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)
