4. Getting it right

Getting things done just isn’t enough. Readability, reliability, and maintainability are crucial – not only in science.

Goal

Getting familiar with the infrastructure necessary to deal sensibly with larger projects. Everything spanning more than 100 lines of code or taking more than two weeks to accomplish is a larger project. Working in science – and programming for getting your science done – is a larger project.

• 4.1. Version control (git)
  • 4.1.1. Why version control?
  • 4.1.2. Git fundamentals
  • 4.1.3. Git basics: getting setup and started
  • 4.1.4. Remotes: Synchronising several instances
  • 4.1.5. Branches
  • 4.1.6. Conflicts: merging, stashing
  • 4.1.7. Collaboration: pull requests
  • 4.1.8. Tags and Releases
  • 4.1.9. Using web interfaces: Gitea, GitLab, GitHub
  • 4.1.10. Git and binary files
• 4.2. Version numbers (SemVer)
  • 4.2.1. SemVer: Emphasising compatibility
  • 4.2.2. Where to place the version number?
  • 4.2.3. Auto-incrementing version numbers
• 4.3. Debugging
• 4.4. Testing
  • 4.4.1. The why, when, and what of tests
  • 4.4.2. How to write (and run) tests
  • 4.4.3. A paradigm shift: test-driven development
  • 4.4.4. Differences between test code and production code
  • 4.4.5. What if I have a large untested code base?
  • 4.4.6. Wrap-up
• 4.5. Refactoring
• 4.6. Documentation
  • 4.6.1. Typical problems with documentation
  • 4.6.2. Different types of documentation
  • 4.6.3. Documentation in the code
  • 4.6.4. Documentation external to the code
  • 4.6.5. Tools for creating documentation
  • 4.6.6. Documentation in Python: reStructuredText and Sphinx
• 4.7. Packaging
  • 4.7.1. The case for Python packages
  • 4.7.2. Prerequisites
  • 4.7.3. Scripts vs. modules vs. packages
  • 4.7.4. General layout of a Python package
  • 4.7.5. How to (locally) distribute Python packages
  • 4.7.6. Creating stand-alone executables