Lessons Learned from Developing an Open Source Software

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And the unexpected edge they gave me as a data scientist and machine learning engineer

17 min read

2 hours ago

Introduction

Open source has fundamentally transformed the landscape of software development in the past couple of decades, especially in recent years, where Python has arguably dominated the field over all other languages (I’m sure there is scientific, mathematical proof for this in a paper somewhere). Being an incredibly easy language to learn, with its “batteries included” philosophy, it has brought along a ton of remarkable open-source packages in the world of data, ranging from scientific computing and simulations, to numerical analysis and machine learning, to AI and chatbot development these days.

During my early years as a PhD student, Python was not as popular as it is today. A lot of the packages and scientific code in my area of research were written in a language called Interactive Data Language (IDL). You may be surprised to learn that this language was not free — we had to pay a license fee for it. Yes, you read that right, we had to pay to code!

This experience makes me really appreciate the power of Python as not only a programming language, but as a platform where anyone can contribute and create amazing…