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Web performance – Weekend must-read articles #31

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This is our collection of must-read articles for the weekend.  There’s something about performance tuning, Python, web fonts, and more.

Every week we bring you a collection of links to places on the web that we find particularly newsworthy, interesting, entertaining, and topical. We try to focus on some particular area or topic each week, but in general we will cover Internet, web development, networking, web performance, security, and other geeky topics.

This week’s suggested reading

Web fonts performance: making pretty, fast

The use of web fonts is surging. Just over the last year, the use of web fonts has doubled from ~6% to over ~12% according to the HTTP Archive. In the same time, Google Web Fonts has seen a 10x in the amount of requests, recently crossing 1B font views per day across 100M+ web pages. And there are no signs of slowdown in the adoption.

Speed is essential for a great web experience

A presentation by Andy Davies at Canvas Conf.

Clearing browser data

I’m going to focus on caching for the next few months. The first step is a study I launched a few days ago called the Clear Browser Experiment. Before trying to measure the frequency and benefits of caching, I wanted to start by gauging what happens when users clear their cache.

When milliseconds are not enough

Paul Irish presents performance.now(), the High Resolution Timer that was added by the WebPerf Working Group to allow measurement in the Web Platform that’s more precise than what we’ve had with +new Date and the newer Date.now().

Web performance: Why one size doesn’t fit all

When considering web performance, it’s tempting to think that the user experience on any given site or application will be fairly consistent. The reality? Performance is impacted by different variables and ensuring that all users have the best possible experience requires hard work.

Performance “tuning”: running in 1/100th the time

For the 757 Python Meetup group, someone proposed looking at some Python code they had which was slow. The code implemented a variation on the Elo chess rating system. It applied the ratings to other sports, and used the points scored as well as basic win/lose/tie to work out a ranking for sports teams. Very clever stuff. But. It was described as horribly slow. Since it was only 400 lines of code, it was a great subject for review in a Python meetup. I would be able to show some tweaks and performance tips.

Optimize performance and scalability with parallelism and concurrency

If you’d rather watch something than read, here’s a video of Bob Hancock’s presentation at Pycon 2012.

Web Performance Optimisation

And finally, another video. Callum Macdonald talks about “Web Performance Optimisation” at Techmeetup Edinburgh September.

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Image (top) via Shutterstock.

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