Development notes

Getting ready

This section will help you with the steps needed to start working on PacBio Data Processing.

  1. Clone the repository:

    git clone https://gitlab.com/dvelazquez/pacbio-data-processing
    
  2. CD into in:

    cd pacbio-data-processing
    
  3. (optional) Create a virtualenv/venv and activate it. See instructions in Installation.

  4. Install flit:

    pip install flit
    
  5. Install PacBio Data Processing with all the optional dependencies:

    flit install --symlink --deps=develop
    

With this, you should be ready to start coding but… please, keep reading!

Testing

The development of PacBio Data Processing follows the double loop TDD approach. See double loop TDD.

Writing code

double loop TDD is a generalization of plain TDD. A second TDD loop is added to the procedure. This sencond loop is behaviour driven, meaning that the functionality is guiding us in the development process.

In brief, the procedure to develop code with this technique is as follows:

  1. Write a functional test case (aka acceptance test) for the functionality you want to implement. You do this from the point of view of the user. After this step you will have a failing FT for that feature.

  2. Make your FT pass by implementing the needed features in your code following a normal TDD approach. Your point of view is now different from point 1: you look at the problem as a developer. Do not implement more features in your code than your FT requires to pass. In this phase we are just playing the usual TDD game with the goal of making the FT for the current feature pass.

Running the tests

  • For the functional tests

    $ pytest tests/functional
    
  • Unit tests (with coverage)

    $ pytest --cov=pacbio_data_processing tests/unit pacbio_data_processing
    

Writing tests

The FTs rely on pytest (with fixtures; without stdlib’s unittest)

The UTs use unittest from the standard library.

GUI

In a first approximation, the GUI tests were a bit smoky. The tests consisted in:

  1. (FTs) Ensure that if sm-analysis-gui is launched, a process remains there for some time (as one would expect after launching a gui program).

  2. (UTs) Mocky tests to check that Gooey has been employed.

One improvemnet would be using something like PyAutoGUI.