pybamm-cookie

This repository contains a copier template for battery modeling projects using PyBaMM, released under the BSD-3-Clause license. Currently under active development.

📄 Using pybamm-cookie

Generating projects with pybamm-cookie

Manually using copier

Install copier and jinja2_time extension using pip.

pip install copier jinja2-time

Generate a project from the pybamm-cookie template.

copier copy https://github.com/pybamm-team/pybamm-cookie.git . --trust
# this will generate the project in the current working directory
copier copy https://github.com/pybamm-team/pybamm-cookie.git path_to_copy_to/ --trust
# this will generate the project in the specified path

Using pipx (recommended)

You can generate a project by executing the pipx run command which doesn't need any package installations.

pipx run pybamm-cookie --path /path_to_copy_to

Or if you wish to install the pybamm-cookie package and then generate a project, you could do so with the help of following commands.

pipx install pybamm-cookie  # or pip install pybamm-cookie

Navigate into the directory you want your project directory to reside in, or use --path argument to explicitly mention the path where you want your project to be generated.

pybamm-cookie --path /path_to_copy_to

Using pip/pip inside venv

You can also perform a normal pip installation for the pybamm-cookie CLI and generate a project.

pip install pybamm-cookie
pybamm-cookie

Copier will prompt you with various configurations and you may choose the ones that suit your use case. Additionally you can perform pybamm-cookie -h to know the list of actions you can perform with the CLI.

Note

A git repository is automatically initialised when a project is created within a directory. To push the contents to the upstream GitHub repository, create a GitHub repository with the same name as your local repository and do not initialise your GitHub repository with any files such as licenses or README which might conflict with the local repository, follow these steps as listed in the GitHub documentation.

After generation, you can navigate to the generated project and run nox -s generated-project-tests to ensure if the project units are working as intended.

Installing the pybamm-cookie project

This refers to the project used for the development of this template. There are two ways to install this project: either through nox or pip. nox uses uv pip or pip internally, and in this case, creates a virtual environment for you to activate. To install, navigate to the root directory of this repository and execute either of these commands:

nox -s dev or pip install -e .[dev]

To check if the project was successfully installed, import the project inside Python.

import pybamm_cookie

pybamm_cookie.__version__

Project Layout

.
├── .github
│   └── workflows
├── docs
│   └── _static
├── src
│   ├── pybamm_example_project
│   ├── models
│   │   └── input
│   └─ parameters
│       └── input
├── tests
│    ├── generated_project_tests
│    └── user_tests
├─ noxfile.py
└─ pyproject.toml

A basic generated project with pybamm-cookie has a directory structure like the one depicted above. Each directory has a special purpose and is highly recommended to use them for their specific purposes to avoid any errors.

• docs/ contains the basic configuration for building documentation using sphinx.
• src/ contains the main package files under a directory with your specified project name. This is where all your code should be written.
  • models/input/ - Contains the source code for battery models. Refer PyBaMM models to learn how to write your own battery models.
  • parameters/input/ - Contains the source code for parameters sets. Refer PyBaMM parameter sets to learn more on parameter sets.
• tests/ The tests directory contains two sub-directories -
  • generated_project_tests/ - Contains pre-defined tests for verifying if the units inside generated project work well. It can be verified using nox -s generated-project-tests or pytest tests/generated_project_tests command.
  • user_tests/ - This directory contains all the user written tests, the example tests can be copied and modified as per your own needs. We suggest you use pytest to write tests. The tests can be then run by executing nox -s user-tests or pytest tests/user_tests.
• noxfile.py contains basic nox sessions for building documentation and runnings tests.
• pyproject.toml has project metadata and build backend configurations.
• github/workflows/ has all the basic CI configurations to automate tests and builds on GitHub Actions.

🚀 Motivation

This project aims to enhance the usability of PyBaMM for both newcomers and experienced users alike by providing standardised templates that incorporate best practices and automation tools. The pybamm-cookie template is set to lower the barrier to battery modeling, making it easier for the research community to adopt PyBaMM for their battery modeling projects. The project also supports model entry points and parameter set entry points, allowing community contributors to create and share models/parameter sets of their repositories using the copier template without directly adding them upstream. This lets community contributors retain ownership and choose license terms and also grants flexibility to the PyBaMM team in supporting models. Support for all of GitHub’s functionality and infrastructure is contained within the template.

🛠️ Contributing to pybamm-cookie

If you'd like to help us develop pybamm-cookie by improving the template's features, writing documentation, or fixing embarrassing bugs, please have a look at these guidelines.

📫 Get in touch

For any questions, comments, suggestions or bug reports, please see the contact page.

📃 License

The pybamm-cookie project is open source code. For more information about its license, see LICENSE.

✨ Credits

This project is highly inspired by these two projects -

• SciCookie, a cookiecutter template developed by Open Science Labs to provide a boilerplate to generate Python based projects with a hassle free experience.
• scientific-python/cookie, a project that supports copier/cookiecutter/cruft template generation for new Python projects based on Scientific Python developer guide.