titiler-application
A modern dynamic tile server built on top of FastAPI and Rasterio/GDAL.
Decision gist · record as of 2026-08-14
Yes, if you need a ready-to-run tile server for raster geospatial data. The package is actively maintained, has no known vulnerabilities, and low install friction. It is most valuable as a demo or starting point rather than a production service—for production use, you would typically customize it by extending titiler's modular components. The MIT license poses no restrictions.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.11 or later; a web server is needed to run the FastAPI application.
- Low friction: ships as a wheel and depends on six titiler packages that form a cohesive ecosystem.
- Maintenance is active with a recent release 16 days old and steady repository activity.
License · maintenance · safety
MIT (permissive) — MIT license is permissive and imposes no restrictions on use, modification, or redistribution in commercial or private projects.
last release 2026-07-29 (16 days) · last repo commit 2026-08-11 · 1,145 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 81,905 downloads/mo, #14,192 on PyPI
Alternatives
Verify before relying
pip install titiler.application
python -m titiler.application.main- Whether the demo application includes example data or requires external raster sources to be configured.
- Performance characteristics and scalability limits for concurrent tile requests.
- Specific GDAL/Rasterio system dependencies and their installation requirements.
What it is and what it does
titiler.application is a demonstration FastAPI web service that serves raster geospatial data as map tiles. It builds on titiler-core, titiler-extensions, titiler-mosaic, and titiler-xarray to provide a complete, runnable tile server with support for Cloud Optimized GeoTIFFs, MosaicJSON mosaics, STAC catalogs, and xarray-backed datasets. The application includes a landing page, configurable caching and CORS settings, and exposes OGC-compliant tile endpoints.
The package is intended as both a reference implementation and a starting point for custom tile-serving applications. It demonstrates how to compose titiler's modular components into a working service and can be launched immediately after installation. It targets geospatial professionals, data engineers, and researchers who need to publish raster data as web-accessible tiles.
Use it for
- Launch a tile server for Cloud Optimized GeoTIFFs without writing custom FastAPI code.
- Serve STAC collections and MosaicJSON mosaics as interactive map tiles.
- Prototype or demo a geospatial tile API before building a production service.
- Integrate xarray-backed climate or scientific data into a web mapping application.
- Explore titiler's capabilities and architecture through a working reference application.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need a ready-to-run tile server for raster geospatial data.
The package is actively maintained, has no known vulnerabilities, and low install friction. It is most valuable as a demo or starting point rather than a production service—for production use, you would typically customize it by extending titiler's modular components. The MIT license poses no restrictions.
Install
titiler-application on PyPI
Before you install
Low friction: ships as a wheel and depends on six titiler packages that form a cohesive ecosystem. Maintenance is active with a recent release 16 days old and steady repository activity. Requires Python 3.11 or later.
Requires Python 3.11 or later; a web server is needed to run the FastAPI application.
License in practice
MIT license is permissive and imposes no restrictions on use, modification, or redistribution in commercial or private projects.
Quickstart
pip install titiler.application
python -m titiler.application.main
Verify before relying
- Whether the demo application includes example data or requires external raster sources to be configured.
- Performance characteristics and scalability limits for concurrent tile requests.
- Specific GDAL/Rasterio system dependencies and their installation requirements.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 6 packagespydantic-settingsstarlette-cramjamtitiler-coretitiler-extensionstitiler-mosaictitiler-xarray |
| Maintenance | Actively maintained 16 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 81,905 / month, #14,192 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: Information TechnologyIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/Engineering :: GIS |
Evidence: titiler_application-2.2.1-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “cog fastapi application”
- titiler-applicationProvides a ready-to-run FastAPI application for serving Cloud…
- titiler-coreProvides FastAPI-based building blocks to create dynamic tile servers…
- titiler-extensionsProvides pluggable extension classes for TiTiler's TilerFactory to…
Give your agent the search over MCP, or paste the wish link into any chat.
More GIS packages
Shapely provides Python tools for creating, manipulating, and analyzing 2D geometric objects (points, lines, polygons) using the GEOS library, with both scalar and vectorized NumPy-based operations.
pyproj provides a Python interface to PROJ, enabling cartographic projections and coordinate system transformations for geospatial applications.
GeoPandas extends pandas DataFrames to handle geographic data, combining pandas operations with shapely geometry and spatial analysis capabilities that would otherwise require a spatial database.
Install it if you work with geographic data in Python and want to avoid setting up a spatial database or learning a separate GIS tool.
geopy is a Python client for geocoding and distance calculation that converts addresses to coordinates and vice versa using multiple web-based geocoding services, and computes geodesic and great-circle distances between geographic points.
Install it if you need geocoding or distance calculations in your application.
Pyogrio provides fast, bulk-oriented read and write access to vector spatial data formats (Shapefile, GeoPackage, GeoJSON, etc.) via GDAL/OGR bindings, typically for use with GeoPandas GeoDataFrames.
h3 provides Python bindings to Uber's H3 geospatial indexing library, converting geographic coordinates into hierarchical hexagonal grid cells and performing spatial operations on them.
See also titiler-core · titiler-mosaic · titiler-extensions · cogeo-mosaic · rio-tiler · async-tiff · rio-cogeo · pmtiles · large-image · xyzservices