to properly understand documentation and improve your git/github knowledge.