The compression of a trie may not be the best because of the node storage requirement. I've benchmarked the memory usage of some Python trie libraries here: htt

The compression of a trie may not be the best because of the node storage requirement. I've benchmarked the memory usage of some Python trie libraries here: http://kmike.ru/python-data-structures/ http://kmike.ru/python-data-structures/ I also tried to compress "/usr/share/dict/words" with https://github.com/kmike/DAWG https://github.com/kmike/DAWG and https://github.com/kmike/marisa-trie https://github.com/kmike/marisa-trie Python libraries: import dawg import marisa_trie words = open('/usr/share/dict/words', 'r').read().splitlines() dawg.DAWG(words).save('words.dawg') marisa_trie.Trie(words).save('words.trie') The result is a bit surprising: 1220612 words.dawg 743128 words.trie Please note that MARISA-trie is not a classic trie, it is a smart & crazy recursive trie (something like DAWG-Trie hybrid). By the way, I was expecting DAWG to perform much better; for my data (5mln Russian words) the DAWG compression was much more impressive.