Iron python VS Ray

If you're interested in learning more about the challenges and tradeoffs, both Jython (https://www.jython.org/) and IronPython (https://ironpython.net/) have been around for a long time and there's a lot of reading material on that subject.

There are several ways of bypassing the GIL. First of all, the GIL is only present in the C implementation of Python, CPython. Other implementations of Python like Jython, IronPython, and PyPy don't have the GIL. Additionally, Python provides the multiprocessing library, which allows for parallelism in your Python program.

I am not set on .NET, but just curious, so thanks for the suggestions. Interesting that it's billed as cross-plaform, but doesn't do it that well. I just searched 'python wrapper for .net' and found PythonNET. Also, it seems yes IronPython is active.

You mean like this?

In that case, I think it's enough if you go here, then download and install the MSI file: https://github.com/IronLanguages/ironpython2/releases/tag/ipy-2.7.12

There are quite a lot of ways to run scripting languages in C#. I've no idea what JSR223 is but .NET has DLR for example. There are also multiple libraries: IronPython, NLua, Jint and Jurassic for Javascript. There's also older version of CS-Script working with .NET Framework.

But does it Microsoft python https://ironpython.net

If you need control over how the script runs, access to variables etc, I can highly recommend IronPython, but it might be overkill for what you need.

22. Ray | Github | tutorial

Training times for GSM8k are mentioned here: https://github.com/ray-project/ray/tree/master/doc/source/te...

Here's a reference from RLlib that points to docs and an example, and here's one from one of my projects that includes all my own implementations

RLlib

⦿ AWS Glue Data Quality - Automatic data quality rule recommendations based on your data AWS Glue for Ray - Data integration with Ray (ray.io), a popular new open-source compute framework that helps you scale Python workloads

https://ray.io (just dropping the link)

I've wondered whether it's easier to add data analyst stuff to Elixir that Python seems to have, or add features to Python that Erlang (and by extension Elixir) provides out of the box.

By what I can see, if you want multiprocessing on Python in an easier way (let's say running async), you have to use something like ray core[0], then if you want multiple machines you need redis(?). Elixir/Erlang supports this out of the box.

Explorer[1] is an interesting approach, where it uses Rust via Rustler (Elixir library to call Rust code) and uses Polars as its dataframe library. I think Rustler needs to be reworked for this usecase, as it can be slow to return data. I made initial improvements which drastically improves encoding (https://github.com/elixir-nx/explorer/pull/282 and https://github.com/elixir-nx/explorer/pull/286, tldr 20+ seconds down to 3).

[0] https://github.com/ray-project/ray

Adding these for anyone who had a similar question about Ray vs dask 1, 2, 3