yew VS NumPy

I coded up a game of life implementation in rust and web assembly using https://yew.rs/ as an effort to sharpen my rust skills and it resulted as a fun toy. You can find the source here: https://gitlab.com/reedrichards/wvdom Enjoy!

UI template: Yew - (https://yew.rs/)

I'm surprised nobody said they'd use [Yew](https://yew.rs/), especially given the premise of this being for a passion project.

This example shows updating an existing state: https://github.com/yewstack/yew/blob/04909dd942eb64285652d96a2621bdf7be3fa912/examples/timer_functional/src/main.rs

1. Not related to npm, but related to the web.

2. True, but compilers are generally better than transpilers.

3. Have you seen https://yew.rs/ ?

You could use Yew to write web apps, which can be opened on Android phones.

What about Yew and Iced?

In NumPy with @, dot() or matmul():

In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication.

Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:

numpy: A library for scientific computing in Python

Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy.

I was looking at all the big projects like numpy, pytorch, flask, etc.

I wish the NumPy devs would more thoroughly consider adding full fluent API support, e.g. x.sqrt().ceil(). [Issue #24081]