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XML5 and Python Leftovers

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  • The case for XML5

    My XML5 idea is over twelve years old now.


    XML in browsers has much less of a compatibility footprint. Coupled with XML not always returning a tree for a given byte stream making backwards compatible (in the sense that old well-formed documents parse the same way) extensions to it is possible. There is a chance for it to ossify like text/html though, so perhaps XML5 ought to be amended somewhat to leave room for future changes.

  • Linting with Flake8

    For so long the word "Linting" meant nothing to me. It sounded like some supercoder leet speak that was way out of my league. Then I discovered flake8 and realised I was a fool.

    This article is a simple one. It covers what linting is; what Flake8 is and has an embarrassing example of it in use.

    Before we get started, I need to get something off my chest. I don't know why but I really hate the word "linting". It's a hatred akin to people and the word "moist".

  • PyPy's new JSON parser

    In the last year or two I have worked on and off on making PyPy's JSON faster, particularly when parsing large JSON files. In this post I am going to document those techniques and measure their performance impact. Note that I am quite a lot more constrained in what optimizations I can apply here, compared to some of the much more advanced approaches like Mison, Sparser or SimdJSON because I don't want to change the json.loads API that Python programs expect, and because I don't want to only support CPUs with wide SIMD extensions. With a more expressive API, more optimizations would be possible.
    There are a number of problems of working with huge JSON files: deserialization takes a long time on the one hand, and the resulting data structures often take a lot of memory (usually they can be many times bigger than the size of the file they originated from). Of course these problems are related, because allocating and initializing a big data structure takes longer than a smaller data structure. Therefore I always tried to attack both of these problems at the same time.
    One common theme of the techniques I am describing is that of optimizing the parser for how JSON files are typically used, not how they could theoretically be used. This is a similar approach to the way dynamic languages are optimized more generally: most JITs will optimize for typical patterns of usage, at the cost of less common usage patterns, which might even become slower as a result of the optimizations.

  • Getting Started with Python PyAutoGUI

    In this tutorial, we're going to learn how to use pyautogui library in Python 3. The PyAutoGUI library provides cross-platform support for managing mouse and keyboard operations through code to enable automation of tasks. The pyautogui library is also available for Python 2; however, we will be using Python 3 throughout the course of this tutorial.

    A tool like this has many applications, a few of which include taking screenshots, automating GUI testing (like Selenium), automating tasks that can only be done with a GUI, etc.

    Before you go ahead with this tutorial, please note that there are a few prerequisites. You should have a basic understanding of Python's syntax, and/or have done at least beginner level programming in some other language. Other than that, the tutorial is quite simple and easy to follow for beginners.

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