rio-cogeo
Cloud Optimized GeoTIFF (COGEO) creation plugin for rasterio
Decision gist · record as of 2026-08-14
Yes. rio-cogeo is actively maintained, has low install friction, carries a permissive BSD license, and solves a concrete problem for anyone working with geospatial rasters in cloud environments. The four runtime dependencies are well-established geospatial libraries. No known security vulnerabilities. Install if you need to create or validate Cloud Optimized GeoTIFFs.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires GDAL > 2.3.2 and Rasterio with GDAL bindings; Python >= 3.11.
- Low install friction with a pure-wheel distribution and four straightforward runtime dependencies (click, morecantile, pydantic, rasterio).
- Actively maintained as of 2026-06-23 with recent releases.
License · maintenance · safety
permissive license (permissive) — BSD 3-Clause permissive license allows commercial and private use with minimal restrictions—include the license text and copyright notice in distributions.
last release 2026-03-27 (140 days) · last repo commit 2026-06-23 · 394 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 390,863 downloads/mo, #7,019 on PyPI
Alternatives
Verify before relying
pip install rio-cogeo
from rio_cogeo.cogeo import cog_translate
from rasterio.io import MemoryFile
cog_translate('input.tif', 'output_cog.tif')- Whether the package supports the newer GDAL 3.1+ COG driver via --use-cog-driver by default in version 7.0.2.
- Specific performance characteristics or file-size overhead from internal overviews and 512x512 tiling.
What it is and what it does
rio-cogeo is a Rasterio plugin that transforms GeoTIFF files into Cloud Optimized GeoTIFFs (COGs), a format optimized for cloud storage and remote access. It enforces COG specifications while adding internal overviews and 512x512 internal tiles to enable efficient partial-file reads over HTTP. The package provides both programmatic and command-line interfaces for conversion and validation, built on top of Rasterio's geospatial I/O layer.
The plugin depends on click for CLI scaffolding, morecantile for tile management, pydantic for configuration validation, and rasterio for the underlying GDAL integration. It targets modern Python (3.11+) and is actively maintained. Users working with geospatial data in cloud environments—particularly those serving raster data over the web or storing large imagery in object storage—use it to pre-process files into a format that minimizes bandwidth and latency for remote clients.
Use it for
- Convert existing GeoTIFF archives to COG format for efficient cloud storage and HTTP range-request access.
- Validate that raster files meet COG specifications before publishing to cloud platforms like AWS S3 or GCS.
- Automate batch COG creation in geospatial data pipelines to optimize downstream web-based visualization or analysis.
- Create cloud-native raster datasets with internal overviews for multi-resolution web map serving.
- Integrate COG generation into geospatial ETL workflows to reduce data transfer costs in cloud environments.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
rio-cogeo is actively maintained, has low install friction, carries a permissive BSD license, and solves a concrete problem for anyone working with geospatial rasters in cloud environments. The four runtime dependencies are well-established geospatial libraries. No known security vulnerabilities. Install if you need to create or validate Cloud Optimized GeoTIFFs.
Install
rio-cogeo on PyPI
Before you install
Low install friction with a pure-wheel distribution and four straightforward runtime dependencies (click, morecantile, pydantic, rasterio). Actively maintained as of 2026-06-23 with recent releases.
Requires GDAL > 2.3.2 and Rasterio with GDAL bindings; Python >= 3.11.
License in practice
BSD 3-Clause permissive license allows commercial and private use with minimal restrictions—include the license text and copyright notice in distributions.
Quickstart
pip install rio-cogeo
from rio_cogeo.cogeo import cog_translate
from rasterio.io import MemoryFile
cog_translate('input.tif', 'output_cog.tif')Verify before relying
- Whether the package supports the newer GDAL 3.1+ COG driver via --use-cog-driver by default in version 7.0.2.
- Specific performance characteristics or file-size overhead from internal overviews and 512x512 tiling.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesclickmorecantilepydanticrasterio |
| Maintenance | Actively maintained 140 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 390,863 / month, #7,019 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_cogeo-7.0.2-py3-none-any.whl
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See also rio-tiler · titiler-core · cogeo-mosaic · titiler-application · rasterio · rioxarray · titiler-extensions · rio-stac · supermorecado · cogapp