Contributing to PyFastANI

For bug fixes or new features, please file an issue before submitting a pull request. If the change isn’t trivial, it may be best to wait for feedback.

Setting up a local repository

Make sure you clone the repository in recursive mode, so you also get the wrapped code of FastANI which is exposed as a git submodule:

$ git clone --recursive https://github.com/althonos/pyfastani

Compiling the extension

Compiling requires the boost::math module from Boost. Depending on your system, you may have to install them yourself.

To compile the extension, use the following command:

$ python setup.py build_ext

Running tests

Tests are written as usual Python unit tests with the unittest module of the standard library. Running them requires the extension to be built locally:

$ python setup.py build_ext --debug --inplace
$ python -m unittest discover -vv

Running benchmarks

Query fragments mapping

The benches folder contains benchmarks for evaluating the performance of the node connection scoring step, essentially to make sure that the multi-threading makes it faster.

Start by building pyfastani locally:

$ python setup.py build_ext --inplace

Then make sure you have the required packages and data:

$ pip install --user -r benches/mapping/requirements.txt
$ python benches/data/download.py

Finally, run the benchmarks and plot the results:

$ python benches/mapping/bench.py -d benches/data/ -o times.json
$ python benches/mapping/plot.py -i times.json --show

Coding guidelines

This project targets Python 3.6 or later.

Python objects should be typed; since it is not supported by Cython, you must manually declare types in type stubs (.pyi files). In Python files, you can add type annotations to function signatures (supported in Python 3.5) or in variable assignments (supported from Python 3.6 onward).

Interfacing with C

When interfacing with C, and in particular with pointers, use assertions everywhere you assume the pointer to be non-NULL.

Interfacing with C++

When wrapping objects, use stack allocation where possible.