2.5 Productivity tools - Python for Scientific Computing 2023
There are various tools that can make your own human time more efficient - productivity tools. These do things and find problems that are easy for a computer but hard or annoying for a human. Things like finding simple bugs or reformatting code. We'll discuss linting and code formatting, and have a discussion about other things and how we actually usually work.
https://aaltoscicomp.github.io/python...
00:00 What do we mean by productivity tools?
02:07 Linters
13:37 Exercise 1: linters
14:30 Going over the exercise and more linter Q&A
16:57 Code formatters
21:15 The "black" code formatter (demo)
24:57 Discussion
34:33 Final news of the day
34:55 More discussion of productivity tools
37:08 Wrap-up
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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