---
id: python-cmr
version: "0.13.0"
license: MIT
license_treatment: permissive
maintenance: active
---

# python-cmr — Python wrapper to the NASA Common Metadata Repository (CMR) API.

License: permissive · Maintenance: active · Downloads: 160.1K/mo

## What it is and what it does

Python CMR is a wrapper library for NASA's EOSDIS Common Metadata Repository API that simplifies querying earth science metadata. It provides query builder classes (CollectionQuery, GranuleQuery, ToolQuery, ServiceQuery, VariableQuery) that let you filter by geographic bounds, temporal ranges, platform, instrument, archive center, and other criteria without manually constructing URLs or handling encoding. The library validates input before sending requests and returns results as JSON-accessible Python dictionaries by default, though it supports multiple output formats including XML, CSV, KML, and others.

The package is designed for researchers and developers who need to discover and access earth observation data from NASA's archive. You chain filter methods together to build queries, then call get() to retrieve results. It handles the details of URL construction and parameter validation, reducing the chance of malformed requests. The library supports both the operational CMR and UAT environments, and can work with authentication tokens for restricted access.

Use it for:

- Discover satellite imagery collections by archive center and keyword to identify available datasets for your research area
- Query granules (individual data files) by geographic point or bounding box to find observations covering a specific location
- Filter granules by temporal range and platform to retrieve data from a specific satellite during a particular time period
- Retrieve cloud cover and instrument metadata to programmatically select the highest-quality observations for analysis
- Batch download granule metadata in multiple formats (JSON, XML, CSV, KML) for integration into data processing pipelines
- Search for tools and services available in the CMR to discover processing capabilities alongside the raw data

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides a Python wrapper around NASA's Common Metadata Repository (CMR) API to query earth science collections, granules, services, tools, and variables with input validation and URL encoding.

Yes. The package is actively maintained, has no known vulnerabilities, low install friction, and directly solves the problem of querying NASA's earth science metadata repository. It's well-suited for researchers and developers working with satellite data who want to avoid manual API construction. The permissive MIT license poses no restrictions.

## Install

pip install python-cmr
uv add python-cmr
poetry add python-cmr

## Installing python-cmr

Before you install: Low friction: pure Python wheel with three common runtime dependencies (python-dateutil, requests, typing-extensions). Actively maintained since its adoption from the original author, with recent commits and no known vulnerabilities.

License in practice: MIT license is permissive; you can use, modify, and distribute this package freely in commercial or private projects with minimal restrictions.

Quickstart:

pip install python-cmr

from cmr import CollectionQuery, GranuleQuery

api = CollectionQuery()
collections = api.archive_center("LP DAAC").keyword("AST_L1*").get(5)

api = GranuleQuery()
granules = api.short_name("AST_L1T").point(-112.73, 42.5).get(3)

Verify before relying:

- Whether all CMR API parameters are covered by the current version or if some require direct API calls
- Performance characteristics when retrieving large result sets (e.g., the 25,000 granule example mentioned)
- Whether authentication tokens are required for all queries or only certain datasets

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 160.1K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

NASA CMR API wrapper, earth science metadata query, granule collection search, EOSDIS data discovery, geospatial data catalog, satellite metadata access, earth observation search, nasa-api, earth-science, geospatial

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