Crude static Huffman example, that could definitely be improved: 5 bits 0 0000-1111 acde fghi lmno rstu 7 bits 10 00000-11111 bjkp qvwx yzAB C

Crude static Huffman example, that could definitely be improved: 5 bits 0 0000-1111 acde fghi lmno rstu 7 bits 10 00000-11111 bjkp qvwx yzAB CDEF GHIK LMNO PRST UVWY 7 bits 110 0000-1111 JQXZ 0123 4567 89/. 8 bits 111 00000-11110 !@#$ $%^& *()_ {}[] `~+= |\"' ;:<> ,? (space at the end) 16 bits 11111111 00000000-11111111 plus UTF-8 1 to 256 unicode characters encoded as UTF-8 You could even include some bigrams in this sort of table. There's some code here that could maybe be used for that sort of static huffman tree: https://github.com/ryancdotorg/lztp/blob/main/generate-seed.js https://github.com/ryancdotorg/lztp/blob/main/generate-seed.... Alternatively, have something like this: 00 000000-111111 1-64 characters, 5 bits each 01 000000-111111 1-64 characters, 6 bits each 10 000000-111111 1-64 characters, ~6.4 bits each (character set of 84 characters, every 5 packed into 32 bits) 11 000000-111111 1-64 characters, UTF-8 This is vaguely similar to how data is encoded for QR codes. As pointed out elsewhere, this will not outperform zstd with a dictionary trained on a corpus, but zstd would require pulling in a lot of code.