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a minimal project layout for a research code project

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A minimal project

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.

create virtual environment

conda create --name ENVNAME --file environment.yml

install package

pip install -e .

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