Courses - Google Code University - Google Code. Lecture Slides and Video Archives. Hacking - Beginning txt. Popular RFC Title Index 1. Bash by example, Part 3.
Six ways to write more comprehensible code. I learned to write, clear, maintainable code the hard way.
For the last twelve years, I've made my living writing computer games and selling them over the Net using the marketing technique that was once charmingly known as shareware. What this means is that I start with a blank screen, start coding, and, a few tens of thousands of lines of code later, I have something to sell. This means that, if I make a stinky mess, I'm doing it in my own nest. When I'm chasing down a bug at 3 a.m., staring at a nightmare cloud of spaghetti code, and I say, "Dear God, what idiot child of married cousins wrote this garbage? ", the answer to that question is "Me.
" So I have been well rewarded by learning about good, sane programming techniques. But there are many who, like me, stumbled into programming in an unexpected or unusual way and never had anyone drill this stuff into them. The example case Figure 1. The game will take place in periods of time called Waves. Killing an alien gives you some points. 9 Ways to Instantly Code Faster. Twice a month, we revisit or update some of our readers’ favorite posts and sessions from throughout the history of Nettuts+.
This tutorial was first published last September. Doesn't the title say it all? There are a wide variety of tools and techniques which can drastically improve the speed at which we code. Particularly during time-sensitive settings, even a savings of a few seconds per iteration can add up substantially over the course of the month. I'll show you eleven of my favorite tools in this article. 1. Combine the power and specificity of CSS selectors with HTML mark-up, and you get Zen Coding.
How to Design Programs. Programming Texts/Tutorials. Biggus Biggus is a pure-Python library for handling very large (i.e. too large for system memory) n-dimensional arrays.
It has two main components: Representation, lazy indexing, and conversion to persistent files and NumPy arrays; andLazy calculation. At the core of Biggus is the Array which provides a simple, consistent, NumPy-esque interface to n-dimensional data which avoids reading data until explicitly requested by user code. Commonly these Array objects are created by wrapping "concrete" data sources such as HDF5 variables, netCDF4 variables, or even just NumPy arrays. Once created, Array objects can be concatenated and stacked to form new Array objects, which can themselves be concatenated and stacked as required. In addition, all Array objects can be indexed to extract subsets. User code may request any Array object be saved to a "concrete" data form (e.g.