Sqlite solving - #4
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Enable math functions[1] by using a dedicated fresh build of sqlite3 instead of native stdlib, which is compiled without it. Build is from pysqlite3 lib, specced as pre-built binary, I don't have all day to compile this myself. See pysqlite3 project docs[2] specifying their sqlite3 config flags. [1]: https://www.sqlite.org/lang_mathfunc.html [2]: https://github.com/coleifer/pysqlite3
Now the sqlite in Python supports math operators, we can fill in entropy via SQL operations, rather than compute in pure Python. This is because crucial math func log2 is now available in pysqlite3. Unfortunately I'm limited by my own personal knowledge of SQL now. Great project to learn though, I'm really enjoying this low-stakes deep dive into SQL with tangible benefits at the end, even if I'm just recreating the results of 3blue1brown at the end: Building this on top of literate_wordle is nice bonus.
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Not sure I really want to make another "novel" of this, but investigate solving of Wordle, by brute-force statistics, inspired by 3Blue1Brown.
I've never felt like I mastered SQL, so this is a perfect opportunity to learn, by using sqlite3!
New
sqlite_solve.pyfile, pre-computing all wordle guesses against all answers, storing result in new sqlite tables.Tables allow solving wordle in a basic way: pick a good guess, input in wordle, insert the score in DB in a query that lists answers that match that score for that guess.
But as 3Blue1Brown video (linked in docstring) explains, we can optimize guess selection via information theory. This is still WIP in SQL (limited by my own knowledge of SQL queries)