sqlx VS rayon

What exactly are you missing? I haven't really written "boring corporate backend stuff" in a few years but something like sqlx provides everything I've ever needed there.

Badges are the little rectangles you typically see at the top of a crate's README: https://github.com/launchbadge/sqlx/blob/main/README.md

SQLX has entered the chat [1].

[1] https://github.com/launchbadge/sqlx

Database : SqLite (using sqlx).

The current (well, removed) MSSQL sqlx driver also doesn't support encrypted connections (https://github.com/launchbadge/sqlx/issues/1552), so it might work locally on an unnamed instance but not over the network until they add in the newer driver (which will be closed source but for an OSS project you should be able to request a free license I think)

I'm considering making my own wrapper over lower-level database drivers. There are a lot of features in sqlx that I don't need, and the latest version seems to have removed useful data structures that SQLPage is using. It also removed support for SQL Server.

add Ed25519 to AuthPlugin enum on https://github.com/launchbadge/sqlx/blob/061fdcabd72896d9bc3abb4ea4af6712a04bc0a8/sqlx-core/src/mysql/connection/auth.rs and implement them using these crates:

Do some operations with .iter() then later use rayon to parallelize. So you can show how easy is to add a dependency and how easy is to parallelize.

rayon: Async CPU runtime for parallelism.

In the quest for more efficient solutions, the ONNX runtime emerged as a beacon of performance. The decision to transition from Typescript to Rust was an unconventional yet pivotal one. Driven by Rust's robust parallel processing capabilities using Rayon and seamless integration with ONNX through the ort crate, Repo-Query unlocked a realm of unparalleled efficiency. The result? A transformation from sluggish processing to, I have to say it, blazing-fast performance.

With a lot of rayon, blood, sweat and tears I finally managed to simulate a million buildings at 60fps :) Feel free to AMA, game is Combine And Conquer

(see https://github.com/rayon-rs/rayon/tree/master/src/iter/plumbing)

I did some very basic testing with this crate : https://crates.io/crates/rayon and it seems to work :

Sequentially, generating tree-sitter AST for each file and querying for the links of each file takes around 2.3 seconds. However, I randomly remembered this crate rayon, and I decided to test it. It ended up improving the performance (just by changing 2 lines of code) to 200-300ms by parallelizing the iterators and tree-sitter queries. MAJOR.

Now if you really want to use Rust, you can rewrite only the part that are slowing down your consumer. It's easy by using Py03 and maturin. Maybe also rayon to parallelize.

Maybe rayon could make some loops there and there faster if needed.