The Weekly Top 10: Python Web Development Resources
Written by Alex Armstrong   
Wednesday, 14 September 2016

Python is the topic of this week's catch of blog posts that might otherwise have escaped your notice. There are a couple of courses, a round up of books, a couple of servings of Django, Python compared to SQL for data analysis and more. In short, something for every Pythonista. - Most Popular Django Sites

The first question we ask ourselves when we approach a new project: is Django really the best option here? To be more certain about it, we wrote a script that would gather all the Django sites on the Internet and analyze the list we receive. The script is still processing and the final results will come later. So we started with 5 popular sites on Django that everyone knows and we had a proof that they are currently working on Django Framework. - Programming for Everybody (Getting Started with Python)

This course aims to teach everyone the basics of programming computers using Python. We cover the basics of how one constructs a program from a series of simple instructions in Python. The course has no pre-requisites and avoids all but the simplest mathematics. - Making Django CMS as Easy to Install as WordPress

Probably more than any other software in the world, WordPress has done a magnificent job making web content management not just available, but easy and effective too, for a huge number of people. There's a lot to learn from the success of WordPress – especially if like us you'd rather find a way to emulate that success than decry WordPress's supposed failings. Here's what we learnt from their success. - Profiling Python in Production

We recently reduced CPU usage across our fleet by 80%. One key technique that made this possible was a lightweight profiling strategy that we could run in production. This post is about the ways we approached instrumentation, the tradeoffs involved, and some tools you can use to optimize your own apps (including code!). - Thinking in SQL vs Thinking in Python

Over the years, I've used a variety of languages and tools to analyze data. When we started working to integrate Python Notebooks with our SQL editor, I got pulled back into using a scripted language for analysis. With it came yet another way of thinking and a new mental framework to learn. While the benefits of this new workflow – which largely provides the benefits of my SQL to R workflow without the costs – were clearly enough to make the transition worth it, it would've been much easier had I known a few things up front. - Data Normalization in Python

In honor of the opening of another season of America's Pasttime, I was working on a post that uses data from the MLB. What I realized was that as I was writing the post, I found that I kept struggling with inconsistent data across different seasons. It was really annoying and finally it hit me: This is what I should be writing about! Why not just dedicate an entire post to normalizing data! - Course: Python Jumpstart by Building 10 Apps

Programming is fun and profitable. Learning to become a software developer should be equally fun! This course will teach you everything you need to know about the Python language all the while building interesting and engaging applications. - Import a Docker Container in Python

Docker containers are awesome for isolating applications from each other, but what if you want them to talk to each other? For instance, if you're developing an app in python that needs to interact with software written in another language. We created sidomo – Simple Docker Module so that if you can get your weirdo app to run in any linux environment, then you can instantly call it from Python with zero added effort. - The Best Python books in 2016

So you think about learning Python? Stop thinking about it – start doing it! In this article I compare a list of the current best Python books – especially for beginners. - Beginner's guide to Web Scraping in Python (using BeautifulSoup)

The need and importance of extracting data from the web is becoming increasingly loud and clear. Every few weeks, I find myself in a situation where we need to extract data from the web. Sadly, not all websites provide an API. Some do it because they do not want the readers to extract huge information in structured way, while others don't provide APIs due to lack of technical knowledge. What do you do in these cases? Well, we need to scrape the website to fetch the information.

From Our Partners

Ixia - The DDoS Attack that Never Happened

The attack started at 9:09 AM. 50,000 TCP SYN requests per second started hitting the public website of a major financial institution. A few minutes later the rate increased to 100,000, and finally to 300,000 SYN requests per second. But this DDoS attack never really happened.





Other Weekly Top 10s

Professional Development

Mainly Magento

JavaScript Development Resources

SharePoint and Other CMS Platforms

Web Design Matters

Ruby and Rails


Web Development Resources

PHP Web Development Resources 

AngularJS Web Development Resources

Web Design

JavaScript Programming Resources


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Last Updated ( Wednesday, 23 November 2016 )