gonum VS Paste JSON as Code • quicktype

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

Quicktype automates the generation of code from JSON data. It's a real timesaver when dealing with complex JSON structures in your applications.

Nice! JSON schemas are really useful, we use them a lot for code generation. Another library that does this for multiple languages is https://quicktype.io/ . It's great, but not so actively developed.

Quicktype is a speedy way to transform JSON data into well-structured, type-safe code in any programming language. Can help simplify the process of generating models and serializers from JSON, schema, or GraphQL—for secure, efficient data handling. 6-20PM finds it a "Godsend to convert JSON into data structures in any language."

Good candidate modules for these initial conversions are utility functions and code related to external APIs or specifications. It is possible to automatically generate TypeScript type definitions from Swagger contracts, GraphQL or JSON schemas to be included in your project. as well as you can use website called https://quicktype.io/ to generate types and interfaces in order to user them in your tsx or ts file.

Using Codable structs is better than dictionaries. Paste the JSON into https://quicktype.io/ and it will create the structs for you.

May be quicktype.io?

Check out quicktype.io. You can paste in your JSON and it will build your model for you. There's even an option for creating constructors. And you can choose your programming language. I usually spend some time cleaning it up a bit. It's not the perfect solution and I don't use it all the time, but it sure saves time for complicated models.

Hello. I used quicktype.io to try and implement an api in my code.