Development

APyTypes is an open source project and contributions are very welcome! From bug reports, through enhancement suggestions, to better documentation and code.

The development happens at https://github.com/apytypes/apytypes where you also can provide suggestions and report bugs.

Here, there will be some development information to be expanded over time.

Pre-requisites

Most required packages will be installed during the installation process, but a few things are required:

• A C/C++ compiler supporting at least C++17.

• CMake

Clone the repository

To clone the repository, do

git clone https://github.com/apytypes/apytypes.git

However, if you want to contribute to the development, it is preferred to first fork your own copy and then clone that. See the next section.

Fork and clone

Go to the repository in GitHub and then click the Fork button. This will create a copy of APyTypes in your own user space. Now, click the Code button and clone using either ssh (preferred) or https. For ssh to work you need to set up ssh keys.

Installation

To install APyTypes from a cloned git-version, make sure that you stand in the directory containing the cloned git-version, then do:

python -m pip install .

Any change in the C++-code will require a reinstallation, so this is something done frequently during development.

If you want to run tests, instead doing

python -m pip install .[test]

will also install the test dependencies required. (This only needs to be done once, or when the dependencies are updated.)

Run test suite

To run all test cases do:

python -m pytest lib

Update stub files

There is a script in the root directory stubgen.sh that must be executed to update the stub-files in case any additional Python-level methods or classes are added or if argument names or Python-level docstrings are changed.

Run floating-point tests vs Berkeley TestFloat

Randomly generated test cases from Berkeley TestFloat can be run for the floating-point datatypes. These are not executed by using pytest but instead with a dedicated Python script. To use it, start by installing Berkeley TestFloat, and make sure to add the binary testfloat_gen to your PATH. You can then see example usage of the script by running

cd lib/test/apyfloat/
python run_berkeley_cases.py -h

These are intended to more long running tests. If any bugs or deviations are found, dedicated tests should be added to the regular test suite.