gophernotes
whirlisp
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| gophernotes | whirlisp | |
|---|---|---|
| 10 | 5 | |
| 3,769 | 17 | |
| 0.9% | - | |
| 3.0 | 4.9 | |
| 6 months ago | about 3 years ago | |
| Go | Common Lisp | |
| MIT License | - |
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gophernotes
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Go: What We Got Right, What We Got Wrong
https://github.com/gopherdata/gophernotes
I've had this bookmarked for some time and just havent gotten around to it.
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Alternative REPL to "gore"
Gopher Notes Kernel for jupyter notebooks? Could be useful :)
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GoNB, a new Jupyter Notebook Kernel for Go
I started this because gophernotes was not working for another project I'm slowing working on -- it is interpreted, and not up-to-date (generics, etc).
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How To Develop In Go Without Commenting Out?
A go kernel is available at https://github.com/gopherdata/gophernotes
- Is there a program or plugin in that's similar to jupyter notebooks or google collab for Go lang?
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Why Lisp?
> You do know that statically typed languages have REPLs too? Like the ML family, including Haskell.
I do, but that I don't see how that relates to the bit of my post which you've quoted. I certainly didn't claim or imply that REPL and static type systems were mutually exclusive, only that REPLs are a poor substitute for many static analysis tasks.
> And when using something like a Jupyter notebook with a kernel for your compiled language https://github.com/gopherdata/gophernotes you can do similar interactive programming.
Yeah, I'm aware. I operate a large JupyterHub cluster (among many other things) at work. :)
> Lisp REPLs take that a step further, as you interact with and in your whole actually running program.
That sounds nice, but it's too abstract to persuade IMHO.
- Scripting in Go
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I just started learning Go and my senior gave me link of "Learn Go with tests" as a place where i should be learning .... i am finding this thing very complex compared to other tutorials, why so and what should i do?
If you are coming from python,jupyter notebook, gophernotes is a great library to setup your own playground.
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Go+: Go designed for data science
Why can't you just build libraries to make Go a better language for data science? There's already Go support for a Jupyter Notebooks kernel: https://github.com/gopherdata/gophernotes
whirlisp
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Understanding the Power of Lisp (2020)
I wrote this to try and show how that could happen in a realistic enough way to make sense:
https://github.com/codr7/whirlisp
- Why Lisp?
- Show HN: A Whirlwind Lisp Adventure
What are some alternatives?
gomacro - Interactive Go interpreter and debugger with REPL, Eval, generics and Lisp-like macros
SICL - A fresh implementation of Common Lisp
yaegi - Yaegi is Another Elegant Go Interpreter
cafe-latte - An implementation of Common Lisp dynamic variables, control flow operators, and condition system in plain Java.
gonum - Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more
sicp - HTML5/EPUB3 version of SICP
lgo - Interactive Go programming with Jupyter
oh - A new Unix shell.
nyxt - Nyxt - the hacker's browser.
circle - The compiler is available for download. Get it!
nbview - View Jupyter Notebooks in your terminal
excoptional - A fully typed, zero-dependency implementation of the functional programming Option object for JavaScript and TypeScript