Using Node-RED for RSS feeds
I was using Huginn for about a year for the purpose of ingesting data and outputting RSS feeds. This week I swapped out Huginn and started using Node-RED instead. So far it’s working out well and I’m loving the new setup. This post will highlight the nodes I coded for Node-RED to work it for my purpose, but first a little bit of background.
Table of Contents
- Why Huginn or Node-RED?
- Reasons for Replacing Huginn
- Using Node-RED
- Node-RED on Raspberry Pi 3
Why Huginn or Node-RED?
Almost every news update I read is through RSS feeds synchronized to my phone. RSS allows me to have a superior reading experience, and the synchronization feature of the app on my phone allows me to read offline during my commute.
Currently the service I use for synchronization is BazQux. Other options I’ve used in the past include Newsblur, and self-host options such as Miniflux and Coldsweat. Once my BazQux subscription runs out, I’m probably going to investigate self-host options again.
In order to read everything via RSS feeds, either the news source needs to provide the RSS feed or I need to produce the RSS feed myself. For example, Twitter doesn’t provide a RSS feed, so I wrote some code that runs on AppEngine and converts tweets into a RSS feed. It’s a much better way to read Twitter in my opinion. I also apply additional filters on top of the Twitter feed, which is where Huginn and Node-RED comes in.
Huginn and Node-RED allows me to automate the filtering process and automate the steps needed to take a data source that doesn’t have RSS feed and produce one. Another example of where I do this is the Asuswrt-Merlin Changelog. The changelog is just a blob of text. I use Huginn and Node-RED to periodically retrieve the text and split it up into RSS feed entries.
Reasons for Replacing Huginn
I don’t want to take anything away from Huginn. It’s an awesome open-source software and I love it. That said, its main downside for me is its hefty requirements to run it well. The 2GB recommended configuration is more expensive than I’d like.
Initially I used a $30/year OpenVZ VM that I found through LowEndTalk. It didn’t have enough resources to run Huginn well. I then paid for a $65/year OpenVZ VM that had 6GB RAM and that’s what I ended up using for Huginn for the past year. For comparison, a Droplet with 2GB RAM on DigitalOcean would cost $240/year. Even though DigitalOcean uses KVM, that’s just way too much for my taste.
In contrast Node-RED can run on a Raspberry Pi with less than 2GB RAM. I learned about Node-RED a little while ago from a Hacker News thread, and it’s been on my target ever since.
One other advantage for Node-RED is its better debuggability. I can hook up debug nodes to examine messages flowing through each part of the pipeline more easily.
The problem with Node-RED for my usage is that it’s mainly aimed at IoT applications. Huginn felt more tailored for my purpose of transforming and producing RSS feeds.
In the past year, I worked on implementing the missing pieces needed for Node-RED to service my needs.
The most critical deficiency of Node-RED is the inability to produce RSS feeds. Node-RED comes with the feedparser node that can consume RSS feeds, but there isn’t anything to produce a RSS feed. I wrote node-red-contrib-rss in order to rectify this gap. You can install it with
npm install node-red-contrib-rss in your
Below are the nodes I use to produce the Asuswrt changelog RSS feed:
|The timestamp node periodically kicks off a HTTP request to fetch the changelog. The pre and parse nodes then transforms the data into individual entries. Finally the node-red-contrib-rss node produces the RSS feed and then the file node saves to disk.|
The node-red-contrib-rss configuration looks like the screenshot below:
|You basically configure the metadata for the RSS feed, and define how properties of the incoming messages in the pipeline maps to RSS entries. The node expects the incoming msg.payload to be an array of objects.|
The built-in node used for filtering messages in the pipeline is rather primitive. I wanted the ability to deal with incoming message payload being an Array, but the built-in Switch node can’t do that. The node-red-contrib-filter was created for this need. I also added the ability to direct messages to an arbitrary number of outputs. My filter node is powerful and does everything the built-in one can do plus more.
Below is the configuration for filtering Twitter messages:
|This flow periodically retrieves a Twitter feed, then uses the filtering node to dump stuff I don’t care about, and finally produce the resulting RSS feed.|
The configuration for the filter node:
|Showing an example of filtering out DeviantArt’s membership nag. I don’t need to see that on Twitter. I already pay for points or pay for art on a need-to basis, and I don’t browse DeviantArt enough to care about the Core Membership perks.|
Node-RED on Raspberry Pi 3
Node-RED comes bundled with Raspberry Pi, and I’ve always liked the idea of having a Raspberry Pi at home to do whatever I want it to do. I bought a RPi 3 from MCM Electronics for $35 + tax + $7.99 shipping.
I’m currently using only 170MB of RAM on the RPi, so you can see that Node-RED’s requirements isn’t high at all. I could have used the $30/year cheapo VM with Node-RED too, but the RPi setup is roughly the same cost and will save money as the time goes on. It also has the advantage of sitting in a trusted environment (my home) rather than some OpenVZ VM by some random host company. Should I decide to store more sensitive data in the future, the RPi setup is much better.