dock VS rayon

Just some friendly feedback: from the page you've linked to and this post, it's a little confusing to figure out what this is and why I should use it over the native Docker CLI. The GitHub page is a little more informative - even adding a framing headline like "A tool for using Docker containers as environments" or "Dock is a thin wrapper around the Docker CLI that makes Docker environments seamless" above the screenshot on your landing page would probably go a long way to communicating what your tool does and who should care.

I'm adding tests around the newest subcommand in dock, which is a thin wrapper around docker to streamline the use of Docker in a "development" context (as opposed to a deployment context). I recently added the run subcommand for running a command in the newest build of a Docker container, which will have certain configurable shortcuts, like running the command with the local user's ID, bind mounting the local project directory, and "nesting" the Docker daemon.

Hi /u/benzaita, thanks for sharing. I'm working on a tool with similar functionality (dock), so it's interesting to see a different approach in the same space. The features and Why use dockerized are great breakdowns of the advantages of this approach, and points that I've often made or observed myself, so it's great to have lists of these points to reference.

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.