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How to control the value of a Datapoint using t6 ?

This recipe will help you to figure out how the transformation preprocessor should be implemented and how you can use it.

How to control the value of a Datapoint using t6 ?

In this recipe, our target will be to have a Flow to collect measurement on a sanitized format using a sensor that does not format the float correctly.

Check prerequisites

t6 require a Flow to store specific measurements. To use this recipe you’d first need to create a Flow like the following example. Feel free to review the technical documentation for details

{
    "name": "My Flow that contains only floats normalized values",
    "data_type": "e7dbdc23-5fa8-4083-b3ec-bb99c08a2a35",
    "require_signed": false,
    "require_encrypted": false,
    "retention": "retention1w",
    "preprocessor": [
        {
            "name": "transform",
            "mode": "replace",
            "pattern": "(,)",
            "replacer": "."
        },
        {
            "name": "sanitize",
            "datatype": "float"
        }
    ]
}

Basically, this Flow is setting the datatype as a Float, and 2 preprocessors will fire before saving datapoint to the Flow:

Once your Flow created (that will contains your measurements), take note of the flow.data.id on the Api results. This value will be used on datapoints creation as the referring variable {{$flow_id}}.

Create datapoints

Here we are going to post datapoints as string with a non-normalized value (we’ll use a coma instead of a dot for decimals).

{
    "value": "100,456798",
    "flow_id": "{{$flow_id}}",
    "save": true,
    "publish": true
}

And voilà, you’ll notice the Api results will transform the initial value into a Float using a correct Float value. The preprocessor array in the result shows all the values along the preprocessor computation. There is a double sanitization to Float as the latest one is forced by t6 on any datapoint posted ; we would have removed the sanitize preprocessor on the Flow creation above with exactly the same result.

"value": 100.456798,
"preprocessor": [
    {
        "name": "transform",
        "mode": "replace",
        "pattern": "(,)",
        "replacer": ".",
        "initialValue": "100,456798",
        "transformedValue": "100.456798",
        "message": "Transformed to replace.",
        "status": "completed"
    },
    {
        "name": "sanitize",
        "datatype": "float",
        "initialValue": "100.456798",
        "message": "Converted to float.",
        "status": "completed"
    },
    {
        "name": "sanitize",
        "datatype": "float",
        "initialValue": "100.456798",
        "message": "Converted to float.",
        "status": "completed"
    }
],

To have more details on Datapoints, read the technical documentation.

Tagged on #recipe, #flow, #preprocessor,