Regression #87
GitHub Actions / Regression test results for ops
failed
Jun 25, 2024 in 0s
44 fail, 530 pass in 44m 53s
574 tests 530 ✅ 44m 53s ⏱️
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1 files 44 ❌
Results for commit 2ac3719.
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Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C2832224417-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 23s]
Raw output
Failed: Unable to find latitude and longitude variables.
collection_concept_id = 'C2832224417-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2832224417-POCLOUD', 'concept-id': 'G3071779083-POCLOUD', 'concept-type': 'granul...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2832224417-POCLOUD'}]}, 'meta': {'association-details': {'collecti...me': 'look', 'Size': 2, 'Type': 'OTHER'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -9999.0}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw8/test_spatial_subset_C2832224410')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
> lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables)
verify_collection.py:398:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
dataset = <xarray.Dataset> Size: 232B
Dimensions: (ydim_grid: 1, xdim_grid: 1, look: 1,
... -0.43
history_json: [{"date_time": "2024-...
file_to_subset = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw8/test_spatial_subset_C2832224410/69127672_RSS_SMAP_SSS_L2C_r49943_20240607T102958_2024159_NRT_V06.0_001.nc4')
collection_variable_list = [{'associations': {'collections': [{'concept-id': 'C2832224417-POCLOUD'}]}, 'meta': {'association-details': {'collecti...me': 'look', 'Size': 2, 'Type': 'OTHER'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -9999.0}], ...}}, ...]
def get_lat_lon_var_names(dataset: xarray.Dataset, file_to_subset: str, collection_variable_list: List[Dict]):
# Try getting it from UMM-Var first
lat_var_json, lon_var_json, _ = get_coordinate_vars_from_umm(collection_variable_list)
lat_var_name = get_variable_name_from_umm_json(lat_var_json)
lon_var_name = get_variable_name_from_umm_json(lon_var_json)
if lat_var_name and lon_var_name:
return lat_var_name, lon_var_name
logging.warning("Unable to find lat/lon vars in UMM-Var")
# If that doesn't work, try using cf-xarray to infer lat/lon variable names
try:
latitude = [lat for lat in dataset.cf.coordinates['latitude']
if lat.lower() in VALID_LATITUDE_VARIABLE_NAMES][0]
longitude = [lon for lon in dataset.cf.coordinates['longitude']
if lon.lower() in VALID_LONGITUDE_VARIABLE_NAMES][0]
return latitude, longitude
except:
logging.warning("Unable to find lat/lon vars using cf_xarray")
# If that still doesn't work, try using l2ss-py directly
try:
# file not able to be flattened unless locally downloaded
shutil.copy(file_to_subset, 'my_copy_file.nc')
nc_dataset = netCDF4.Dataset('my_copy_file.nc', mode='r+')
# flatten the dataset
nc_dataset_flattened = podaac.subsetter.group_handling.transform_grouped_dataset(nc_dataset, 'my_copy_file.nc')
args = {
'decode_coords': False,
'mask_and_scale': False,
'decode_times': False
}
with xarray.open_dataset(
xarray.backends.NetCDF4DataStore(nc_dataset_flattened),
**args
) as flat_dataset:
# use l2ss-py to find lat and lon names
lat_var_names, lon_var_names = podaac.subsetter.subset.compute_coordinate_variable_names(flat_dataset)
os.remove('my_copy_file.nc')
if lat_var_names and lon_var_names:
lat_var_name = lat_var_names.split('__')[-1] if isinstance(lat_var_names, str) else lat_var_names[0].split('__')[-1]
lon_var_name = lon_var_names.split('__')[-1] if isinstance(lon_var_names, str) else lon_var_names[0].split('__')[-1]
return lat_var_name, lon_var_name
except ValueError:
logging.warning("Unable to find lat/lon vars using l2ss-py")
# Still no dice, try using the 'units' variable attribute
for coord_name, coord in dataset.coords.items():
if 'units' not in coord.attrs:
continue
if coord.attrs['units'] == 'degrees_north' and lat_var_name is None:
lat_var_name = coord_name
if coord.attrs['units'] == 'degrees_east' and lon_var_name is None:
lon_var_name = coord_name
if lat_var_name and lon_var_name:
return lat_var_name, lon_var_name
else:
logging.warning("Unable to find lat/lon vars using 'units' attribute")
# Out of options, fail the test because we couldn't determine lat/lon variables
> pytest.fail(f"Unable to find latitude and longitude variables.")
E Failed: Unable to find latitude and longitude variables.
verify_collection.py:358: Failed
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:365 Using granule G3071779083-POCLOUD for test
INFO root:verify_collection.py:381 Sending harmony request https://harmony.earthdata.nasa.gov/C2832224417-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-82.28062499999999%3A82.08362499999998%29&subset=lon%284.504874999999998%3A175.500125%29&granuleId=G3071779083-POCLOUD
INFO root:verify_collection.py:385 Submitted harmony job 3eaccd87-678c-4f8b-aa73-37b788ce609a
INFO root:verify_collection.py:391 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw8/test_spatial_subset_C2832224410/69127672_RSS_SMAP_SSS_L2C_r49943_20240607T102958_2024159_NRT_V06.0_001.nc4
WARNING root:verify_collection.py:302 Unable to find lat/lon vars in UMM-Var
WARNING root:verify_collection.py:312 Unable to find lat/lon vars using cf_xarray
WARNING root:verify_collection.py:342 Unable to find lat/lon vars using l2ss-py
WARNING root:verify_collection.py:355 Unable to find lat/lon vars using 'units' attribute
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1918210023-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 51s]
Raw output
OSError: [Errno group not found: PRODUCT] 'PRODUCT'
ds = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f7cdb366240>
group = '/METADATA/PRODUCT', mode = 'r'
create_group = <function _netcdf4_create_group at 0x7f7cdf923eb0>
def _nc4_require_group(ds, group, mode, create_group=_netcdf4_create_group):
if group in {None, "", "/"}:
# use the root group
return ds
else:
# make sure it's a string
if not isinstance(group, str):
raise ValueError("group must be a string or None")
# support path-like syntax
path = group.strip("/").split("/")
for key in path:
try:
> ds = ds.groups[key]
E KeyError: 'PRODUCT'
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:190: KeyError
During handling of the above exception, another exception occurred:
collection_concept_id = 'C1918210023-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1918210023-GES_DISC', 'concept-id': 'G3130184867-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1918210023-GES_DISC'}]}, 'meta': {'association-details': {'collect...RL': 'https://cdn.earthdata.nasa.gov/umm/variable/v1.9.0', 'Version': '1.9.0'}, 'Name': 'PRODUCT/qa_value', ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw0/test_spatial_subset_C1918210020')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
g = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=g, decode_times=False)
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:432:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
verify_collection.py:423: in group_walk
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=g, decode_times=False)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/api.py:571: in open_dataset
backend_ds = backend.open_dataset(
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:646: in open_dataset
store = NetCDF4DataStore.open(
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:409: in open
return cls(manager, group=group, mode=mode, lock=lock, autoclose=autoclose)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:356: in __init__
self.format = self.ds.data_model
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:418: in ds
return self._acquire()
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:413: in _acquire
ds = _nc4_require_group(root, self._group, self._mode)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
ds = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f7cdb366240>
group = '/METADATA/PRODUCT', mode = 'r'
create_group = <function _netcdf4_create_group at 0x7f7cdf923eb0>
def _nc4_require_group(ds, group, mode, create_group=_netcdf4_create_group):
if group in {None, "", "/"}:
# use the root group
return ds
else:
# make sure it's a string
if not isinstance(group, str):
raise ValueError("group must be a string or None")
# support path-like syntax
path = group.strip("/").split("/")
for key in path:
try:
ds = ds.groups[key]
except KeyError as e:
if mode != "r":
ds = create_group(ds, key)
else:
# wrap error to provide slightly more helpful message
> raise OSError(f"group not found: {key}", e)
E OSError: [Errno group not found: PRODUCT] 'PRODUCT'
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:196: OSError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:365 Using granule G3130184867-GES_DISC for test
INFO root:verify_collection.py:381 Sending harmony request https://harmony.earthdata.nasa.gov/C1918210023-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-76.42954999999999%3A-59.996449999999996%29&subset=lon%28-159.497975%3A127.364975%29&granuleId=G3130184867-GES_DISC
INFO root:verify_collection.py:385 Submitted harmony job 98df1aef-124e-4fc8-9c10-b0d6f960a44d
INFO root:verify_collection.py:391 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw0/test_spatial_subset_C1918210020/69127677_S5P_OFFL_L2_HCHO_20240624T031300_20240624T045430_34699_03_020601_20240625T190508_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C2087131083-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 31s]
Raw output
OSError: [Errno group not found: PRODUCT] 'PRODUCT'
ds = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f0e68a99640>
group = '/METADATA/PRODUCT', mode = 'r'
create_group = <function _netcdf4_create_group at 0x7f0e712f97e0>
def _nc4_require_group(ds, group, mode, create_group=_netcdf4_create_group):
if group in {None, "", "/"}:
# use the root group
return ds
else:
# make sure it's a string
if not isinstance(group, str):
raise ValueError("group must be a string or None")
# support path-like syntax
path = group.strip("/").split("/")
for key in path:
try:
> ds = ds.groups[key]
E KeyError: 'PRODUCT'
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:190: KeyError
During handling of the above exception, another exception occurred:
collection_concept_id = 'C2087131083-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2087131083-GES_DISC', 'concept-id': 'G3130317459-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2087131083-GES_DISC'}]}, 'meta': {'association-details': {'collect.../variable/v1.9.0', 'Version': '1.9.0'}, 'Name': 'METADATA/QA_STATISTICS/aerosol_index_354_388_histogram_bounds'}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw4/test_spatial_subset_C2087131080')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
g = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=g, decode_times=False)
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:432:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
verify_collection.py:423: in group_walk
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=g, decode_times=False)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/api.py:571: in open_dataset
backend_ds = backend.open_dataset(
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:646: in open_dataset
store = NetCDF4DataStore.open(
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:409: in open
return cls(manager, group=group, mode=mode, lock=lock, autoclose=autoclose)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:356: in __init__
self.format = self.ds.data_model
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:418: in ds
return self._acquire()
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:413: in _acquire
ds = _nc4_require_group(root, self._group, self._mode)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
ds = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f0e68a99640>
group = '/METADATA/PRODUCT', mode = 'r'
create_group = <function _netcdf4_create_group at 0x7f0e712f97e0>
def _nc4_require_group(ds, group, mode, create_group=_netcdf4_create_group):
if group in {None, "", "/"}:
# use the root group
return ds
else:
# make sure it's a string
if not isinstance(group, str):
raise ValueError("group must be a string or None")
# support path-like syntax
path = group.strip("/").split("/")
for key in path:
try:
ds = ds.groups[key]
except KeyError as e:
if mode != "r":
ds = create_group(ds, key)
else:
# wrap error to provide slightly more helpful message
> raise OSError(f"group not found: {key}", e)
E OSError: [Errno group not found: PRODUCT] 'PRODUCT'
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:196: OSError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:365 Using granule G3130317459-GES_DISC for test
INFO root:verify_collection.py:381 Sending harmony request https://harmony.earthdata.nasa.gov/C2087131083-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-76.41945%3A-59.41255%29&subset=lon%2880.11795000000001%3A154.33004999999997%29&granuleId=G3130317459-GES_DISC
INFO root:verify_collection.py:385 Submitted harmony job 2dea2b36-1273-422a-b493-ea1ced1113bf
INFO root:verify_collection.py:391 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw4/test_spatial_subset_C2087131080/69127708_S5P_OFFL_L2_AER_AI_20240624T063600_20240624T081730_34701_03_020600_20240625T202645_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C2832221740-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 43s]
Raw output
harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
collection_concept_id = 'C2832221740-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2832221740-POCLOUD', 'concept-id': 'G3059748792-POCLOUD', 'concept-type': 'granul...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2832221740-POCLOUD'}]}, 'meta': {'association-details': {'collecti...rization_2', 'Size': 2, 'Type': 'OTHER'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -9999.0}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw1/test_spatial_subset_C2832221740')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
> harmony_client.wait_for_processing(job_id, show_progress=True)
verify_collection.py:386:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7faa29a36830>
job_id = 'ff27470e-668f-4f9d-83c7-fc75d24e19d9', show_progress = True
def wait_for_processing(self, job_id: str, show_progress: bool = False) -> None:
"""Retrieve a submitted job's completion status in percent.
Args:
job_id: UUID string for the job you wish to interrogate.
Returns:
The job's processing progress as a percentage.
:raises
Exception: This can happen if an invalid job_id is provided or Harmony services
can't be reached.
"""
# How often to refresh the screen for progress updates and animating spinners.
ui_update_interval = 0.33 # in seconds
running_w_errors_logged = False
intervals = round(self.check_interval / ui_update_interval)
if show_progress:
with progressbar.ProgressBar(max_value=100, widgets=progressbar_widgets) as bar:
progress = 0
while progress < 100:
progress, status, message = self.progress(job_id)
if status == 'failed':
> raise ProcessingFailedException(job_id, message)
E harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:986: ProcessingFailedException
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:365 Using granule G3059748792-POCLOUD for test
INFO root:verify_collection.py:381 Sending harmony request https://harmony.earthdata.nasa.gov/C2832221740-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-82.29042474999999%3A82.03317474999999%29&subset=lon%28-171.0%3A171.0%29&granuleId=G3059748792-POCLOUD
INFO root:verify_collection.py:385 Submitted harmony job ff27470e-668f-4f9d-83c7-fc75d24e19d9
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C2936721448-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 23s]
Raw output
Failed: Unable to find latitude and longitude variables.
collection_concept_id = 'C2936721448-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2936721448-POCLOUD', 'concept-id': 'G3062447313-POCLOUD', 'concept-type': 'granul...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2936721448-POCLOUD'}]}, 'meta': {'association-details': {'collecti...rization_2', 'Size': 2, 'Type': 'OTHER'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -9999.0}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw3/test_spatial_subset_C2936721440')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
> lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables)
verify_collection.py:398:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
dataset = <xarray.Dataset> Size: 240B
Dimensions: (ydim_grid: 1, xdim_grid: 1, look: 1,
... -0.43
history_json: [{"date_time": "2...
file_to_subset = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw3/test_spatial_subset_C2936721440/69127848_RSS_SMAP_SSS_L2C_r47700_20240106T014035_2024006_FNL_V05.3.nc4')
collection_variable_list = [{'associations': {'collections': [{'concept-id': 'C2936721448-POCLOUD'}]}, 'meta': {'association-details': {'collecti...rization_2', 'Size': 2, 'Type': 'OTHER'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -9999.0}], ...}}, ...]
def get_lat_lon_var_names(dataset: xarray.Dataset, file_to_subset: str, collection_variable_list: List[Dict]):
# Try getting it from UMM-Var first
lat_var_json, lon_var_json, _ = get_coordinate_vars_from_umm(collection_variable_list)
lat_var_name = get_variable_name_from_umm_json(lat_var_json)
lon_var_name = get_variable_name_from_umm_json(lon_var_json)
if lat_var_name and lon_var_name:
return lat_var_name, lon_var_name
logging.warning("Unable to find lat/lon vars in UMM-Var")
# If that doesn't work, try using cf-xarray to infer lat/lon variable names
try:
latitude = [lat for lat in dataset.cf.coordinates['latitude']
if lat.lower() in VALID_LATITUDE_VARIABLE_NAMES][0]
longitude = [lon for lon in dataset.cf.coordinates['longitude']
if lon.lower() in VALID_LONGITUDE_VARIABLE_NAMES][0]
return latitude, longitude
except:
logging.warning("Unable to find lat/lon vars using cf_xarray")
# If that still doesn't work, try using l2ss-py directly
try:
# file not able to be flattened unless locally downloaded
shutil.copy(file_to_subset, 'my_copy_file.nc')
nc_dataset = netCDF4.Dataset('my_copy_file.nc', mode='r+')
# flatten the dataset
nc_dataset_flattened = podaac.subsetter.group_handling.transform_grouped_dataset(nc_dataset, 'my_copy_file.nc')
args = {
'decode_coords': False,
'mask_and_scale': False,
'decode_times': False
}
with xarray.open_dataset(
xarray.backends.NetCDF4DataStore(nc_dataset_flattened),
**args
) as flat_dataset:
# use l2ss-py to find lat and lon names
lat_var_names, lon_var_names = podaac.subsetter.subset.compute_coordinate_variable_names(flat_dataset)
os.remove('my_copy_file.nc')
if lat_var_names and lon_var_names:
lat_var_name = lat_var_names.split('__')[-1] if isinstance(lat_var_names, str) else lat_var_names[0].split('__')[-1]
lon_var_name = lon_var_names.split('__')[-1] if isinstance(lon_var_names, str) else lon_var_names[0].split('__')[-1]
return lat_var_name, lon_var_name
except ValueError:
logging.warning("Unable to find lat/lon vars using l2ss-py")
# Still no dice, try using the 'units' variable attribute
for coord_name, coord in dataset.coords.items():
if 'units' not in coord.attrs:
continue
if coord.attrs['units'] == 'degrees_north' and lat_var_name is None:
lat_var_name = coord_name
if coord.attrs['units'] == 'degrees_east' and lon_var_name is None:
lon_var_name = coord_name
if lat_var_name and lon_var_name:
return lat_var_name, lon_var_name
else:
logging.warning("Unable to find lat/lon vars using 'units' attribute")
# Out of options, fail the test because we couldn't determine lat/lon variables
> pytest.fail(f"Unable to find latitude and longitude variables.")
E Failed: Unable to find latitude and longitude variables.
verify_collection.py:358: Failed
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:365 Using granule G3062447313-POCLOUD for test
INFO root:verify_collection.py:381 Sending harmony request https://harmony.earthdata.nasa.gov/C2936721448-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-82.29044999999999%3A82.08044999999998%29&subset=lon%284.51755%3A175.50045%29&granuleId=G3062447313-POCLOUD
INFO root:verify_collection.py:385 Submitted harmony job d4997e1d-83f0-4f2c-a0e1-a041a5110a4d
INFO root:verify_collection.py:391 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw3/test_spatial_subset_C2936721440/69127848_RSS_SMAP_SSS_L2C_r47700_20240106T014035_2024006_FNL_V05.3.nc4
WARNING root:verify_collection.py:302 Unable to find lat/lon vars in UMM-Var
WARNING root:verify_collection.py:312 Unable to find lat/lon vars using cf_xarray
WARNING root:verify_collection.py:342 Unable to find lat/lon vars using l2ss-py
WARNING root:verify_collection.py:355 Unable to find lat/lon vars using 'units' attribute
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C2799465526-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 49s]
Raw output
RuntimeError: NetCDF: Can't open HDF5 attribute
collection_concept_id = 'C2799465526-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2799465526-POCLOUD', 'concept-id': 'G3127099964-POCLOUD', 'concept-type': 'granul...DateTime': '2024-06-24T11:13:37.759Z'}, 'GranuleUR': 'SWOT_IPN_2PfP017_138_20240623_230318_20240623_235445_swot', ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2799465526-POCLOUD'}]}, 'meta': {'association-details': {'collecti...a: off nadir angle from Ku band', 'Dimensions': [{'Name': 'time', 'Size': 2690, 'Type': 'TIME_DIMENSION'}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw7/test_spatial_subset_C2799465520')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
> lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables)
verify_collection.py:398:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
verify_collection.py:318: in get_lat_lon_var_names
nc_dataset = netCDF4.Dataset('my_copy_file.nc', mode='r+')
src/netCDF4/_netCDF4.pyx:2495: in netCDF4._netCDF4.Dataset.__init__
???
src/netCDF4/_netCDF4.pyx:1891: in netCDF4._netCDF4._get_grps
???
src/netCDF4/_netCDF4.pyx:3616: in netCDF4._netCDF4.Group.__init__
???
src/netCDF4/_netCDF4.pyx:1927: in netCDF4._netCDF4._get_vars
???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
> ???
E RuntimeError: NetCDF: Can't open HDF5 attribute
src/netCDF4/_netCDF4.pyx:2034: RuntimeError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:365 Using granule G3127099964-POCLOUD for test
INFO root:verify_collection.py:381 Sending harmony request https://harmony.earthdata.nasa.gov/C2799465526-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%2867.742205%3A77.420995%29&subset=lon%28124.586265%3A178.579135%29&granuleId=G3127099964-POCLOUD
INFO root:verify_collection.py:385 Submitted harmony job 1b889b2a-a4b3-4c47-b268-b0f064d46e74
INFO root:verify_collection.py:391 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw7/test_spatial_subset_C2799465520/69127852_SWOT_IPN_2PfP017_138_20240623_230318_20240623_235445_subsetted.nc4
WARNING root:verify_collection.py:302 Unable to find lat/lon vars in UMM-Var
WARNING root:verify_collection.py:312 Unable to find lat/lon vars using cf_xarray
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1251101457-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 22s]
Raw output
OSError: [Errno -101] NetCDF: HDF error: 'my_copy_file.nc'
collection_concept_id = 'C1251101457-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1251101457-GES_DISC', 'concept-id': 'G3056242015-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1251101457-GES_DISC'}]}, 'meta': {'association-details': {'collect... 'Extracted from _FillValue metadata attribute', 'Type': 'SCIENCE_FILLVALUE', 'Value': -999.989990234375}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw2/test_spatial_subset_C1251101450')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
> lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables)
verify_collection.py:398:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
verify_collection.py:318: in get_lat_lon_var_names
nc_dataset = netCDF4.Dataset('my_copy_file.nc', mode='r+')
src/netCDF4/_netCDF4.pyx:2469: in netCDF4._netCDF4.Dataset.__init__
???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
> ???
E OSError: [Errno -101] NetCDF: HDF error: 'my_copy_file.nc'
src/netCDF4/_netCDF4.pyx:2028: OSError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:365 Using granule G3056242015-GES_DISC for test
INFO root:verify_collection.py:381 Sending harmony request https://harmony.earthdata.nasa.gov/C1251101457-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-85.5%3A85.5%29&subset=lon%28-171.0%3A171.0%29&granuleId=G3056242015-GES_DISC
INFO root:verify_collection.py:385 Submitted harmony job 47511a19-be88-4d10-884c-a581135a41e7
INFO root:verify_collection.py:391 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw2/test_spatial_subset_C1251101450/69127854_MLS-Aura_L2GP-HCN_v04-25-c01_2024d152_subsetted.nc4
WARNING root:verify_collection.py:302 Unable to find lat/lon vars in UMM-Var
WARNING root:verify_collection.py:312 Unable to find lat/lon vars using cf_xarray
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1627516300-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 37s]
Raw output
OSError: [Errno group not found: PRODUCT] 'PRODUCT'
ds = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f0e68986d40>
group = '/METADATA/PRODUCT', mode = 'r'
create_group = <function _netcdf4_create_group at 0x7f0e712f97e0>
def _nc4_require_group(ds, group, mode, create_group=_netcdf4_create_group):
if group in {None, "", "/"}:
# use the root group
return ds
else:
# make sure it's a string
if not isinstance(group, str):
raise ValueError("group must be a string or None")
# support path-like syntax
path = group.strip("/").split("/")
for key in path:
try:
> ds = ds.groups[key]
E KeyError: 'PRODUCT'
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:190: KeyError
During handling of the above exception, another exception occurred:
collection_concept_id = 'C1627516300-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1627516300-GES_DISC', 'concept-id': 'G1902371249-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1627516300-GES_DISC'}]}, 'meta': {'association-details': {'collect...asa.gov/umm/variable/v1.9.0', 'Version': '1.9.0'}, 'Name': 'PRODUCT/ozone_total_vertical_column_precision', ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw4/test_spatial_subset_C1627516300')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
g = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=g, decode_times=False)
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:432:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
verify_collection.py:423: in group_walk
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=g, decode_times=False)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/api.py:571: in open_dataset
backend_ds = backend.open_dataset(
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:646: in open_dataset
store = NetCDF4DataStore.open(
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:409: in open
return cls(manager, group=group, mode=mode, lock=lock, autoclose=autoclose)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:356: in __init__
self.format = self.ds.data_model
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:418: in ds
return self._acquire()
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:413: in _acquire
ds = _nc4_require_group(root, self._group, self._mode)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
ds = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f0e68986d40>
group = '/METADATA/PRODUCT', mode = 'r'
create_group = <function _netcdf4_create_group at 0x7f0e712f97e0>
def _nc4_require_group(ds, group, mode, create_group=_netcdf4_create_group):
if group in {None, "", "/"}:
# use the root group
return ds
else:
# make sure it's a string
if not isinstance(group, str):
raise ValueError("group must be a string or None")
# support path-like syntax
path = group.strip("/").split("/")
for key in path:
try:
ds = ds.groups[key]
except KeyError as e:
if mode != "r":
ds = create_group(ds, key)
else:
# wrap error to provide slightly more helpful message
> raise OSError(f"group not found: {key}", e)
E OSError: [Errno group not found: PRODUCT] 'PRODUCT'
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:196: OSError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:365 Using granule G1902371249-GES_DISC for test
INFO root:verify_collection.py:381 Sending harmony request https://harmony.earthdata.nasa.gov/C1627516300-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-78.0453%3A-60.6907%29&subset=lon%28-164.82465%3A-84.66935000000001%29&granuleId=G1902371249-GES_DISC
INFO root:verify_collection.py:385 Submitted harmony job fbc5152a-4f33-4502-aa27-4c3cfd3557ea
INFO root:verify_collection.py:391 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw4/test_spatial_subset_C1627516300/69127942_S5P_OFFL_L2_O3_20200712T224601_20200713T002730_14238_01_010108_20200715T122623_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1918209846-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 38s]
Raw output
ValueError: did not find a match in any of xarray's currently installed IO backends ['netcdf4']. Consider explicitly selecting one of the installed engines via the ``engine`` parameter, or installing additional IO dependencies, see:
https://docs.xarray.dev/en/stable/getting-started-guide/installing.html
https://docs.xarray.dev/en/stable/user-guide/io.html
collection_concept_id = 'C1918209846-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1918209846-GES_DISC', 'concept-id': 'G3130461149-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1918209846-GES_DISC'}]}, 'meta': {'association-details': {'collect...tracted from _FillValue metadata attribute', 'Type': 'SCIENCE_FILLVALUE', 'Value': 9.969209968386869e+36}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw7/test_spatial_subset_C1918209840')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
> subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
verify_collection.py:395:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/api.py:552: in open_dataset
engine = plugins.guess_engine(filename_or_obj)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
store_spec = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw7/test_spatial_subset_C1918209840/69128024_S5P_OFFL_L2_O3_20240623T235001_20240624T013130_34697_03_020601_20240625T154916_subsetted.nc4')
def guess_engine(
store_spec: str | os.PathLike[Any] | BufferedIOBase | AbstractDataStore,
) -> str | type[BackendEntrypoint]:
engines = list_engines()
for engine, backend in engines.items():
try:
if backend.guess_can_open(store_spec):
return engine
except PermissionError:
raise
except Exception:
warnings.warn(f"{engine!r} fails while guessing", RuntimeWarning)
compatible_engines = []
for engine, (_, backend_cls) in BACKEND_ENTRYPOINTS.items():
try:
backend = backend_cls()
if backend.guess_can_open(store_spec):
compatible_engines.append(engine)
except Exception:
warnings.warn(f"{engine!r} fails while guessing", RuntimeWarning)
installed_engines = [k for k in engines if k != "store"]
if not compatible_engines:
if installed_engines:
error_msg = (
"did not find a match in any of xarray's currently installed IO "
f"backends {installed_engines}. Consider explicitly selecting one of the "
"installed engines via the ``engine`` parameter, or installing "
"additional IO dependencies, see:\n"
"https://docs.xarray.dev/en/stable/getting-started-guide/installing.html\n"
"https://docs.xarray.dev/en/stable/user-guide/io.html"
)
else:
error_msg = (
"xarray is unable to open this file because it has no currently "
"installed IO backends. Xarray's read/write support requires "
"installing optional IO dependencies, see:\n"
"https://docs.xarray.dev/en/stable/getting-started-guide/installing.html\n"
"https://docs.xarray.dev/en/stable/user-guide/io"
)
else:
error_msg = (
"found the following matches with the input file in xarray's IO "
f"backends: {compatible_engines}. But their dependencies may not be installed, see:\n"
"https://docs.xarray.dev/en/stable/user-guide/io.html \n"
"https://docs.xarray.dev/en/stable/getting-started-guide/installing.html"
)
> raise ValueError(error_msg)
E ValueError: did not find a match in any of xarray's currently installed IO backends ['netcdf4']. Consider explicitly selecting one of the installed engines via the ``engine`` parameter, or installing additional IO dependencies, see:
E https://docs.xarray.dev/en/stable/getting-started-guide/installing.html
E https://docs.xarray.dev/en/stable/user-guide/io.html
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/plugins.py:197: ValueError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:365 Using granule G3130461149-GES_DISC for test
INFO root:verify_collection.py:381 Sending harmony request https://harmony.earthdata.nasa.gov/C1918209846-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-76.430375%3A-59.420625%29&subset=lon%28-165.206125%3A170.823125%29&granuleId=G3130461149-GES_DISC
INFO root:verify_collection.py:385 Submitted harmony job 6818adb1-5fa5-4dbe-9f89-ee5c2f7cbf2b
INFO root:verify_collection.py:391 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw7/test_spatial_subset_C1918209840/69128024_S5P_OFFL_L2_O3_20240623T235001_20240624T013130_34697_03_020601_20240625T154916_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C2251464495-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 10m 0s]
Raw output
Failed: Timeout >600.0s
collection_concept_id = 'C2251464495-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2251464495-POCLOUD', 'concept-id': 'G3123215106-POCLOUD', 'concept-type': 'granul...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2251464495-POCLOUD'}]}, 'meta': {'association-details': {'collecti...ame': 'ddm', 'Size': 5, 'Type': 'OTHER'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -9999.0}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw1/test_spatial_subset_C2251464490')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
> harmony_client.wait_for_processing(job_id, show_progress=True)
verify_collection.py:386:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7faa278fe380>
job_id = '7e4b270b-f6bb-40b9-9142-7b79cffdb062', show_progress = True
def wait_for_processing(self, job_id: str, show_progress: bool = False) -> None:
"""Retrieve a submitted job's completion status in percent.
Args:
job_id: UUID string for the job you wish to interrogate.
Returns:
The job's processing progress as a percentage.
:raises
Exception: This can happen if an invalid job_id is provided or Harmony services
can't be reached.
"""
# How often to refresh the screen for progress updates and animating spinners.
ui_update_interval = 0.33 # in seconds
running_w_errors_logged = False
intervals = round(self.check_interval / ui_update_interval)
if show_progress:
with progressbar.ProgressBar(max_value=100, widgets=progressbar_widgets) as bar:
progress = 0
while progress < 100:
progress, status, message = self.progress(job_id)
if status == 'failed':
raise ProcessingFailedException(job_id, message)
if status == 'canceled':
print('Job has been canceled.')
break
if status == 'paused':
print('\nJob has been paused. Call `resume()` to resume.', file=sys.stderr)
break
if (not running_w_errors_logged and status == 'running_with_errors'):
print('\nJob is running with errors.', file=sys.stderr)
running_w_errors_logged = True
# This gets around an issue with progressbar. If we update() with 0, the
# output shows up as "N/A". If we update with, e.g. 0.1, it rounds down or
# truncates to 0 but, importantly, actually displays that.
if progress == 0:
progress = 0.1
for _ in range(intervals):
bar.update(progress) # causes spinner to rotate even when no data change
sys.stdout.flush() # ensures correct behavior in Jupyter notebooks
if progress >= 100:
break
else:
> time.sleep(ui_update_interval)
E Failed: Timeout >600.0s
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:1009: Failed
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:365 Using granule G3123215106-POCLOUD for test
INFO root:verify_collection.py:381 Sending harmony request https://harmony.earthdata.nasa.gov/C2251464495-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-38.0%3A38.0%29&subset=lon%28-171.0%3A171.0%29&granuleId=G3123215106-POCLOUD
INFO root:verify_collection.py:385 Submitted harmony job 7e4b270b-f6bb-40b9-9142-7b79cffdb062
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C2087216100-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 1m 3s]
Raw output
OSError: [Errno group not found: PRODUCT] 'PRODUCT'
ds = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7fe90a5a2f40>
group = '/METADATA/PRODUCT', mode = 'r'
create_group = <function _netcdf4_create_group at 0x7fe90ee56950>
def _nc4_require_group(ds, group, mode, create_group=_netcdf4_create_group):
if group in {None, "", "/"}:
# use the root group
return ds
else:
# make sure it's a string
if not isinstance(group, str):
raise ValueError("group must be a string or None")
# support path-like syntax
path = group.strip("/").split("/")
for key in path:
try:
> ds = ds.groups[key]
E KeyError: 'PRODUCT'
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:190: KeyError
During handling of the above exception, another exception occurred:
collection_concept_id = 'C2087216100-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2087216100-GES_DISC', 'concept-id': 'G3130460866-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2087216100-GES_DISC'}]}, 'meta': {'association-details': {'collect...m/variable/v1.9.0', 'Version': '1.9.0'}, 'Name': 'METADATA/QA_STATISTICS/aerosol_mid_pressure_histogram_bounds'}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw6/test_spatial_subset_C2087216100')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
g = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=g, decode_times=False)
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:432:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
verify_collection.py:423: in group_walk
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=g, decode_times=False)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/api.py:571: in open_dataset
backend_ds = backend.open_dataset(
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:646: in open_dataset
store = NetCDF4DataStore.open(
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:409: in open
return cls(manager, group=group, mode=mode, lock=lock, autoclose=autoclose)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:356: in __init__
self.format = self.ds.data_model
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:418: in ds
return self._acquire()
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:413: in _acquire
ds = _nc4_require_group(root, self._group, self._mode)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
ds = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7fe90a5a2f40>
group = '/METADATA/PRODUCT', mode = 'r'
create_group = <function _netcdf4_create_group at 0x7fe90ee56950>
def _nc4_require_group(ds, group, mode, create_group=_netcdf4_create_group):
if group in {None, "", "/"}:
# use the root group
return ds
else:
# make sure it's a string
if not isinstance(group, str):
raise ValueError("group must be a string or None")
# support path-like syntax
path = group.strip("/").split("/")
for key in path:
try:
ds = ds.groups[key]
except KeyError as e:
if mode != "r":
ds = create_group(ds, key)
else:
# wrap error to provide slightly more helpful message
> raise OSError(f"group not found: {key}", e)
E OSError: [Errno group not found: PRODUCT] 'PRODUCT'
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:196: OSError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:365 Using granule G3130460866-GES_DISC for test
INFO root:verify_collection.py:381 Sending harmony request https://harmony.earthdata.nasa.gov/C2087216100-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-76.4551%3A-59.9669%29&subset=lon%28-159.4374%3A127.6754%29&granuleId=G3130460866-GES_DISC
INFO root:verify_collection.py:385 Submitted harmony job 9497fa2c-327e-4740-83a0-99da7aae0801
INFO root:verify_collection.py:391 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw6/test_spatial_subset_C2087216100/69128064_S5P_OFFL_L2_AER_LH_20240624T031300_20240624T045430_34699_03_020600_20240625T190510_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_temporal_subset[C2068529568-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 35s]
Raw output
harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
collection_concept_id = 'C2068529568-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2068529568-POCLOUD', 'concept-id': 'G2586738585-POCLOUD', 'concept-type': 'granul...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2068529568-POCLOUD'}]}, 'meta': {'association-details': {'collecti...ze': 4193, 'Type': 'ALONG_TRACK_DIMENSION'}, {'Name': 'ni', 'Size': 243, 'Type': 'CROSS_TRACK_DIMENSION'}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw5/test_temporal_subset_C206852950')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_temporal_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
temporal_subset = get_half_temporal_extent(start_time, end_time)
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection,
granule_id=[granule_json['meta']['concept-id']],
temporal=temporal_subset)
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
> harmony_client.wait_for_processing(job_id, show_progress=True)
verify_collection.py:530:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7f456f85a860>
job_id = 'b075414e-5686-4a2a-9996-79eac2efd639', show_progress = True
def wait_for_processing(self, job_id: str, show_progress: bool = False) -> None:
"""Retrieve a submitted job's completion status in percent.
Args:
job_id: UUID string for the job you wish to interrogate.
Returns:
The job's processing progress as a percentage.
:raises
Exception: This can happen if an invalid job_id is provided or Harmony services
can't be reached.
"""
# How often to refresh the screen for progress updates and animating spinners.
ui_update_interval = 0.33 # in seconds
running_w_errors_logged = False
intervals = round(self.check_interval / ui_update_interval)
if show_progress:
with progressbar.ProgressBar(max_value=100, widgets=progressbar_widgets) as bar:
progress = 0
while progress < 100:
progress, status, message = self.progress(job_id)
if status == 'failed':
> raise ProcessingFailedException(job_id, message)
E harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:986: ProcessingFailedException
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:511 Using granule G2586738585-POCLOUD for test
INFO root:verify_collection.py:524 Sending harmony request https://harmony.earthdata.nasa.gov/C2068529568-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=time%28%222023-01-11T10%3A04%3A49%22%3A%222023-01-11T10%3A54%3A15%22%29&granuleId=G2586738585-POCLOUD
INFO root:verify_collection.py:528 Submitted harmony job b075414e-5686-4a2a-9996-79eac2efd639
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_temporal_subset[C2724057189-LARC_CLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 3s]
Raw output
ValueError: time data '2023-12-30T23:24:23+00:00' does not match format '%Y-%m-%dT%H:%M:%S.%fZ'
collection_concept_id = 'C2724057189-LARC_CLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2724057189-LARC_CLOUD', 'concept-id': 'G2829371222-LARC_CLOUD', 'concept-type': '... 'ProductionDateTime': '2023-12-31T03:28:32+00:00'}, 'GranuleUR': 'TEMPO_NO2_L2_V01_20231230T232423Z_S011G06.nc', ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2724057189-LARC_CLOUD'}]}, 'meta': {'association-details': {'colle...acted from _FillValue metadata attribute', 'Type': 'SCIENCE_FILLVALUE', 'Value': -1.0000000150474662e+30}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw2/test_temporal_subset_C272405710')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_temporal_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
> temporal_subset = get_half_temporal_extent(start_time, end_time)
verify_collection.py:515:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
verify_collection.py:167: in get_half_temporal_extent
start_dt = datetime.strptime(start, '%Y-%m-%dT%H:%M:%S.%fZ')
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/_strptime.py:568: in _strptime_datetime
tt, fraction, gmtoff_fraction = _strptime(data_string, format)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
data_string = '2023-12-30T23:24:23+00:00', format = '%Y-%m-%dT%H:%M:%S.%fZ'
def _strptime(data_string, format="%a %b %d %H:%M:%S %Y"):
"""Return a 2-tuple consisting of a time struct and an int containing
the number of microseconds based on the input string and the
format string."""
for index, arg in enumerate([data_string, format]):
if not isinstance(arg, str):
msg = "strptime() argument {} must be str, not {}"
raise TypeError(msg.format(index, type(arg)))
global _TimeRE_cache, _regex_cache
with _cache_lock:
locale_time = _TimeRE_cache.locale_time
if (_getlang() != locale_time.lang or
time.tzname != locale_time.tzname or
time.daylight != locale_time.daylight):
_TimeRE_cache = TimeRE()
_regex_cache.clear()
locale_time = _TimeRE_cache.locale_time
if len(_regex_cache) > _CACHE_MAX_SIZE:
_regex_cache.clear()
format_regex = _regex_cache.get(format)
if not format_regex:
try:
format_regex = _TimeRE_cache.compile(format)
# KeyError raised when a bad format is found; can be specified as
# \\, in which case it was a stray % but with a space after it
except KeyError as err:
bad_directive = err.args[0]
if bad_directive == "\\":
bad_directive = "%"
del err
raise ValueError("'%s' is a bad directive in format '%s'" %
(bad_directive, format)) from None
# IndexError only occurs when the format string is "%"
except IndexError:
raise ValueError("stray %% in format '%s'" % format) from None
_regex_cache[format] = format_regex
found = format_regex.match(data_string)
if not found:
> raise ValueError("time data %r does not match format %r" %
(data_string, format))
E ValueError: time data '2023-12-30T23:24:23+00:00' does not match format '%Y-%m-%dT%H:%M:%S.%fZ'
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/_strptime.py:349: ValueError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:511 Using granule G2829371222-LARC_CLOUD for test
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1442068505-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 34s]
Raw output
OSError: [Errno group not found: PRODUCT] 'PRODUCT'
ds = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7fe90a507040>
group = '/METADATA/PRODUCT', mode = 'r'
create_group = <function _netcdf4_create_group at 0x7fe90ee56950>
def _nc4_require_group(ds, group, mode, create_group=_netcdf4_create_group):
if group in {None, "", "/"}:
# use the root group
return ds
else:
# make sure it's a string
if not isinstance(group, str):
raise ValueError("group must be a string or None")
# support path-like syntax
path = group.strip("/").split("/")
for key in path:
try:
> ds = ds.groups[key]
E KeyError: 'PRODUCT'
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:190: KeyError
During handling of the above exception, another exception occurred:
collection_concept_id = 'C1442068505-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1442068505-GES_DISC', 'concept-id': 'G1628685470-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1442068505-GES_DISC'}]}, 'meta': {'association-details': {'collect...hdata.nasa.gov/umm/variable/v1.9.0', 'Version': '1.9.0'}, 'Name': 'PRODUCT/methane_mixing_ratio_precision', ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw6/test_spatial_subset_C1442068500')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
g = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=g, decode_times=False)
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:432:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
verify_collection.py:423: in group_walk
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=g, decode_times=False)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/api.py:571: in open_dataset
backend_ds = backend.open_dataset(
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:646: in open_dataset
store = NetCDF4DataStore.open(
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:409: in open
return cls(manager, group=group, mode=mode, lock=lock, autoclose=autoclose)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:356: in __init__
self.format = self.ds.data_model
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:418: in ds
return self._acquire()
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:413: in _acquire
ds = _nc4_require_group(root, self._group, self._mode)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
ds = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7fe90a507040>
group = '/METADATA/PRODUCT', mode = 'r'
create_group = <function _netcdf4_create_group at 0x7fe90ee56950>
def _nc4_require_group(ds, group, mode, create_group=_netcdf4_create_group):
if group in {None, "", "/"}:
# use the root group
return ds
else:
# make sure it's a string
if not isinstance(group, str):
raise ValueError("group must be a string or None")
# support path-like syntax
path = group.strip("/").split("/")
for key in path:
try:
ds = ds.groups[key]
except KeyError as e:
if mode != "r":
ds = create_group(ds, key)
else:
# wrap error to provide slightly more helpful message
> raise OSError(f"group not found: {key}", e)
E OSError: [Errno group not found: PRODUCT] 'PRODUCT'
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:196: OSError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:365 Using granule G1628685470-GES_DISC for test
INFO root:verify_collection.py:381 Sending harmony request https://harmony.earthdata.nasa.gov/C1442068505-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-82.468625%3A-64.100375%29&subset=lon%28-112.00605%3A163.26405%29&granuleId=G1628685470-GES_DISC
INFO root:verify_collection.py:385 Submitted harmony job 62fae8ea-8939-4193-a914-7f1592db5466
INFO root:verify_collection.py:391 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw6/test_spatial_subset_C1442068500/69128218_S5P_OFFL_L2_CH4_20190806T003836_20190806T022006_09387_01_010302_20190812T015759_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_temporal_subset[C2832221740-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 51s]
Raw output
harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
collection_concept_id = 'C2832221740-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2832221740-POCLOUD', 'concept-id': 'G3059748792-POCLOUD', 'concept-type': 'granul...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2832221740-POCLOUD'}]}, 'meta': {'association-details': {'collecti...rization_2', 'Size': 2, 'Type': 'OTHER'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -9999.0}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw4/test_temporal_subset_C283222170')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_temporal_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
temporal_subset = get_half_temporal_extent(start_time, end_time)
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection,
granule_id=[granule_json['meta']['concept-id']],
temporal=temporal_subset)
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
> harmony_client.wait_for_processing(job_id, show_progress=True)
verify_collection.py:530:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7f0e687f5e70>
job_id = 'cad06a99-4273-4177-826a-aaf59a36ca2a', show_progress = True
def wait_for_processing(self, job_id: str, show_progress: bool = False) -> None:
"""Retrieve a submitted job's completion status in percent.
Args:
job_id: UUID string for the job you wish to interrogate.
Returns:
The job's processing progress as a percentage.
:raises
Exception: This can happen if an invalid job_id is provided or Harmony services
can't be reached.
"""
# How often to refresh the screen for progress updates and animating spinners.
ui_update_interval = 0.33 # in seconds
running_w_errors_logged = False
intervals = round(self.check_interval / ui_update_interval)
if show_progress:
with progressbar.ProgressBar(max_value=100, widgets=progressbar_widgets) as bar:
progress = 0
while progress < 100:
progress, status, message = self.progress(job_id)
if status == 'failed':
> raise ProcessingFailedException(job_id, message)
E harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:986: ProcessingFailedException
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:511 Using granule G3059748792-POCLOUD for test
INFO root:verify_collection.py:524 Sending harmony request https://harmony.earthdata.nasa.gov/C2832221740-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=time%28%222024-05-29T21%3A47%3A47.250000%22%3A%222024-05-29T22%3A38%3A39.750000%22%29&granuleId=G3059748792-POCLOUD
INFO root:verify_collection.py:528 Submitted harmony job cad06a99-4273-4177-826a-aaf59a36ca2a
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_temporal_subset[C2036877509-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 33s]
Raw output
harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
collection_concept_id = 'C2036877509-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2036877509-POCLOUD', 'concept-id': 'G3130431005-POCLOUD', 'concept-type': 'granul...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2036877509-POCLOUD'}]}, 'meta': {'association-details': {'collecti...ize': 409, 'Type': 'CROSS_TRACK_DIMENSION'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -128}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw2/test_temporal_subset_C203687750')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_temporal_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
temporal_subset = get_half_temporal_extent(start_time, end_time)
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection,
granule_id=[granule_json['meta']['concept-id']],
temporal=temporal_subset)
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
> harmony_client.wait_for_processing(job_id, show_progress=True)
verify_collection.py:530:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7f2c1ac7e8c0>
job_id = 'a15868a0-6522-4a39-8c46-2a07f7c465df', show_progress = True
def wait_for_processing(self, job_id: str, show_progress: bool = False) -> None:
"""Retrieve a submitted job's completion status in percent.
Args:
job_id: UUID string for the job you wish to interrogate.
Returns:
The job's processing progress as a percentage.
:raises
Exception: This can happen if an invalid job_id is provided or Harmony services
can't be reached.
"""
# How often to refresh the screen for progress updates and animating spinners.
ui_update_interval = 0.33 # in seconds
running_w_errors_logged = False
intervals = round(self.check_interval / ui_update_interval)
if show_progress:
with progressbar.ProgressBar(max_value=100, widgets=progressbar_widgets) as bar:
progress = 0
while progress < 100:
progress, status, message = self.progress(job_id)
if status == 'failed':
> raise ProcessingFailedException(job_id, message)
E harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:986: ProcessingFailedException
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:511 Using granule G3130431005-POCLOUD for test
INFO root:verify_collection.py:524 Sending harmony request https://harmony.earthdata.nasa.gov/C2036877509-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=time%28%222024-06-25T19%3A59%3A48.500000%22%3A%222024-06-25T20%3A50%3A27.500000%22%29&granuleId=G3130431005-POCLOUD
INFO root:verify_collection.py:528 Submitted harmony job a15868a0-6522-4a39-8c46-2a07f7c465df
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_temporal_subset[C2847232536-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 33s]
Raw output
harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
collection_concept_id = 'C2847232536-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2847232536-POCLOUD', 'concept-id': 'G3130420622-POCLOUD', 'concept-type': 'granul...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2847232536-POCLOUD'}]}, 'meta': {'association-details': {'collecti...ze': 3200, 'Type': 'CROSS_TRACK_DIMENSION'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -128}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw5/test_temporal_subset_C284723250')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_temporal_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
temporal_subset = get_half_temporal_extent(start_time, end_time)
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection,
granule_id=[granule_json['meta']['concept-id']],
temporal=temporal_subset)
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
> harmony_client.wait_for_processing(job_id, show_progress=True)
verify_collection.py:530:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7f456f61a4d0>
job_id = 'ea525174-d720-4c7a-81c3-689feac9cf5f', show_progress = True
def wait_for_processing(self, job_id: str, show_progress: bool = False) -> None:
"""Retrieve a submitted job's completion status in percent.
Args:
job_id: UUID string for the job you wish to interrogate.
Returns:
The job's processing progress as a percentage.
:raises
Exception: This can happen if an invalid job_id is provided or Harmony services
can't be reached.
"""
# How often to refresh the screen for progress updates and animating spinners.
ui_update_interval = 0.33 # in seconds
running_w_errors_logged = False
intervals = round(self.check_interval / ui_update_interval)
if show_progress:
with progressbar.ProgressBar(max_value=100, widgets=progressbar_widgets) as bar:
progress = 0
while progress < 100:
progress, status, message = self.progress(job_id)
if status == 'failed':
> raise ProcessingFailedException(job_id, message)
E harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:986: ProcessingFailedException
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:511 Using granule G3130420622-POCLOUD for test
INFO root:verify_collection.py:524 Sending harmony request https://harmony.earthdata.nasa.gov/C2847232536-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=time%28%222024-06-25T20%3A37%3A32.250000%22%3A%222024-06-25T20%3A38%3A14.750000%22%29&granuleId=G3130420622-POCLOUD
INFO root:verify_collection.py:528 Submitted harmony job ea525174-d720-4c7a-81c3-689feac9cf5f
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_temporal_subset[C2205618339-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 36s]
Raw output
harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
collection_concept_id = 'C2205618339-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2205618339-POCLOUD', 'concept-id': 'G2214736338-POCLOUD', 'concept-type': 'granul...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2205618339-POCLOUD'}]}, 'meta': {'association-details': {'collecti...ze': 6922, 'Type': 'CROSS_TRACK_DIMENSION'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -128}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw5/test_temporal_subset_C220561830')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_temporal_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
temporal_subset = get_half_temporal_extent(start_time, end_time)
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection,
granule_id=[granule_json['meta']['concept-id']],
temporal=temporal_subset)
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
> harmony_client.wait_for_processing(job_id, show_progress=True)
verify_collection.py:530:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7f456f6c5b40>
job_id = '8eb05572-2ca0-4079-93a4-de67ef366398', show_progress = True
def wait_for_processing(self, job_id: str, show_progress: bool = False) -> None:
"""Retrieve a submitted job's completion status in percent.
Args:
job_id: UUID string for the job you wish to interrogate.
Returns:
The job's processing progress as a percentage.
:raises
Exception: This can happen if an invalid job_id is provided or Harmony services
can't be reached.
"""
# How often to refresh the screen for progress updates and animating spinners.
ui_update_interval = 0.33 # in seconds
running_w_errors_logged = False
intervals = round(self.check_interval / ui_update_interval)
if show_progress:
with progressbar.ProgressBar(max_value=100, widgets=progressbar_widgets) as bar:
progress = 0
while progress < 100:
progress, status, message = self.progress(job_id)
if status == 'failed':
> raise ProcessingFailedException(job_id, message)
E harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:986: ProcessingFailedException
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:511 Using granule G2214736338-POCLOUD for test
INFO root:verify_collection.py:524 Sending harmony request https://harmony.earthdata.nasa.gov/C2205618339-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=time%28%222020-06-17T11%3A13%3A21.500000%22%3A%222020-06-17T11%3A41%3A06.500000%22%29&granuleId=G2214736338-POCLOUD
INFO root:verify_collection.py:528 Submitted harmony job 8eb05572-2ca0-4079-93a4-de67ef366398
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_temporal_subset[C2596986276-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 10m 0s]
Raw output
Failed: Timeout >600.0s
collection_concept_id = 'C2596986276-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2596986276-POCLOUD', 'concept-id': 'G3130301193-POCLOUD', 'concept-type': 'granul...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2596986276-POCLOUD'}]}, 'meta': {'association-details': {'collecti...: 243, 'Type': 'CROSS_TRACK_DIMENSION'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -32768.0}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw9/test_temporal_subset_C259698620')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_temporal_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
temporal_subset = get_half_temporal_extent(start_time, end_time)
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection,
granule_id=[granule_json['meta']['concept-id']],
temporal=temporal_subset)
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
> harmony_client.wait_for_processing(job_id, show_progress=True)
verify_collection.py:530:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:984: in wait_for_processing
progress, status, message = self.progress(job_id)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:955: in progress
response = session.get(self._status_url(job_id))
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/requests/sessions.py:602: in get
return self.request("GET", url, **kwargs)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/requests/sessions.py:589: in request
resp = self.send(prep, **send_kwargs)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/requests/sessions.py:703: in send
r = adapter.send(request, **kwargs)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/requests/adapters.py:589: in send
resp = conn.urlopen(
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/urllib3/connectionpool.py:793: in urlopen
response = self._make_request(
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/urllib3/connectionpool.py:537: in _make_request
response = conn.getresponse()
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/urllib3/connection.py:466: in getresponse
httplib_response = super().getresponse()
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/http/client.py:1375: in getresponse
response.begin()
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/http/client.py:318: in begin
version, status, reason = self._read_status()
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/http/client.py:279: in _read_status
line = str(self.fp.readline(_MAXLINE + 1), "iso-8859-1")
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/socket.py:705: in readinto
return self._sock.recv_into(b)
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/ssl.py:1307: in recv_into
return self.read(nbytes, buffer)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <ssl.SSLSocket [closed] fd=-1, family=AddressFamily.AF_INET, type=SocketKind.SOCK_STREAM, proto=6>
len = 8192, buffer = <memory at 0x7fbcba67bf40>
def read(self, len=1024, buffer=None):
"""Read up to LEN bytes and return them.
Return zero-length string on EOF."""
self._checkClosed()
if self._sslobj is None:
raise ValueError("Read on closed or unwrapped SSL socket.")
try:
if buffer is not None:
> return self._sslobj.read(len, buffer)
E Failed: Timeout >600.0s
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/ssl.py:1163: Failed
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:511 Using granule G3130301193-POCLOUD for test
INFO root:verify_collection.py:524 Sending harmony request https://harmony.earthdata.nasa.gov/C2596986276-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=time%28%222024-06-25T16%3A58%3A44.500000%22%3A%222024-06-25T17%3A22%3A19.500000%22%29&granuleId=G3130301193-POCLOUD
INFO root:verify_collection.py:528 Submitted harmony job 9f86afd6-df16-4e2d-8c98-6049ab0bcd30
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_temporal_subset[C2499940517-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 36s]
Raw output
harmony.harmony.ProcessingFailedException: WorkItem failed: Could not get result item file size
collection_concept_id = 'C2499940517-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2499940517-POCLOUD', 'concept-id': 'G2529918741-POCLOUD', 'concept-type': 'granul...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2499940517-POCLOUD'}]}, 'meta': {'association-details': {'collecti..._TRACK_DIMENSION'}, {'Name': 'ni', 'Size': 120, 'Type': 'CROSS_TRACK_DIMENSION'}], 'LongName': 'longitude', ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw3/test_temporal_subset_C249994050')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_temporal_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
temporal_subset = get_half_temporal_extent(start_time, end_time)
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection,
granule_id=[granule_json['meta']['concept-id']],
temporal=temporal_subset)
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
> harmony_client.wait_for_processing(job_id, show_progress=True)
verify_collection.py:530:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7fed3e0ca6b0>
job_id = 'ccdac7c6-32de-409c-9312-ec7b94dbd01e', show_progress = True
def wait_for_processing(self, job_id: str, show_progress: bool = False) -> None:
"""Retrieve a submitted job's completion status in percent.
Args:
job_id: UUID string for the job you wish to interrogate.
Returns:
The job's processing progress as a percentage.
:raises
Exception: This can happen if an invalid job_id is provided or Harmony services
can't be reached.
"""
# How often to refresh the screen for progress updates and animating spinners.
ui_update_interval = 0.33 # in seconds
running_w_errors_logged = False
intervals = round(self.check_interval / ui_update_interval)
if show_progress:
with progressbar.ProgressBar(max_value=100, widgets=progressbar_widgets) as bar:
progress = 0
while progress < 100:
progress, status, message = self.progress(job_id)
if status == 'failed':
> raise ProcessingFailedException(job_id, message)
E harmony.harmony.ProcessingFailedException: WorkItem failed: Could not get result item file size
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:986: ProcessingFailedException
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:511 Using granule G2529918741-POCLOUD for test
INFO root:verify_collection.py:524 Sending harmony request https://harmony.earthdata.nasa.gov/C2499940517-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=time%28%222016-02-23T04%3A21%3A40%22%3A%222016-02-23T04%3A23%3A08%22%29&granuleId=G2529918741-POCLOUD
INFO root:verify_collection.py:528 Submitted harmony job ccdac7c6-32de-409c-9312-ec7b94dbd01e
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_temporal_subset[C2596983413-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 31s]
Raw output
harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
collection_concept_id = 'C2596983413-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2596983413-POCLOUD', 'concept-id': 'G3130301128-POCLOUD', 'concept-type': 'granul...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2596983413-POCLOUD'}]}, 'meta': {'association-details': {'collecti...: 243, 'Type': 'CROSS_TRACK_DIMENSION'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -32768.0}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw5/test_temporal_subset_C259698340')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_temporal_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
temporal_subset = get_half_temporal_extent(start_time, end_time)
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection,
granule_id=[granule_json['meta']['concept-id']],
temporal=temporal_subset)
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
> harmony_client.wait_for_processing(job_id, show_progress=True)
verify_collection.py:530:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7f456f871990>
job_id = '27a8cc14-1049-4f04-b2c7-71bf69728a17', show_progress = True
def wait_for_processing(self, job_id: str, show_progress: bool = False) -> None:
"""Retrieve a submitted job's completion status in percent.
Args:
job_id: UUID string for the job you wish to interrogate.
Returns:
The job's processing progress as a percentage.
:raises
Exception: This can happen if an invalid job_id is provided or Harmony services
can't be reached.
"""
# How often to refresh the screen for progress updates and animating spinners.
ui_update_interval = 0.33 # in seconds
running_w_errors_logged = False
intervals = round(self.check_interval / ui_update_interval)
if show_progress:
with progressbar.ProgressBar(max_value=100, widgets=progressbar_widgets) as bar:
progress = 0
while progress < 100:
progress, status, message = self.progress(job_id)
if status == 'failed':
> raise ProcessingFailedException(job_id, message)
E harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:986: ProcessingFailedException
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:511 Using granule G3130301128-POCLOUD for test
INFO root:verify_collection.py:524 Sending harmony request https://harmony.earthdata.nasa.gov/C2596983413-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=time%28%222024-06-25T10%3A36%3A07%22%3A%222024-06-25T11%3A25%3A33%22%29&granuleId=G3130301128-POCLOUD
INFO root:verify_collection.py:528 Submitted harmony job 27a8cc14-1049-4f04-b2c7-71bf69728a17
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_temporal_subset[C2499940520-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 36s]
Raw output
harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
collection_concept_id = 'C2499940520-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2499940520-POCLOUD', 'concept-id': 'G2521659785-POCLOUD', 'concept-type': 'granul...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2499940520-POCLOUD'}]}, 'meta': {'association-details': {'collecti... 'Type': 'CROSS_TRACK_DIMENSION'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -3.4028235e+38}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw4/test_temporal_subset_C249994050')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_temporal_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
temporal_subset = get_half_temporal_extent(start_time, end_time)
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection,
granule_id=[granule_json['meta']['concept-id']],
temporal=temporal_subset)
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
> harmony_client.wait_for_processing(job_id, show_progress=True)
verify_collection.py:530:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7f0e68a90ac0>
job_id = '1ade3ccf-08cd-41c0-b689-0cbc5f180492', show_progress = True
def wait_for_processing(self, job_id: str, show_progress: bool = False) -> None:
"""Retrieve a submitted job's completion status in percent.
Args:
job_id: UUID string for the job you wish to interrogate.
Returns:
The job's processing progress as a percentage.
:raises
Exception: This can happen if an invalid job_id is provided or Harmony services
can't be reached.
"""
# How often to refresh the screen for progress updates and animating spinners.
ui_update_interval = 0.33 # in seconds
running_w_errors_logged = False
intervals = round(self.check_interval / ui_update_interval)
if show_progress:
with progressbar.ProgressBar(max_value=100, widgets=progressbar_widgets) as bar:
progress = 0
while progress < 100:
progress, status, message = self.progress(job_id)
if status == 'failed':
> raise ProcessingFailedException(job_id, message)
E harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:986: ProcessingFailedException
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:511 Using granule G2521659785-POCLOUD for test
INFO root:verify_collection.py:524 Sending harmony request https://harmony.earthdata.nasa.gov/C2499940520-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=time%28%222015-12-04T05%3A38%3A52.500000%22%3A%222015-12-04T05%3A52%3A37.500000%22%29&granuleId=G2521659785-POCLOUD
INFO root:verify_collection.py:528 Submitted harmony job 1ade3ccf-08cd-41c0-b689-0cbc5f180492
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_temporal_subset[C1996881807-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 32s]
Raw output
harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
collection_concept_id = 'C1996881807-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1996881807-POCLOUD', 'concept-id': 'G2011686539-POCLOUD', 'concept-type': 'granul...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1996881807-POCLOUD'}]}, 'meta': {'association-details': {'collecti...ze': 3200, 'Type': 'CROSS_TRACK_DIMENSION'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -128}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw8/test_temporal_subset_C199688180')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_temporal_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
temporal_subset = get_half_temporal_extent(start_time, end_time)
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection,
granule_id=[granule_json['meta']['concept-id']],
temporal=temporal_subset)
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
> harmony_client.wait_for_processing(job_id, show_progress=True)
verify_collection.py:530:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7f9decb40b80>
job_id = 'ebe550d7-e547-42e4-b516-ede67d4ea687', show_progress = True
def wait_for_processing(self, job_id: str, show_progress: bool = False) -> None:
"""Retrieve a submitted job's completion status in percent.
Args:
job_id: UUID string for the job you wish to interrogate.
Returns:
The job's processing progress as a percentage.
:raises
Exception: This can happen if an invalid job_id is provided or Harmony services
can't be reached.
"""
# How often to refresh the screen for progress updates and animating spinners.
ui_update_interval = 0.33 # in seconds
running_w_errors_logged = False
intervals = round(self.check_interval / ui_update_interval)
if show_progress:
with progressbar.ProgressBar(max_value=100, widgets=progressbar_widgets) as bar:
progress = 0
while progress < 100:
progress, status, message = self.progress(job_id)
if status == 'failed':
> raise ProcessingFailedException(job_id, message)
E harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:986: ProcessingFailedException
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:511 Using granule G2011686539-POCLOUD for test
INFO root:verify_collection.py:524 Sending harmony request https://harmony.earthdata.nasa.gov/C1996881807-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=time%28%222016-02-25T18%3A20%3A46%22%3A%222016-02-25T18%3A21%3A28%22%29&granuleId=G2011686539-POCLOUD
INFO root:verify_collection.py:528 Submitted harmony job ebe550d7-e547-42e4-b516-ede67d4ea687
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_temporal_subset[C2036878029-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 45s]
Raw output
harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
collection_concept_id = 'C2036878029-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2036878029-POCLOUD', 'concept-id': 'G3130476207-POCLOUD', 'concept-type': 'granul...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2036878029-POCLOUD'}]}, 'meta': {'association-details': {'collecti...ze': 3712, 'Type': 'CROSS_TRACK_DIMENSION'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -128}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw7/test_temporal_subset_C203687800')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_temporal_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
temporal_subset = get_half_temporal_extent(start_time, end_time)
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection,
granule_id=[granule_json['meta']['concept-id']],
temporal=temporal_subset)
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
> harmony_client.wait_for_processing(job_id, show_progress=True)
verify_collection.py:530:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7fbb1c7928f0>
job_id = '057b91e8-d6f3-4333-87f0-2fc4b35d52ca', show_progress = True
def wait_for_processing(self, job_id: str, show_progress: bool = False) -> None:
"""Retrieve a submitted job's completion status in percent.
Args:
job_id: UUID string for the job you wish to interrogate.
Returns:
The job's processing progress as a percentage.
:raises
Exception: This can happen if an invalid job_id is provided or Harmony services
can't be reached.
"""
# How often to refresh the screen for progress updates and animating spinners.
ui_update_interval = 0.33 # in seconds
running_w_errors_logged = False
intervals = round(self.check_interval / ui_update_interval)
if show_progress:
with progressbar.ProgressBar(max_value=100, widgets=progressbar_widgets) as bar:
progress = 0
while progress < 100:
progress, status, message = self.progress(job_id)
if status == 'failed':
> raise ProcessingFailedException(job_id, message)
E harmony.harmony.ProcessingFailedException: WorkItem failed: podaac/l2ss-py:2.10.0: Service request failed with an unknown error
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:986: ProcessingFailedException
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:511 Using granule G3130476207-POCLOUD for test
INFO root:verify_collection.py:524 Sending harmony request https://harmony.earthdata.nasa.gov/C2036878029-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=time%28%222024-06-25T21%3A33%3A05.500000%22%3A%222024-06-25T21%3A39%3A16.500000%22%29&granuleId=G3130476207-POCLOUD
INFO root:verify_collection.py:528 Submitted harmony job 057b91e8-d6f3-4333-87f0-2fc4b35d52ca
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_temporal_subset[C2724037909-LARC_CLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 5s]
Raw output
ValueError: time data '2023-12-30T23:24:23+00:00' does not match format '%Y-%m-%dT%H:%M:%S.%fZ'
collection_concept_id = 'C2724037909-LARC_CLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2724037909-LARC_CLOUD', 'concept-id': 'G2829370114-LARC_CLOUD', 'concept-type': '...ProductionDateTime': '2023-12-31T02:12:29+00:00'}, 'GranuleUR': 'TEMPO_CLDO4_L2_V01_20231230T232423Z_S011G06.nc', ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2724037909-LARC_CLOUD'}]}, 'meta': {'association-details': {'colle...acted from _FillValue metadata attribute', 'Type': 'SCIENCE_FILLVALUE', 'Value': -1.0000000150474662e+30}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw5/test_temporal_subset_C272403790')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...M1SxaPfRwaV4PnJa7zbVFlZLcvBhRvf4vqzuF5YM7NH6FVZLvYlGKaafF6MKL_It0xU_qyGVtYqXMQZPxtw3-X8U0FJk7UpNs1KArBsF0dKaHHXtrfp8lA'
@pytest.mark.timeout(600)
def test_temporal_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
> temporal_subset = get_half_temporal_extent(start_time, end_time)
verify_collection.py:515:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
verify_collection.py:167: in get_half_temporal_extent
start_dt = datetime.strptime(start, '%Y-%m-%dT%H:%M:%S.%fZ')
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/_strptime.py:568: in _strptime_datetime
tt, fraction, gmtoff_fraction = _strptime(data_string, format)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
data_string = '2023-12-30T23:24:23+00:00', format = '%Y-%m-%dT%H:%M:%S.%fZ'
def _strptime(data_string, format="%a %b %d %H:%M:%S %Y"):
"""Return a 2-tuple consisting of a time struct and an int containing
the number of microseconds based on the input string and the
format string."""
for index, arg in enumerate([data_string, format]):
if not isinstance(arg, str):
msg = "strptime() argument {} must be str, not {}"
raise TypeError(msg.format(index, type(arg)))
global _TimeRE_cache, _regex_cache
with _cache_lock:
locale_time = _TimeRE_cache.locale_time
if (_getlang() != locale_time.lang or
time.tzname != locale_time.tzname or
time.daylight != locale_time.daylight):
_TimeRE_cache = TimeRE()
_regex_cache.clear()
locale_time = _TimeRE_cache.locale_time
if len(_regex_cache) > _CACHE_MAX_SIZE:
_regex_cache.clear()
format_regex = _regex_cache.get(format)
if not format_regex:
try:
format_regex = _TimeRE_cache.compile(format)
# KeyError raised when a bad format is found; can be specified as
# \\, in which case it was a stray % but with a space after it
except KeyError as err:
bad_directive = err.args[0]
if bad_directive == "\\":
bad_directive = "%"
del err
raise ValueError("'%s' is a bad directive in format '%s'" %
(bad_directive, format)) from None
# IndexError only occurs when the format string is "%"
except IndexError:
raise ValueError("stray %% in format '%s'" % format) from None
_regex_cache[format] = format_regex
found = format_regex.match(data_string)
if not found:
> raise ValueError("time data %r does not match format %r" %
(data_string, format))
E ValueError: time data '2023-12-30T23:24:23+00:00' does not match format '%Y-%m-%dT%H:%M:%S.%fZ'
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/_strptime.py:349: ValueError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:511 Using granule G2829370114-LARC_CLOUD for test
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