def open_dataset(self,
time_range: TimeRangeLike.TYPE = None,
region: PolygonLike.TYPE = None,
var_names: VarNamesLike.TYPE = None,
protocol: str = None) -> Any:
time_range = TimeRangeLike.convert(time_range) if time_range else None
var_names = VarNamesLike.convert(var_names) if var_names else None
selected_file_list = self._find_files(time_range)
if not selected_file_list:
msg = 'CCI Open Data Portal data source "{}"\ndoes not seem to have any datasets'.format(self.id)
if time_range is not None:
msg += ' in given time range {}'.format(TimeRangeLike.format(time_range))
raise DataAccessError(msg)
files = self._get_urls_list(selected_file_list, _ODP_PROTOCOL_OPENDAP)
try:
ds = open_xarray_dataset(files)
if region:
ds = normalize_impl(ds)
ds = subset_spatial_impl(ds, region)
if var_names:
ds = ds.drop([var_name for var_name in ds.data_vars.keys() if var_name not in var_names])
return ds
except OSError as e:
if time_range:
raise DataAccessError("Cannot open remote dataset for time range {}:\n"
"{}"
.format(TimeRangeLike.format(time_range), e), source=self) from e
else:
raise DataAccessError("Cannot open remote dataset:\n"
"{}"
.format(TimeRangeLike.format(time_range), e), source=self) from e
def open_dataset(self,
time_range: TimeRangeLike.TYPE = None,
region: PolygonLike.TYPE = None,
var_names: VarNamesLike.TYPE = None,
protocol: str = None) -> Any:
time_range = TimeRangeLike.convert(time_range) if time_range else None
if region:
region = PolygonLike.convert(region)
if var_names:
var_names = VarNamesLike.convert(var_names)
paths = []
if time_range:
time_series = list(self._files.values())
file_paths = list(self._files.keys())
for i in range(len(time_series)):
if time_series[i]:
if isinstance(time_series[i], Tuple) and \
time_series[i][0] >= time_range[0] and \
time_series[i][1] <= time_range[1]:
paths.extend(self._resolve_file_path(file_paths[i]))
elif isinstance(
time_series[i], datetime
) and time_range[0] <= time_series[i] < time_range[1]:
paths.extend(self._resolve_file_path(file_paths[i]))
else:
for file in self._files.items():
paths.extend(self._resolve_file_path(file[0]))
if paths:
paths = sorted(set(paths))
try:
ds = open_xarray_dataset(paths)
if region:
ds = normalize_impl(ds)
ds = subset_spatial_impl(ds, region)
if var_names:
ds = ds.drop([
var_name for var_name in ds.data_vars.keys()
if var_name not in var_names
])
return ds
except OSError as e:
if time_range:
raise DataAccessError(
"Cannot open local dataset for time range {}:\n"
"{}".format(TimeRangeLike.format(time_range), e),
source=self) from e
else:
raise DataAccessError("Cannot open local dataset:\n"
"{}".format(e),
source=self) from e
else:
if time_range:
raise DataAccessError(
"No local datasets available for\nspecified time range {}".
format(TimeRangeLike.format(time_range)),
source=self)
else:
raise DataAccessError("No local datasets available",
source=self)
def _load_json_file(json_path: str):
if os.path.isfile(json_path):
try:
with open(json_path) as fp:
return json.load(fp=fp) or {}
except json.decoder.JSONDecodeError as e:
raise DataAccessError(
"Cannot load data source config from {}".format(
json_path)) from e
else:
raise DataAccessError(
"Data source config does not exists: {}".format(json_path))
def _fetch_solr_json(base_url,
query_args,
offset=0,
limit=3500,
timeout=10,
monitor: Monitor = Monitor.NONE):
"""
Return JSON value read from paginated Solr web-service.
"""
combined_json_dict = None
num_found = -1
# we don't know ahead of time how much request are necessary
with monitor.starting("Loading", 10):
while True:
monitor.progress(work=1)
paging_query_args = dict(query_args or {})
# noinspection PyArgumentList
paging_query_args.update(offset=offset,
limit=limit,
format='application/solr+json')
url = base_url + '?' + urllib.parse.urlencode(paging_query_args)
try:
with urllib.request.urlopen(url, timeout=timeout) as response:
json_text = response.read()
json_dict = json.loads(json_text.decode('utf-8'))
if num_found is -1:
num_found = json_dict.get('response',
{}).get('numFound', 0)
if not combined_json_dict:
combined_json_dict = json_dict
if num_found < limit:
break
else:
docs = json_dict.get('response', {}).get('docs', [])
combined_json_dict.get('response',
{}).get('docs', []).extend(docs)
if num_found < offset + limit:
break
except (urllib.error.HTTPError, urllib.error.URLError) as e:
raise DataAccessError(
"Downloading CCI Open Data Portal index failed: {}\n{}".
format(e, base_url)) from e
except socket.timeout:
raise DataAccessError(
"Downloading CCI Open Data Portal index failed: connection timeout\n{}"
.format(base_url))
offset += limit
return combined_json_dict
def _load_index(self):
try:
esgf_json_dict = _load_or_fetch_json(
_fetch_solr_json,
fetch_json_args=[
_ESGF_CEDA_URL,
dict(type='Dataset',
replica='false',
latest='true',
project='esacci')
],
cache_used=self._index_cache_used,
cache_dir=get_metadata_store_path(),
cache_json_filename='dataset-list.json',
cache_timestamp_filename='dataset-list-timestamp.json',
cache_expiration_days=self._index_cache_expiration_days)
cci_catalogue_service = EsaCciCatalogueService(_CSW_CEDA_URL)
csw_json_dict = _load_or_fetch_json(
cci_catalogue_service.getrecords,
fetch_json_args=[],
cache_used=self._index_cache_used,
cache_dir=get_metadata_store_path(),
cache_json_filename='catalogue.json',
cache_timestamp_filename='catalogue-timestamp.json',
cache_expiration_days=self._index_cache_expiration_days)
except DataAccessError as e:
raise DataAccessError(
"Cannot download CCI Open Data Portal ECV index:\n{}".format(
e),
source=self) from e
self._csw_data = csw_json_dict
self._esgf_data = esgf_json_dict
def test_with_source(self):
store = SimpleDataStore('hihi', [])
try:
raise DataAccessError("haha", source=store)
except DataAccessError as e:
self.assertEqual(str(e), 'Data store "hihi": haha')
self.assertIs(e.source, store)
self.assertIs(e.cause, None)
source = SimpleDataSource('hehe')
try:
raise DataAccessError("haha", source=source)
except DataAccessError as e:
self.assertEqual(str(e), 'Data source "hehe": haha')
self.assertIs(e.source, source)
self.assertIs(e.cause, None)
def test_plain(self):
try:
raise DataAccessError("haha")
except DataAccessError as e:
self.assertEqual(str(e), "haha")
self.assertEqual(e.source, None)
self.assertEqual(e.cause, None)
def test_with_cause(self):
e1 = ValueError("a > 5")
try:
raise DataAccessError("hoho") from e1
except DataAccessError as e2:
self.assertEqual(str(e2), "hoho")
self.assertIs(e2.source, None)
self.assertIs(e2.cause, e1)
def _save_data_source(self, data_source):
json_dict = data_source.to_json_dict()
dump_kwargs = dict(indent=' ', default=self._json_default_serializer)
file_name = os.path.join(self._store_dir, data_source.id + '.json')
try:
with open(file_name, 'w') as fp:
json.dump(json_dict, fp, **dump_kwargs)
except EnvironmentError as e:
raise DataAccessError("Couldn't save data source config file {}\n"
"{}".format(file_name, e),
source=self) from e
def _make_local(self,
local_ds: LocalDataSource,
time_range: TimeRangeLike.TYPE = None,
region: PolygonLike.TYPE = None,
var_names: VarNamesLike.TYPE = None,
monitor: Monitor = Monitor.NONE):
local_id = local_ds.id
time_range = TimeRangeLike.convert(time_range)
region = PolygonLike.convert(region)
var_names = VarNamesLike.convert(var_names)
time_range, region, var_names = self._apply_make_local_fixes(
time_range, region, var_names)
compression_level = get_config_value('NETCDF_COMPRESSION_LEVEL',
NETCDF_COMPRESSION_LEVEL)
compression_enabled = True if compression_level > 0 else False
do_update_of_verified_time_coverage_start_once = True
verified_time_coverage_start = None
verified_time_coverage_end = None
encoding_update = dict()
if compression_enabled:
encoding_update.update({
'zlib': True,
'complevel': compression_level
})
if region or var_names:
protocol = _ODP_PROTOCOL_OPENDAP
else:
protocol = _ODP_PROTOCOL_HTTP
local_path = os.path.join(local_ds.data_store.data_store_path,
local_id)
if not os.path.exists(local_path):
os.makedirs(local_path)
selected_file_list = self._find_files(time_range)
if not selected_file_list:
msg = 'CCI Open Data Portal data source "{}"\ndoes not seem to have any datasets'.format(
self.id)
if time_range is not None:
msg += ' in given time range {}'.format(
TimeRangeLike.format(time_range))
raise DataAccessError(msg)
try:
if protocol == _ODP_PROTOCOL_OPENDAP:
do_update_of_variables_meta_info_once = True
do_update_of_region_meta_info_once = True
files = self._get_urls_list(selected_file_list, protocol)
monitor.start('Sync ' + self.id, total_work=len(files))
for idx, dataset_uri in enumerate(files):
child_monitor = monitor.child(work=1)
file_name = os.path.basename(dataset_uri)
local_filepath = os.path.join(local_path, file_name)
time_coverage_start = selected_file_list[idx][1]
time_coverage_end = selected_file_list[idx][2]
try:
child_monitor.start(label=file_name, total_work=1)
remote_dataset = xr.open_dataset(dataset_uri)
if var_names:
remote_dataset = remote_dataset.drop([
var_name for var_name in
remote_dataset.data_vars.keys()
if var_name not in var_names
])
if region:
remote_dataset = normalize_impl(remote_dataset)
remote_dataset = subset_spatial_impl(
remote_dataset, region)
geo_lon_min, geo_lat_min, geo_lon_max, geo_lat_max = region.bounds
remote_dataset.attrs[
'geospatial_lat_min'] = geo_lat_min
remote_dataset.attrs[
'geospatial_lat_max'] = geo_lat_max
remote_dataset.attrs[
'geospatial_lon_min'] = geo_lon_min
remote_dataset.attrs[
'geospatial_lon_max'] = geo_lon_max
if do_update_of_region_meta_info_once:
local_ds.meta_info['bbox_maxx'] = geo_lon_max
local_ds.meta_info['bbox_minx'] = geo_lon_min
local_ds.meta_info['bbox_maxy'] = geo_lat_max
local_ds.meta_info['bbox_miny'] = geo_lat_min
do_update_of_region_meta_info_once = False
if compression_enabled:
for sel_var_name in remote_dataset.variables.keys(
):
remote_dataset.variables.get(
sel_var_name).encoding.update(
encoding_update)
remote_dataset.to_netcdf(local_filepath)
child_monitor.progress(work=1,
msg=str(time_coverage_start))
finally:
if do_update_of_variables_meta_info_once:
variables_info = local_ds.meta_info.get(
'variables', [])
local_ds.meta_info['variables'] = [
var_info for var_info in variables_info
if var_info.get('name') in remote_dataset.
variables.keys() and var_info.get(
'name') not in remote_dataset.dims.keys()
]
do_update_of_variables_meta_info_once = False
local_ds.add_dataset(
os.path.join(local_id, file_name),
(time_coverage_start, time_coverage_end))
if do_update_of_verified_time_coverage_start_once:
verified_time_coverage_start = time_coverage_start
do_update_of_verified_time_coverage_start_once = False
verified_time_coverage_end = time_coverage_end
child_monitor.done()
else:
outdated_file_list = []
for file_rec in selected_file_list:
filename, _, _, file_size, url = file_rec
dataset_file = os.path.join(local_path, filename)
# todo (forman, 20160915): must perform better checks on dataset_file if it is...
# ... outdated or incomplete or corrupted.
# JSON also includes "checksum" and "checksum_type" fields.
if not os.path.isfile(dataset_file) or (
file_size
and os.path.getsize(dataset_file) != file_size):
outdated_file_list.append(file_rec)
if outdated_file_list:
with monitor.starting('Sync ' + self.id,
len(outdated_file_list)):
bytes_to_download = sum(
[file_rec[3] for file_rec in outdated_file_list])
dl_stat = _DownloadStatistics(bytes_to_download)
file_number = 1
for filename, coverage_from, coverage_to, file_size, url in outdated_file_list:
dataset_file = os.path.join(local_path, filename)
sub_monitor = monitor.child(work=1.0)
# noinspection PyUnusedLocal
def reporthook(block_number, read_size,
total_file_size):
dl_stat.handle_chunk(read_size)
sub_monitor.progress(work=read_size,
msg=str(dl_stat))
sub_monitor_msg = "file %d of %d" % (
file_number, len(outdated_file_list))
with sub_monitor.starting(sub_monitor_msg,
file_size):
urllib.request.urlretrieve(
url[protocol],
filename=dataset_file,
reporthook=reporthook)
file_number += 1
local_ds.add_dataset(
os.path.join(local_id, filename),
(coverage_from, coverage_to))
if do_update_of_verified_time_coverage_start_once:
verified_time_coverage_start = coverage_from
do_update_of_verified_time_coverage_start_once = False
verified_time_coverage_end = coverage_to
except OSError as e:
raise DataAccessError(
"Copying remote data source failed: {}".format(e),
source=self) from e
local_ds.meta_info['temporal_coverage_start'] = TimeLike.format(
verified_time_coverage_start)
local_ds.meta_info['temporal_coverage_end'] = TimeLike.format(
verified_time_coverage_end)
local_ds.save(True)
def _load_or_fetch_json(fetch_json_function,
fetch_json_args: list = None,
fetch_json_kwargs: dict = None,
cache_used: bool = False,
cache_dir: str = None,
cache_json_filename: str = None,
cache_timestamp_filename: str = None,
cache_expiration_days: float = 1.0) -> Sequence:
"""
Return (JSON) value of fetch_json_function or return value of a cached JSON file.
"""
json_obj = None
cache_json_file = None
if cache_used:
if cache_dir is None:
raise ValueError(
'if cache_used argument is True, cache_dir argument must not be None'
)
if cache_json_filename is None:
raise ValueError(
'if cache_used argument is True, cache_json_filename argument must not be None'
)
if cache_timestamp_filename is None:
raise ValueError(
'if cache_used argument is True, cache_timestamp_filename argument must not be None'
)
if cache_expiration_days is None:
raise ValueError(
'if cache_used argument is True, cache_expiration_days argument must not be None'
)
cache_json_file = os.path.join(cache_dir, cache_json_filename)
cache_timestamp_file = os.path.join(cache_dir,
cache_timestamp_filename)
timestamp = datetime(year=2000, month=1, day=1)
if os.path.exists(cache_timestamp_file):
with open(cache_timestamp_file) as fp:
timestamp_text = fp.read()
timestamp = datetime.strptime(timestamp_text,
_TIMESTAMP_FORMAT)
time_diff = datetime.now() - timestamp
time_diff_days = time_diff.days + time_diff.seconds / 3600. / 24.
if time_diff_days < cache_expiration_days:
if os.path.exists(cache_json_file):
with open(cache_json_file) as fp:
json_text = fp.read()
json_obj = json.loads(json_text)
if json_obj is None:
# noinspection PyArgumentList
try:
# noinspection PyArgumentList
json_obj = fetch_json_function(*(fetch_json_args or []),
**(fetch_json_kwargs or {}))
if cache_used:
os.makedirs(cache_dir, exist_ok=True)
# noinspection PyUnboundLocalVariable
with open(cache_json_file, 'w') as fp:
fp.write(json.dumps(json_obj, indent=' '))
# noinspection PyUnboundLocalVariable
with open(cache_timestamp_file, 'w') as fp:
fp.write(datetime.utcnow().strftime(_TIMESTAMP_FORMAT))
except Exception as e:
if cache_json_file and os.path.exists(cache_json_file):
with open(cache_json_file) as fp:
json_text = fp.read()
json_obj = json.loads(json_text)
else:
if isinstance(e, DataAccessError):
raise DataAccessError(
"Cannot fetch information from CCI Open Data Portal server."
) from e
else:
raise e
return json_obj
def test_plain(self):
try:
raise DataAccessError("haha")
except DataAccessError as e:
self.assertEqual(str(e), "haha")
self.assertIsInstance(e, Exception)
def create_data_source(self,
data_source_id: str,
region: PolygonLike.TYPE = None,
title: str = None,
time_range: TimeRangeLike.TYPE = None,
var_names: VarNamesLike.TYPE = None,
meta_info: OrderedDict = None,
lock_file: bool = False):
self._init_data_sources()
if title:
if not meta_info:
meta_info = OrderedDict()
meta_info['title'] = title
if not data_source_id.startswith('%s.' % self.id):
data_source_id = '%s.%s' % (self.id, data_source_id)
lock_filename = '{}.lock'.format(data_source_id)
lock_filepath = os.path.join(self._store_dir, lock_filename)
pid = os.getpid()
create_time = int(psutil.Process(pid).create_time() * 1000000)
data_source = None
for ds in self._data_sources:
if ds.id == data_source_id:
if lock_file and os.path.isfile(lock_filepath):
with open(lock_filepath, 'r') as lock_file:
writer_pid = lock_file.readline()
if writer_pid:
writer_create_time = -1
writer_pid, writer_timestamp = [
(int(val) for val in writer_pid.split(":"))
if ":" in writer_pid else writer_pid,
writer_create_time
]
if psutil.pid_exists(
writer_pid) and writer_pid != pid:
if writer_timestamp > writer_create_time:
writer_create_time = int(
psutil.Process(
writer_pid).create_time() *
1000000)
if writer_create_time == writer_timestamp:
raise DataAccessError(
'Data source "{}" is currently being created by another '
'process (pid:{})'.format(
ds.id, writer_pid),
source=self)
# ds.temporal_coverage() == time_range and
if ds.spatial_coverage() == region \
and ds.variables_info == var_names:
data_source = ds
data_source.set_completed(False)
break
raise DataAccessError(
'Data source "{}" already exists.'.format(data_source_id),
source=self)
if not data_source:
data_source = LocalDataSource(data_source_id,
files=[],
data_store=self,
spatial_coverage=region,
variables=var_names,
temporal_coverage=time_range,
meta_info=meta_info,
status=DataSourceStatus.PROCESSING)
data_source.set_completed(False)
self._save_data_source(data_source)
if lock_file:
with open(lock_filepath, 'w') as lock_file:
lock_file.write("{}:{}".format(pid, create_time))
return data_source
