def initialize_proxy():
"""
Initialize user defined proxy settings, read proxy setting from config file.
Populates value to 3rd-party libraries using proper environment variables.
"""
from os import environ
http_proxy_config = get_config_value(_CONFIG_KEY_HTTP_PROXY)
https_proxy_config = get_config_value(_CONFIG_KEY_HTTPS_PROXY)
if http_proxy_config:
environ['http_proxy'] = http_proxy_config
if https_proxy_config:
environ['https_proxy'] = https_proxy_config
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 _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) if time_range else None
region = PolygonLike.convert(region) if region else None
var_names = VarNamesLike.convert(
var_names) if var_names else None # type: Sequence
compression_level = get_config_value('NETCDF_COMPRESSION_LEVEL',
NETCDF_COMPRESSION_LEVEL)
compression_enabled = True if compression_level > 0 else False
encoding_update = dict()
if compression_enabled:
encoding_update.update({
'zlib': True,
'complevel': compression_level
})
local_path = os.path.join(local_ds.data_store.data_store_path,
local_id)
data_store_path = local_ds.data_store.data_store_path
if not os.path.exists(local_path):
os.makedirs(local_path)
monitor.start("Sync " + self.id, total_work=len(self._files.items()))
for remote_relative_filepath, coverage in self._files.items():
child_monitor = monitor.child(work=1)
file_name = os.path.basename(remote_relative_filepath)
local_relative_filepath = os.path.join(local_id, file_name)
local_absolute_filepath = os.path.join(data_store_path,
local_relative_filepath)
remote_absolute_filepath = os.path.join(
self._data_store.data_store_path, remote_relative_filepath)
if isinstance(coverage, Tuple):
time_coverage_start = coverage[0]
time_coverage_end = coverage[1]
if not time_range or time_coverage_start >= time_range[
0] and time_coverage_end <= time_range[1]:
if region or var_names:
do_update_of_variables_meta_info_once = True
do_update_of_region_meta_info_once = True
try:
remote_dataset = xr.open_dataset(
remote_absolute_filepath)
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_absolute_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))
child_monitor.done()
else:
shutil.copy(remote_absolute_filepath,
local_absolute_filepath)
local_ds.add_dataset(
local_relative_filepath,
(time_coverage_start, time_coverage_end))
child_monitor.done()
monitor.done()
return local_id
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_name = local_ds.name
local_id = local_ds.name
time_range = TimeRangeLike.convert(time_range) if time_range else None
region = PolygonLike.convert(region) if region else None
var_names = VarNamesLike.convert(
var_names) if var_names else None # type: Sequence
compression_level = get_config_value('NETCDF_COMPRESSION_LEVEL',
NETCDF_COMPRESSION_LEVEL)
compression_enabled = True if compression_level > 0 else False
encoding_update = dict()
if compression_enabled:
encoding_update.update({
'zlib': True,
'complevel': compression_level
})
local_path = os.path.join(local_ds.data_store.data_store_path,
local_id)
data_store_path = local_ds.data_store.data_store_path
if not os.path.exists(local_path):
os.makedirs(local_path)
monitor.start("Sync " + self.name, total_work=len(self._files.items()))
for remote_relative_filepath, coverage in self._files.items():
child_monitor = monitor.child(work=1)
file_name = os.path.basename(remote_relative_filepath)
local_relative_filepath = os.path.join(local_id, file_name)
local_absolute_filepath = os.path.join(data_store_path,
local_relative_filepath)
remote_absolute_filepath = os.path.join(
self._data_store.data_store_path, remote_relative_filepath)
if isinstance(coverage, Tuple):
time_coverage_start = coverage[0]
time_coverage_end = coverage[1]
remote_netcdf = None
local_netcdf = None
if not time_range or time_coverage_start >= time_range[
0] and time_coverage_end <= time_range[1]:
if region or var_names:
try:
remote_netcdf = NetCDF4DataStore(
remote_absolute_filepath)
local_netcdf = NetCDF4DataStore(
local_absolute_filepath,
mode='w',
persist=True)
local_netcdf.set_attributes(
remote_netcdf.get_attrs())
remote_dataset = xr.Dataset.load_store(
remote_netcdf)
process_region = False
if region:
geo_lat_min = self._get_harmonized_coordinate_value(
remote_dataset.attrs, 'geospatial_lat_min')
geo_lat_max = self._get_harmonized_coordinate_value(
remote_dataset.attrs, 'geospatial_lat_max')
geo_lon_min = self._get_harmonized_coordinate_value(
remote_dataset.attrs, 'geospatial_lon_min')
geo_lon_max = self._get_harmonized_coordinate_value(
remote_dataset.attrs, 'geospatial_lon_max')
geo_lat_res = self._get_harmonized_coordinate_value(
remote_dataset.attrs,
'geospatial_lon_resolution')
geo_lon_res = self._get_harmonized_coordinate_value(
remote_dataset.attrs,
'geospatial_lat_resolution')
if not (isnan(geo_lat_min)
or isnan(geo_lat_max)
or isnan(geo_lon_min)
or isnan(geo_lon_max)
or isnan(geo_lat_res)
or isnan(geo_lon_res)):
process_region = True
[lat_min, lon_min, lat_max,
lon_max] = region.bounds
lat_min = floor(
(lat_min - geo_lat_min) / geo_lat_res)
lat_max = ceil(
(lat_max - geo_lat_min) / geo_lat_res)
lon_min = floor(
(lon_min - geo_lon_min) / geo_lon_res)
lon_max = ceil(
(lon_max - geo_lon_min) / geo_lon_res)
# TODO (kbernat): check why dataset.sel fails!
remote_dataset = remote_dataset.isel(
drop=False,
lat=slice(lat_min, lat_max),
lon=slice(lon_min, lon_max))
geo_lat_max = lat_max * geo_lat_res + geo_lat_min
geo_lat_min += lat_min * geo_lat_res
geo_lon_max = lon_max * geo_lon_res + geo_lon_min
geo_lon_min += lon_min * geo_lon_res
if not var_names:
var_names = [
var_name for var_name in
remote_netcdf.variables.keys()
]
var_names.extend([
coord_name
for coord_name in remote_dataset.coords.keys()
if coord_name not in var_names
])
child_monitor.start(label=file_name,
total_work=len(var_names))
for sel_var_name in var_names:
var_dataset = remote_dataset.drop([
var_name for var_name in
remote_dataset.variables.keys()
if var_name != sel_var_name
])
if compression_enabled:
var_dataset.variables.get(
sel_var_name).encoding.update(
encoding_update)
local_netcdf.store_dataset(var_dataset)
child_monitor.progress(work=1,
msg=sel_var_name)
if process_region:
local_netcdf.set_attribute(
'geospatial_lat_min', geo_lat_min)
local_netcdf.set_attribute(
'geospatial_lat_max', geo_lat_max)
local_netcdf.set_attribute(
'geospatial_lon_min', geo_lon_min)
local_netcdf.set_attribute(
'geospatial_lon_max', geo_lon_max)
finally:
if remote_netcdf:
remote_netcdf.close()
if local_netcdf:
local_netcdf.close()
local_ds.add_dataset(
local_relative_filepath,
(time_coverage_start, time_coverage_end))
child_monitor.done()
else:
shutil.copy(remote_absolute_filepath,
local_absolute_filepath)
local_ds.add_dataset(
local_relative_filepath,
(time_coverage_start, time_coverage_end))
child_monitor.done()
monitor.done()
return local_id
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) if time_range else None
var_names = VarNamesLike.convert(var_names) if var_names else None # type: Sequence
compression_level = get_config_value('NETCDF_COMPRESSION_LEVEL', NETCDF_COMPRESSION_LEVEL)
compression_enabled = True if compression_level > 0 else False
encoding_update = dict()
if compression_enabled:
encoding_update.update({'zlib': True, 'complevel': compression_level})
local_path = os.path.join(local_ds.data_store.data_store_path, local_id)
data_store_path = local_ds.data_store.data_store_path
if not os.path.exists(local_path):
os.makedirs(local_path)
monitor.start("Sync " + self.id, total_work=len(self._files.items()))
for remote_relative_filepath, coverage in self._files.items():
child_monitor = monitor.child(work=1)
file_name = os.path.basename(remote_relative_filepath)
local_relative_filepath = os.path.join(local_id, file_name)
local_absolute_filepath = os.path.join(data_store_path, local_relative_filepath)
remote_absolute_filepath = os.path.join(self._data_store.data_store_path, remote_relative_filepath)
if isinstance(coverage, Tuple):
time_coverage_start = coverage[0]
time_coverage_end = coverage[1]
if not time_range or time_coverage_start >= time_range[0] and time_coverage_end <= time_range[1]:
if region or var_names:
do_update_of_variables_meta_info_once = True
do_update_of_region_meta_info_once = True
remote_dataset = None
try:
remote_dataset = xr.open_dataset(remote_absolute_filepath)
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 = adjust_spatial_attrs_impl(subset_spatial_impl(remote_dataset, region),
allow_point=False)
if do_update_of_region_meta_info_once:
# subset_spatial_impl
local_ds.meta_info['bbox_maxx'] = remote_dataset.attrs['geospatial_lon_max']
local_ds.meta_info['bbox_minx'] = remote_dataset.attrs['geospatial_lon_min']
local_ds.meta_info['bbox_maxy'] = remote_dataset.attrs['geospatial_lat_max']
local_ds.meta_info['bbox_miny'] = remote_dataset.attrs['geospatial_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_absolute_filepath)
child_monitor.progress(work=1, msg=str(time_coverage_start))
finally:
if do_update_of_variables_meta_info_once and remote_dataset is not None:
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()]
# noinspection PyUnusedLocal
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))
child_monitor.done()
else:
shutil.copy(remote_absolute_filepath, local_absolute_filepath)
local_ds.add_dataset(local_relative_filepath, (time_coverage_start, time_coverage_end))
child_monitor.done()
monitor.done()
return local_id
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_name = local_ds.name
local_id = local_ds.name
time_range = TimeRangeLike.convert(time_range) if time_range else None
region = PolygonLike.convert(region) if region else None
var_names = VarNamesLike.convert(
var_names) if var_names else None # type: Sequence
compression_level = get_config_value('NETCDF_COMPRESSION_LEVEL',
NETCDF_COMPRESSION_LEVEL)
compression_enabled = True if compression_level > 0 else False
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 protocol == _ODP_PROTOCOL_OPENDAP:
files = self._get_urls_list(selected_file_list, protocol)
monitor.start('Sync ' + self.name, 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]
remote_netcdf = None
local_netcdf = None
try:
remote_netcdf = NetCDF4DataStore(dataset_uri)
local_netcdf = NetCDF4DataStore(local_filepath,
mode='w',
persist=True)
local_netcdf.set_attributes(remote_netcdf.get_attrs())
remote_dataset = xr.Dataset.load_store(remote_netcdf)
process_region = False
if region:
geo_lat_min = self._get_harmonized_coordinate_value(
remote_dataset.attrs, 'geospatial_lat_min')
geo_lat_max = self._get_harmonized_coordinate_value(
remote_dataset.attrs, 'geospatial_lat_max')
geo_lon_min = self._get_harmonized_coordinate_value(
remote_dataset.attrs, 'geospatial_lon_min')
geo_lon_max = self._get_harmonized_coordinate_value(
remote_dataset.attrs, 'geospatial_lon_max')
geo_lat_res = self._get_harmonized_coordinate_value(
remote_dataset.attrs, 'geospatial_lon_resolution')
geo_lon_res = self._get_harmonized_coordinate_value(
remote_dataset.attrs, 'geospatial_lat_resolution')
if not (isnan(geo_lat_min) or isnan(geo_lat_max)
or isnan(geo_lon_min) or isnan(geo_lon_max)
or isnan(geo_lat_res) or isnan(geo_lon_res)):
process_region = True
[lat_min, lon_min, lat_max,
lon_max] = region.bounds
lat_min = floor(
(lat_min - geo_lat_min) / geo_lat_res)
lat_max = ceil(
(lat_max - geo_lat_min) / geo_lat_res)
lon_min = floor(
(lon_min - geo_lon_min) / geo_lon_res)
lon_max = ceil(
(lon_max - geo_lon_min) / geo_lon_res)
# TODO (kbernat): check why dataset.sel fails!
remote_dataset = remote_dataset.isel(
drop=False,
lat=slice(lat_min, lat_max),
lon=slice(lon_min, lon_max))
geo_lat_max = lat_max * geo_lat_res + geo_lat_min
geo_lat_min += lat_min * geo_lat_res
geo_lon_max = lon_max * geo_lon_res + geo_lon_min
geo_lon_min += lon_min * geo_lon_res
if not var_names:
var_names = [
var_name
for var_name in remote_netcdf.variables.keys()
]
var_names.extend([
coord_name
for coord_name in remote_dataset.coords.keys()
if coord_name not in var_names
])
child_monitor.start(label=file_name,
total_work=len(var_names))
for sel_var_name in var_names:
var_dataset = remote_dataset.drop([
var_name
for var_name in remote_dataset.variables.keys()
if var_name != sel_var_name
])
if compression_enabled:
var_dataset.variables.get(
sel_var_name).encoding.update(encoding_update)
local_netcdf.store_dataset(var_dataset)
child_monitor.progress(work=1, msg=sel_var_name)
if process_region:
local_netcdf.set_attribute('geospatial_lat_min',
geo_lat_min)
local_netcdf.set_attribute('geospatial_lat_max',
geo_lat_max)
local_netcdf.set_attribute('geospatial_lon_min',
geo_lon_min)
local_netcdf.set_attribute('geospatial_lon_max',
geo_lon_max)
finally:
if remote_netcdf:
remote_netcdf.close()
if local_netcdf:
local_netcdf.close()
local_ds.add_dataset(
os.path.join(local_id, file_name),
(time_coverage_start, 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.name,
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:
if monitor.is_cancelled():
raise InterruptedError
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)
if monitor.is_cancelled():
raise InterruptedError
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))
local_ds.save()
monitor.done()