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Building Interactive Trading Charts in Jetpack Compose

4 min readMay 16, 2025

In today’s fintech apps, professional-grade charts are not just nice-to-have — they’re expected. Whether it’s for stock markets, crypto, or forex, users want real-time, interactive, and insightful visuals. And with Jetpack Compose, we finally have the flexibility to build them from scratch, without relying on bulky third-party libraries.

In this article, I’ll walk you through how I built interactive trading charts using Jetpack Compose, featuring:

✅ Smooth area/line chart
✅ Live + historical data updates
✅ Target price markers (highest, median, lowest)
✅ Crosshair on touch
✅ Drag-to-pan
✅ Pinch-to-zoom
✅ Clean Architecture for modularity and scalability

Let’s dive in!

🚀 Why Jetpack Compose for Charts?

Jetpack Compose is Android’s modern UI toolkit. Unlike XML-based layouts, it provides direct control over drawing and gestures — exactly what we need for financial charting. Combine that with state management, animations, and custom canvases, and you get a responsive, powerful charting foundation.

🧱 The Architecture (Clean FTW)

I built the chart using Clean Architecture, with 3 layers:

  • UI Layer (Jetpack Compose)
    Handles rendering, gestures, and UI interactions.
  • Domain Layer
    Contains business logic (e.g., transforming raw data into chart points).
  • Data Layer
    Deals with fetching historical + live data (e.g., REST APIs or WebSockets).

This structure makes the code easier to test, scale, and debug.

📊 Drawing the Chart — AreaChartDynamic

Using Canvas, I drew a dynamic line/area chart. Here’s the basic structure:

Canvas(modifier = Modifier.fillMaxSize()) {
drawLine(
color = Color.Blue,
start = Offset(startX, startY),
end = Offset(endX, endY),
strokeWidth = 4f
)
}

All X coordinates are adjusted for zoom/drag (more on that below).

🎯 Target Price Indicators

To help users visualize forecasted price points, I added:

  • Highest target (green)
  • Median target (yellow)
  • Lowest target (red)

Each is drawn as a colored circle using BoxWithCircle, and positioned next to the chart.

I also connected them with dashed lines from the end of the chart:

drawIntoCanvas { canvas ->
val paint = Paint().asFrameworkPaint().apply {
color = Color.Gray.toArgb()
strokeWidth = 2f
pathEffect = DashPathEffect(floatArrayOf(10f, 10f), 0f)
}
canvas.nativeCanvas.drawLine(startX, startY, endX, endY, paint)
}

The vertical alignment is ensured by passing Y-offsets through a lambda from LineChartNumbers.

🎯 Connecting Dashed Lines to Target Circles

Target prices are drawn in a separate column. To align the dashed lines correctly:

  1. LineChartNumbers measures and exposes each Y-offset using onGloballyPositioned.
  2. These offsets are passed back to the main composable via a callback (onOffsetsCalculated).
  3. DashedLines draws from the end point of the chart to each target price circle.

This approach maintains clean separation between the chart and the marker layout, while still achieving precise alignment.

👆 Crosshair Interaction

Using Jetpack Compose gestures, I implemented a crosshair that tracks touch position:

var crosshairX by remember { mutableStateOf<Float?>(null) }

pointerInput(Unit) {
detectDragGestures { change, _ ->
crosshairX = change.position.x
}
}

Then, I drew a vertical and horizontal guide line using drawLine inside the chart canvas.

This helps users track exact values while scrubbing across the chart.

🧭 Drag-to-Pan

Users can also drag to scroll horizontally across the chart history.

var chartOffsetX by remember { mutableStateOf(0f) }

pointerInput(Unit) {
detectDragGestures { _, dragAmount ->
chartOffsetX += dragAmount.x
}
}

Each data point’s X-coordinate is offset by chartOffsetX. I also clamp the value to avoid over-dragging.

🔍 Pinch-to-Zoom

For zooming in/out, I used calculateZoom() inside a pointerInput gesture block:

var zoomLevel by remember { mutableStateOf(1f) }

pointerInput(Unit) {
forEachGesture {
awaitPointerEventScope {
val event = awaitPointerEvent()
if (event.changes.size >= 2) {
val zoomChange = event.calculateZoom()
zoomLevel = (zoomLevel * zoomChange).coerceIn(0.5f, 3f)
}
}
}
}

Each chart point’s X spacing is scaled with this factor:

val scaledX = (index * spacingX * zoomLevel) + chartOffsetX

This creates a native pinch-to-zoom experience without using any external libraries.

🔁 Live and Historical Data

I built the chart to support:

  • Live data via WebSocket or polling
  • Historical ranges (1D, 1W, 1M, 1Y, etc.)

Changing the selected timeframe re-fetches the data, and the chart automatically animates the new range.

🌈 Visual Polish

  • Used Path and gradients for filled area charts.
  • Circles for price markers are color-coded (Success/Warning/Error).
  • Added smooth animation using animateFloatAsState for transitions.
  • All visuals follow a soft, modern style with rounded edges and subtle shadows.

📦 Modular Components

Each piece is modular and reusable:

  • AreaChartDynamic: Main chart rendering
  • DashedLines: Connects chart to target markers
  • LineChartNumbers: Renders circle markers
  • ChartCrosshair: Handles gesture + crosshair drawing

This allows easy reuse across different chart screens or asset types.

✨ Final Thoughts

Building trading charts in Jetpack Compose is not only possible — it’s powerful.

With full control over:

  • Drawing
  • Gestures
  • State
  • Animation

…you can craft a fully custom charting experience rivaling major trading platforms.

And by sticking to Clean Architecture, everything stays testable and modular.

Whether you’re working on a stock tracker, crypto app, or personal finance dashboard, Compose gives you the power to bring charts to life — your way.

👋 Let’s Connect

💬 Got questions? Want code samples? Drop a comment below.
🔗 Follow for more Compose, Kotlin, and mobile app architecture content!

— — — — — — — — — Thank You — — — — — — — — — —

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Naveen Udesh
Naveen Udesh

Written by Naveen Udesh

Mobile Enthusiast - Android Developer #android #kotlin #flutter

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