  We present Cryptomite, a Python library of randomness extractor
implementations. The library offers a range of two-source, seeded and
deterministic randomness extractors, together with parameter calculation
modules, making it easy to use and suitable for a variety of applications. We
also present theoretical results, including new extractor constructions and
improvements to existing extractor parameters. The extractor implementations
are efficient in practice and tolerate input sizes of up to $2^{40} > 10^{12}$
bits. They are also numerically precise (implementing convolutions using the
Number Theoretic Transform to avoid floating point arithmetic), making them
well suited to cryptography. The algorithms and parameter calculation are
described in detail, including illustrative code examples and performance
benchmarking.
