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by peterhj 3537 days ago
Rust has been pretty critical to me for getting my work up and running with minimal debugging (I'm in CS grad school, working on deep learning and optimization). I'm super productive programming in Rust, which is also generally a pleasure to write in.

Just last week I had to land a pretty major refactoring (swapping out a single wrapper type for a differentiable "operator" with an implicit operator graph instead). It basically just worked out of the box as soon as I got it to compile. Definitely something to be said for working _with_ the compiler and its messages on moving, borrowing, mutability etc. (Incidentally, if I had to program exclusively in C++11/14, thanks to Rust I'd have become much better at programming in C++.)
1 comments
thecity2 3537 days ago
Curious since you say you work on deep learning/optimization. I'm a data scientist who does most everything in Python, but I've been interested in learning Rust. What is the state of "data science" toolkit for Rust at this point? For reference, I regularly use sklearn, Pandas, and Spark and would be looking for similar tools.
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peterhj 3537 days ago
I'm not sure that there's a mature Rust alternative to "all of the above" quite yet. Some things that I've had to build for my own work (not always "built," sometimes I just wrote FFI bindings) include:

* N-D dense arrays, fashionably simply called tensors these days ;) (this I wrote from scratch to suit my own needs, but there are several implementations of this in Rust, as well as in C++)

* linear algebra (bindings to BLAS, LAPACK etc.)

* numerical integration (bindings to GSL or QUADPACK)

* optimization and machine learning (this I work on day-to-day)

* neural networks (I also work on this)

* multicore/manycore/GPU/distributed support (and this)

There's also the more practical aspects of using Pandas/iPython (Jupyter)/Spark for data science, including ETL, interactive work, and plotting, which IMO are not quite there yet in the Rust ecosystem. But I think that a lot of the pieces are there, e.g. bleeding fast CSV parsing libraries (https://github.com/BurntSushi/rust-csv), and what's left is the important last mile of bringing these things together in ergonomic libraries or frameworks.

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