Additional considerations

Unit tests

Writing unit tests is an important asset on code that needs to run in different platforms and a great way to make sure all is OK. Test units are run with nose. To run the test units on your package call:

$ ./bin/nosetests -v
bob.example.library.test.test_reverse ... ok

Ran 1 test in 0.253s


This example shows the results of the tests in the bob.example.project package. Ideally, you should write test units for each function of your package …


You should put additional packages needed for testing (e.g. nosetests) in the test-requirements.txt file.

Continuous integration (CI)


This is valid for people at Idiap (or external bob contributors with access to Idiap’s gitlab)


Before going into CI, you should make sure that your pacakge has a gitlab repository. If not, do the following in your package root folder:

$ git init
$ git remote add origin`basename $(pwd)`
$ git add bob/ buildout.cfg COPYING doc/ MANIFEST.IN README.rst requirements.txt version.txt
$ git commit -m '[Initial commit]'
$ git push -u origin master

Copy the appropriate yml template for the CI builds:

# for pure python
$ curl -k --silent > .gitlab-ci.yml
# for c/c++ extensions
$ curl -k --silent | tr -d '\r' > .gitlab-ci.yml

Add the file to git:

$ git add .gitlab-ci.yml

The ci file should work out of the box. It is long-ish, but generic to any package in the system.

You also need to enable the following options - through gitlab - on your project:

  1. In the project “Settings” page, make sure builds are enabled
  2. If you have a private project, check the package settings and make sure that the “Deploy Keys” for our builders (all conda-* related servers) are enabled
  3. Visit the “Runners” section of your package settings and enable all conda runners, for linux and macosx variants
  4. Go into the “Variables” section of your package setup and add common variables corresponding to the usernames and passwords for uploading wheels and documentation tar balls to our (web DAV) server, as well as PyPI packages. You can copy required values from [the “Variables” section of bob.admin]( N.B.: You must be logged into gitlab to access that page.
  5. Make sure to disable the service “Build e-mails” (those are very annoying)
  6. Setup the coverage regular expression under “CI/CD pipelines” to have the value ^TOTAL.*s+(d+%)$, which is adequate for figuring out the output of coverage report

Python package namespace

We like to make use of namespaces to define combined sets of functionality that go well together. Python package namespaces are explained in details here together with implementation details. For bob packages, we usually use the bob namespace, using several sub-namespaces such as, bob.ip, bob.learn, bob.db or (like here) bob.example.

The scripts you created should also somehow contain the namespace of the package. In our example, the script is named, reflecting the namespace bob.example

Distributing your work

To distribute a package, we recommend you use PyPI. Python Packaging User Guide contains details and good examples on how to achieve this. Moreover, you can provide a conda package for your PyPI package for easier installation. In order to create a conda package, you need to create a conda recipe for that package.

For more detailed instructions on how to achieve this, please see the guidelines on bob.template.