Adapted from The Good Research Code Handbook
|-- data
|-- docs
|-- results
|-- scripts
|-- src
|-- tests
-- .gitignore
-- environment.yml
-- pyproject.toml
-- README.md
data: Where you put raw data for your project. You usually won’t sync this to source control, unless you use very small, text-based datasets (< 10 MBs).
docs: Where you put documentation, including Markdown and reStructuredText (reST). Calling it docs makes it easy to publish documentation online through Github pages.
results: Where you put results, including checkpoints, hdf5 files, pickle files, as well as figures and tables. If these files are heavy, you won’t put these under source control.
scripts: Where you put scripts - Python and bash alike - as well as .ipynb notebooks.
src: Where you put reusable Python modules for your project. This is the kind of python code that you import.
tests: Where you put tests for your code. We’ll cover testing in a later lesson.
conda create --name ENVNAME --file environment.yml
pip install -e .