console VS evcxr

tokio-console is a debugger for Rust async programs that use Tokio. To get started, add the console-subscriber crate to your project and add the following line which will initialise the subscriber and allow tokio-console to connect to it:

You could try https://github.com/tokio-rs/console to debug and profile what happens with tokio tasks in your program.

The tokio-console CLI is a fun one. The console-subscriber supports shipping to a console server running elsewhere, apparently. That gives you a window into what's happening now.

Tokio console maybe? https://github.com/tokio-rs/console

If I add "console_subscriber::init()" line as https://github.com/tokio-rs/console recommends, tracing_subscriber cannot be initialized.

I'm building an HTTP load tester called pdc! I have run out of obvious (to me at least) places to look for performance gains. I'm achieving around 45,000 requests per second, per core. Right now I'm using hyper with a separate tokio runtime (in current thread mode) running on each core. So far having runtime on each core/NUMA node has really helped with cache coherency. Any recommendations for profiling beyond tokio console or tokio metrics (Convenient timing amirite!)?

It was just an accident and has been fixed https://github.com/tokio-rs/console/issues/270.

P.S. Tokio [now also has Tokio Console](https://github.com/tokio-rs/console) allowing you to conveniently troubleshoot your tasks if they are causing issues :)

You can opt-in to async runtime such as tokio, and you can use tokio-rs/console for it's top-like metric

Emacs didn't invent REPL, and it's common everywhere. For Rust: https://github.com/evcxr/evcxr/blob/main/evcxr_repl/README.m.... But heck, the compiler is reasonably fast enough that any IDE can REPL by compiling the code.

The value here is more in being able to read a script before you run it, then have it run fast, maybe tweaking something here and there. And a compiled script will run 10,000 times faster than LISP, which can be important.

https://github.com/evcxr/evcxr can run Rust in a Jupyter notebook. It's not Golang but close enough.

The engine uses rust_decimal::Decimal to represent high precision decimal numbers, like the weight property. Serialization of RocksDB keys is done by the storekey crate. To know how Yumi's machine stores diffs, we can now ask- How does storekey serialize rust_decimal? Well, using evcxr to run Rust in Jupyter, the answer is as a null-terminated string:

In theory you should be able to create Rust notebooks (Jupyter notebook) using evcxr so maybe some AI, data analysis, prototyping make sense if you aim for good performance in final application (protype in evcxr and use notebook as reference to implement final application in Rust for speed and safety).

You should check out evcxr

There is also implementations of rust REPLs, like the beautifully named evcxr.