PyCall.jl
fast-ruby
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PyCall.jl | fast-ruby | |
---|---|---|
28 | 4 | |
1,435 | 5,641 | |
1.3% | 0.2% | |
6.1 | 4.6 | |
18 days ago | 4 months ago | |
Julia | Ruby | |
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.
PyCall.jl
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I just started into Julia for ML
For point 3 you can use https://github.com/cjdoris/PythonCall.jl or https://github.com/JuliaPy/PyCall.jl (and their respective Python sister packages).
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Am I dumb in thinking I can use Rust as a Fast Python and leave it at that?
Julia and Python interop should not be a problem at all. Actually Julia has one of the best interops I’ve ever seen, so much that swift copied it. https://github.com/JuliaPy/PyCall.jl
- Which tools do you use for python + Data Science?
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I don't want to abandon Rust for Julia
One small note, julia also has great python interop via PyCall.jl
- Faster Python calculations with Numba: 2 lines of code, 13× speed-up
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Interoperability in Julia
It is possible to call Python from Julia using PyCall. Then to install PyCall, run the command in the Julia REPL.
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Why is Python so used in the machine learning?
That said, you can run python modules in Julia. So you can just export your code as a module and then use it in Julia via the PyCall package. short description here github here <— you’d just add the pacakge via the really nice package manager built into julia, but for link for more detailed documentation
- Use rust code in Python with pyo3
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Writing entire programs in Cython
You can integrate Python and Julia code with https://github.com/JuliaPy/PyCall.jl and https://github.com/JuliaPy/pyjulia .
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Why Co–Star Uses Haskell
> I'd love to use Julia and Rust instead, but the ecosystems and users aren't there yet.
fast-ruby
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Sorry for this noobest question
In this perspective, maybe the compilation of approaches by Fast Ruby provides a similar point of entry.
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Super readable String operations with `delete_prefix` and `delete_suffix`
Stylistically, chomp has a bit more of the whimsy that you might expect from Ruby, while delete_suffix is a nice mirroring of delete_prefix and more explicitly named. Both have similar performance benchmarks and are faster than sub.
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Ruby 3.0.0 Released
If you’re interested in speed, check this repo: even among Ruby idioms there are big speed differences.
What are some alternatives?
Rails style guide - A community-driven Ruby on Rails style guide
Ruby style guide - A community-driven Ruby coding style guide
py2many - Transpiler of Python to many other languages
RSpec style guide - RSpec Best Practices
Fundamental Ruby - :books: Fundamental programming with ruby examples and references. It covers threads, SOLID principles, design patterns, data structures, algorithms. Books for reading. Repo for website https://github.com/khusnetdinov/betterdocs
Best-Ruby - Ruby Tricks, Idiomatic Ruby, Refactoring and Best Practices
contracts.ruby - Contracts for Ruby.
julia - The Julia Programming Language
Revise.jl - Automatically update function definitions in a running Julia session
are-we-fast-yet - Are We Fast Yet? Comparing Language Implementations with Objects, Closures, and Arrays
Functional Ruby
Genie.jl - 🧞The highly productive Julia web framework