uniffi-rs VS pybind11

On my youtube series "Growing up Rust", I'm building a personal CRM in Rust with a Swift frontend. I'm using CQRS and an event-driven architecture with the least amount of swift as possible. I'm using UniFFI to generate the bindings for swift (and in this example python)

Not officially. We currently have bindings for rust, python, golang and swift.

These were the most asked for bindings (python for ml, golang for networking and swift for ios apps).

We are using uniffi https://mozilla.github.io/uniffi-rs/

Would you need C or C++ bindings?

An alternative is metacall. The example in the readme is about calling Python from Javascript, but it also works with other languages, like Ruby, C#, Java, and other languages

https://github.com/metacall/core

List of supported languages here https://github.com/metacall/core/blob/develop/docs/README.md...

In the future, maybe webidl (or extensions of it) will bring interoperability between languages too. At the moment there is https://mozilla.github.io/uniffi-rs/ for interoperability between Rust and a number of languages (basically the ones mozilla needs: Swift, Kotlin, Javascript)

The tooling for the first kind -- calling Rust from another language -- is a bit less developed, and tends to rely on code generation that doesn't necessarily produce a natural C API. cbindgen, uniffi, cxx, and Diplomat all take this course.

Mozilla's uniffi-rs is really good. You write a common IDL and the bindings are generated automatically.

https://github.com/mozilla/uniffi-rs

At Mozilla we built a multi-language bindings generator: https://github.com/mozilla/uniffi-rs/

Is there a connection with Mozilla UniFFI ?

Rust <> Swift/ Kotlin works very well with uniffi-rs by Mozilla: https://github.com/mozilla/uniffi-rs

I'm investigating using C++ to build a REST server, and would love to know of people's experiences with Crow-- or whether they would recommend something else as a "medium-level" abstraction C++ web server. As background, I started off experimenting with Python/FastAPI, which is great, but there is too much friction to translate from pybind11-exported C++ objects to the format that FastAPI expects, and, of course, there are inherent performance limitations using Python, which could impact scaling up if the project were to be successful.

I have a C++ function computing a large tensor which I would like to return to Python as a NumPy array via pybind11.

This is based on the Google Ink Stroke Modeler C++ library, and using pybind11 to make it available on python.

pybind11 makes it easy to call C++ from Python if you want to mix.

If you've never used Pybind before these pybind tests[1] and this repo[2] have good examples you can crib to get started (in addition to the docs). Once you handle passing/returning/creating the main data types (list, tuple, dict, set, numpy array) the first time, then it's mostly smooth sailing.

Pybind offers a lot of functionality, but core "good parts" I've found useful are (a) use a numpy array in Python and pass it to a C++ method to work on, (b) pass your python data structure to pybind and then do work on it in C++ (some copy overhead), and (c) Make a class/struct in C++ and expose it to Python (so no copying overhead and you can create nice cache-aware structs, etc.).

[1] https://github.com/pybind/pybind11/blob/master/tests/test_py...

I have a python module for which the logic is written in C++ and I use pybind11 to expose the objects and functions to Python.

Reading from Python requires a wrapper, using pybind11 this is fairly done.

Also I can highly recommend starting using C++ to augment your Python code, i.e. find the parts that are slow or undoable in Python and write those in C++ then expose them as Python functions. You can use https://github.com/pybind/pybind11 to call C++ code from Python.