Array Filter
What It Does
Creates a sub-graph that evaluates each item in an array, returning a new array containing only the items where your condition evaluates to true. You define the filtering condition in the inner graph using a custom combination of nodes.
Inputs
array
The array to filter
List
Yes
Dynamic inputs
Any inputs you add to the inner graph will appear here
Varies
No
Outputs
value
A new array containing only the items that match your condition
List
Inner Graph Special Inputs
value
The current array item being evaluated
Any
index
The current position in the array
Number
length
The total length of the array
Number
Inner Graph Required Output
matches
Whether the current item should be included in the result
Yes/No

How to Use It
Drag the Array Filter node into your graph.
Connect your array to the "array" input. In this example the input is a Harmonic series outputting an array [16, 18, 21. 24, 28, 32].
Click on the Subgraph Explorer button on the Array filer node to open and edit the inner graph.
In the inner graph, build your condition using the special "value" input. In this case a simple Compare node to check if the value is < 32. The output is a boolean.
Connect your condition's result to the "matches" input on the Output node. The "matches" accepts a boolean.
Return to the main graph, where you can use the filtered array output. The output is an array of two values [16, 18] which is matching the condition in the subgraph.


Tips
The inner graph runs once for each item in the array.
You can add your own inputs to the inner graph's Input node, which will appear as inputs on the main Array Filter node.
For complex filtering, you can build any logic you need in the inner graph.
If no items match your condition, the output will be an empty array.
See Also
Array Find: Similar to Array Filter, but returns only the first matching item instead of all matching items.
Find First Match: For simple comparison-based searching (greater than, less than).
Linear Search: For exact-match searching of a single item.
Use Cases
Data Filtering: Remove unwanted items from datasets based on custom criteria.
Collection Refinement: Keep only items that meet specific business rules or thresholds.
Conditional Processing: Process only the subset of items that require attention.
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