---
id: rio-tiler
version: "9.4.2"
license: BSD 3-Clause License Copyright (c) 2021, cogeotiff All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following… (full text in the JSON record)
license_treatment: permissive
maintenance: active
---

# rio-tiler — User friendly Rasterio plugin to read raster datasets.

License: permissive · Maintenance: active · Downloads: 361.4K/mo

## 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 above — 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

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

- License: BSD 3-Clause License Copyright (c) 2021, cogeotiff All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following… (full text in the JSON record) (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 361.4K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

read raster tiles from geotiff, slippy map tile extraction, cloud optimized geotiff reader, rasterio wrapper for tiles, stac raster data access, remote raster data reading, geospatial tile server library, geospatial, raster-data, cloud-optimized-geotiff

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