gonb
ipe
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gonb
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Go, Python, Rust, and production AI applications
I've had these strong feelings and the OP describes it really well. Despite being a polyglot programmer, I really struggle with Python, both in expression and performance (unless it's just config for GPUs).
Some of this frustration was recently an "Unpopular Opinion" on the Go Time Podcast regarding Python being great for "data exploration" but not for "data engineering": https://changelog.com/gotime/304#t=3196
I've been yearning for better interactive tooling and ML-related libraries bridge this gap and started using some even in just the last week:
* GoNB (Golang-support for Jupyter notebooks, also from a Googler) https://github.com/janpfeifer/gonb
* That uses Go-Plotly for graphs/UI: https://github.com/MetalBlueberry/go-plotly
* GoMLX (GoNB author is also on that project, many thanks Jan!) https://github.com/gomlx/gomlx
* Hidden at the end of OP is LangChainGo for LLMs, which I haven't used yet: https://github.com/tmc/langchaingo
Pick those up and let's make the Go community stronger together!
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The Golang Saga: A Coder’s Journey There and Back Again. Part 2: The Data Expedition
When I created a new Jupyter file in Go, I faced a challenge trying to replicate the development process I usually follow with Python. In Python and Jupyter Notebook I can conveniently run code in separate parts, saving previous values in memory and using cells to organize code. This flexibility was missing in Go, and it took me some time to figure out a solution. However, I came across a helpful tutorial that explained how to use caching with the Go Kernel, making the process smoother with gonb.
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The Golang Saga: A Coder’s Journey There and Back Again. Part 1: Leaving the Shire
I needed one more thing to make myself feel at home, something I usually use with Python. When working with data, I often turned to the Jupyter VSCode extension for its convenience. To my relief, I discovered that a Go kernel existed, tailored perfectly for my needs.
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GoMLX -- Accelerated ML for Go
Training library, with some pretty-printing. Including plots for GoNB Jupyter notebook.
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GoNB, a new Jupyter Notebook Kernel for Go
Tutorial (and demo) here. Source code in github.com/janpfeifer/gonb.
ipe
We haven't tracked posts mentioning ipe yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
fleet
Gor - GoReplay is an open-source tool for capturing and replaying live HTTP traffic into a test environment in order to continuously test your system with real data. It can be used to increase confidence in code deployments, configuration changes and infrastructure changes.
Docker - Notary is a project that allows anyone to have trust over arbitrary collections of data
restic - Fast, secure, efficient backup program
myLG - Network Diagnostic Tool
borg - Search and save shell snippets without leaving your terminal
Hugo - The world’s fastest framework for building websites.
nes - NES emulator written in Go.
gomlx - GoMLX -- Accelerated ML Libraries for Go
drive - Google Drive client for the commandline
weather-project - Weather analyzer pet project
heka - DEPRECATED: Data collection and processing made easy.