gophernotes
gonum
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| gophernotes | gonum | |
|---|---|---|
| 10 | 24 | |
| 3,766 | 7,249 | |
| 0.8% | 1.4% | |
| 3.0 | 8.2 | |
| 6 months ago | 6 days ago | |
| Go | Go | |
| MIT License | BSD 3-clause "New" or "Revised" 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
gonum
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How to set up interface to accept multi-dimension array?
But if you want to see what can be done for numeric stuff, check out gonum. Personally, I still wouldn't use Go, and I rather suspect it's still pretty easy to reach for something like what you're trying to do and not find it because Go just can't write that type sensibly, but you can at least see what is available, written by people who disagree with me about Go not being a great language for this.
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packages similar to Pandas
Numpy functionality is largely covered by https://www.gonum.org/ but for pandas I'm not sure if there is an equivalent as widely accepted. However, you might try https://github.com/rocketlaunchr/dataframe-go which I have not tried but it looks like it covers some of what you're looking for
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What libraries are missing?
Math libraries. It's just gonum right now. Missing things that often require people to link C or Python libs. E.g. https://github.com/gonum/gonum/issues/354
- Gonum Numerical Packages
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SIMD Accelerated vector math
Maybe this way you could avoid having Mul, Mul_Inplace, Mul_Into variants. Gonum mostly follows the same pattern.
- Modern hardware is fast, so let's choose the slowest language to balance it out
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graph: A generic Go library for creating graph data structures and performing operations on them. It supports different kinds of graphs such as directed graphs, acyclic graphs, or trees.
How does this compare to gonum graph? https://github.com/gonum/gonum/tree/master/graph
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From Python to NumPy
Go is quite a bit cleaner than Python and its concurrency/parallelism primitives can be well suited to scientific workloads.
You may want to have a look at Gonum (https://www.gonum.org), and the Go HEP package developed by CERN (https://go-hep.org).
I was also surprised to see DSP and pretty sophisticated packages, although I never used them: https://awesome-go.com/science-and-data-analysis
And of course Go has Jupyter integration, it's almost like running a script thanks to its fast compilation time.
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Go for science?
You should check out this https://github.com/gonum/gonum
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What makes concurrency in Go better than multiprocesing/multithreading in Python?
No, using CPU extensions and GPUs is a different thing than doing multitasking. There is Gonum but it is still slower than Numpy: https://github.com/gonum/gonum/issues/511
What are some alternatives?
gomacro - Interactive Go interpreter and debugger with REPL, Eval, generics and Lisp-like macros
dataframe-go - DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration
yaegi - Yaegi is Another Elegant Go Interpreter
gosl - Linear algebra, eigenvalues, FFT, Bessel, elliptic, orthogonal polys, geometry, NURBS, numerical quadrature, 3D transfinite interpolation, random numbers, Mersenne twister, probability distributions, optimisation, differential equations.
lgo - Interactive Go programming with Jupyter
Stats - A well tested and comprehensive Golang statistics library package with no dependencies.
nyxt - Nyxt - the hacker's browser.
gonum/plot - A repository for plotting and visualizing data
nbview - View Jupyter Notebooks in your terminal
PiHex - PiHex Library, written in Go, generates a hexadecimal number sequence in the number Pi in the range from 0 to 10,000,000.
PurefunctionPipelineDataflow - My Blog: The Math-based Grand Unified Programming Theory: The Pure Function Pipeline Data Flow with principle-based Warehouse/Workshop Model
goraph - Package goraph implements graph data structure and algorithms.