A solution to the problem of finding five English words with 25 distinct characters, as posed in this video by Matt Parker: https://www.youtube.com/watch?v=_-AfhLQfb6w

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Introduction

I came to the same algorithm everyone else did independently, but I've added a few things that help (mainly #6). My python code uses the same algorithm as the c++, but has better comments and is easier to read.

1. Depth first search. Pick one word at a time, check if it collides with previous word.
2. Use bitmasks to represent the words for faster detection if a word reuses a letter.
3. When picking the next word, only check words that are using the lowest bit (i.e. letter) missing. A tiny hitch is that you have to keep track of which letter you get to skip.
4. Store each word in separate lists based the lowest bit. By separating them, you only have to check one list of words to use, dramatically reducing how many words to check at each layer of the depth search.
5. Instead of putting the bits in alphabetic order, sort letters/bits based on their frequency in all words. When combined with the above steps, this makes the search start with the hard letters to use. Otherwise, you'll start with a word like learn which eats up tons of easy letters making it hard to find words that need them.
6. As in step 4, also separate lists based on if they've used the most common letters. This is equivalent to essentially precaching bitmask collision detections. Out of 5977 unique bitmasks, with steps 1-5, you completely skip and never check 409 words. With this step, 2230 are never checked directly. How many of the top bits to use affects performance. Too many and you waste time fumbling through lists. Too few and you miss out on the sweet caching opportunities. In my code, this is controlled by theletter_buckets variable/constant. Experimentally, 4-7 is pretty good. Actual best is language and hardware dependent.
7. Multithreading! I'm proud to say that my single threaded algorithm can hold it's own against oisyn/parkerwords which uses multithreading. But there's no reason this algorithm can't be multithreaded as well. I completely stole oisyn's implementation here, so I can't claim that as my own. It was eerie reading their code and seeing how similar it was to mine.

Example sorted word table into separate buckets. Rows are the least common letter used. Columns are which most common letters they don't use. This table only uses the top 3 bits. My c++ seems to prefer 6, and python likes 5. Other peoples' implementations effectivly use 0 and collapse each row into 1 bucket.

	sea	ea	sa	a	se	e	s	{}
q	moqui quick 10 more	hdqrs qophs 9 more	cequi coque 16 more	queys quest 2 more	antiq faqir 20 more	qaids qiyas 10 more	aequi caque 9 more	sequa
j	bijou brujo 30 more	djins fujis 20 more	bejig benjy 43 more	ejusd jebus 15 more	anjou arjun 62 more	hajis jacks 14 more	bejan djave 19 more	hajes jades 7 more
x	boxty bronx 25 more	nyxis oxids 8 more	bemix beryx 67 more	boxes coxes 24 more	acrux adfix 47 more	axils axons 5 more	adnex axile 23 more	axels axers 6 more
z	blitz bortz 29 more	grosz liszt 12 more	benzo bezil 41 more	bizes cozes 14 more	arzun azido 58 more	azons czars 12 more	adoze adzer 39 more	adzes fazes 8 more
v	bovid bovld 48 more	divus intsv 23 more	bevil bevor 92 more	coves dives 32 more	admov alvin 69 more	alvus amvis 27 more	above aevum 65 more	avens avers 12 more
f	clift comfy 101 more	bumfs coifs 77 more	befit befog 93 more	chefs clefs 36 more	adolf afgod 94 more	afros alifs 50 more	afire afley 43 more	alefs cafes 9 more
w	blowy blown 83 more	blows brows 63 more	below bewig 87 more	bowse brews 43 more	ablow adown 111 more	aswim awols 57 more	alowe awber 41 more	askew awest 9 more
k	bikol birky 120 more	bilks birks 105 more	becky biked 98 more	becks bikes 49 more	aking akron 130 more	adusk amoks 61 more	ackey acker 45 more	alkes asked 9 more
b	bichy bidry 117 more	bhuts bilos 62 more	becry becut 110 more	belis belts 40 more	abdom abhor 123 more	abysm abris 37 more	abend abide 55 more	abets abies 7 more
g	ching chung 121 more	chugs clogs 67 more	chego cheng 94 more	doges dregs 30 more	acing agony 110 more	agios agism 45 more	aegir agend 44 more	aegis agers 9 more
p	chimp chirp 104 more	chips chops 80 more	chelp cypre 92 more	copes dopes 40 more	acoup adopt 99 more	alisp aphis 52 more	adept ayelp 38 more	adeps aesop 9 more
m	chimu chirm 75 more	chums comus 49 more	celom chime 74 more	cymes comes 35 more	admin admit 85 more	adsum alums 37 more	admen ahmed 37 more	acmes ahems 8 more
h	child chino 66 more	chins chits 47 more	cheir chert 51 more	chest choes 27 more	achor ahind 65 more	alish arish 35 more	ached achen 23 more	aches ashed 7 more
y	cydon cindy 40 more	cyrus cloys 34 more	cedry ceryl 37 more	cosey desyl 16 more	acidy acryl 42 more	acyls ayins 23 more	acedy aiery 12 more	ayens asyle 3 more
d	cloud contd 23 more	clods cords 29 more	cetid cider 39 more	cedis codes 21 more	acold acrid 38 more	acids adios 22 more	acned acred 21 more	aides andes 5 more
c	clint cloit 18 more	cions clons 21 more	ceint cento 20 more	ceils celts 16 more	acoin acorn 23 more	acost actus 15 more	acier acone 13 more	acies acnes 4 more
u	rutin tourn 3 more	inust irous 13 more	enrut intue 13 more	etuis euros 11 more	alout altun 13 more	ainus alnus 10 more	alenu aleut 6 more	aures salue 2 more
n	inrol intro nilot	insol instr 5 more	eloin enrol 7 more	elsin enols 7 more	aloin altin 7 more	airns anils 7 more	aeron alien 7 more	aeons anise 3 more
t	lirot	islot isort 2 more	eliot lerot liter	islet iters 3 more	ariot latro 2 more	airts alist 4 more	alert aliet 3 more	aotes arest 2 more
l		loris	oiler	liers lores		aliso arils orals	ariel leora	aisle aloes arles
o				ireos		orias		arose
i								aesir
r
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e
a

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Future optimizations

• Use mmap to load the file. I'm on Windows so I can't, but I hear it can be an additional 10% speedup.
• Multithread the file parsing too. There's 370k words in the words list. If thread overhead isn't too much, this is easily parallelable.
• Get someone like stew675 or miniBill to implemented it along side all of their other hyper micro optimizations. ^{_{hint hint, nudge nudge, wink wink}}.
• I suspect that ordering my top bits based on frequency alone may not be optimal. Just like the optimal wordle strategy should consider the combined effect of multiple guesses together instead of each guess individually.