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asf_search

PyPI version Conda version Conda platforms

PyPI pyversions PyPI license

Github workflow

Python wrapper for the ASF SearchAPI

import asf_search as asf
import json

results = asf.granule_search(['ALPSRS279162400', 'ALPSRS279162200'])
print(f'Granule search results: {json.dumps(results, indent=2)}')

wkt = 'POLYGON((-135.7 58.2,-136.6 58.1,-135.8 56.9,-134.6 56.1,-134.9 58.0,-135.7 58.2))'
results = asf.geo_search(platform=[asf.PLATFORM.SENTINEL1], intersectsWith=wkt, maxResults=10)
print(f'Geographic search results: {json.dumps(results, indent=2)}')

Install

In order to easily manage dependencies, we recommend using dedicated project environments via Anaconda/Miniconda or Python virtual environments.

asf_search can be installed into a conda environment with

conda install -c conda-forge asf_search

or into a virtual environment with

python -m pip install asf_search

Usage

Programmatically searching for ASF data is made simple with asf_search. Several search functions are provided:

  • geo_search() Find product info over an area of interest using a WKT string
  • granule_search() Find product info using a list of scenes
  • product_search() Find product info using a list of products
  • search() Find product info using any combination combination of search parameters
  • stack() Find a baseline stack of products using a reference scene
  • Additionally, numerous constants are provided to ease the search process

Examples of all of the above can be found in examples/

Development

Branching

Instance Branch Description, Instructions, Notes
Stable stable Accepts merges from Working and Hotfixes
Working master Accepts merges from Features/Issues and Hotfixes
Features/Issues topic-* Always branch off HEAD of Working
Hotfix hotfix-* Always branch off Stable

For an extended description of our workflow, see https://gist.github.com/digitaljhelms/4287848