reproducible-coding-workshop

Repo for reproducible coding workshop

Based on material in:

• https://dsi-cores.github.io/OpenByDesign/01-research-practices-%28practical%29/02-reproducible-data-analysis.html
• https://textbook.nipraxis.org/intro.html

Prerequisites:

• Basic Python programming skills (including numpy)
• Basic understanding of git and GitHub
• Basic understanding of neuroimaging data
• Personal computer set up according to the setup instructions

Schedule:

Hour 1:

• overview of clean coding practices in Python
• group code review exercise:
  • With your group, spend 10 minutes going over this anti-example code, with the following questions in mind:
    • What are the different parts of the code doing?
    • What code smells do you sense?
    • How might you refactor it to address these?
  • Appoint a group spokesperson who can report back if called upon

Hour 2:

• Working with neuroimaging data
• Beyond the notebook
  • using jupytext
  • linting with flake8
  • autoformatting with blue

Hour 3:

• Tutorial: software testing with PyTest

Hour 4:

• Validating data analysis workflows