Question 1

How to compile a Rust project to MicroPython using wasm2mpy?

Accepted Answer

First, compile your Rust code to WebAssembly, then use wasm2mpy's toolchain to convert it to a .mpy module. Follow the build instructions in the README, but note that support varies by architecture—check the status table for compatibility.

Question 2

wasm2mpy vs native C modules for MicroPython: which is better?

Accepted Answer

wasm2mpy offers multi-language support and easier portability from WebAssembly, but native C modules might have slightly lower overhead and better integration. Choose wasm2mpy if you need to reuse code from languages like Rust or Zig; opt for native C for maximum performance on specific hardware.

Question 3

Does wasm2mpy work on Raspberry Pi Pico for AI inference?

Accepted Answer

Yes, the README lists Raspberry Pi Pico as a compatible target, and it's designed for AI applications. You can compile models to WASM and run them with near-native performance, though ensure your module fits within memory constraints.

Question 4

How to access and modify WASM memory from Python in wasm2mpy?

Accepted Answer

Use the _memory attribute on the imported module, as shown in the example: assign bytes to slices for writing or read them directly. This allows efficient data passing without serialization overhead.

Question 5

What are the limitations of wasm2mpy on ESP32?

Accepted Answer

While ESP32 is well-supported, memory usage can be high for large modules, and some language features might not fully optimize. Refer to the CoreMark results and status table for specific performance and compatibility notes.

Question 6

Can I use wasm2mpy for real-time signal processing on STM32?

Accepted Answer

It can accelerate processing, but the WebAssembly layer may introduce jitter; for hard real-time requirements, pure native code is safer. Use it for compute-heavy tasks where slight latency is acceptable.

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