rio-tiler
User friendly Rasterio plugin to read raster datasets.
Decision gist · record as of 2026-08-14
Yes. rio-tiler is actively maintained, has low install friction, carries no known vulnerabilities, and solves a concrete problem in geospatial workflows. Install it if you need to read raster data (especially tiles or remote sources) without wrestling with raw Rasterio/GDAL APIs. The BSD license is permissive. Only caveat: Rasterio itself requires system GDAL libraries, which may add setup complexity in some environments.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires rasterio and GDAL to be installed; rasterio typically requires system libraries (libgdal, libproj).
- Low friction: pure-Python wheel, 11 runtime dependencies including well-maintained geospatial libraries (rasterio, numpy, pydantic, morecantile).
- Active maintenance with a release 25 days ago.
License · maintenance · safety
permissive license (permissive) — BSD 3-Clause permissive license allows commercial and private use with minimal restrictions; redistribution requires license and copyright notice.
last release 2026-07-20 (25 days) · last repo commit 2026-08-12 · 591 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 361,387 downloads/mo, #7,238 on PyPI
Alternatives
Verify before relying
from rio_tiler.io import Reader
with Reader("my.tif") as image:
img = image.tile(x, y, z) # read mercator tile
img = image.part(bbox) # read bounding box
pt = image.point(lon, lat) # read pixel value- Whether XarrayReader optional dependency installation (pip install rio-tiler["xarray"]) is documented clearly in package metadata.
- Performance characteristics when reading large remote datasets or many tiles in sequence.
What it is and what it does
rio-tiler is a Python wrapper around Rasterio and GDAL that simplifies reading raster data from diverse sources—local GeoTIFFs, remote HTTP URLs, S3 buckets, and cloud storage. It was originally built to generate slippy-map tiles dynamically from large raster sources, but has evolved to offer general-purpose raster I/O with user-friendly methods for tile extraction, bounding-box queries, point sampling, and feature-based reads.
The package abstracts away low-level Rasterio complexity, returning data as rio-tiler ImageData objects. It supports STAC item reading (merging bands across multiple assets), Xarray datasets, non-georeferenced images, mosaic operations, and multiple tile-matrix sets via morecantile. Runtime dependencies include numpy, pydantic, cachetools, and geospatial libraries; it requires Python 3.11 or later.
Use it for
- Extract Web Mercator tiles from Cloud Optimized GeoTIFFs for dynamic web-map rendering.
- Read pixel values or spatial subsets from remote raster sources without downloading entire files.
- Merge and resample bands from multiple STAC assets into a single composite image.
- Sample raster values at specific geographic coordinates (lon/lat points).
- Build tile servers or mosaic services that combine multiple raster sources on-the-fly.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
rio-tiler is actively maintained, has low install friction, carries no known vulnerabilities, and solves a concrete problem in geospatial workflows. Install it if you need to read raster data (especially tiles or remote sources) without wrestling with raw Rasterio/GDAL APIs. The BSD license is permissive. Only caveat: Rasterio itself requires system GDAL libraries, which may add setup complexity in some environments.
Install
rio-tiler on PyPI
Before you install
Low friction: pure-Python wheel, 11 runtime dependencies including well-maintained geospatial libraries (rasterio, numpy, pydantic, morecantile). Active maintenance with a release 25 days ago.
Requires rasterio and GDAL to be installed; rasterio typically requires system libraries (libgdal, libproj).
License in practice
BSD 3-Clause permissive license allows commercial and private use with minimal restrictions; redistribution requires license and copyright notice.
Quickstart
from rio_tiler.io import Reader
with Reader("my.tif") as image:
img = image.tile(x, y, z) # read mercator tile
img = image.part(bbox) # read bounding box
pt = image.point(lon, lat) # read pixel valueVerify before relying
- Whether XarrayReader optional dependency installation (pip install rio-tiler["xarray"]) is documented clearly in package metadata.
- Performance characteristics when reading large remote datasets or many tiles in sequence.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 11 packagesattrscachetoolscolor-operationshttpx2morecantilenumexprnumpypydanticpystacrasteriotyping-extensions |
| Maintenance | Actively maintained 25 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 361,387 / month, #7,238 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 :: BSD LicenseProgramming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/Engineering :: GIS |
Evidence: rio_tiler-9.4.2-py3-none-any.whl
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See also async-tiff · pmtiles · rasterio · rio-cogeo · titiler-application · supermorecado · xarray-spatial · titiler-mosaic · rioxarray · titiler-core