Skip to content

stjordanis/xtensor-julia-cookiecutter

 
 

xtensor-cookiecutter

Travis Appveyor Documentation Status Join the Gitter Chat

A cookiecutter template for creating a custom Julia extension with xtensor

What is xtensor-julia-cookiecutter?

xtensor-julia-cookiecutter helps extension authors create Julia extension modules making use of xtensor.

It takes care of the initial work of generating a project skeleton with

  • A complete Julia package comprising the extension module

  • A few examples included in the resulting project including

    • A universal function defined from C++
    • A function making use of an algorithm from the STL on a Julia N-D array
    • Unit tests
    • The generation of the HTML documentation with sphinx

Usage

Install cookiecutter:

$ pip install cookiecutter

After installing cookiecutter, use the xtensor-julia-cookiecutter:

$ cookiecutter https://github.com/xtensor-stack/xtensor-julia-cookiecutter.git

As xtensor-julia-cookiecutter runs, you will be asked for basic information about your custom extension project. You will be prompted for the following information:

  • author_name: your name or the name of your organization,
  • author_email: your project's contact email,
  • github_project_name: name of the GitHub repository for your project,
  • github_organization_name: name of the GithHub organization for your project,
  • julia_package_name: name of the Python package created by your extension,
  • cpp_namespace: name for the cpp namespace holding the implementation of your extension,
  • project_short_description: a short description for your project.

This will produce a directory containing all the required content for a minimal extension project making use of xtensor with all the required boilerplate for package management, together with a few basic examples.

Resources

About

Cookiecutter for a Julia project making use of xtensor

Resources

License

Code of conduct

Security policy

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • CMake 53.6%
  • Julia 30.3%
  • C++ 12.4%
  • Python 3.7%