Chain.jl
MLStyle.jl
| Chain.jl | MLStyle.jl | |
|---|---|---|
| 8 | 5 | |
| 346 | 390 | |
| - | - | |
| 4.2 | 6.6 | |
| 2 months ago | about 2 months ago | |
| Julia | Julia | |
| MIT License | MIT License |
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Chain.jl
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Pains of Julia compared to python
The [Chain.jl package](https://github.com/jkrumbiegel/Chain.jl) is becoming idiomatic for these kind of pipelines.
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Transition from R Tidyverse to Julia (VS Code)
If you do have tabular data in a dataframe you have a few options for data manipulation, the most popular packages are probably DataFramesMeta and Query, although in my opinion the best way to manipulate dataframes is with the functions built in to DataFrames.jl and using a package like Chain.jl or Pipe.jl to pipe the functions into each other like magrittr in R.
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The (updated) history of the pipe operator in R
The Julia community built a better piping method than any other language has AFAIK: Chain.jl.
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What are some of your favourite macros?
@chain and @match.
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Why is piping so well-accepted in the R community compared to those in Julia and Python?
Have you ever tried Infiltrator.jl and Chain.jl?
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https://np.reddit.com/r/Julia/comments/nnu6if/julia_object_oriented_programming_with_dot/h0anaru/
You are right. However, sometimes well used is very useful, and readable. One suggestion, in Julia I suggest Chain.jl, because it allows intercalate easily the output for debugging:
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Julia Update: Adoption Keeps Climbing; Is It a Python Challenger?
I also like pipe syntax and I've found there is nice support for it in Julia. There are some nice packages to improve it over base [1].
Have you checked queryverse [2]?
[1] https://github.com/jkrumbiegel/Chain.jl
MLStyle.jl
- Mlstyle.jl: “Functionalprogramming.jl”
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Does anyone really like what Mathematica achieves, but hates the syntax?
It seems to have all the lovable traits you stated, except ML style patterns but there's MLStyle developing.
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What are some of your favourite macros?
@chain and @match.
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Pattern Matching Accepted for Python
> and we're stuck with an inferior Lisp/ML, especially in the scientific sector.
You will love Julia.
Here is some links:
https://julialang.org/blog/2012/02/why-we-created-julia/
Julia: Dynamism and Performance Reconciled by Design (https://dl.acm.org/doi/pdf/10.1145/3276490)
https://opensourc.es/blog/basics-multiple-dispatch/
And when you start finding things that you miss, Julia and the community got you with excellent Metaprogramming support.
https://github.com/thautwarm/MLStyle.jl
https://github.com/MikeInnes/Lazy.jl
https://github.com/jkrumbiegel/Chain.jl
What are some alternatives?
Pipe.jl - An enhancement to julia piping syntax
Match.jl - Advanced Pattern Matching for Julia
Genie.jl - 🧞The highly productive Julia web framework
gcc
Revise.jl - Automatically update function definitions in a running Julia session
flynt - A tool to automatically convert old string literal formatting to f-strings
JLD2.jl - HDF5-compatible file format in pure Julia
peps - Python Enhancement Proposals
PaddedViews.jl - Add virtual padding to the edges of an array
trivia - Pattern Matcher Compatible with Optima
Infiltrator.jl - No-overhead breakpoints in Julia
kalk - Scientific calculator with math syntax that supports user-defined variables and functions, complex numbers, and estimation of derivatives and integrals