I love Python and I love the fact that nowadays Python is being used in science and engineering more than ever! Python has a mature set of general purposes libraries that help scientists extract the best out of their data.
Among some libraries, I couldn’t forget to mention numpy (numerical computation), scipy (scientific programming), matplotlib (visualization), pandas (data processing), and scikit-learn (data science/machine learning).
Most of the success around Python and its libraries is due to their fast-growing, energetic, and welcoming communities. Those libraries I mentioned are developed in a daily basis by experts from academia and industry and also by students.
In the past years, I’ve been involved with open source software development primarily thanks to Google ❤️, Github ❤️, and NASA ❤️.
Here is a list of projects I’m more involved with:
- astropy: A community Python library for Astronomy
- photutils: Image photometry in Python
- pyke: A suite of Python tools to analyze Kepler/K2 data
- oktopus: A soft-bodied, eight-armed package for beautiful inference