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@@ -11,14 +11,14 @@ In this tutorial we're going to introduce an **event-driven model**, where data
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Here's the model that we're going to build. Given a stream of random numbers, we'll trigger `HighEvent` whenever the value is above `0.8` and `LowEvent` whenever the value is below `0.2`. This allows us to funnel data into different parts of the model: in this case we'll just save the latest high/low values to a file at each step. In the diagram the _dotted lines_ represent the flow of event data: `FindHighLowValues` will publish events, while `CollectHigh` and `CollectLow` will subscribe to receive high and low events respectively.
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