junya737 / openmm

The practice for OpenMM

datascience-template

Well structured and tested data science project template. You can use this template when creating the data sicence repository.

📁 Organized: The project structure is refereed to Cookiecutter Data Science

🚀 Prepared: Major libraries are prepared in environment.yml. If you are familiar with Colaboratory environment, please use environment-colab.yml .

✅ Tested: scripts are checked by common linter when pre-commit.

Here is the notebook link to provide the quick access to your analysis. You can create the conda environment by Right click Build Conda Environment or conda create -f environment.yml in Studio Lab.

Project Structure

.
├── data
│   ├── external                    # data from third party sources.
│   ├── processed                   # data after processing
│   ├── interim                     # data that transformed
│   └── raw                         # raw data
├── models                          # store models
├── notebooks                       # store notebooks
├── docs                            # documentation for your project
├── .gitignore                      # ignore files that cannot commit to Git
├── .pre-commit-config.yaml         # configurations for pre-commit
├── pyproject.toml                  # dependencies for poetry
├── README.md                       # describe your project
├── scripts                         # store source code used in notebook
│   └── __init__.py                 # make src a Python module
└── tests                           # store tests
    └── __init__.py                 # make tests a Python module

Customization

• environment.yml: Please specify the packages and versions. As a default, no version is specified.
• .pre-commit-config.yaml: Please check the rev to check the code.
• Change the Notebook url for Open in Studio Lab.