7 ms·

You can run Rust code in a Jupyter notebook

146 points by nbrempel 4y ago

ismailmaj 4y ago
I stopped using evcxr when I realized that I could get the same instant feedback with rust-analyzer and a properly configured IDE. Maybe it can be useful for data exploration with polars but I still prefer Python for that.
- ejanus 4y ago
  Could you give steps on how you configured your ide?
deleted 4y ago
[deleted]
schneems 4y ago
That’s interesting. This is really interesting: a REPL for Rust https://github.com/google/evcxr/blob/main/evcxr_repl/README.md https://github.com/google/evcxr/blob/main/evcxr_repl/README.....
Kab1r 4y ago
I could see myself using this for prototyping
wiseowise 4y ago
> Disclaimer > This is not an officially supported Google product. It's released by Google only because the (original) author happens to work there.
- dijit 4y ago
  standard for a 20% project.
  - netr0ute 4y ago
    Is this how all the 20% projects work?
    - dijit 4y ago
      if they are open sourced, yeah
      - netr0ute 4y ago
        If so, then I'm not going to Google in a million years.
        User23 4y ago
        Gmail was a 20% project.
grepLeigh 4y ago
Between Rust kernels for Jupyter notebooks, PolarRS, and Gstreamer bindings, Rust has become my tool of choice for computer vision pipelines. I used to prototype in Python, then re-implement the final algorithm in Rust for performance on an embedded device. Now I just start prototyping in Rust.
- orlp 4y ago
  I'm interested in possibly contributing / optimizing in polars, I would be curious to hear from a user first-hand which things are painful and/or slow still.
  - bobbylarrybobby 4y ago
    Painful (polars-lazy): - Very scant documentation. Many things missing docs, many documented items missing examples. - Using a custom function in a map. You have to do this `Ok(series.type()?.into_iter().map(...).collect::<ChunkedArray<_>>()).into_series()` dance every time, and it's annoying. And you have to specify the output type even though it should be inferable from the function body. - There is no good way to "get-or-null" a column, i.e., treat an absent column as all null. You have to try to select the column, check if that errored, and if so insert a column of nulls (casted to the correct type) before proceeding. - Perhaps because it uses Arrow under the hood, there is no such thing as a non-nullable column. You just always have to handle nulls. - A bit verbose due to the lack of Into<Expr> implementations for most basic types. E.G., `lit(false)` instead of `false` because `bool` is not `Into<Expr>`. - It's a bit confusing at times which features you need for which abilities, and things will panic at runtime if you don't have the necessary features enabled (e.g., the strptime function has a tz_aware:bool parameter that panics if it's true but you don't have the time zone feature enabled). Ultimately it's a young library and so I guess it comes with the territory. It's still fantastic and having used it I'd be hard pressed to go back to pandas even despite all the flaws.
  - grepLeigh 4y ago
    To echo the other comment, I've found digging around the test suites to be more reliable and comprehensive than the official examples/documentation. If you're running into issues with the Lazy API, read through these tests and see if that clears anything up: https://github.com/pola-rs/polars/tree/master/polars/polars-lazy/src/tests https://github.com/pola-rs/polars/tree/master/polars/polars-... My usage is very narrow (aggregating a dataframe of bounding box observations over a sliding time window) and I only use streaming Arrow IPC, which both work great!
batterylow 4y ago
Evcxr is great, and I used it to write Data Analysis with Rust Notebooks [1]! There's also this video on getting up and running with it [2], although it's 2 years old. Ultimately, the ecosystem isn't yet as convenient as something like Python. I used to keep an eye on "Are we learning yet?" [3] - although it's been a while now! [1] https://datacrayon.com/shop/product/data-analysis-with-rust-notebooks/ https://datacrayon.com/shop/product/data-analysis-with-rust-... [2] https://www.youtube.com/watch?v=SZKEzNL9als https://www.youtube.com/watch?v=SZKEzNL9als [3] https://www.arewelearningyet.com https://www.arewelearningyet.com
- kibwen 4y ago
  Note that you can install evcxr and use it as a Rust REPL in your terminal (see https://github.com/google/evcxr/blob/main/evcxr_repl/README.md https://github.com/google/evcxr/blob/main/evcxr_repl/README.... ). (Tip: alias it to something that you'll actually remember how to type!)
lynndotpy 4y ago
Evcxr has been instrumental for just learning Rust, IME. Being able to type a line of code and get immediate feedback is one of the great pleasures of interpreted languages. Really useful when "try into" or "unwrap", etc. are still unfamiliar!
pornel 4y ago
Word of warning: evcxr runs Rust in unoptimized debug mode. This is really unoptimized to the point it's sometimes slower than Python.
epage 4y ago
I'm interested in making REPL support for Rust first-class and am curious where people think evcxr lets you down in usability and any suggestions in overcoming them. Compiled languages offer unique challenges for REPLs and I feel like I've not seen it pulled off well.
- rowanG077 4y ago
  Did you try GHCi? The interactive REPL of GHC (Haskell)? I feel it's the best REPL I have tried. Certainly beats out Python and JS.
eternalban 4y ago
How cool. This motivated a quick search - this could be fun: How to write your own kernel https://jupyter-client.readthedocs.io/en/stable/kernels.html https://jupyter-client.readthedocs.io/en/stable/kernels.html All the language kernels (a lot of abandoned ones - the mariaDB one ('binder') will take a while to load but SQL in Jupyter!) https://github.com/jupyter/jupyter/wiki/Jupyter-kernels https://github.com/jupyter/jupyter/wiki/Jupyter-kernels p.s. sadly the Brainfuck kernel is kaput. don't get your hopes up.
Alifatisk 4y ago
So this is sort of a repl for Rust?

146 points by nbrempel 4y ago

I stopped using evcxr when I realized that I could get the same instant feedback with rust-analyzer and a properly configured IDE. Maybe it can be useful for data exploration with polars but I still prefer Python for that.

ejanus 4y ago
Could you give steps on how you configured your ide?

deleted 4y ago

[deleted]

schneems 4y ago

That’s interesting. This is really interesting: a REPL for Rust https://github.com/google/evcxr/blob/main/evcxr_repl/README.md https://github.com/google/evcxr/blob/main/evcxr_repl/README.....

Kab1r 4y ago

I could see myself using this for prototyping

wiseowise 4y ago

> Disclaimer > This is not an officially supported Google product. It's released by Google only because the (original) author happens to work there.

dijit 4y ago
standard for a 20% project.
- netr0ute 4y ago
  Is this how all the 20% projects work?
  - dijit 4y ago
    if they are open sourced, yeah
    - netr0ute 4y ago
      If so, then I'm not going to Google in a million years.
      - User23 4y ago
        Gmail was a 20% project.

grepLeigh 4y ago

Between Rust kernels for Jupyter notebooks, PolarRS, and Gstreamer bindings, Rust has become my tool of choice for computer vision pipelines. I used to prototype in Python, then re-implement the final algorithm in Rust for performance on an embedded device. Now I just start prototyping in Rust.

orlp 4y ago
I'm interested in possibly contributing / optimizing in polars, I would be curious to hear from a user first-hand which things are painful and/or slow still.
- bobbylarrybobby 4y ago
  Painful (polars-lazy): - Very scant documentation. Many things missing docs, many documented items missing examples. - Using a custom function in a map. You have to do this `Ok(series.type()?.into_iter().map(...).collect::<ChunkedArray<_>>()).into_series()` dance every time, and it's annoying. And you have to specify the output type even though it should be inferable from the function body. - There is no good way to "get-or-null" a column, i.e., treat an absent column as all null. You have to try to select the column, check if that errored, and if so insert a column of nulls (casted to the correct type) before proceeding. - Perhaps because it uses Arrow under the hood, there is no such thing as a non-nullable column. You just always have to handle nulls. - A bit verbose due to the lack of Into<Expr> implementations for most basic types. E.G., `lit(false)` instead of `false` because `bool` is not `Into<Expr>`. - It's a bit confusing at times which features you need for which abilities, and things will panic at runtime if you don't have the necessary features enabled (e.g., the strptime function has a tz_aware:bool parameter that panics if it's true but you don't have the time zone feature enabled). Ultimately it's a young library and so I guess it comes with the territory. It's still fantastic and having used it I'd be hard pressed to go back to pandas even despite all the flaws.
- grepLeigh 4y ago
  To echo the other comment, I've found digging around the test suites to be more reliable and comprehensive than the official examples/documentation. If you're running into issues with the Lazy API, read through these tests and see if that clears anything up: https://github.com/pola-rs/polars/tree/master/polars/polars-lazy/src/tests https://github.com/pola-rs/polars/tree/master/polars/polars-... My usage is very narrow (aggregating a dataframe of bounding box observations over a sliding time window) and I only use streaming Arrow IPC, which both work great!

batterylow 4y ago

Evcxr is great, and I used it to write Data Analysis with Rust Notebooks [1]! There's also this video on getting up and running with it [2], although it's 2 years old. Ultimately, the ecosystem isn't yet as convenient as something like Python. I used to keep an eye on "Are we learning yet?" [3] - although it's been a while now! [1] https://datacrayon.com/shop/product/data-analysis-with-rust-notebooks/ https://datacrayon.com/shop/product/data-analysis-with-rust-... [2] https://www.youtube.com/watch?v=SZKEzNL9als https://www.youtube.com/watch?v=SZKEzNL9als [3] https://www.arewelearningyet.com https://www.arewelearningyet.com

kibwen 4y ago
Note that you can install evcxr and use it as a Rust REPL in your terminal (see https://github.com/google/evcxr/blob/main/evcxr_repl/README.md https://github.com/google/evcxr/blob/main/evcxr_repl/README.... ). (Tip: alias it to something that you'll actually remember how to type!)

lynndotpy 4y ago

Evcxr has been instrumental for just learning Rust, IME. Being able to type a line of code and get immediate feedback is one of the great pleasures of interpreted languages. Really useful when "try into" or "unwrap", etc. are still unfamiliar!

pornel 4y ago

Word of warning: evcxr runs Rust in unoptimized debug mode. This is really unoptimized to the point it's sometimes slower than Python.

epage 4y ago

I'm interested in making REPL support for Rust first-class and am curious where people think evcxr lets you down in usability and any suggestions in overcoming them. Compiled languages offer unique challenges for REPLs and I feel like I've not seen it pulled off well.

rowanG077 4y ago
Did you try GHCi? The interactive REPL of GHC (Haskell)? I feel it's the best REPL I have tried. Certainly beats out Python and JS.

eternalban 4y ago

How cool. This motivated a quick search - this could be fun: How to write your own kernel https://jupyter-client.readthedocs.io/en/stable/kernels.html https://jupyter-client.readthedocs.io/en/stable/kernels.html All the language kernels (a lot of abandoned ones - the mariaDB one ('binder') will take a while to load but SQL in Jupyter!) https://github.com/jupyter/jupyter/wiki/Jupyter-kernels https://github.com/jupyter/jupyter/wiki/Jupyter-kernels p.s. sadly the Brainfuck kernel is kaput. don't get your hopes up.

Alifatisk 4y ago

So this is sort of a repl for Rust?