Pyrlang
explorer
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Pyrlang | explorer | |
---|---|---|
4 | 20 | |
586 | 976 | |
1.5% | 3.7% | |
3.7 | 9.4 | |
5 months ago | 4 days ago | |
Python | Elixir | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Pyrlang
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Office files processing
- Using Ports to call CLIs that take care of this (e.g. Poppler for PDFs, Libreoffice in `--headless` mode) - Use jInterface to startup a JVM with Apache POI to work on this specific workflow (I have an example here to work with Java Image API). You can also do this with other languages (Golang , Python and other).
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Updated Erlport alternative ?
If you're talking about the library, it has been updated recently as you can see here https://github.com/Pyrlang/Pyrlang/commits/master
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Ask HN: Is Elixir Still Relevant?
- Python: https://github.com/Pyrlang/Pyrlang
explorer
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Polars
The Explorer library [0] in Elixir uses Polars underneath it.
[0] https://github.com/elixir-explorer/explorer
- Unpacking Elixir: Concurrency
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Elixir Livebook is a secret weapon for documentation
To ensure you do not miss this: LiveBook comes with a Vega Lite integration (https://livebook.dev/integrations -> https://livebook.dev/integrations/vega-lite/), which means you get access to a lot of visualisations out of the box, should you need that (https://vega.github.io/vega-lite/).
In the same "standing on giant's shoulders" stance, you can use Explorer (see example LiveBook at https://github.com/elixir-explorer/explorer/blob/main/notebo...), which leverages Polars (https://www.pola.rs), a very fast DataFrame library and now a company (https://www.pola.rs/posts/company-announcement/) with 4M$ seed.
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Does anyone else hate Pandas?
Already exists. Check out https://github.com/elixir-nx/explorer which provides a tidyverse-like API in Elixir using polars as the back end.
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Data wrangling in Elixir with Explorer, the power of Rust, the elegance of R
José from the Livebook team. I don't think I can make a pitch because I have limited Python/R experience to use as reference.
My suggestion is for you to give it a try for a day or two and see what you think. I am pretty sure you will find weak spots and I would be very happy to hear any feedback you may have. You can find my email on my GitHub profile (same username).
In general we have grown a lot since the Numerical Elixir effort started two years ago. Here are the main building blocks:
* Nx (https://github.com/elixir-nx/nx/tree/main/nx#readme): equivalent to Numpy, deeply inspired by JAX. Runs on both CPU and GPU via Google XLA (also used by JAX/Tensorflow) and supports tensor serving out of the box
* Axon (https://github.com/elixir-nx/axon): Nx-powered neural networks
* Bumblebee (https://github.com/elixir-nx/bumblebee): Equivalent to HuggingFace Transformers. We have implemented several models and that's what powers the Machine Learning integration in Livebook (see the announcement for more info: https://news.livebook.dev/announcing-bumblebee-gpt2-stable-d...)
* Explorer (https://github.com/elixir-nx/explorer): Series and DataFrames, as per this thread.
* Scholar (https://github.com/elixir-nx/scholar): Nx-based traditional Machine Learning. This one is the most recent effort of them all. We are treading the same path as scikit-learn but quite early on. However, because we are built on Nx, everything is derivable, GPU-ready, distributable, etc.
Regarding visualization, we have "smart cells" for VegaLite and MapLibre, similar to how we did "Data Transformations" in the video above. They help you get started with your visualizations and you can jump deep into the code if necessary.
I hope this helps!
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Would you still choose Elixir/Phoenix/LiveView if scaling and performance weren’t an issue to solve for?
There's a package in the Nx ecosystem called Explorer (https://github.com/elixir-nx/explorer). It uses bindings for the rust library, polars, which is much more betterer than Pandas.
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Updated Erlport alternative ?
FWIW around April this year I started using erlport with python polars in a production ETL app because explorer didn't have the features I needed at the time.
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ElixirConf 2022 - That's a wrap!
Machine learning is rapidly expanding within the Elixir ecosystem, with tools such as Nx, Axon, and Explorer being used both by individuals and companies such as Amplified, as mentioned above.
- Dataframes but for Elixir
- Quick candlestick summaries with Elixir's Explorer
What are some alternatives?
python-socketio - Python Socket.IO server and client
dplyr - dplyr: A grammar of data manipulation
ergo - An actor-based Framework with network transparency for creating event-driven architecture in Golang. Inspired by Erlang. Zero dependencies.
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
geventmp - GeventMP - Gevent Multiprocessing Extension
axon - Nx-powered Neural Networks
pnrw - PNRW is a Python Wrapper for the Nano RPC Protocol
db-benchmark - reproducible benchmark of database-like ops
Ignareo-ISML-auto-voter - Ignareo the Carillon, a web crawler/spider template of ultimate high concurrency built for leprechauns. Carillons as the best web spiders; Long live the golden years of leprechauns! (ISML=international saimoe; 2022 ISML is last ISML)
arrow2 - Transmute-free Rust library to work with the Arrow format
ergo - a Framework for creating microservices using technologies and design patterns of Erlang/OTP in Golang [Moved to: https://github.com/ergo-services/ergo]
wasmex - Execute WebAssembly from Elixir