4.3 Packaging - Python for Scientific Computing 2021

How to package and distribute software you write.

01:30 What is packaging? How do you distribute code?
02:37 Creating a new sample project
03:52 Adding __init__.py to make it a package
14:42 Adding the README.md file
17:52 Using pip to install locally or from Github directly.
20:26 Using PyPI (Python Package Index) to distribute packages
21:22 Twine to upload, sdist to build the distribution
24:26 Installing from PyPI, examining the package
27:01 Discussion, when would you use this?
28:24 Conda packages
29:35 Q&A: pip install -e, installing in other locations

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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.

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