preplish
Pluto.jl
preplish | Pluto.jl | |
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9 | 78 | |
4 | 4,880 | |
- | - | |
5.0 | 9.5 | |
7 months ago | 6 days ago | |
Perl | JavaScript | |
GNU General Public License v3.0 only | MIT License |
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preplish
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Interactive GCC (igcc) is a read-eval-print loop (REPL) for C/C++
> what's wrong with that?
Why nothing at all, of course. A REPL need not be more than a way to test and explore syntax, functions, and logical structures.
> the user experience is REPL-ish and it can help some people learn the _basics_ of the language
PREPLISH exists for Perl ^_^
https://github.com/viviparous/preplish
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online Perl editor
If this is for testing of syntax or of trivial code, it sounds like a good use-case for running a local REPL. (Example: https://github.com/viviparous/preplish)
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Not Your Grandfatherās Perl
This is a simple REPL project and the readme lists other Perl REPLs.
https://github.com/viviparous/preplish
Perl's concise syntax makes working in a REPL a pleasure. Python has a REPL but the design of the language makes it expand both in length (for loops) and in width (tabs).
I am a recent convert to working in a REPL first to test programming ideas.
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Has someone curated Perl data science resources somewhere? I've seen many such collections for other languages. Something like this, but with more modules and what they do:
I made this solution for some of my simple data wrangling: https://github.com/viviparous/preplish
- Is there any good reason not to use perl scripts in place of bash logic?
- Working with __DATA__ sections without Mojolicious
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Acme-ConspiracyTheory-Random
I tried the module it in a Perl REPL (https://github.com/viviparous/preplish) and got the following ravings that are worthy of a US loony politician:
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On Repl-Driven Programming
I agree with you that the immediate start-up and feedback is a great benefit to the coder. This is why I dislike complex, Rube-Goldbergian REPL systems.
There is a use-case for a throw-away interaction with a REPL. For example, how does $builtinFuncX work, or how would $data best be imported into a structure?
A REPL can also be a good initial approach to a more ambitious problem. In this case, a REPL can be good for focus and discipline.
If the second case is going to answer your concern and be constructive, it's necessary to be able to build the code for sharing and cleanly export the code for re-use.
I've had success tackling challenges using REPLs for Python and Perl [1] in both ways. But no tooling is going to solve the problem of a sloppy teammate who claims success just because "it compiles" and "it works on my box". A person who knows how to build good tooling goes further.
[1] https://github.com/viviparous/preplish
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Interactive C++ for Data Science
It is Jupyter is a Rube-Goldbergian nightmare. Python is a memory hog. There are better solutions, to be sure.
A simple REPL is all that's needed to both do A-type and B-type data exploration. (I won't use the term "data scientist", it's an exaggeration in most cases.)
Python has a REPL, R has a REPL, Perl has PDL and both a simple REPL (https://github.com/viviparous/preplish) and a more complex one (https://metacpan.org/pod/Reply).
Jupyter should not be used as an IDE because it is the wrong tool for development. A-type data explorers just want a painless UI and may not care much about the horrible agglutination of incomplete/slow/broken solutions that Jupyter represents.
Pluto.jl
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Potential of the Julia programming language for high energy physics computing
I thought that notebook based development and package based development were diametrically opposed in the past, but Pluto.jl notebooks have changed my mind about this.
A Pluto.jl notebook is a human readable Julia source file. The Pluto.jl package is itself developed via Pluto.jl notebooks.
https://github.com/fonsp/Pluto.jl
Also, the VSCode Julia plugin tooling has really expanded in functionality and usability for me in the past year. The integrated debugging took some work to setup, but is fast enough to drop into a local frame.
https://code.visualstudio.com/docs/languages/julia
Julia is the first language I have achieved full life cycle integration between exploratory code to sharable package. It even runs quite well on my Android. 2023 is the first year I was able to solve a differential equation or render a 3D surface from a calculated mesh with the hardware in my pocket.
- Pluto.jl: Simple, reactive programming environment for Julia
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Ask HN: Why don't other languages have Jupyter style notebooks?
Re Julia there is also pluto.jl that is another notebook-like environment for julia. It's been a few years since I played with it but it looked cool, for example it handles state differently so you don't get into the same messes as with ipython notebooks. https://plutojl.org/
- Pluto: Simple Reactive Notebooks for Julia
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Looking for a Julia gui framework with a demo like EGUI
For this, Notebooks are often used. Julia offers a uniquely nice and interactive Pluto notebook for the web https://github.com/fonsp/Pluto.jl
- Excel Labs, a Microsoft Garage Project
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IPyflow: Reactive Python Notebooks in Jupyter(Lab)
I believe this is what Pluto sets out to do for Julia.
I used it as part of the āComputational Thinkingā with Julia course a year or two back. Even then the beta software was very good and some of the demos the Pluto dev showed were nothing short of amazing
https://plutojl.org/
- For Julia is there some thing like VSCode's python interactive window?
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What have you "washed your hands of" in Python?
I think what you want is Pluto!
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Show HN: Out of order execution in Jupyter notebooks is a solved problem
I like how Pluto.jl handles this:
> Pluto offers an environment where changed code takes effect instantly and where deleted code leaves no trace. Unlike Jupyter or Matlab, there is no mutable workspace, but rather, an important guarantee:
> At any instant, the program state is completely described by the code you see.
[1] https://github.com/fonsp/Pluto.jl
What are some alternatives?
xeus-cling - Jupyter kernel for the C++ programming language
vim-slime - A vim plugin to give you some slime. (Emacs)
tinyspec-cling - tiny spectral synthesizer with livecoding support
rmarkdown - Dynamic Documents for R
examples - Fully-working mlpack example programs
Weave.jl - Scientific reports/literate programming for Julia
transformers - š¤ Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Dash.jl - Dash for Julia - A Julia interface to the Dash ecosystem for creating analytic web applications in Julia. No JavaScript required.
jupyter - An interface to communicate with Jupyter kernels.
IJulia.jl - Julia kernel for Jupyter
slimux - SLIME inspired tmux integration plugin for Vim
Tables.jl - An interface for tables in Julia