robotframework-kicadlibrary 1.1.1

Robot Framework KiCAD library

robotframework-kicadlibrary

A Robot Framework library for validating KiCad designs.

Releases are available via regular PyPI as well as GitHib releases. Example projects/usage is available under the examples/ sub-directory.

Keyword documentation is available online, as well as downloadable via GitHub Releases.

Getting Started

Prerequisites

You'll need an installation of Python, as well as pip and a working installation of KiCad. Please consult your operating system documentation on how to install these tools.

You will also need Robot Framework installed, but if you're installing using pip, Robot Framework will automatically be installed for you.

Installing KiCad, PIP and the library

This is dependent on your local operating system, but if you'te running any form of Unix-clone, it should typically be something in the lines of:

# Debian based systems
$ sudo apt-get install python-pip kicad
$ sudo pip install robotframework-kicadlibrary

# RedHat based systems:
$ sudo yum -y install epel-release
$ sudo yum -y install python-pip kicad
$ sudo pip install robotframework-kicadlibrary

Installing using PIP with existing environment

$ pip install robotframework-kicadlibrary

Using the library

*** Variables ***
Library    KiCadLibrary    schema=myproject.sch    pcb=myproject.kicad_pcb

*** Test cases ***
Module pads should be on grid
    Module Pads Should Be On Grid    50 mil    reference=.*$

Contributing

Any and all contributions are welcome, in the form of pull requests.

Versioning

We use SemVer for versioning. For the versions available, see the releases on this repository.

Authors

• Martin Kjellstrand - Initial work - madworx

License

This project is licensed under the MIT License - see the LICENSE.txt file for details

Developer information / Preparing a release

To create a release please follow this outline:

• Do your development work in a separate branch.
• Write unit-tests (tests/) and/or integration tests (examples/) for your code.
• Once all local tests validate, and you have 100% code coverage, push to GitHub.

If you have commit access to the main repository

• Once build hooks at Github/Sonarcloud/pyup etc have completed, tag a pre-release (x.y.zrc0)
• If that build completes, perform a PR into master, squashing the commit history.
• Tag the master branch with the new release version, ahdering to semantic versioning.
• Remove any pre artifacts from Docker Hub and PyPI.
• Delete the rc* tags from the repository. git tag -d x.y.zrcN, followed by git push origin :x.y.zpreN.

If you don't have commit access to the main repository

• Submit a PR towards the master branch of the main repository.