SQLite4 documentation describes the new key/value database that will serve as SQLite4's default storage layer.
After reading a bit about the new storage layer, I wanted to try it out as a standalone database. After pulling down the SQLite4 source code and reading through the LSM header file (it's very small!), I started coding and the result is now on GitHub: python-lsm-db and readthedocs: lsm-db docs.
API Browser for Flask-DebugToolbar
In this post, I’ll walk you through the process of setting up a jobs-queueing infrastructure, using Django, Celery, RabbitMQ, and Amazon Web Services. While building this system, I found that there was good documentation for each different component, but relatively little on how to fit the pieces together.
We recently had occasion to reconfigure some of our existing servers to use Amazon Web Services Elastic Load Balancers in front of them. Setting this up isn't hard, exactly, but there are a lot of moving parts that have to mesh correctly before things start to work, so I thought I'd write down what we did.
“…Django Girls main email account is regularly receiving questions from various companies asking us if we know some Django Girls alumni who might be interested in working for them. On the other hand, we also get questions from our alumni asking us if we know some companies who are looking for junior devs in city X.
So we’ve decided to build a “jobs” section on our website, where we can post job listings that we endorse and make it easier for employers and Django Girls to find each other!…”
If you are in NY worth attending.
Flask API is an implementation of the same web browsable APIs that Django REST framework provides.
It gives you properly content negotiated responses and smart request parsing.
It is currently a work in progress, but the fundamentals are in place and you can already start building kick-ass browsable Web APIs with it. If you want to start using Flask API right now go ahead and do so, but be sure to follow the release notes of new versions carefully.
This is frequently used as a programming challenge. There are a few ways to do this, but here is one especially interesting way that I've found. For this guide, we'll assume we want a list of all primes under 50.
Cynthia is from Buenos Aires, Argentina. She works as a Python/Django developer. Cynthia is a tech events attendee enthusiast: Django, Python, infrastructure, architecture, devops, frontend… She also participates in several local communities.
Python 3.5.0rc1 is now available for download.
This is a preview release, and its use is not recommended for production settings. However, as a "release candidate", it should be very similar to the final product. Python 3.5.0 final is scheduled for release in mid-September.
This is a simple extension for pylint that aims to check some common mistakes in django projects.
The Big List of Naughty Strings is a list of strings which have a high probability of causing issues when used as user-input data. Includes a python script to give you the json.
Will poll for Retweet Contests and retweet them. Inspired by http://www.hscott.net/twitter-contest-winning-as-a-service/
Enters "Re-tweet to win"-type contests on twitter.
A script that tags Pocket articles based on the time required to read them.
Flask-Hashing is a Flask extension that provides an easy way to hash data and check a hash of a value against a given hash. Flask-Hashing uses hashlib to actually hash data.
This extension prevents the user from needing to worry about how to hash data. Instead, developers are provided a simple call to do any necessary hashing of data.
PlotSummary is a python program that will scan a specified directory for plaintext files and produce a range of graphs based on the frequency and distribution of words within those files.
A Microsoft OneDrive client on Linux.
Post GIFs to Twitter by doing "@slashgif coffee break".