Building Interactive Trading Charts in Jetpack Compose
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:
LineChartNumbers
measures and exposes each Y-offset usingonGloballyPositioned
.- These offsets are passed back to the main composable via a callback (
onOffsetsCalculated
). 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 renderingDashedLines
: Connects chart to target markersLineChartNumbers
: Renders circle markersChartCrosshair
: 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.
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