Metaflow

Metaflow is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning.

pip install metaflow

Metaflow More Info

Metflow GitHub

Photon

Photon can extract the following data while crawling:

URLs (in-scope & out-of-scope)
URLs with parameters (example.com/gallery.php?id=2)
Intel (emails, social media accounts, amazon buckets etc.)
Files (pdf, png, xml etc.)
Secret keys (auth/API keys & hashes)
JavaScript files & Endpoints present in them
Strings matching custom regex pattern
Subdomains & DNS related data
The extracted information is saved in an organized manner or can be exported as json.

Python Regular Expression

A Regular Expression, is a sequence of characters that forms a search pattern. Python has a built-in package called re, which can be used to work with Regular Expressions.

(Example Code to remove symbols and numbers - compatible with Python 2.7.17)
import re
import string
input_str = "58597884|01:31:50|The rise of python stated by pythonforengineers blog"
print"Before Processing:",input_str
result = re.sub(r'\d+', '', input_str)
result = result.translate(string.maketrans("",""), string.punctuation)
print"After Processing:",result

More Details

Python Open Source Project - Manim

Manim is an animation engine for explanatory math videos. It's used to create precise animations programmatically. 

Install it from PyPI via pip:        pip3 install manimlib

Click here for more info

Surprise - A Python scikit for recommender systems

Surprise is a Python scikit building and analyzing recommender systems that deal with explicit rating data. Surprise stands for Simple Python Recommendation System Engine.

Surprise was designed with the following purposes in mind:

Give users perfect control over their experiments.
Alleviate the pain of dataset handling.
Provide various ready-to-use prediction algorithms.
Make it easy to implement new algorithm ideas.
Provide tools to evaluate, analyse and compare the algorithms performance.

For more info http://surpriselib.com