Welcome to the Advanced Python Workshop! This 20-hour course is designed to help researchers move beyond single-script, single-data-file analyses and adopt best practices in version control, collaboration, data management, modular coding, workflow orchestration, and environment management. If you’re eager to make your research code more robust, reproducible, and scalable, you’re in the right place!
Before the workshop, please ensure you have installed the following tools:
- Git
- Conda (via Anaconda, Miniconda, or Miniforge)
- Visual Studio Code (VSCode)
- GIN CLI Client
| Date | Topic | Short Description |
|---|---|---|
| Feb 24 (9–12:30) | Git, GitHub, Conda, VSCode, & READMEs | An introduction to reproducibility concepts, environment management, and collaborative coding practices. Learn to manage your code and dependencies via Git, GitHub, Conda, and VSCode. |
| Mar 3 (9–12:30) | Functions, Modules, & Testing | Dive into writing reusable functions, structuring larger projects into modules, and using Pytest to ensure code reliability. |
| Mar 10 (9–12:30) | Dependency Inversion | Implement advanced design patterns for testability and modularity, making your codebase easier to extend and maintain. |
| Mar 24 (9–12:30) | Conditionals, Loops, & File Processing | Automate repetitive tasks using Python’s control flow structures. Learn to find files with glob and serialize metadata in JSON for streamlined data handling. |
| Mar 31 (9–12:30) | Scientific Data Organization with HDF5 and GIN. | Explore the HDF5 file format for efficient, large-scale scientific data management and how to integrate it into your Python workflows and back it up with GIN. |
| Apr 7 (9–12:30) | Workflow Management with Snakemake | Orchestrate multi-step pipelines, manage complex data analysis workflows, and ensure reproducibility using Snakemake. |
Note: An optional “Joker” session is tentatively planned for April 9 (9–12:30). Content will be determined based on class progress and participant feedback.
