Warframe-OCR VS maturin

Yes, you can link them statically. Here's a Python script I wrote to install and build a Python module in Rust. It will install the required development libraries on Linux and build a static build of tesseract on Windows (it also downloads the LLVM based clang compiler, I forgot why). Then it set up two environment variables VCPKG_ROOT to discover the tesseract library and RUSTFLAGS -Ctarget-feature=+crt-static (this forces the vpkg crate to link tesseract:x64-windows-static and not the dynamic version).

Tesseract is slow but not too slow. I wrote a multi-threaded wrapper around the Rust bindings und a Python wrapper around that. Granted it is not very polished and I apparently forgot to make the Rust repository public but it works. The previous version of the project for which I made this wrote the image to disk and called the tesseract binary which took half a minute for a few of images. Definitely not usable for real-time processing. Now it takes around 200-300 ms with 12 worker threads. I'm not sure if there is further potential to make it faster though.

I don't like maturin workflow either because it installs directly to the python environment. This is not very useful during development. I wrote a module import file which loads the python module from the shared library. You could easily invoke cargo before importing the module (remember to delete the previous shared library file) to have a fully automated development processes.

This story unfolds as a captivating journey where the agile Flounder, representing the Python programming language, navigates the vast seas of coding under the wise guidance of Sebastian, symbolizing Rust. Central to their adventure are three powerful tridents: cargo, PyO3, and maturin.

-- Maturin on GitHub

My new favorite way to write very fast libraries for Python is to just use Rust and Maturin:

https://github.com/PyO3/maturin

It basically automates everything for you. If you use it with Github actions, it will compile wheels for you on each release for every platform and python version you want, and even upload them to PyPi (pip) for you. Everything feels very modern and well thought out. People really care about good tooling in the Rust world.

Python first, you will be able to experiment quickly with the notebooks. Then maybe write (or rewrite) some modules in Rust that you can expose as python modules, with py03 and maturin. Feel free to publish useful packages on both crates.io and pypi.org, so you can contribute to Python and Rust ecosystems.

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.

It's relatively easy to extend Python with project like Py03[0] and Maturin[1]. Polars[2] is the perfect example of that.

It's not easy to push coworkers/companies to use an unfamiliar language. Rust isn't fast to learn. You need very good arguments and a good usecase to make it works.

I doubt that learning Rust will help you more that learning more about the data engineers tools, so this isn't really "worth" your time.

[0] -- https://pyo3.rs/v0.18.3/

[1] -- https://github.com/PyO3/maturin

[2] -- https://www.pola.rs/

In this case, PyO3/maturin does all the setup and getting the module into Python. They also have docs going into a lot more depth on this.

Lastly if you're willing to introduce Rust, I'd consider a gradual approach using native libraries built in rust with PYO3. Check the maturin guide that helps you to streamline the build process of native libraries : https://github.com/PyO3/maturin . From there you could try to find hotspots in your python app and replace those with a native implementation.