# How to Integrate GeoLibre with Other Geospatial Tools: A Complete Developer Guide > Integrate GeoLibre with other geospatial tools using its plugin architecture for seamless data consumption, processing, and embeddable components. Unlock powerful interoperability. - Repository: [Open Geospatial Solutions/GeoLibre](https://github.com/opengeos/GeoLibre) - Tags: how-to-guide - Published: 2026-08-16 --- **GeoLibre integrates with external geospatial tools through a store-driven, plugin-centric architecture that supports data consumption, processing APIs, and embeddable components for seamless interoperability.** GeoLibre (opengeos/GeoLibre) is designed from the ground up to bridge the gap between desktop GIS workflows and modern web-based geospatial stacks. Whether you need to pull data from cloud platforms, embed maps in external dashboards, or offload heavy processing to Python tools, its modular architecture provides clear integration points. This guide covers the core mechanisms for connecting GeoLibre with Jupyter notebooks, GIS servers, cloud data platforms, and custom web applications. --- ## Data Source Plugins: The Primary Integration Layer GeoLibre loads geospatial data through **built-in plugins** that wrap common APIs and services. Registration happens in [`apps/geolibre-desktop/src/hooks/usePlugins.ts`](https://github.com/opengeos/GeoLibre/blob/main/apps/geolibre-desktop/src/hooks/usePlugins.ts), with individual plugin implementations under `packages/plugins/src/plugins/`. ### Supported Data Sources | Source | Plugin Location | Authentication | |--------|-----------------|----------------| | **Planetary Computer** | [`packages/plugins/src/plugins/planetary-computer.ts`](https://github.com/opengeos/GeoLibre/blob/main/packages/plugins/src/plugins/planetary-computer.ts) | OAuth 2.0 | | **Google Earth Engine** | [`packages/plugins/src/plugins/earth-engine.ts`](https://github.com/opengeos/GeoLibre/blob/main/packages/plugins/src/plugins/earth-engine.ts) | OAuth 2.0 | | **Overture Maps** | [`packages/plugins/src/plugins/overture.ts`](https://github.com/opengeos/GeoLibre/blob/main/packages/plugins/src/plugins/overture.ts) | None required | | **Generic Web Services** | [`packages/plugins/src/plugins/wms.ts`](https://github.com/opengeos/GeoLibre/blob/main/packages/plugins/src/plugins/wms.ts), [`packages/plugins/src/plugins/wmts.ts`](https://github.com/opengeos/GeoLibre/blob/main/packages/plugins/src/plugins/wmts.ts) | Token-based | Each plugin conforms to a standard interface defined in the core store (`@geolibre/core`), enabling uniform layer management regardless of data origin. --- ## File and Remote Data Ingestion ### Browser-Side Parsing with DuckDB-WASM Local files (Shapefile, GeoJSON, GeoParquet, FlatGeobuf) are parsed directly in the browser using **DuckDB-WASM** via the `ST_Read` spatial extension. The fallback to **shpjs** handles legacy Shapefiles when needed. ### Remote File Handling Remote files pass through [`packages/plugins/src/plugins/remote-file-formats.ts`](https://github.com/opengeos/GeoLibre/blob/main/packages/plugins/src/plugins/remote-file-formats.ts), which enforces a **size limit** (`MAX_REMOTE_FILE_BYTES`) to prevent memory exhaustion. ```tsx // Internal pattern for remote file registration // From: packages/plugins/src/plugins/remote-file-formats.ts const MAX_REMOTE_FILE_BYTES = 500 * 1024 * 1024; // 500 MB default export async function fetchRemoteLayer(url: string, options: RemoteOptions) { const head = await fetch(url, { method: 'HEAD' }); const size = parseInt(head.headers.get('content-length') || '0'); if (size > MAX_REMOTE_FILE_BYTES) { throw new Error(`Remote file exceeds size limit: ${size} bytes`); } // Stream to DuckDB-WASM or delegated download return loadToStore(url, options.format); } ``` --- ## Python FastAPI Side-Car for Heavy Processing CPU-intensive operations—WhiteboxTools geoprocessing, rasterio workflows, large vector operations—run in a **separate Python process** accessible via REST API. ### Architecture | Component | Path | Purpose | |-----------|------|---------| | Side-car server | `backend/geolibre_server/` | FastAPI application | | API definitions | [`backend/geolibre_server_api/README.md`](https://github.com/opengeos/GeoLibre/blob/main/backend/geolibre_server_api/README.md) | OpenAPI specification | | Frontend proxy | `/sidecar/*` routes | CORS-handled bridge | ### Endpoints - `POST /sidecar/vector/upload` — Ingest vector files for processing - `POST /sidecar/raster/upload` — Ingest raster files - `POST /sidecar/whitebox/run` — Execute WhiteboxTools algorithms - `GET /sidecar/layers/{id}/export` — Retrieve processed results ### Jupyter Notebook Integration ```python # Using the side-car from a Jupyter notebook import requests import json # Upload a raster to the side-car for processing files = {'file': open('elevation.tif', 'rb')} resp = requests.post( 'http://localhost:8765/sidecar/raster/upload', files=files ) layer_id = resp.json()['layerId'] # Run a Whitebox hillshade tool via the side-car payload = { "layerId": layer_id, "tool": "hillshade", "azimuth": 315, "altitude": 45 } resp = requests.post( 'http://localhost:8765/sidecar/whitebox/run', json=payload ) result = resp.json() print("Hillshade saved to:", result['outputPath']) ``` The side-car enables **bidirectional workflow**: Python tools can push data into GeoLibre for visualization, and GeoLibre can trigger processing pipelines that return results to Python environments. --- ## SQL Workspace for Query Interoperability The **SQL workspace** ([`docs/user-guide/sql-workspace.md`](https://github.com/opengeos/GeoLibre/blob/main/docs/user-guide/sql-workspace.md)) exposes loaded layers through **SQLite/Spatialite-compatible syntax**, making GeoLibre interoperable with any tool that understands SQL-based geospatial queries. ```sql -- Example: Querying layers from the SQL workspace SELECT name, ST_Area(geometry) as area_sqm, population / ST_Area(geometry) * 1000000 as density FROM cities_layer WHERE ST_Within(geometry, ST_GeomFromText('POLYGON((...))')) AND population > 100000; ``` The workspace communicates with the central store in `@geolibre/core`, ensuring query results reflect live layer state and trigger appropriate UI updates. --- ## Embedding GeoLibre in External Applications The `@geolibre/embed` package provides a **drop-in iframe component** for web integration. ### React Component Usage ```tsx // Embedding GeoLibre in a React application // Install: npm install @geolibre/embed import { GeoLibreEmbed } from '@geolibre/embed'; function DashboardMap() { return ( console.log('Selected:', layer.id)} /> ); } ``` ### Plain HTML Usage ```html
``` The embedded map maintains **two-way synchronization**: host page events can trigger layer changes, and map interactions can broadcast selection events to the parent window. --- ## Import and Export Formats GeoLibre supports standard exchange formats for tool-to-tool data flow: | Format | Export Location | Use Case | |--------|---------------|----------| | **GeoPackage** | [`packages/processing/src/wasm-convert.ts`](https://github.com/opengeos/GeoLibre/blob/main/packages/processing/src/wasm-convert.ts) | QGIS, ArcGIS interoperability | | **PMTiles** | [`packages/processing/src/wasm-convert.ts`](https://github.com/opengeos/GeoLibre/blob/main/packages/processing/src/wasm-convert.ts) | Web-optimized visualization | | **GeoJSON** | [`packages/processing/src/wasm-convert.ts`](https://github.com/opengeos/GeoLibre/blob/main/packages/processing/src/wasm-convert.ts) | Universal exchange, web APIs | | **FlatGeobuf** | [`packages/processing/src/wasm-convert.ts`](https://github.com/opengeos/GeoLibre/blob/main/packages/processing/src/wasm-convert.ts) | Streaming large datasets | UI handling resides in [`apps/geolibre-desktop/src/lib/whitebox-distance-params.ts`](https://github.com/opengeos/GeoLibre/blob/main/apps/geolibre-desktop/src/lib/whitebox-distance-params.ts) for export parameter configuration. --- ## Custom Plugin Development External developers can extend GeoLibre without modifying core code. Plugins are distributed as **ZIP archives** containing: ``` my-plugin.zip ├── plugin.json # Manifest with metadata, entry point ├── index.js # Main plugin code └── assets/ # Icons, stylesheets ``` The [`plugin.json`](https://github.com/opengeos/GeoLibre/blob/main/plugin.json) schema is documented in [`docs/plugin-api.md`](https://github.com/opengeos/GeoLibre/blob/main/docs/plugin-api.md). Plugins register data sources, processing steps, or UI panels through the same APIs used by built-in providers. --- ## Common Integration Scenarios ### Scenario 1: Jupyter ↔ GeoLibre Round-Trip 1. Launch GeoLibre with side-car enabled (`docker compose up backend`) 2. From notebook: upload raster via `/sidecar/raster/upload` 3. Trigger Whitebox processing, retrieve result path 4. Load result back into notebook with `rasterio` 5. Push new analysis output to GeoLibre for visualization ### Scenario 2: Live Dashboard with Embedded Map 1. Deploy `@geolibre/embed` in React/Vue/Svelte dashboard 2. Configure `configUrl` pointing to dynamic JSON endpoint 3. Dashboard updates JSON; embedded map auto-refreshes layers 4. Map selections trigger dashboard detail panel updates via `onLayerSelect` callback ### Scenario 3: Custom Data Feed Integration ```bash # Add a remote GeoJSON source via CLI npx geolibre add-layer \ --type remote-geojson \ --url "https://services.example.com/api/live-tracks.geojson" \ --name "Live Vehicle Tracks" \ --refresh-interval 30 ``` --- ## Summary - **Plugin architecture** ([`usePlugins.ts`](https://github.com/opengeos/GeoLibre/blob/main/usePlugins.ts)) enables cloud platform integration without core changes - **DuckDB-WASM and remote-file-formats.ts** handle diverse file formats browser-side - **FastAPI side-car** (`backend/geolibre_server`) bridges to Python geoprocessing stacks - **SQL workspace** provides standards-based query interoperability - **`@geolibre/embed`** package allows map embedding in any web application - **Standard export formats** (GeoPackage, PMTiles, GeoJSON) ensure tool compatibility - **Plugin API** ([`docs/plugin-api.md`](https://github.com/opengeos/GeoLibre/blob/main/docs/plugin-api.md)) supports third-party extensions via ZIP manifests --- ## Frequently Asked Questions ### How do I connect GeoLibre to Google Earth Engine? Enable the Earth Engine plugin in the data sources panel, complete OAuth authentication, and browse the catalog directly. The plugin implementation in [`packages/plugins/src/plugins/earth-engine.ts`](https://github.com/opengeos/GeoLibre/blob/main/packages/plugins/src/plugins/earth-engine.ts) handles token refresh and image collection conversion to GeoLibre layers. ### Can I use GeoLibre processing from Python without the desktop app? Yes. Run the FastAPI side-car independently (`cd backend/geolibre_server && uvicorn main:app`), then interact with endpoints at `http://localhost:8765/sidecar/`. The full API specification is in [`backend/geolibre_server_api/README.md`](https://github.com/opengeos/GeoLibre/blob/main/backend/geolibre_server_api/README.md). ### What is the maximum file size for remote data sources? The default limit is **500 MB** (`MAX_REMOTE_FILE_BYTES` in [`remote-file-formats.ts`](https://github.com/opengeos/GeoLibre/blob/main/remote-file-formats.ts)). This prevents browser memory issues with DuckDB-WASM. For larger datasets, use the side-car upload endpoint which streams to disk. ### How do I create a custom plugin for my organization's internal data API? Create a ZIP with a [`plugin.json`](https://github.com/opengeos/GeoLibre/blob/main/plugin.json) manifest pointing to your JavaScript entry file. Implement the standard plugin interface to register a data source that fetches from your API. See [`docs/plugin-api.md`](https://github.com/opengeos/GeoLibre/blob/main/docs/plugin-api.md) for the full specification and example implementations in `packages/plugins/src/plugins/`.