{"categories":[{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis"}],"enrichment":{"capability":"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.","skillfed_tags":["geospatial","stac-catalog","metadata-management"],"use_cases":["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."],"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\u2014the 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.\n\nMost 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.","worth_installing":"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\u2014install 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."},"id":"pystac-core","links":{"html":"https://skillfed.io/packages/pystac-core","md":"https://skillfed.io/packages/pystac-core.md","pypi":"https://pypi.org/project/pystac-core/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-27","license_spdx":null,"license_treatment":"permissive","name":"pystac-core","python_support":"supports_current","summary":"Core functionality for PySTAC without extensions. Most users will want to use pystac, not this package"},"popularity":{"monthly_downloads":3992866,"position":2406,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"1.15.2"}