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:
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_nem> 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
.
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.