A few questions about Slepian and generalized gaussian windows
The Slepian sequences are a family of functions.  Most algorithms calculate 2*NW - 1  sequences at once for a given NW.  N is the number of points in the sequence and W decides half the width of the mainlobe in the frequency domain for the Fourier transform of a given Slepian sequence.  Typically you would use an NW of 3 or 4 for your signal processing.

In scipy, they are asking for the $N$ (m in the Python code) and the $W$ (width in the Python code) parameter separately while in matlab you input the time-bandwidth product $NW$ as a single parameter.  This makes sense because you're typically calculating the Slepian sequences for a fixed window size, $N$.

If you are estimating the power spectrum of a stationary time series the DPSS are the set of windows you should use.

The generalized Gaussian function returns a Gaussian-like function raised to successively higher powers depending on the p parameter.  As p is raised to successively higher powers the generalized Gaussian becomes narrower in the time domain.  The nice property of a Gaussian is that it is it's own Fourier transform and it is the function that achieves the limit concerning the uncertainty principle.  A Gaussian function may be useful if you would like to compute a short-time Fourier transform or spectrogram as an estimator for a time-varying power spectrum of a non-stationary time series.