The application of compressors for text statistics is fun, but it's a software equivalent of discovering that speakers and microphones are in principle the same device.

(KL divergence of letter frequencies is the same thing as ratio of lengths of their Huffman-compressed bitstreams, but you don't need to do all this bit-twiddling for real just to count the letters)

The article views compression entirely through Python's limitations.

> gzip and LZW don’t support incremental compression

This may be true in the Python's APIs, but is not true about these algorithms in general.

They absolutely support incremental compression even in APIs of popular lower-level libraries.

Snapshotting/rewinding of the state isn't exposed usually (custom gzip dictionary is close enough in practice, but a dedicated API would reuse its internal caches). Algorithmically it is possible, and quite frequently used by the compressors themselves: Zopfli tries lots of what-if scenarios in a loop. Good LZW compression requires rewinding to a smaller symbol size and restarting compression from there after you notice the dictionary stopped being helpful. The bitstream has a dedicated code for this, so this isn't just possible, but baked into the design.