clerk
portal
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clerk | portal | |
---|---|---|
22 | 12 | |
1,697 | 837 | |
1.6% | - | |
8.5 | 9.5 | |
6 days ago | 4 days ago | |
Clojure | Clojure | |
ISC License | 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.
clerk
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The Current State of Clojure's Machine Learning Ecosystem
Something I really like in the Clojure data science stack that isn't mentioned is Clerk* — an interesting take on notebooks. I think it's a good gateway into Clojure for those coming from a Python or R background.
*https://clerk.vision/
- Improve Jupyter Notebook Reruns by Caching Cells
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Critique of Lazy Sequences in Clojure
Clojure's lazy sequences by default are wonderful ergonomically, but it provides many ways to use strict evaluation if you want to. They aren't really a hassle either. I've been doing Clojure for the last few years and have a few grievances, but overall it's the most coherent, well thought out language I've used and I can't recommend it enough.
There is the issue of startup time with the JVM, but you can also do AOT compilation now so that really isn't a problem. Here are some other cool projects to look at if you're interested:
Malli: https://github.com/metosin/malli
Babashka: https://github.com/babashka/babashka
Clerk: https://github.com/nextjournal/clerk
- Moldable Live Programming for Clojure
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Morse, an open-source interactive tool for inspecting Clojure
I'm really enjoying using Clojure with Clerk: https://github.com/nextjournal/clerk
It's a bit like a Jupyter notebook, but you get to use your own editor, you still have a normal Clojure REPL, it's stored in git like "normal" code, etc.
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Adding Clerk to a Leiningen Project
Hey all, I'm new to Clojure and would appreciate your help with a few questions I had getting started. I'm using Leiningen to setup my projects and manage my packages as recommended in Brave & True. So far I've been able to add any dependencies I've needed without much issue, Neanderthal, tech.v3.dataset, etc. I'm interested in data science, and was hoping to set up a notebook environment to be able to quickly produce data visualizations on the fly since I'm used to working with Jupyter. I came across Clerk, but I'm having some trouble adding it to my project. Here's what I tried:
- Clojure Turns 15 panel discussion video
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The program is the database is the interface
Clojure also has Clerk, which is like Jupyter, but more befitting Clojure's overall philosophy: https://clerk.vision/
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Clojure conventions for writing complicated mathematical calculations?
If I were working long enough with gnarly enough equations I'd look into using Clerk to visualize the equations with MathJax or similar, probably following Sam Ritchie's footsteps with SICMUtils. To me this is the true readability answer: lisp notation for precise implementations, compiling to a rich & familiar visual representation.
portal
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What I Have Changed My Mind About in Software Development
Tracing debuggers give you the best of both worlds. I've recently started using Flow-storm [0], by @jpmonettas), and it's been quite transformative. You can still easily see the values flowing through your system (better than just "prints"), and it can handle multi-threaded / async scenarios quite nicely. You don't need to manually step through code, you can just "see" your data flow, and when you have loops or some other form of iteration, you can see the data for each pass. Coupling this with a good data visualization tool (such as Portal [1]) really feels like magic. I've been doing Clojure for quite a few years now, and was very happy with my plain REPL-driven workflow, but this is way better.
[0] https://github.com/jpmonettas/flow-storm-debugger
[1] https://github.com/djblue/portal
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Visual-tools meeting 16 - Calva Notebooks & Portal - summary & recording
In this meeting, Lukas Domagala of the Calva team and Chris Badahdah, Portal's creator, presented Calva Notebooks, their integration with Portal, and other Portal updates.
- Clojure at the REPL: Data Visualization
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Request Support for Clojure in JetBrains new Fleet IDE
Also my dot-clojure and vscode-calva-setup repos have some interesting stuff in for using/customizing Portal for use with VS Code: * https://github.com/seancorfield/dot-clojure * https://github.com/seancorfield/vscode-calva-setup * https://github.com/djblue/portal
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Book recommendation focusing on tooling?
One thing that really helps with debugging is learning to use tap>. Even after a decade of using Clojure, I found it game changing. I personally use it with djblue/portal, which has a lot of bells and whistles, but isn't too hard to get going with the basics. You don't need an UI for tap>, though, if you don't want it.
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Best practices for maintaining REPL "hygiene"?
You may want to try using tap> for debugging, which avoids this problem and is generally more convenient in my experience. I use it to log values with either an atom or Portal.
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Things about clojure or tooling, you found out way too late.
Portal makes deving so much easier! Having your tapped data available to inspect and transform in the Portal UI is much easier, cleaner, and faster than in the REPL/output window.
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Clay, a way to write Clojure data science notebook value renderers that are portable across the landscape of Clojure notebook & dataviz tools
Clay is an attempt to create compatibility across data science notebook plugin scripts. Today, Clojure's data viz tools (e.g. Clerk, djbue/Portal) offer similar abstractions for scientists to 1) create notebook documents and 2) enable dynamic exploration of data. These tools all work by attaching rendering metadata to values. But the render code is not portable across tools, which means a script written for one tool is not compatible with all the others, and this inhibits scientific work and makes the toolchain inaccessible to scientists who don't know Clojure.
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Love Clojure, challenged by discoverability
tag / stick into something like https://github.com/djblue/portal makes this problem instantly go away, and I get a whole bunch extra stuff at the same time: https://www.youtube.com/watch?v=gIoadGfm5T8 If you MUST have it codified somewhere, probably the next highest leverage point is to use specs. Typically we do this when you've a single set of data structures that are widely reused (as opposed to, say, a map that's only used between a single SPA component and an API call). I've tried both clojure.spec and Malli. Clojure's spec is satisfactory. Malli's ergonomics and performance are fantastic. https://github.com/metosin/malli
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Sublime (love) Clojure
;; :main-opts ["-m" "cognitect.rebl"]}
Into your '~/.clojure/deps.edn'.
From there I can just add 'rebl' as a profile to my Intellj when you start a REPL it starts automatically.
There are also alternative tools like Portal to do the same things: https://github.com/djblue/portal
Or: https://vlaaad.github.io/reveal/
What are some alternatives?
next-auth - Authentication for the Web.
reveal - Read Eval Visualize Loop for Clojure
libpython-clj - Python bindings for Clojure
dot-clojure - My .clojure/deps.edn file
JD Esurvey - JD eSurvey is an open source enterprise survey web application written in Java and based on the Spring Framework. Check out the tutorial videos to find out more about the application features.
truss - Assertions micro-library for Clojure/Script
leo-editor - Leo is an Outliner, Editor, IDE and PIM written in 100% Python.
flow-storm-debugger - A debugger for Clojure and ClojureScript with some unique features.
pytudes - Python programs, usually short, of considerable difficulty, to perfect particular skills.
obb - Ad-hoc ClojureScript scripting of Mac applications via Apple's Open Scripting Architecture.
tech.ml.dataset - A Clojure high performance data processing system
cljs-devtools - A collection of Chrome DevTools enhancements for ClojureScript developers