3.3 Libraries - Python for Scientific Computing 2023
Your code doesn't exist alone. It is one part of a large ecosystem, where many other things exist for you to build off of. This is (more than anything) a discussion about the broader ecosystem, what you would want to build off of, and what you can do to make your code reusable.
https://aaltoscicomp.github.io/python...
00:00 Motivation and introduction
06:00 Glossary
09:24 The SciPy ecosystem
12:14 Connecting Python to other languages
14:21 How can you tell if you should use some library?
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Python for Scientific Computing is a bridge between basic Python courses and scientific work with Python. This is a basic to intermediate course in Python tools such as NumPy, SciPy, Matplotlib, and Pandas. It also covers some more advanced tools, such as Binder, releasing software, data formats, etc. It is suitable for people who have a basic understanding of Python and want to know some internals and important libraries for science. We don't cover anything in too much depth, but we do introduce you to all of the main tools you will need.
This course was put on as a collaboration between partners in Finland, Norway, and Sweden, coordinated by Aalto Scientific Computing.
Links:
Playlist: • Python for Scientific Computing 2023
Course material: https://aaltoscicomp.github.io/python...
Workshop webpage: https://scicomp.aalto.fi/training/sci...
Aalto Scientific Computing: https://scicomp.aalto.fi/
CodeRefinery: https://coderefinery.org