Antoine Pitrou added the comment:
> What constitutes "enough" is a value judgment that many vary from
> application to application. For some applications, a much weaker PRNG
> would suffice, but we decided long ago that we wanted the full power of MT.
I don't really understand for which application 20000 bits of seeding entropy
would be required *in practice*. Surely MT has other interesting properties
(such as the statistical distribution of the output) than its insanely large
cycle length, that make it desirable as a PRNG.
The paper you linked to ("Good Practice in (Pseudo) Random Number Generation
for Bioinformatics Applications") doesn't suggest feeding a 20000 bits seed, it
actually seems to say that 64 bits is enough for numerical simulations run on
large clusters.
While reading 20000 bits off of /dev/urandom might be fast under Linux, it
might not necessarily be the case on other systems. It doesn't sound reasonable
to read this many data if there isn't a strong reason for doing it.
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<http://bugs.python.org/issue21470>
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