Straight from the JSON Feed homepage:
We — Manton Reece and Brent Simmons — have noticed that JSON has become the developers’ choice for APIs, and that developers will often go out of their way to avoid XML. JSON is simpler to read and write, and it’s less prone to bugs.
So we developed JSON Feed, a format similar to RSS and Atom but in JSON. It reflects the lessons learned from our years of work reading and publishing feeds.
See the spec. It’s at version 1, which may be the only version ever needed. If future versions are needed, version 1 feeds will still be valid feeds.
I came across this interesting Python tool that helps with real-time face detection and emotion and gender classification. Here is a more complete brief description from the project page:
Real-time face detection and emotion/gender classification using fer2013/IMDB datasets with a keras CNN model and openCV.
- IMDB gender classification test accuracy: 96%.
- fer2013 emotion classification test accuracy: 66%.
In the spirit of validating everything against a schema (validating JSON, validating CSV), here is another option – YANG:
YANG is a data modeling language for the definition of data sent over the NETCONF network configuration protocol. The name is an acronym for “Yet Another Next Generation”. The YANG data modeling language was developed by the NETMOD working group in the Internet Engineering Task Force (IETF) and was published as RFC 6020 in October 2010. The data modeling language can be used to model both configuration data as well as state data of network elements. Furthermore, YANG can be used to define the format of event notifications emitted by network elements and it allows data modelers to define the signature of remote procedure calls that can be invoked on network elements via the NETCONF protocol. The language, being protocol independent, can then be converted into any encoding format, e.g. XML or JSON, that the network configuration protocol supports.
YANG is a modular language representing data structures in an XML tree format. The data modeling language comes with a number of built-in data types. Additional application specific data types can be derived from the built-in data types. More complex reusable data structures can be represented as groupings. YANG data models can use XPATH expressions to define constraints on the elements of a YANG data model.
Like many other standards, formats, and tools developed by very smart people, YANG can be used for much more than just networking configuration. If you data and states fit into its model, give it a try.
Here are a few resources that you might find useful in the process:
Listing, Iterating, and Loading JSON in Ansible Playbooks – for those days when you need to offload part of your configuration onto external JSON files, but don’t have a spare day to try, fail and repeat.
J Cole Morrison wrote an excellent guide into AWS IAM policies. It’s super useful for anyone who have tried implementing IAM policies and failed (or even barely succeeded).
What is an AWS IAM Policy?
A set of rules that, under the correct
conditions, define what
actions the policy
principal or holder can take to specified AWS
That still sounds a bit stiff. How about:
Who can do what to which resources. When do we care?
There we go. Let’s break down the simple statement even more…
Compared to all the AWS documentation one has to dive through, this one is a giant time saver!
Linux utils that you might not know covers a few Linux command line utilities that aren’t very famous:
- column, for “columnating” lists, which is very useful for display of table-like data (think CSV, for example);
- cal, for displaying calendars;
- factor, for calculating factors;
- numfmt, for formatting numbers and converting them to/from human-readable formats;
- shred, for overwriting the content of a deleted file, making it much more difficult to recover.
Supercharge your ecommerce is a collection of reviews of some of the best ecommerce plugins for WordPress. It covers a variety of options from the most famous like WooCommerce to some less known ones. Here’s a list of of what’s reviewed:
The Guardian is covering a 100+ internal training manuals, spreadsheets, and flowcharts that they’ve seen that Facebook has for training their editorial / censorship staff.
There’s plenty to learn from and think about. Once again, it’s shown how complex modern communications and discussions are, and how tricky it is to separate violent and abusive content from careless comments. Here’s a thought provoking example:
My brother wrote a follow-up – HAProxy abuse filtering and rate limiting – to his previous post – Nginx rate limit by user agent (control bots). This is just a tip of the iceberg that we are working with at the office, but it’s pretty cool.
Hopefully, soon enough our Ansible playbooks will be up to date and shareable…