This project assumes you have Anaconda or Miniconda installed on your machine. If you do not, please install from https://docs.conda.io/en/latest/miniconda.html. This is my boilerplate loosely based on Cookie Cutter Data Science, with modifications including easier Anaconda support, isort seeding, pre-commit configs, and Travis CI. If you would like to run a CI pipeline, make sure you have an account on Travis CI and authorize builds on your GitHub repository. Otherwise, you may remove .travis.yml.

1. git clone this repository in the desired directory on your local machine.
2. cd into the project directory.
3. To create a conda environment:

   conda create -n <env_name> dep1 dep2 ...
   conda env export --no-builds --from-history | grep -v "prefix" > environment.yml
   

   These export command flags add only explicit dependencies to environment.yml and prevent cross-platform build issues with dependencies during CI. If you would like to use the pre-made environment.yml in this project, create an environment as follows:

   conda env create -f environment.yml
   

4. Run conda env update && conda activate <env_name>.
5. Run pip install -e ..
6. Run pre-commit install.
7. If you want to run CI, change conda activate boilerplate to conda activate <your_env_name>.
8. If you wish to use documentation, make any edits necessary in docs/source/conf.py and docs/source/index.rst, or add your own reStructuredText pages.
9. If you to include test coverage in your build: In .travis.yml, uncomment python -m pytest tests --cov=src --cov-fail-under=0 and change the --cov-fail-under value in to your intended test coverage percentage.