Sinatra VS NumPy

Compared to Ruby on Rails, a full-stack web framework, Sinatra is a very lean micro-framework originally developed by Blake Mizerany to help Ruby developers build applications with "minimal effort".

a Sinatra app hosted on Heroku on the domain http://example.com

Let's say I have the simplest single-file Sinatra app. The hello world on their homepage will do. I want to run it under Apache with Phusion Passenger, AKA mod_rails.

Sinatra is the oldest competitor of Rails. Although it's not that popular anymore, it's still used in some simple and performance focused services.

Sinatra is fine as long as you have a small number of routes, because its router is O(n): https://github.com/sinatra/sinatra/blob/ac5404dbd897a4b3c5b3921d2f89fecd3b540ed3/lib/sinatra/base.rb#L1008-L1010

https://github.com/sinatra/sinatra A classy web-development dressed in a DSL (official / canonical repo)

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]