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Hey folks, thanks for creating and maintaining Prophet for all these years, I've used it more times than I care to imagine 🙂
This isn't really an issue at all, but I thought you might be interested to know I've translated the Python implementation to Rust as part of the augurs time series toolkit. The main reason wasn't really performance (since Prophet already leans heavily on Stan/numpy), but for browser builds: the Rust library can be compiled to WASM and used in the browser, which is fun. In this build, cmdstan is replaced by a WASM component which wraps up Stan's optimizer. This approach also works server-side by running the MLE optimization inside Wasmtime, which is nicer (and results in fewer platform-specific issues) than cmdstan.
There's a demo which includes the Prophet lib, and an npm package which re-exports some basic functionality, in case anyone wants to play around.
Maybe this is helpful to someone in future. Merry Christmas!
The text was updated successfully, but these errors were encountered:
Hey folks, thanks for creating and maintaining Prophet for all these years, I've used it more times than I care to imagine 🙂
This isn't really an issue at all, but I thought you might be interested to know I've translated the Python implementation to Rust as part of the augurs time series toolkit. The main reason wasn't really performance (since Prophet already leans heavily on Stan/numpy), but for browser builds: the Rust library can be compiled to WASM and used in the browser, which is fun. In this build, cmdstan is replaced by a WASM component which wraps up Stan's optimizer. This approach also works server-side by running the MLE optimization inside Wasmtime, which is nicer (and results in fewer platform-specific issues) than cmdstan.
There's a demo which includes the Prophet lib, and an npm package which re-exports some basic functionality, in case anyone wants to play around.
Maybe this is helpful to someone in future. Merry Christmas!
The text was updated successfully, but these errors were encountered: