Uso de Flows en Kotlin para Controlar Intervalos de Tiempo y Emisión de Datos

In localization projects, proper timing control is key to optimize emissions and throughput. Kotlin offers specific tools such as Flows, ideal to output data at regular intervals and control reactive processes efficiently. Here we explain how to implement a timer using these functionalities.

What is a Flow in Kotlin and what is it for?

A Flow in Kotlin is a way to handle reactive scheduling by emitting data streams. It allows to emit values at different intervals, process them with intermediate operators and perform actions with termination operators. Its main application is to execute time and frequency controlled tasks, such as emitting locations or times.

How to build a Flow that emits time intervals?

To create a timer using Flows, we must initially:

• Create a "Domain" folder containing a class called "Timer".
• Inside this class we define a function that emits custom time intervals using a FlowBuilder.

For example, in our timer we start an initial timestamp(lastEmitTime) using System.currentTimeMillis() and then open an infinite loop that:

• Captures the current time(currentTime).
• Calculates the interval by subtracting currentTime - lastEmitTime to generate an actual duration.
• Emits this interval every 200 milliseconds.
• It updates lastEmitTime with the current value to start a new accurate measurement.

This allows for precise handling, although small variations may occur due to internal execution in the system.

How to activate and control the Flow emission?

Activating a Flow requires specific termination operators:

• With LifecycleScope.launch, we activate the emission using the collect function, which allows to receive and process the emitted data.
• Another practical way is to use launchIn(LifecycleScope) combined with the onEach operator, which makes it easy to perform specific actions for each intermediate broadcast before terminating them.

Both operators act as final triggers of Flows; without these operators the data broadcast will not start, setting up a cold Flow.

How to combine different Flows effectively?

It is possible and easy to combine multiple Flows emissions using specific operators such as zip or combine to merge different information:

• For example, combining the emission of time intervals with random values. You use:
• zip: will emit a combine each time both Flows have new data available.
• Operators such as scan can accumulate or operationally transform the streams.

The result is an organized and synchronized flow, useful for complex scenarios such as data visualization in controlled periods.

By implementing these steps correctly, you can significantly optimize the reactive management of your Android application, improving accuracy in time-critical tasks and continuous data streaming.

Do you have questions about implementing Flows in Kotlin? Leave us your question in the comments, we will be happy to help you.