The official announcements are out, and my former employer Metaweb no longer exists. I’m happy that the ideas, and most of the people, have found a home, but it feels strange that the company is no longer a distinct entity. In many ways it makes a lot of sense for Google to end up owning them, and I hope the former-Metaweb-now-Google employees prosper.
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One of the great things about unit testing is that you can get into a game-like mode where you make incremental but measurable progress—“flow”, basically—but what if it’s just not similar enough to a game for you?
Install Unit Testing Achievements, a Python package that works with nose, unittest, and Django. Somewhat crazy, definitely hilarious. Some of the achievements themselves are excellent, such as My God, It’s Full of Dots: The suite has at least 2,001 passing tests.
Sadly not yet working is another one I like, Heisenbug: Make a passing suite fail without changing anything.
After a highly enjoyable, productive, and extended period, it’s time for me to return to the world of paid work.
I’m quite happy with the things I’ve done during my time off. Many of them are important only to me, but then, it’s been my time off.
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This post could be summarized as “regular expressions are a lot faster than naive for loops”.
I’ve been working on improving the script I use for live wordcount in Vim, partly for performance and partly so that I can package it up as a plugin and share it with other people. Along the way I’ve improved the speed of the script rather significantly, and will go through the key part of that change here.
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I’m going to compare seven different ways in Python to make one list out of several lists containing different numbers of elements, something that strikes me as a common but not necessarily everyday operation.
The philosophy of Python is that generally there should be one obvious and reasonable way to do things. I really like this philosophy—except when the Python way isn’t the way I prefer, of course.
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I’ve been writing Python fairly steadily for the past couple of years, and a significant amount of that has been for my own projects; Python is what I tend to use to scratch workflow-related itches. That’s great, but many of these projects reach a point short of “finished” when I stop working on them.
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Refactoring is rewriting source code while preserving the functionality of that code. I’m currently refactoring my Python script for Subversion status, because I want to experiment with sharing code on bitbucket and it seemed like a reasonable first project to put up there.
Some people hate refactoring, but I often enjoy it. I get a kick out of figuring out how to make code “better”, although that’s often a subjective judgment. In this case, when I opened up the script to have a look at it, I immediately saw a function that I knew I wanted to refactor. I’m amused by the enjoyment I derived from making the fairly simple change.
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After reading Dhananjay Nene’s comment on my post about a functional style approach to the “find longest repeater” problem, I decided to follow the line from that comment and divide the program into functions for finding the longest contiguous block and then for comparing the blocks. Naturally, I wanted to do this without using any variables…
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Last night a friend asked me what functional programming was, and as part of my answer I decided to rewrite a trivial program in the functional style to see what it was like. I did this in Python without using the functional module.
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Over the last couple of weeks I’ve been hacking away on scripts to customize Vim, replicating the scripts I made for jEdit. I’m more or less done, and this blog post is being written in MacVim. This hopefully means that when I’m done with it I’ll be able to publish it from within Vim, the same as with jEdit.
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The Python Challenge seems like a good way to have fun with Python through puzzle-solving. As with all riddles, it’s important to read the questions carefully…
I’m currently trying out Vim (again), and have made more progress this time, mainly due to Seth’s help. The key things that have made it better:
Really, though, the key first one was :set hidden. Before that I felt that I had completely misunderstood Vim’s file management model.
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I really like this idea from Dave Thomas: code katas, small pieces of programming practice involving some repetition. I came by it via Katacasts, a collection of screencasts of people doing the katas. I particularly recommend Gary Bernardt’s String Calculator in Python and Vim. (Which has inspired me to try once again to get past the vim file management issues I have.)
I’ve been looking at a bunch of coding exercises recently, including the demo for Codility, and recalled an exercise that I came up with as an interview question. It’s not incredibly difficult, but strikes me as a good “real-world” exercise—it’s based on a task I had to perform while working on the discuss functionality for freebase.com.
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I came across these on Hacker News recently, and think they’re worth calling out: Python Speed Performance Tips.
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In 2009 I achieved some significant things that weren’t on my list of goals, although they’re not concrete achievements in the same sense.
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Python Tips, Tricks, and Hacks at Siafoo is an excellent overview of useful Python knowledge. I was familiar with most of it but still think it’s worth reading over. I did learn a couple of new things, too.
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Earlier this evening Gever suggested a service dedicated to shortening URLs that had geolocation data in them. My immediate responses were that a) this was a great idea, and b) that I wanted the shortened URLs to still be human-readable in some sense—specifically, I wanted a person to be able to look at two URLs returned by this service and have some idea of how close to each other they were.
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This post details why they’re making the move. I find this of interest partly because it’s a move from a very popular web language (PHP) to one that’s become vastly more popular in the last couple of years (Python), and also because Django is the one major Python framework I haven’t tried out yet. Because of my liking for Python, I have a personal bias that makes me happy to see a prominent project such as this one move to the language.
I find it odd that they’re going from Subversion to git instead of to Mercurial, but I like the fact that they’re moving their documentation to the reStructuredText-based Sphinx.
Test-Driven Development (TDD) is a programming methodology that calls for programmers to first write tests that will only be passed by code that meets the specifications for whatever component they’re working on, and then to write the code for the component and keep working on it until it passes the tests.
I don’t tend to use Test-Driven Development, even though I often think I should. When working on personal projects, I don’t even write many tests after the code is done, and that’s something I should definitely do. But I generally regard it as a good practice.
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I never knew about this optional third parameter to list slices—in addition to e.g. getting the third to fifth items in a list with somelist[2:5], you can also get every nth item with somelist[::n].
This makes it very easy to get every odd or even item in a list, odd with somelist[::2] and even with somelist[1::2].
Where I think this is particularly handy is if you have to grab e.g. three-line chunks out of some text:
chunks = []
lines = text.split("\n")
for i in range(0, len(lines))[::3]:
chunk = []
chunk.append(lines[i])
chunk.append(lines[i+1])
chunk.append(lines[i+2])
chunks.append("\n".join(chunk))
It took me a while to get there, but I now have a working toolchain to automate going from an RTF file (or a Word document) to reStructuredText. The final link took the longest to find, and turned out to have been right there all along (no, I’m not going to turn this into a retelling of The Alchemist). But if you’re interested in how to get from Word to a sane format (like reStructuredText), this post will interest you.
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