catala VS NumPy

Programming and law can go together tho https://github.com/CatalaLang/catala

Law is a mess, in part because its authors take shortcuts. For example, from the first example on CatalaLang's README.md:

> If the property was acquired by gift [and various conditions apply], then for the purpose of determining loss the basis shall be such fair market value. [emphasis added]

I think (and I'm not a lawyer or a tax expert) that this means that the basis of an asset can have a different value for the purpose of determining gain or determining loss. Wow, basis isn't just a number, although one might not notice this if one didn't read the six emphasized words.

But the Catala code seems to completely ignore this. Oops. I filed an issue:

https://github.com/CatalaLang/catala/issues/514

In a real use case, I imagine that substantial refactoring of the parts that consume basis might be needed when one notices that the basis is not a number.

Catals is a language trying to exactly this.

There's even a programming language for that: https://catala-lang.org/

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]