anyhow VS rust

Depending on your use case, thiserror and/or anyhow.

There is ? as well as the anyhow(https://github.com/dtolnay/anyhow) crate that deals with long nested result chains.

There are crates out there that help you reduce this boiler plate. thiserror is good for creating custom errors and color-eyre or anyhow are good for dynamic errors.

Give anyhow a look.

I've brought anyhow::Result into scope, making error handling super easy to use. We don't need to specify all our Error types. It can automatically convert any errors that implement std::error::Error, which should be all of them. If an error propagates all the way up to main(), we'll get all the info it's captured printed to stdout.

Alternatively, if you've got a lot of error types and you're outside a library (so directly in a binary where you don't plan to reuse code elsewhere) you can use anyhow. This gives you an error type you can basically propagate any other error through. On top of that you can attach context information at every return. It's basically a more complicated Result>.

One approach is to define a separate error type for each crate and then use anyhow, eyre or Box to wrap the error, whever a function can return errors originating in several different crates.

Have you tried anyhow and thiserror for making it as simple as .context("Message") or ? to type-convert and propagate errors up the call stack?

You can use Tensorflow for Rust to simplify that task and avoid pain with regex. Just have the right mindset.

What is the benefit of this compared to using bindings/a wrapper to Tensorflow, or other ML libraries written in C/C++, such as this community hosted project on tensorflow's github. If it's just for fun that is a valid enough reason imo, just curious since you describe it as a better Tensorflow because of the typing vs using the python wrapper, when there already exist ways to interact with tensorflow with both Rust and other statically typed languages, also including C++ (officially supported), C#, Haskell and Scala, as well as probably having bindings not mentioned on the documentation for more niche languages.

(3) You could use TensorFlow as your executor: https://github.com/tensorflow/rust

TensorFlow has language support for TypeScript well as Rust.

Thank you for the restponse! With tensorflow I am probably better of with something like; [tensorflow rust bindings](https://github.com/tensorflow/rust/tree/master/src). But I believe some useful extensions are still written in python for example; [TFDV](https://github.com/tensorflow/data-validation).. and how about scikit-learn or even something that is simpler like fb-prophet that is entirely written in python?

Tensorflow bindings exist, technically, but they're in a pretty rough state AFAIK.

tensorflow/rust (Rust): Rust language bindings for TensorFlow