5 min readJul 5, 2023
Refactoring Node-RED flows: Duplicate computation
Node-RED is flow-based visual programming, which requires a new way of thinking when it comes to refactoring and programming generally.
This article is canonically hosted at blog.openmindmap.org and is better viewed there as code-blocks are replaced by flow images.
Node-RED models data flows between computational nodes. The lines represent the flow of data and the large colourful rectangles are the computational components, i.e., nodes.
Import to note, data flows from left to right: the left side of a node is the input side and the right side is the output node. I have indicated this by using arrows on the input side, the Node-RED editor does not have arrows so these are only here for presentational purposes.
Data may be altered by the nodes and all alterations are passed down the flow. A node may only have zero or one input but many outputs. Each output, i.e. line out of a node, is a duplication of the data object returned by the node.
This means that each node has its own copy of the data. Which implies that data objects should not be excessive in size since duplication, i.e. cloning, costs time and memory.
Note: I use Node-RED version 3.0.2 for this, your mileage might vary.
Computational Duplication
I am going to deal with something that has often happened to me: copy & pasting of nodes leads to duplication of computational code, i.e. nodes.
How to deal with deal with duplication? Visual programming also aims to apply the Don’t Repeat Yourself — DRY principle, but how to handle that in a visual manner?
Starting with this flow:
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How to handle the duplication?
An initial idea would be to do something like this:
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Node-RED does not allow us to specify which output flow to take: all output is passed to all connected nodes.
Here the problem becomes how to select the correct purple node after doing the common computation?
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One solution could be to set a flag somewhere further up the flow and then have a switch node make divert the flow according to that flag:
(Note: setting a flag in Node-RED terms means adding an attribute to the data object passing allow the flow. This modified data object arrives at the switch node.)
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A switch as one output connector per if-clause. So if we had a third value for the flag, then our switch would have three output connectors. Something like this pseudo code:
if flag == 1 then output-connector-1
if flag == 2 then output-connector-2
else output-connector-3Then the switch would like this:
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Commonality comes first
An alternative approach is sometimes to perform commonality before the specifics:
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The flag for the switch (lots of hand-waving here) is set somewhere up further the flow!
Subflows
This approach to duplication is fine if there is only one area of duplication but what if we had two different and disconnected flows that use the same code?
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Enter Subflows! Subflows are a concept within Node-RED for bundling together nodes into a mini-flow, i.e., a subflow.
Subflows can be created by highlighting the common nodes and going to the Node-RED menu and selecting Subflows --> Selection to Subflow.
The subflow then becomes:
In the subflow editor, one can specify the number of outputs (one in this case) and whether the subflow has zero or one input (also one in this case).
Our flows become this:
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Subflows with multiple outputs
Subflows can have multiple output connectors (not to be confused with connections) and if we look at the top flow, we have the switch node:
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Our subflow becomes this:
And our flows become this:
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And here in lies the disadvantage of having Subflows sharing change. The challenge of finding the balance between code commonality remains, even with a visual programming environment.
More approaches?
I am sure there more approaches (including creating nodes), if you have any ideas please send me an email.
