---
id: pystac-core
version: "1.15.2"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# pystac-core — Core functionality for PySTAC without extensions. Most users will want to use pystac, not this package

License: permissive · Maintenance: active · Downloads: 4.0M/mo

## What it is and what it does

PySTAC Core is the base library for working with the STAC specification, a standardized format for organizing and describing geospatial and temporal assets. It provides Python classes and methods to construct, parse, and manipulate STAC catalogs, collections, and items—the core data structures that describe where imagery and other raster data live, when they were captured, and how to access them. The library depends only on python-dateutil for date handling, keeping the core lightweight; optional dependencies add JSON validation, faster serialization, network retry logic, and Jupyter display support.

Most users will want the main pystac package instead, which includes extension implementations; this core package is for those building custom extensions or needing a minimal STAC foundation. The library follows semantic versioning and has recently moved extension implementations into separate packages so they can evolve independently of the core API.

Use it for:

- Build a custom STAC catalog to organize and describe a collection of satellite or aerial imagery with metadata.
- Parse and traverse existing STAC catalogs to discover and access geospatial assets programmatically.
- Develop a STAC extension or specialized tool that needs the core catalog and item structures without bundled extensions.
- Validate STAC JSON structures against the specification (with optional jsonschema dependency).
- Integrate STAC metadata into a geospatial data pipeline or web service.

## Worth the install?

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

PySTAC Core provides the foundational API for reading, writing, and working with SpatioTemporal Asset Catalog (STAC) metadata in Python, handling catalog structure, assets, and item management without extension implementations.

Yes, if you need to work directly with STAC catalogs in Python and either want a minimal core dependency footprint or are building custom extensions. No, if you are a typical user of STAC data—install the main pystac package instead, which includes extensions and is recommended for most use cases. The core package is production-ready, actively maintained, and carries no known vulnerabilities.

## Install

pip install pystac-core
uv add pystac-core
poetry add pystac-core

## Installing pystac-core

Before you install: Low friction installation with a single runtime dependency (python-dateutil). Active maintenance with a recent release 18 days ago and ongoing commits. Supports current Python versions (3.10–3.13).

License in practice: Apache-2.0 permissive license allows broad use, modification, and distribution with minimal restrictions, suitable for both open-source and commercial projects.

Quickstart:

pip install pystac-core
import pystac
# Create or load a STAC catalog
catalog = pystac.Catalog(id='my-catalog', description='My STAC catalog')

Requires Python 3.10 or later.

Verify before relying:

- Whether optional dependencies (jsonschema, orjson, urllib3, jinja2) are required for typical workflows or truly optional for core use.
- Performance characteristics when handling large catalogs or deeply nested STAC structures.
- Compatibility guarantees with different STAC specification versions beyond the current implementation.

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 4.0M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

STAC catalog Python library, spatiotemporal asset metadata, geospatial catalog management, STAC specification implementation, raster imagery catalog, asset catalog API, geospatial, stac-catalog, metadata-management

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