Jupyter Scala
py2many
Jupyter Scala | py2many | |
---|---|---|
6 | 29 | |
1,564 | 593 | |
0.0% | 1.5% | |
9.0 | 8.1 | |
15 days ago | about 1 month ago | |
Scala | Python | |
BSD 3-clause "New" or "Revised" License | MIT License |
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Jupyter Scala
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💐 Making VSCode itself a Java REPL 🔁
Checkout almond
- A Python-compatible statically typed language erg-lang/erg
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EDA libraries for Scala and Spark?
What about https://github.com/alexarchambault/plotly-scala and https://almond.sh/
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Is there any editor or IDE that supports Ammonite with inline dependencies?
I use Almond in JupyterLab, which has pretty solid code completion. In IntelliJ, you can create a scratch sc file and run lines of it in the Scala REPL. That's really convenient for code completion and I normally will use that when I'm testing something from a specific project.
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Recommended option for "Java with different syntax"?
The UI part. There's only the scala REPL. I think the closest is a scala kernel for Jupyter notebooks, check this out: https://almond.sh/
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An SQL Solution for Jupyter
We have used https://almond.sh/ to create a Spark SQL interpreter using Jupyter Notebooks - plus a whole lot more which you can see here: https://arc.tripl.ai/tutorial
After seeing many companies writing ETL using code we decided it was too hard to manage at scale so provided this abstraction layer - which is heavily centered around expressing business logic in SQL - to standardise development (JupyterLab) and allow rapid deployments.
py2many
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Transpiler, a Meaningless Word
> Another problem is that there are hundreds of built-in library functions that need to be compiled from Python from C
An approach I've advocated as one of the main authors of py2many is that all of the python builtin functions be written in a subset of python[1] and then compiled into native code. This has the benefit of avoiding GIL, problems with C-API among other things.
Do checkout the examples here[2] which work out of the box for many of the 8-9 supported backends.
[1] https://github.com/py2many/py2many/blob/main/doc/langspec.md
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py2many VS kithon - a user suggested alternative
2 projects | 17 Jun 2023
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Why I'm still using Python
https://github.com/py2many/py2many/blob/main/doc/langspec.md
Reimplement a large enough, commonly used subset of python stdlib using this dialect and we may be in the business of writing cross platform apps (perhaps start with android and Ubuntu/Gnome)
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Codon: A high-performance Python compiler
For py2many, there is an informal specification here:
https://github.com/py2many/py2many/blob/main/doc/langspec.md
Would be great if all the authors of "python-like" languages get together and come up with a couple of specs.
I say a couple, because there are ones that support the python runtime (such as cython) and the ones which don't (like py2many).
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A Python-compatible statically typed language erg-lang/erg
It'd not fully solve your issue, but have you ever seen https://github.com/py2many/py2many ?
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Omyyyy/pycom: A Python compiler, down to native code, using C++
Cython doesn't consume python3 type hints and needs special type hints of its own. But it's certainly more mature than other players in the field.
What we need is a rpython suitable for app programming and a stdlib written in that dialect.
https://github.com/py2many/py2many/blob/main/doc/langspec.md
- I made a Python compiler, that can compile Python source down to fast, standalone executables.
- PyTorch: Where we are headed and why it looks a lot like Julia (but not exactly)
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Show HN: prometeo – a Python-to-C transpiler for high-performance computing
No intermediate AST. To understand the various stages of transpilation and separation of language specific and independent rewriters, this file is a good starting point:
https://github.com/adsharma/py2many/blob/main/py2many/cli.py...
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Implicit Overflow Considered Harmful (and how to fix it)
Link to the test that's relevant for this discussion:
https://github.com/adsharma/py2many/blob/main/tests/cases/in...
This is an explicit deviation from python's bigint, which doesn't map very well to systemsey languages. The next logical step is to build on this to have dependent and refinement types.
Work in progress here:
https://github.com/adsharma/Typpete
What are some alternatives?
sparkmagic - Jupyter magics and kernels for working with remote Spark clusters
pybind11 - Seamless operability between C++11 and Python
Metals - Scala language server with rich IDE features 🚀
PyO3 - Rust bindings for the Python interpreter
Vegas - The missing MatPlotLib for Scala + Spark
PythonNet - Python for .NET is a package that gives Python programmers nearly seamless integration with the .NET Common Language Runtime (CLR) and provides a powerful application scripting tool for .NET developers.
Apache Flink - Apache Flink
PyCall.jl - Package to call Python functions from the Julia language
Deeplearning4j - Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation.
julia - The Julia Programming Language
Scio - A Scala API for Apache Beam and Google Cloud Dataflow.
rust-numpy - PyO3-based Rust bindings of the NumPy C-API