gonum VS Gin

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.

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

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

Maybe this way you could avoid having Mul, Mul_Inplace, Mul_Into variants. Gonum mostly follows the same pattern.

How does this compare to gonum graph? https://github.com/gonum/gonum/tree/master/graph

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.

You should check out this https://github.com/gonum/gonum

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

Now let’s define the functions that will be called whenever a request hits our API. All the functions will be referencing the context provided by the Gin web framework. Paste the following code below the sample slice we just added to api.go:

We will be using Gorilla Mux. As per their last update, they have a new group of maintainers, and their repos have shown activity to confirm that. The tutorial can be easily replicated in any other framework or library as well. So, while we will be using Gorilla Mux, you can try to replicate it in Gin or Fiber as well.

Now, let's dive into the fun part – creating our basic ToDo application using the powerful Gin framework. This section will walk you through the steps, breaking down the code into manageable snippets.

Thanks to the AWS Lambda Web Adapter, the application built as a (good old) REST/HTTP API using a familiar library (in this case, Gin.

Excellent Performance: Sponge is built on the gin framework, providing outstanding performance for web service development.

In this blog, we will delve into the fascinating realm of handling images in a Golang application, leveraging the power of the Gin framework for RESTful API development, MongoDB as a robust NoSQL database, and the mongo-driver library for seamless interaction with MongoDB. To store images efficiently, we'll explore the intricacies of GridFS, a specification within MongoDB for storing large files as separate chunks.

It uses Gin as the HTTP framework and PostgreSQL as the database with pgx as the driver and Squirrel as the query builder. It also utilizes Redis as the caching layer with go-redis as the client.

I have created an application with Go in Gin-Gonic. In my frontend (Nuxt3/TypeScript) I always get a CORS error:

We use Gin web framework https://gin-gonic.com for the routing, Gin provides a balance between performance, ease of use and extensibility making it a preferred choice for building and running web applications in Go.