Chariots template

chariots provides a template to create Chariot templates that take care of the boilerplate involved. This template is inspired by the DataScience audreyr/cookiecutter-pypackage and drivendata/cookiecutter-data-science project templates so you may find some similarities

to create a new project, just use

$ chariots new

you can then follow the prompts to customize your template (if you don’t know what to put, follow the defaults). If you want a minimalist example (using the classic iris dataset), you can put y`in the `use_iris_example parameter.

File Structure

the file structure of the project is as follows:

.
├── AUTHORS.rst
├── LICENSE
├── MANIFEST.in
├── Makefile
├── README.rst
├── docs
│   ├── Makefile
│   ├── authors.rst
│   ├── conf.py
│   ├── index.rst
│   ├── installation.rst
│   ├── make.bat
│   └── modules.rst
├── iris
│   ├── __init__.py
│   ├── app.py
│   ├── cli.py
│   ├── ops
│   │   ├── __init__.py
│   │   ├── data_ops
│   │   │   └── __init__.py
│   │   ├── feature_ops
│   │   │   └── __init__.py
│   │   └── model_ops
│   │       └── __init__.py
│   └── pipelines
│       └── __init__.py
├── iris_local
│   ├── data
│   └── ops
├── notebooks
│   └── example_notebook.ipynb
├── requirements.txt
├── requirements_dev.txt
├── setup.cfg
├── setup.py
└── tests
    └── test_server.py`

the iris folder (it will take the name of your project) is the main module of the project. It contains three main parts:

• the ops module contains all your Chariot ops. this is where most of the models/preprocessing goes (in their specific subfolders)

• the pipelines module defines the different pipelines of your project

• the app module provides the Chariots app that you can use to deploy your pipeline

the iris_local folder is where the chariots app will be mounted on (to load and save data/models) by default

the notebooks folder is where you can put you exploration and reporting notebooks

tools

the template provides several tools in order to facilitate development:

a cli interface that include

$ my_great_project start

to start the server

a makefile to build the doc, clean the project and more

and more to come… -