A short description of the project.
├── LICENSE <- The LICENSE using this project.
├── README.md <- The top-level README for developers using this project.
├── CHANGELOG.md <- The top-level CHANGELOG for developers using this project.
├── env.default <- Environment vars definition
├── Makefile <- Makefile with commands
├──.editorconfig <- Helps maintain consistent coding styles
├──.pre-commit-config <- Helps setup github basic precommit hooks
├── Dockerfile <- Docker file definition
├── docker-compose.yml <- Docker configs environment definition
├── .dockerignore <- files don't want to copy inside container
├── .gitignore <- files don't want to copy in githubs
├── .github <- github configs
│ └── pull_request_template.md <- github pr template
├── requirements.txt <- The requirements for development
├── data
│ ├── processed <- The final, canonical data sets.
│ └── raw <- The original data.
|
└── notebooks <- Naming convention is a number (for ordering),
│ the creator's initials, and a short `-` delimited e.g.
│ `1.0-jqp-initial-data-exploration`.
├──.env
├──.dockerignore
├──requirements.txt <- Notebooks requirements
├──Dockerfile <- Sets up Jupyter notebooks environment
├──jupyter_notebook_config.py <- Configure Jupyter notebooks
├── template_notebooks <- where the notebooks template will live.
│
├── Lab <- Testing and development
│
└── Final <- The final cleaned notebooks for reports/ designers /
developers etc.
- With docker and docker-compose in your system, you can develop inside containers:
make up
And if you want to get into the main container:
make inside
- Install requirements on your machine:
make requirements
- Set up a new environment in your machine
make create_environment && make requirements
make init-prehooks
By default this will treat your project remote branch as git@github.com:Vizzuality/testenv_sadfas
if you need to change it don't forget to modify the Makefile
before running this command. Take into account that this will create a new repository under the vizzuality organization once you git push -u origin master
You can run your tests:
make test
You can lint and reformat your code:
make lint
or up and serve the documentation:
make serve-doc
Project based on the cookiecutter data science project template. #cookiecutterdatascience