Run Python scripts directly inside ATAK on your Android device. AutoPie brings the full power of the Python ecosystem — NumPy, Pandas, Rasterio, OpenCV — to the tactical edge, enabling custom automations, geospatial processing pipelines, and AI workflows without cloud dependency.
AutoPie integrates Chaquopy — the Python SDK for Android — directly into the Tactical AI DuckDB plugin. This brings the world's most widely used geospatial scripting language to your Android device, enabling operators, analysts, and integrators to write and execute custom Python scripts that interact with the full plugin stack: DuckDB, GeoPackage, MapLibre, ATAK markers, and hardware sensors.
Python is the lingua franca of geospatial analysis, AI/ML pipelines, and data science. Libraries like GeoPandas, Shapely, Rasterio, and NumPy provide capabilities that no pre-built plugin could fully anticipate. AutoPie turns the analyst's laptop workflow into a field-deployable capability on an Android device.
Built on Chaquopy, AutoPie runs a full Python 3.10+ interpreter natively on Android. The integration is deep — Python code can call Java APIs, access the Android filesystem, and interact with Tactical AI DuckDB's internal services through the AutoPie bridge layer.
AutoPie ships with a curated set of geospatial and scientific Python packages pre-compiled for Android ARM64:
| Library | Category | Tactical Use Case |
|---|---|---|
| NumPy | Numerical Computing | Array operations, coordinate transformations |
| Pandas | Data Analysis | Tabular data processing, CSV/Excel ingestion |
| Rasterio | Raster Processing | GeoTIFF reading, orthomosaic tiling, DEM analysis |
| OpenCV (cv2) | Computer Vision | Image processing, feature detection, drone imagery analysis |
| Shapely | Geometry | Spatial operations, buffer zones, polygon clipping |
| PyProj | Projections | Coordinate system transformations, MGRS/UTM conversion |
| DuckDB (Python API) | Database | Direct SQL queries against the embedded spatial database |
| Requests | HTTP Client | REST API calls, data fetching when connected |
| GeoPandas | Geospatial DataFrames | Feature processing, spatial joins, format conversions |
The AutoPie bridge exposes Tactical AI DuckDB's core services to Python scripts. This allows custom scripts to read and write map state, create markers, execute spatial queries, access hardware sensors, and trigger plugin actions — all from Python code.
AutoPie includes a built-in syntax-highlighted script editor optimized for touchscreen use. Write, edit, and execute scripts directly in ATAK without connecting to a development workstation.
| Editor Feature | Description |
|---|---|
| Syntax Highlighting | Python-aware coloring for keywords, strings, functions |
| Line Numbers | Visible line numbers for debugging |
| Auto-Indent | Automatic indentation for Python blocks |
| Script Library | Save and organize scripts by category |
| Execution Log | Real-time stdout/stderr output during script execution |
| Error Highlighting | Jump to line on syntax or runtime error |
Beyond interactive execution, AutoPie supports scheduled and event-triggered script execution — enabling automated geospatial processing pipelines that run without operator intervention.
When a new GeoTIFF orthomosaic is saved to the device (triggered by DJI or similar UAS), AutoPie automatically: tiles the raster using Rasterio, writes the tiles to GeoPackage, queries DuckDB for building footprints in the area, clips each footprint from the imagery, and loads the results into the Damage Assessment module for AI analysis — all without touching the screen.
A custom script reads all markers placed in the last 30 minutes, groups them by type (enemy, friendly, unknown), runs spatial analysis to calculate distances and bearings, and generates a formatted SALUTE report as a CoT message sent to the team — triggered on a configurable timer or by voice command via the AI Agent.
One of the most powerful AutoPie use cases is on-device LiDAR processing. Using Python bindings for the PDAL-compatible pipeline, raw LiDAR point clouds (.las, .laz) can be processed into DTED elevation data directly on Android:
| Processing Stage | Python Library | Output |
|---|---|---|
| Point Cloud Load | NumPy + custom reader | Structured array of XYZ + intensity |
| Ground Classification | SciPy spatial | Ground vs. non-ground points |
| DEM Interpolation | NumPy griddata | Regular elevation grid |
| DTED Encoding | Custom DT2/DT3 writer | DTED Level 2/3 files |
| ATAK Import | autopie.files | Terrain layer in ATAK |
AutoPie implements a permissions model for script execution in sensitive environments. Scripts must be explicitly approved before execution, and dangerous operations (network access, file deletion) require additional confirmation.