Your Python / TypeScript etc. argument is a strawman, thats why it sounds absurd. Your arguments would hold better if an average person was good and very quick at learning and memoizing complex new things. I don't know if you work with people like that, but that's definitely not the norm. Even developers know little SQL unless it's their specific focus.

In the original comment you said:

> I guarantee you, anyone who knows any other language could learn enough SQL to do 99% of what they wanted in a couple of hours. Give it a day of intensive study, and you’d know the rest. It’s just not that complicated.

Well your "guarantee" does not hold up. Where I live, every college level developer went through multiple semesters of database courses and yet I don't see these people proficient in SQL. In couple hours? 99% of what they need? Absurd

It's not a strawman, it's reductio ad absurdum. SQL and Python are both languages that are commonly used. It would be (currently; who knows in a few years) laughable if someone said they didn't need to deeply understand Python to be able to correctly write Python at an employable level, modulo experience levels - I don't expect a Junior to know the vagaries of the language, e.g. that bools are aliased to integers.

> Even developers know little SQL unless it's their specific focus.

Yes, and I believe this to be deeply problematic. We don't generally allow people to use a language they don't understand in production, except for SQL.

> Where I live, every college level developer went through multiple semesters of database courses and yet I don't see these people proficient in SQL.

That's horrifying.

Look, while I would love it if everyone writing SQL knew relational algebra, basic set theory, and the ins and outs of their specific RDBMS implementation, I think the below suffices for the majority of work in web dev:

    SELECT: extract the columns that are named, optionally with an alias with AS (or simply a space)
    FROM: the [main] table to extract columns from
    [INNER] JOIN: an additional table to examine, returning only their intersection
    LEFT [OUTER] JOIN: an additional table to examine, returning everything in the LHS table, as well as any matches from the RHS table, with NULLs filling in missing data
    RIGHT [OUTER] JOIN: the same as LEFT JOIN, but with the logic swapped
    FULL [OUTER] JOIN: an additional table to examine, returning the union of both tables, regardless of matches
    ON: an expression to use for joining tables, generally consisting of at least one column from each table to match
    WHERE: a predicate (or series of predicates, with boolean operators joining them) to use for filtering the result set
    ORDER BY: one or more columns to order the result set by, in either ascending (ASC) or descending (DESC) order
    GROUP BY: one or more columns (though strictly speaking, this number must match the number of non-aggregated columns in the SELECT) to group the result set by
    LIMIT: a limit for the maximum number of rows returned