Home "Pretty" Continuous Integration for Python
 This is a slightly.. vain question, but BuildBot's output isn't particularly nice to look at.. For example, compared to.. phpUnderControl Jenkins Hudson CruiseControl.rb ..and others, BuildBot looks rather.. archaic I'm currently playing with Hudson, but it is very Java-centric (although with this guide, I found it easier to setup than BuildBot, and produced more info) Basically: is there any Continuous Integration systems aimed at python, that produce lots of shiny graphs and the likes? Update: Since this time the Jenkins project has replaced Hudson as the community version of the package. The original authors have moved to this project as well. Jenkins is now a standard package on Ubuntu/Debian, RedHat/Fedora/CentOS, and others. The following update is still essentially correct. The starting point to do this with Jenkins is different. Update: After trying a few alternatives, I think I'll stick with Hudson. Integrity was nice and simple, but quite limited. I think Buildbot is better suited to having numerous build-slaves, rather than everything running on a single machine like I was using it. Setting Hudson up for a Python project was pretty simple: Download Hudson from http://hudson-ci.org/ Run it with java -jar hudson.war Open the web interface on the default address of http://localhost:8080 Go to Manage Hudson, Plugins, click "Update" or similar Install the Git plugin (I had to set the git path in the Hudson global preferences) Create a new project, enter the repository, SCM polling intervals and so on Install nosetests via easy_install if it's not already In the a build step, add nosetests --with-xunit --verbose Check "Publish JUnit test result report" and set "Test report XMLs" to **/nosetests.xml That's all that's required. You can setup email notifications, and the plugins are worth a look. A few I'm currently using for Python projects: SLOCCount plugin to count lines of code (and graph it!) - you need to install sloccount separately Violations to parse the PyLint output (you can setup warning thresholds, graph the number of violations over each build) Cobertura can parse the coverage.py output. Nosetest can gather coverage while running your tests, using nosetests --with-coverage (this writes the output to **/coverage.xml)