parser VS pyparsing

I find straight forward, dedicated combinators much more readable and practical to use ie. for iterables (context where it makes a lot of sense) [0] example [1], runtime assertions (through refutations, which are much faster than combinators over assertions) [2], parser combinators for smallish grammars [3] etc.

In many cases vanilla/imperative js is more readable and terse, no need to bring functional fanaticism everywhere, just in places where it gives true benefits and in form that can be understood by peers.

Functional code can be beautiful and can also be unreadable/undebugable. Same with imperative code. It's great in js/ts you can pick approach where the problem is expressed more naturally and mix it at will.

[0] https://github.com/preludejs/generator

[1] https://observablehq.com/@mirek/project-euler

[2] https://github.com/preludejs/refute

[3] https://github.com/preludejs/parser

Parser combinators are great, we're using parser combinators in production, they are great ie. for typescript [0].

[0] https://github.com/preludejs/parser

After over a year since the last release of pyparsing, I've bundled up all the bug-fixes and changes, and they are now released as pyparsing 3.1.0. Visit this link for the details.

Look into "parser combinators" for building an interpreter. There's a few ones out there, but PyParsing is one I've seen around that looks pretty nifty.

I havent found a way to specify an exact character match in pyparsing - https://github.com/pyparsing/pyparsing/discussions/443

STDOUT: Lark or pyparsing

Since it is not mentioned in the article: Python users may also want to check out pyparsing [0]. It is slightly different from Parsec/FParsec (for instance, it ignores all whitespace by default), but I think it is a really good project.

[0]: https://github.com/pyparsing/pyparsing/

Here is the page of all the new changes and features in pyparsing 3.0.

Your pyparsing parser might benefit from a tune-up. This page has some performance tips: https://github.com/pyparsing/pyparsing/wiki/Performance-Tips.

If your SQL has fairly complex structure, you will need a full blown SQL parser. If your statements are mostly simple select, you can get pretty close with Pyparsing, here is an example.