frunk
PyCall.jl
frunk | PyCall.jl | |
---|---|---|
7 | 28 | |
1,199 | 1,438 | |
- | 0.3% | |
5.3 | 6.1 | |
2 days ago | about 2 months ago | |
Rust | Julia | |
MIT License | MIT License |
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frunk
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Apply generic function to every tuple element
So rust doesn't support variadics, but I have heard some murmurings around the topic. In the meantime, you can still do a lot with recursive tras. The frunk crate makes working with them a lot easier: In this case
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Self Referencing structs with different generic types
I think the closest possible approach is the one used in frunk where those consecutive types are nested recursively (creating a linked list on type level basically) and special type is used as the end.
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Is there a convenient way to convert a struct<T> (where all fields are of type T) into struct<U> where U: From<T>?
I suggest looking into frunk. You could convert the struct into an HList, map over the values to convert and convert into the target struct. README has some relevant examples.
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Can we make useful streaming APIs that disallow deadlocks?
So a while back I got interested in how rust could provide parallel/concurrent APIs that prevent deadlocking shared state. I now created a Proof-of-Concept stream processing library that attempts to do that. The library makes prodigious use of heterogeneous lists from the frunk library. The basic idea is that you can build a graph by combining source streams as source nodes and mutexes for state, then you can add nodes which subscribe to subsets of the previous nodes using various combinators. You can either
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constduck: compile-time duck typing and reflection powered by const generics
Hey, #[derive(LabelledGeneric)] from frunk does something like this, but without const generics, so it has odd representations for things like type-level strings (it's represented as a tuple of chars so (a, b, c) is the type-level representation of the string "abc")
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Symbolics.jl: A Modern Computer Algebra System for a Modern Language
I don't understand why you call it "trickery or "fake". Church encoding of natural numbers is the same technique used in Agda, Coq and Idris to represent the Peano numbers. It's a completely valid encoding and isomorphic to any other representation.
You don't need to use a fixed-length array either - you can used a recursive linked list at the type-level for an unbounded encoding [1]. The Scala library is an example of that; the Github page even has an example of encoding arbitrary units like sheep and wheat.
[1] https://github.com/lloydmeta/frunk
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Generic associated types encode higher-order functions on types
I wonder if frunk can (ab)use this kind of trick to make their crate even more powerful. IIRC they have a bunch of amazing and horrible workarounds to work with type-level lists.
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).
- The Mojo Programming Language: A Python Superset Drawing from Rust's Strengths
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Calling Chapel, Carbon, and zig code in Julia
PyCall.jl is really handy. Are there any similar projects for calling Chapel code, or Carbon/zig?
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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
What are some alternatives?
tyrade - A pure functional language for type-level programming in Rust
py2many - Transpiler of Python to many other languages
stately-streams - combine mutable state and asynchronous streams without deadlocks
Revise.jl - Automatically update function definitions in a running Julia session
sicmutils - Computer Algebra, Physics and Differential Geometry in Clojure.
julia - The Julia Programming Language
scroll - Scroll - making scrolling through buffers fun since 2016
Genie.jl - 🧞The highly productive Julia web framework
Algebird - Abstract Algebra for Scala
are-we-fast-yet - Are We Fast Yet? Comparing Language Implementations with Objects, Closures, and Arrays
typic - Type-safe transmutations between layout-compatible types.
fast-ruby - :dash: Writing Fast Ruby :heart_eyes: -- Collect Common Ruby idioms.