setoolkit VS NumPy

[2] https://github.com/trustedsec/social-engineer-toolkit

There's programs out there to make these malicious PDFs, word documents, etc https://github.com/trustedsec/social-engineer-toolkit

Social Engineer Toolkit (SET)

Yes, you can find out who clicked, and more. Here's a link to the toolkit's documentation where you can get a lot of other help and tips: https://github.com/trustedsec/social-engineer-toolkit/blob/master/readme/User_Manual.pdf

git clone https://github.com/trustedsec/social-engineer-toolkit/ setoolkit/ cd setoolkit pip3 install -r requirements.txt python setup.py

Setoolkit GitHub

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]