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Prompt arguments

When running the command ccp a prompt will start which enables you to configure your repository. The prompt values and their explanation are as follows:

project_type

Choose the type of project to generate:

  • "package": Python library/package for distribution. Includes example module with functions and is ready for PyPI publishing.
  • "cli": Command-line application built with Typer and Rich. Includes executable entry point and make run command.
  • "notebooks": Data science project with JupyterLab, pandas, numpy, matplotlib, and seaborn. Includes sample notebooks for exploration and visualization, plus notebook testing with nbval.

author

Your full name.

author_email

Your email address associated with your github account.

author_username

Your github handle, i.e. <handle> in https://github.com/<handle>.

project_name

Your project name. Should be equal to the name of your repository and it should only contain alphanumeric characters and -'s.

package_name

The package name, will default to the project_name with all -'s replaced with _. This will be how you import your code later, e.g.

from <package_name> import foo

Note: You can set package_name to "src" to place the Python module inside a src directory.

project_description

A short description of your project.

git_repo

"y" or "n". Whether you want to create a local git repo for the project.

git_server

In case you want to use another git service than github, you can specify it here. The default is github.com.

private_repo

"y" or "n". Whether to create a private repository when creating a remote repository on GitHub. Only relevant if git_repo is set to "y" and you choose to create a remote repository.

mkdocs

"y" or "n". Adds MkDocs documentation to your project. This includes automatically parsing your docstrings and adding them to the documentation. Documentation will be deployed to the gh-pages branch.

github_actions

"y" or "n". Adds GitHub Actions CI/CD workflows to your project. When enabled, your project gets:

  • Continuous Integration: Automated testing across Python 3.9-3.13 and multiple operating systems (Ubuntu, macOS, Windows)
  • Code Quality Checks: Automatic linting (ruff), formatting, and type checking (mypy)
  • Documentation Deployment: Automatic deployment to GitHub Pages when MkDocs is also enabled
  • Security Scanning: CodeQL analysis and dependency vulnerability scanning with weekly automated checks

This adds pytest-cov>=4.0.0 to your dev dependencies for coverage reporting.

codecov

"y" or "n". Enables Codecov integration for coverage reporting. Only relevant if github_actions is also set to "y". When enabled, your CI pipeline will automatically upload coverage reports to Codecov and provide coverage analysis on pull requests.