choices=['L1C', 'L2A'], help='type of image') parser.add_argument('--parallel-downloads', type=int, default=multiprocessing.cpu_count(), help='max number of parallel crops downloads') args = parser.parse_args() if 'all' in args.band: args.band = ALL_BANDS if args.geom and (args.lat or args.lon): parser.error('--geom and {--lat, --lon} are mutually exclusive') if not args.geom and (not args.lat or not args.lon): parser.error('either --geom or {--lat, --lon} must be defined') if args.geom: aoi = args.geom else: aoi = utils.geojson_geometry_object(args.lat, args.lon, args.width, args.height) get_time_series(aoi, start_date=args.start_date, end_date=args.end_date, bands=args.band, out_dir=args.outdir, search_api=args.api, product_type=args.product_type, parallel_downloads=args.parallel_downloads)
import datetime import search_scihub import utils aoi = utils.geojson_geometry_object(29.9793, 31.1346, 5000, 5000) results = search_scihub.search(aoi, start_date=datetime.datetime(2019, 1, 1), end_date=datetime.datetime(2019, 1, 15), satellite='Sentinel-2') expected_titles = ['S2A_MSIL1C_20190114T083311_N0207_R021_T36RUU_20190114T085705', 'S2B_MSIL1C_20190109T083329_N0207_R021_T36RUU_20190109T103019', 'S2A_MSIL1C_20190104T083331_N0207_R021_T36RUU_20190104T104619'] assert([r['title'] for r in results] == expected_titles)