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385 | class CMIP6LegacyDownloader(ThreadedDownloader):
# Prioritise European first, US last, avoiding unnecessary queries
# against nodes further afield (all traffic has a cost, and the coverage
# of local nodes is more than enough)
def __init__(self,
*args,
nodes: object = None,
exclude_nodes: object = None,
search_node: object = "https://esgf-node.llnl.gov/esg-search/search",
**kwargs):
super().__init__(*args,
# TODO: validate ESGF frequencies other than MONTH / YEAR
source_min_frequency=Frequency.YEAR,
source_max_frequency=Frequency.HOUR,
# TODO: request_frequency is a problem, we should batch
# as big as possible, but currently only cache queries
**kwargs)
exclude_nodes = list() if exclude_nodes is None else exclude_nodes
self._search_node = search_node
# self.__connection = None
self._exclude_nodes = exclude_nodes if exclude_nodes is not None else []
def _single_download(self,
var_config: object,
req_dates: object) -> list:
"""Overridden CMIP implementation for downloading from DAP server
Due to the size of the CMIP set and the fact that we don't want to make
1850-2100 yearly requests for all downloads, we have a bespoke and
overridden download implementation for this.
TODO: this could be made to handle much larger date ranges, as individual
files contain centuries of data. Making a search / download per year isn't ideal
:param var_config:
:param req_dates:
"""
query = {
'source_id': self.dataset.source,
'member_id': self.dataset.member,
'frequency': self.dataset.frequency.cmip_id,
'variable_id': var_config.prefix,
'table_id': self.dataset.table_map[var_config.prefix],
'grid_label': self.dataset.grid_map[self.dataset.source][var_config.prefix],
}
results = []
logging.info("Querying ESGF for experiment {} for {}".format(" and ".join(self.dataset.experiments), var_config.name))
query['experiment_id'] = ",".join(self.dataset.experiments)
node_results = None
try:
node_results = self.esgf_search(**query)
except requests.exceptions.HTTPError as e:
logging.error(f"HTTP error {e.response} with collecting node results, "
f"clearing the cache and maybe try a different search node")
self.esgf_search.cache_clear()
if node_results is not None and len(node_results) > 0:
logging.debug("Query: {}".format(query))
logging.debug("Found {}-{}: {} results".format(
",".join(self.dataset.experiments), var_config.name, len(node_results)))
start_date, end_date = req_dates[0], req_dates[-1]
date_proc = lambda s: dt.datetime(int(s[0:4]), int(s[4:6]), 1).date() \
if self.dataset.frequency <= Frequency.MONTH else dt.datetime(int(s[0:4]), int(s[4:6]),
int(s[6:8])).date()
for idx, df in enumerate(node_results):
start, end = [date_proc(date_str) for date_str in df.split("_")[-1].rstrip(".nc").split("-")]
if start <= start_date < end_date <= end \
or start <= start_date <= end \
or start <= end_date <= end:
results.append(df)
else:
logging.warning("No unbounded results for {} from ESGF search {}".format(
var_config.name, ",".join(query.values())))
return None
# Filter by excluded domains and group together the rest for testing
node_grouped_results = dict()
for result in results:
host = urllib.parse.urlparse(result).hostname
if any([excl in host for excl in self._exclude_nodes]):
logging.debug("Skipping {} as in the excluded hosts list".format(host))
continue
if host not in node_grouped_results:
node_grouped_results[host] = []
node_grouped_results[host].append(result)
if len(node_grouped_results) == 0:
# TODO: what really happens when we have this?
logging.warning("NO VALID URLs FOUND for {} from ESGF search {}".format(
var_config.name, ",".join(query.values())))
return None
cmip6_ds = None
download_path = os.path.join(var_config.root_path,
self.dataset.location.name,
os.path.basename(self.dataset.var_filepath(var_config, req_dates)))
if os.path.exists(download_path):
logging.warning(f"We have downloaded data without corresponding output, "
f"so will skip the download: {download_path}")
return [download_path]
logging.debug("\n".join(results))
for node, grouped_results in node_grouped_results.items():
logging.info("Attempting to open data from {}".format(node))
try:
# http://xarray.pydata.org/en/stable/user-guide/io.html?highlight=opendap#opendap
# Avoid 500MB DAP request limit
cmip6_ds = xr.open_mfdataset(grouped_results,
combine='by_coords',
chunks={'time': '499MB'})
except OSError as e:
logging.error("Could not open data from {} - {}".format(node, e.filename))
continue
break
if cmip6_ds is None:
logging.error("We have no URLS that provide data for {} using {}".format(var_config.name, ",".join(query.values())))
return None
try:
rename_vars = {var_config.prefix: var_config.name}
cmip6_da = getattr(cmip6_ds.rename(rename_vars), var_config.name)
if self.dataset.frequency == Frequency.MONTH and start_date.day > 1:
start_date = start_date.replace(day=1)
cmip6_da = cmip6_da.sel(time=slice(start_date,
end_date))
# TODO: possibly other attributes, especially with ocean vars
if var_config.level:
cmip6_da = cmip6_da.sel(plev=int(var_config.level) * 100)
# Note this is happening on the remote end!
cmip6_da = cmip6_da.sel(lat=slice(self.dataset.location.bounds[2],
self.dataset.location.bounds[0]))
# By this point the variable name has stored this info
for omit_coord in ["plev", "height"]:
if omit_coord in cmip6_da.coords:
cmip6_da = cmip6_da.drop_vars(omit_coord)
except (OSError, ValueError, IndexError) as e:
raise DownloaderError("Error encountered: {} for {}".format(e, results))
else:
logging.info("Writing {} to {}".format(cmip6_da, download_path))
os.makedirs(os.path.dirname(download_path), exist_ok=True)
cmip6_da.to_netcdf(download_path)
cmip6_da.close()
if os.path.exists(download_path):
return [download_path]
return None
@lru_cache(1000)
def esgf_search(self,
files_type: str = "OPENDAP",
local_node: bool = False,
latest: bool = True,
project: str = "CMIP6",
format: str = "application%2Fsolr%2Bjson",
use_csrf: bool = False,
**search):
"""
Below taken from
https://hub.binder.pangeo.io/user/pangeo-data-pan--cmip6-examples-ro965nih/lab
and adapted slightly
:param files_type:
:param local_node:
:param latest:
:param project:
:param format:
:param use_csrf:
:param search:
:return:
"""
client = requests.session()
payload = search
payload["project"] = project
payload["type"] = "File"
if latest:
payload["latest"] = "true"
if local_node:
payload["distrib"] = "false"
if use_csrf:
client.get(self._search_node)
if 'csrftoken' in client.cookies:
# Django 1.6 and up
csrftoken = client.cookies['csrftoken']
else:
# older versions
csrftoken = client.cookies['csrf']
payload["csrfmiddlewaretoken"] = csrftoken
payload["format"] = format
offset = 0
numFound = 10000
all_files = []
files_type = files_type.upper()
payload["limit"] = 1000
while offset < numFound:
payload["offset"] = offset
url_keys = []
for k in payload:
url_keys += ["{}={}".format(k, payload[k])]
url = "{}/?{}".format(self._search_node, "&".join(url_keys))
logging.debug("ESGF search URL: {}".format(url))
r = client.get(url)
r.raise_for_status()
resp = r.json()["response"]
numFound = int(resp["numFound"])
resp = resp["docs"]
offset += len(resp)
for d in resp:
# for k in d:
# logging.debug("{}: {}".format(k, d[k]))
for f in d["url"]:
sp = f.split("|")
if sp[-1] == files_type:
all_files.append(sp[0].split(".html")[0])
return sorted(all_files)
|