Once you have your Django projects running, you come to situations, when you need to optimize for performance. The rule of thumb is to find the bottlenecks and then to take action to eliminate them by more idiomatic Python code, database denormalization, caching, or other techniques.
3.x will be the last monolithic release of IPython, as the next release cycle will see the growing project split into its Python-specific and language-agnostic components. Language-agnostic projects (notebook, qtconsole, etc.) will move under the umbrella of the new Project Jupyter name, while Python-specific projects (interactive Python shell, Python kernel, IPython.parallel) will remain under IPython
We ran into a couple of interesting situations recently, and used some helpful tricks to solve them, which of course should be recorded for posterity.
Looks at how Kimono Labs, which structures data at scale, and MonkeyLearn, which provides machine learning capabilities, can be used together to translate data into insight. Kimono is a smart web scraper for getting data from the web by turning websites into APIs. MonkeyLearn is a platform for getting relevant data from text using machine learning.
While proxy models aren't the most critical feature in the Django framework, they do seem to get short shrift. Here's a look into how to use this feature to create new and clean interfaces to data without making changes to your database.
PSF supports its members is in giving grants to fund workshops and events like one held in Warsaw in January. The PSF contributed $1,000 USD to the Geek Girls Carrots Warsaw workshop. Not a huge amount, but enough to make a big impact.
Wingware has released version 5.1 of Wing IDE, our cross-platform integrated development environment for the Python programming language. Wing IDE features a professional code editor with vi, emacs, visual studio, and other key bindings, auto-completion, call tips, context-sensitive auto-editing, goto-definition, find uses, refactoring, a powerful debugger, version control, unit testing, search, project management, and many other features.
A lot of the concepts we mention in this article can be found in Armin Ronacher’s presentation on advanced Flask patterns. Mr.Ronacher did great job enumerating the concepts. Advanced Flask concepts are used to build applications that scale, so let’s talk a little bit about what scaling an application means.
Memoization can be explicitly programmed by the programmer, but some programming languages like Python provide mechanisms to automatically memoize functions.
Magdalena is a Python and web developer from Berlin. She is very interested in open data, data visualization and civic tech. At university she started to use Python. So when searching for a web framework she wanted to use a Python-based one and decided to use Django.
Supporting Python 3. This is a free book about how to make your code support Python 3.
Smart Stack Overflow queries from the command line.
Function overloading for Python 3
A simple cron-like library for executing scheduled jobs.
The Muffin -- A web framework based on Asyncio stack. (early alpha)
A small Django app for managing schedules