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Issue - 139

Worthy Read

Flit is a simple way to Package and deploy Python projects on PyPI, Flit makes it easier by using a simple flit.ini file and assumes common defaults to save your time and typing. I knew about Flit when I was taking a look at Mariatta Wijaya game called Tic Tac Taco Pizza and noticed that she used flit to deploy the game, so we also asked her the reason for using this on the podcast we recorded so I decided to try porting my projects to Flit.

This course bridges the gap between introductory and advanced courses in Python. While there are many excellent introductory Python courses available, most typically do not go deep enough for you to apply your Python skills to research projects. In this course, after first reviewing the basics of Python 3, we learn about tools commonly used in research settings.

Python has a function called sys.getrefcount() that tells you the reference count of an object.

Embed docs directly on your website with a few lines of code.

Can we predict the outcome of a football game given a dataset of past games? That's the question that we'll answer in this episode by using the scikit-learn machine learning library as our predictive tool.
machine learning

Part 2 of 3: The “Docker repo” pattern. Note - Very informative and detailed article for those looking to bring CI + docker into their workflow.

How do Bitcoin markets behave? What are the causes of the sudden spikes and dips in cryptocurrency values? Are the markets for different altcoins inseparably linked or largely independent? How can we predict what will happen next?

Analyzing your sensor data has always been a daunting task and putting your data in the Dashboard has never been an easy task. In this article, we will see how using Python Flask, Pandas and MongoDB you can develop an Analytical Dashboard over a weekend.

Root cause to resolution in 30 secs.

Mimesis is a fast and easy to use library for Python, which helps generate mock data for a variety of purposes (see "Data providers") in a variety of languages (see "Locales"). This data can be particularly useful during software development and testing. The library was written with the use of tools from the standard Python library, and therefore, it does not have any side dependencies.

parallel processing


we will start building a system that uses the profile of the given user and provide recommendation completely based on that user’s preference and liking.
recommendation engine

Bayes Theorem describes the probability of an event, based on prior knowledge of conditions be related of conditions to the event. So it basically fits perfectly for machine learning, because that is exactly what machine learning does: making predictions for the future based on prior experience.
machine learning

Matplotlib is a great and very capable plotting library for Python.

Data sets are not perfect. Sometimes they end up with invalid, corrupt, or missing values. For the project I was working on, I could not have any values that are null or empty. This How-To will walk you through writing a simple Python script to see if your data set has null or empty values, and if so, it will propose two options for how to modify your data.
code snippets



I will share you about how using Dataframe of PySpark as Dataframe of Python.

I will outline the process I typically follow to dig deeper into aspects of the python programming language I am curious about.

This document is intended to Storepilots employees, but worth the read.
coding standards


This PEP describes additions to the Python API and specific behaviors for the CPython implementation that make actions taken by the Python runtime visible to security and auditing tools. The goals in order of increasing importance are to prevent malicious use of Python, to detect and report on malicious use, and most importantly to detect attempts to bypass detection. Most of the responsibility for implementation is required from users, who must customize and build Python for their own environment.



Nuitka is a Python compiler. It's fully compatible with Python 2.6, 2.7, 3.2, 3.3, 3.4, 3.5, and 3.6. You feed it your Python app, it does a lot of clever things, and spits out an executable or extension module.


IPython magic command to profile and view your python code as a heat map using py-heat.


raven - 133 Stars, 20 Fork
raven is a Linkedin information gathering tool that can be used by pentesters to gather information about an organization employees using Linkedin.

unformat - 113 Stars, 6 Fork
generates .clang-format file from example codebase

Pytorch_fine_tuning_Tutorial - 47 Stars, 6 Fork
A short tutorial on performing fine tuning or transfer learning in PyTorch. - 44 Stars, 3 Fork
A Human–Friendly API Service for Crypto Currency Information.

Tiny-URL-Fuzzer - 35 Stars, 1 Fork
A tiny and cute URL fuzzer.

argo - 16 Stars, 13 Fork
Get stuff done with container-native workflows for Kubernetes.

awesome-apistar - 10 Stars, 0 Fork
A curated list of awesome packages, articles, and other cool resources from the API Star community.

htmldate - 2 Stars, 0 Fork
extract the date of HTML documents.

pg-materialize - 2 Stars, 0 Fork
Postgres Materialized View Dependency Manager.

phone-scraper - 0 Stars, 0 Fork
Python library for finding phone numbers in random user input text.