Entries tagged with python
I always told myself I would never release this code. For some time I considered the appearance of my desktop environment a form of creative expression, and by putting the tooling I wrote into the hands of others, I might dilute, somehow, the quality of what I had set out to create. As embarrassing as it is to admit this - after all, the purpose of this work was to create a desktop environment that was functional and aesthetically pleasing, and had nothing to do with anyone else's desktop - I hope that by stating my thought processes I can convey how much I had invested in this project.
In this post I'll describe the tooling I wrote to automate the process of adjusting the appearance of the various software I use on a daily basis. Below is a screenshot of my desktop at the time of writing, with a couple applications running:
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.
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.
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...
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.
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.
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.
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
- Ordered key/value store
- Range searches
- Prefix searches
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
The SQLite source tree is full of wonders. There is the the lemon parser generator, a btree implementation (well, kind of not surprising), multiple search engines, a json library, and more. It looks like Dr. Hipp is also experimenting with integrating the LSM key/value store from SQLite4 as a standalone virtual table.
I've written about the json and full-text search extensions, the lsm key/value store, and the transitive closure extension (useful when querying hierarchical data). In this post I'll be covering another interesting extension, the
spellfix1 extension (documentation).