Entries tagged with python

What happened?

Remember when Python looked like this?

def hello_world(name):
    print 'Hello', name

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Python tool for templating and managing dotfiles

I always told myself I would never release this code. "It has some pretty gritty-looking functions", "it's full of details specific to my setup", etc, was what I told myself. But really I was worried that someone would use it to copy my desktop setup, or even worse, make something cooler than mine. Then a little while back I stopped being so hung up on my desktop being a unique snowflake (in the sea of Arc bullshit out there). In retrospect, it seems a little crazy even... At any rate, my setup is still dank, I'm just ready to share the tooling I use to make it that way!

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Multi-threaded SQLite without the OperationalErrors

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SQLite's write lock and pysqlite's clunky transaction state-machine are a toxic combination for multi-threaded applications. Unless you are very diligent about keeping your write transactions as short as possible, you can easily wind up with one thread accidentally holding a write transaction open for an unnecessarily long time. Threads that are waiting to write will then have a much greater likelihood of timing out while waiting for the lock, giving the illusion of poor performance.

In this post I'd like to share a very effective technique for performing writes to a SQLite database from multiple threads.

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Optimistic locking in Peewee ORM

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In this post I'll share a simple code snippet you can use to perform optimistic locking when updating model instances. I've intentionally avoided providing an implementation for this in peewee, because I don't believe it will be easy to find a one-size-fits-all approach to versioning and conflict resolution. I've updated the documentation to include the sample implementation provided here, however.

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Suffering for fashion: a glimpse into my Linux theming toolchain

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My desktop at the time of writing.

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Here it is a couple months later.

It's been over 2 years since I wrote about the tooling I use to theme my desktop, so I thought I'd post about my current scripts...

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"For Humans" makes me cringe

for chodes

When Kenneth Reitz created the requests library, the Python community rushed to embrace the project, as it provided (finally) a clean, sane API for making HTTP requests. He subtitled his project "Python HTTP Requests for Humans", referring, I suppose, to the fact that his API provided developer-friendly APIs. If naming things "for humans" had stopped there, that would have been fine with me, but instead there's been a steady stream of new projects describing themselves as being "For Humans" and I have issues with that.

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Examples of using Walrus, a lightweight Redis Toolkit

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walrus is my go-to toolkit for working with Redis in Python, and hopefully this post will convince you that it can be your go-to as well. I've tried to include lots of high-level Python APIs built on Redis primitives and the result is quite a lot of functionality. In this post I'll take you on a tour of the library and show examples of how it might be useful in your next project.

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Five reasons you should use SQLite in 2016

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If you haven't heard, SQLite is an amazing database capable of doing real work in real production environments. In this post, I'll outline 5 reasons why I think you should use SQLite in 2016.

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Announcing sophy: fast Python bindings for Sophia Database

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Sophia is a powerful key/value database with loads of features packed into a simple C API. In order to use this database in some upcoming projects I've got planned, I decided to write some Python bindings and the result is sophy. In this post, I'll describe the features of Sophia database, and then show example code using sophy, the Python wrapper.

Here is an overview of the features of the Sophia database:

  • Append-only MVCC database
  • ACID transactions
  • Consistent cursors
  • Compression
  • Ordered key/value store
  • Range searches
  • Prefix searches

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Updated instructions for compiling BerkeleyDB with SQLite for use with Python

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About three years ago I posted some instructions for building the Python SQLite driver for use with BerkeleyDB. While those instructions still work, they have the unfortunate consequence of stomping on any other SQLite builds you've installed in /usr/local. I haven't been able to build pysqlite with BerkeleyDB compiled in, because the source amalgamation generated by BerkeleyDB is invalid. So that leaves us with dynamically linking, and that requires that we use the BerkeleyDB libsqlite, which is exactly what the previous post described.

In this post I'll describe a better approach. Instead of building a modified version of libsqlite3, we'll modify pysqlite to use the BerkeleyDB libdb_sql library.

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