{"categories":[{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/2"}],"enrichment":{"capability":"Signs Azure Blob Storage URLs and STAC objects to grant read access to Planetary Computer datasets, with optional automatic integration into pystac-client workflows.","skillfed_tags":["geospatial","stac","azure-storage"],"use_cases":["Automatically sign STAC search results from Planetary Computer when using pystac-client to access satellite imagery.","Manually sign individual STAC Items or Assets before downloading or processing Planetary Computer datasets.","Sign raw Azure Blob Storage URLs to grant temporary read access to geospatial data without managing credentials directly.","Integrate Planetary Computer data access into geospatial analysis pipelines that already use pystac and pystac-client.","Access Planetary Computer's Blob Storage container directly via ContainerClient or adlfs filesystem abstractions."],"what_it_does":"The Planetary Computer SDK is a Python library for accessing Microsoft's Planetary Computer geospatial data service. It specializes in signing Azure Blob Storage URLs and STAC (SpatioTemporal Asset Catalog) objects to grant read access to satellite imagery and related datasets. The library works with pystac objects (Asset, Item, ItemCollection) and pystac-client's ItemSearch, allowing you to either manually sign individual items or automatically sign all results from a client query.\n\nThe package depends on click, pydantic, pystac, pystac-client, pytz, requests, packaging, and python-dotenv. It requires Python 3.7 or later. While installation is straightforward, the package has been abandoned since July 2023, meaning no active maintenance or updates are being applied\u2014a significant consideration if you rely on it for production geospatial workflows.","worth_installing":"Yes, but with caution. The package is well-designed for its narrow purpose\u2014signing Planetary Computer assets\u2014and has low install friction. However, it is abandoned (last release July 2023, 1136 days ago), so there will be no bug fixes or compatibility updates. Install it only if you are committed to using Planetary Computer data and can accept the risk of eventual incompatibility with newer dependency versions. For new projects, verify that the signing mechanism and API endpoint remain stable."},"id":"planetary-computer","links":{"html":"https://skillfed.io/packages/planetary-computer","md":"https://skillfed.io/packages/planetary-computer.md","pypi":"https://pypi.org/project/planetary-computer/"},"maintenance":{"status":"abandoned"},"meta":{"latest_release":"2023-07-05","license_spdx":null,"license_treatment":"permissive","name":"planetary-computer","python_support":"supports_current","summary":"Planetary Computer SDK for Python"},"popularity":{"monthly_downloads":272043,"position":8213,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.0.0"}