rio-tiler

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

rio-tiler reads raster data from local and remote sources (HTTP, S3, Cloud Storage) via a Rasterio/GDAL wrapper, supporting tile extraction, bounding-box queries, STAC assets, and Xarray datasets.

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

pip install rio-tiler

uv add rio-tiler

poetry add rio-tiler

Installing rio-tiler

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.

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 value

Requires rasterio and GDAL to be installed; rasterio typically requires system libraries (libgdal, libproj).

Verify 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

Evidence: rio_tiler-9.4.2-py3-none-any.whl

Keywords: COGEO, Cloud Optimized Geotiff, STAC, rasterio, slippy-map

Tags

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