[jonathankoren]

I made my own Wordle solver recently that uses frequency analysis of letters and bigrams of five letter English words as a scoring function. It works fairly well.

Someone in this discussion suggested using frequency analysis at position, which seems interesting, especially when trying to locate misplaced letters. I might have to try that.

https://github.com/jonathankoren/wordle-solver

[Supermancho]

What was your source for "English words"? This is an interesting problem, itself.

[jonathankoren]

Googling will give you countless lists. The internet solved that problem decades ago.

The biggest problem is when your guessing dictionary contains words that aren’t in the acceptable word list in Wordle. For that, I generate 10 guesses on each turn. At least one of them should show up. I didn’t want to use Wordle’s dictionary because that felt like cheating.

[Supermancho]

> The biggest problem is when your guessing dictionary contains words that aren’t in the acceptable word list in Wordle.

A dictionary is not interesting, but for the selection of the contents.

> Googling will give you countless lists. The internet solved that problem decades ago.

That's not a solution when the definitive lists all differ. English is a high context language, so the existence of words is both a function of frequency and locality (this includes time periods). Deciding on what's the canonical list isn't "look up what Wordle uses" anymore than Webster or Oxford. That's the problem I'm referencing.

[schappim]

I did the same. My source of words was the Unix dictionary found in macOS. The path is:

  /usr/share/dict/words

When I did the frequency analysis, I scoped it to only 5 letter words.

If you're looking for a great "first guess word", "trace" is one of the words that will yield the most clues.