This article is primarily meant to act as a Python time complexity cheat sheet for those who already understand what time complexity is and how the time complexity of an operation might affect your code. For a more thorough explanation of time complexity see Ned Batchelder's article/talk on this subject.
Many common and unusual algorithms, implemented in Python as learning exercises. If you want to get a sense of what, say, data structures or fuzzy logic would look like in Python, this is a good place to start.
A collection of (mostly) technical things every software developer should know about.
A set of utility functions for iterators, functions, and dictionaries.
Construct is a powerful declarative and symmetrical parser and builder for binary data.
Instead of writing imperative code to parse a piece of data, you declaratively define a data structure that describes your data. As this data structure is not code, you can use it in one direction to parse data into Pythonic objects, and in the other direction, to build objects into binary data.
The library provides both simple, atomic constructs (such as integers of various sizes), as well as composite ones which allow you form hierarchical and sequential structures of increasing complexity. Construct features bit and byte granularity, easy debugging and testing, an easy-to-extend subclass system, and lots of primitive constructs to make your work easier.
A technical reference site that has lots of odd information, most of it PC related. Data formats, file extensions, datastructures and algorithms of sundry kinds and uses, hardware specs, microcontrollers, history, advice... there's a lot of stuff buried in here. If you need something you could do worse than check here first.