This is a supplement to "Forecasting the detection capabilities of third-generation gravitational-wave detectors using \texttt{GWFAST}", where the detection capabilities of the second and third generation of ground-based gravitational-wave detectors are studied. The software used to produce these results is \texttt{GWFAST} (this https URL), a Fisher information \texttt{Python} code that allows us to easily and efficiently estimate signal-to-noise ratios and parameter measurement errors for large catalogs of resolved sources observed by networks of gravitational-wave detectors. In particular, \texttt{GWFAST} includes the effects of the Earth's motion during the evolution of the signal, supports parallel computation, and relies on automatic differentiation rather than on finite differences techniques, which allows the computation of derivatives with accuracy close to machine precision. We also release the library \texttt{WF4Py} (this https URL) implementing state-of-the-art gravitational-wave waveforms in \texttt{Python}. In this supplement we provide a documentation of \texttt{GWFAST} and \texttt{WF4Py} with practical examples and tests of performance and reliability.
