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Issue - 44


Worthy Read

This post is going to be a greatest hits of my open-source libraries and blog posts concerning the use of SQLite with Python. I'll also share a list of some other neat SQLite projects that you may not have heard of before.
sqlite

Wes McKinney started working on Pandas in 2008. Since then, Pandas has become one of the most popular and useful software components for the data scientist. For good reason; using Python, Pandas and iPython/Jupyter notebooks makes it simple and quick to perform analysis on various datasets. In this post, we perform some basic analysis on the City of Baltimore employee salary data from data.gov, but this technique can be used on a wide variety of data sets very easily.
data science

I'm creating an example Python Machine Learning notebook for newcomers to the field. The goal is to show what an example ML project would look like from start to finish. I'd love your feedback or contributions to make it better.
machine learning

Twitter is social media site which allows user to share their thoughts in 140 characters with features like retweet, reply and follow other users etc. Lets make a twitter bot that gets a random Chuck Norris quote from the free API and post it to your twitter timeline after every 1 minutes. - See more at: http://scrolltest.com/10-minutes-to-make-our-twitter-bot-with-tweepy-in-python/#sthash.UeWWjdXT.dpuf
twitter

One thing you may hear said often about test-driven development is that as far as possible, you should test everything in isolation. However, it’s not always immediately clear how you actually go about doing this. In Django, it’s fairly easy to get your head around testing models in isolation because they’re single objects that you can just create, save, and then check their attributes.
django
,
testing

Tutorial and example package for continuous documentation generation in Python.

Michela Ledwidge is an artist and director redefining the space between cinema and games. In 2004 she won a NESTA Invention award for ‘remixable film’, which outlines her vision for playful storytelling and digital culture and continues to underpin her artistic practice. She is co-founder of studio Mod and has been both the creative and technical lead on numerous productions.

I am extremely happy to report that this year’s Frank Willison Award was presented at OSCON 2015 to Jessica McKellar (see Award Ceremony).

In this post I'm going to talk about something that's relatively simple but fundamental to just about any business: Customer Segmentation. At the core of customer segmentation is being able to identify different types of customers and then figure out ways to find more of those individuals so you can... you guessed it, get more customers! In this post, I'll detail how you can use K-Means clustering to help with some of the exploratory aspects of customer segmentation.
machine learning

To understand how a Django Middleware works we need to remember that the basic architecture of Django is composed by a request and a response. A middleware is something that stays in the middle. Let’s give a look to the next diagram, taken from official Django documentation:
django


Projects

cgt - 297 Stars, 16 Fork
Computation Graph Toolkit

continuous-docs - 193 Stars, 7 Fork
Tutorial and example package for continuous documentation generation in Python.

postgresql-metrics - 177 Stars, 4 Fork
Tool that extracts and provides metrics on your PostgreSQL database

shadowsocks - 39 Stars, 105 Fork
See https://github.com/Long-live-shadowsocks/

what-to-watch - 18 Stars, 3 Fork
Python script to help you decide what movie to watch.

toproxy - 16 Stars, 1 Fork
high performance simple tornado http proxy

numpy-tutorial - 9 Stars, 0 Fork
Numpy beginner tutorial

Obfuscate-SSL - 6 Stars, 1 Fork
Traffic obfuscation via ssl