gophernotes
prose
| gophernotes | prose | |
|---|---|---|
| 10 | 1 | |
| 3,772 | 2,924 | |
| 0.6% | - | |
| 3.0 | 1.9 | |
| 6 months ago | almost 2 years ago | |
| Go | Go | |
| MIT License | 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
prose
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Go+: Go designed for data science
Apart from Gonum[1] numerical libraries, I haven't found specific data science related Go libraries in my search for it for some hobby projects when compared to Python ecosystem.
Interestingly Prose[2] A Go library for text processing yielded better results for named-entity extraction when compared to NLTK in my tests in terms of accuracy and obviously performance.
Perhaps Go is not being applied enough in the Data Science/ML and for fields where it's applied (Network) Math in the standard library seems to be sufficient.
[1] https://github.com/gonum/gonum
[2] https://github.com/jdkato/prose
What are some alternatives?
gomacro - Interactive Go interpreter and debugger with REPL, Eval, generics and Lisp-like macros
gse - Go efficient multilingual NLP and text segmentation; support English, Chinese, Japanese and others.
yaegi - Yaegi is Another Elegant Go Interpreter
go-i18n - Translate your Go program into multiple languages.
gonum - Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more
textcat - A Go package for n-gram based text categorization, with support for utf-8 and raw text
lgo - Interactive Go programming with Jupyter
porter2 - High Performance Porter2 Stemmer
nyxt - Nyxt - the hacker's browser.
gojieba - "结巴"中文分词的Golang版本
nbview - View Jupyter Notebooks in your terminal
go-mystem - CGo bindings to Yandex.Mystem