sqlschm VS sqlglot

> The main reason why I ended up building a SQL engine was...just for entertainment. It's been fun learning about all the things

I also wrote an SQL parser [1] for SQLite schema. This was mainly for fun, but also to support the specificities of SQLite schema. I was not happy with the result of other parsers (including sqlglot).

[1] https://github.com/coast-team/sqlschm

SQL is a mess. It is difficult to find a parser that fulfills your needs.

A month ago, I needed a parser to parse SQLite schemas. SQLite has some edge case and I needed a lossless parsing to detect these edge cases.

I finally wrote my own parser [1] to fullfill my needs and to have some fun. This is for a POC project.

[1] https://github.com/coast-team/sqlschm

This is probably referring to "zero changes to your driver code" and not "zero changes to the SQL you send over this driver".

Translating between SQL dialects is notoriously hard and attempts to translate [1] are working in 95% of cases. But the last 5% would require 5x amount of work. That's because "SQL dialect" also includes weird edge cases of type inference of things like COALESCE(5, FALSE) and emulation of system catalogs (pg_catalog, information_schema).

[1] https://github.com/tobymao/sqlglot

Recommend checking out https://github.com/tobymao/sqlglot if you are interested in this capability for other SQL dialects

Tools like this are helpful for:

- Rendering SQL in a consistent way, eg for snapshot testing

sqlglot – Python SQL Parser and Transpiler

In the project we used Python lib networkx and a DiGraph object (Direct Graph). To detect a table reference in a Query, we use sqlglot, a SQL parser (among other things) that works well with Bigquery.

Cool! Is this built with sqlglot[1] on the back end?

[1] https://github.com/tobymao/sqlglot

Wanted to give sqlglot a shoutout as it saved me a ton of time.