def handle(self, *args, **options):
ps = SourceType.objects.get(code='ioc')
for s in ps.station_set.filter(status='active'):
apiclient = IocAPI()
df = apiclient.get_df(s.code)
if df is not None:
serie = get_serie(s, 'SLEV')
load_serie(df['SLEV'].copy(), serie.id)
def handle(self, *args, **options):
ps = SourceType.objects.get(code='arso')
for s in ps.station_set.filter(status='active'):
apiclient = ArsoAPI()
df = apiclient.get_df(s.code)
if df is None:
continue
for k, v in ARSO_PARAMS.items():
if v in df.columns:
serie = get_serie(s, v)
load_serie(df[v].copy(), serie.id)
def handle(self, *args, **options):
ps = SourceType.objects.get(code='davis')
for s in ps.station_set.filter(status='active'):
self.stdout.write("Loading station {} ... ".format(s), ending='')
davisapi = DavisAPI()
df = davisapi.get_df(s.code, 5)
for k, v in PARAMETER_MAP.items():
if k in df.columns:
serie = get_serie(s, v)
load_serie(df[k].copy(), serie.id)
self.stdout.write("[OK]")
def handle(self, *args, **options):
ps = SourceType.objects.get(code='cnr')
for s in ps.station_set.filter(status='active'):
apiclient = GetitAPI()
df = apiclient.get_df(s.code, 24)
if df is None:
continue
for k, v in SOS_PARAMS.items():
print(df.head())
if v in df.columns:
serie = get_serie(s, v)
print(df[v])
load_serie(df[v].copy(), serie.id)
def handle(self, *args, **options):
ps = SourceType.objects.get(code='mtt')
for s in ps.station_set.filter(status='active'):
self.stdout.write("Loading station {} ... ".format(s), ending='')
apiclient = MttAPI()
df = apiclient.get_df(s.code)
if df is not None and df.shape[0] > 0:
for k, v in PARAMETER_MAP.items():
if k in df.columns:
serie = get_serie(s, v)
load_serie(df[k].copy(), serie.id)
self.stdout.write("[OK]")
else:
self.stdout.write("[FAILED]")
def handle(self, *args, **options):
hours = options['hours']
ps = SourceType.objects.get(code='pessl')
for s in ps.station_set.filter(status='active'):
self.stdout.write("Loading station {} ... ".format(s), ending='')
keys = SOURCE_AUTH['pessl'][s.network.code]
pesslapi = PesslAPI(keys['public_key'], keys['private_key'])
df = pesslapi.get_df(s.code, hours)
if df is not None and df.shape[0] > 0:
for k, v in PARAMETER_MAP.items():
if k in df.columns:
serie = get_serie(s, v)
load_serie(df[k].copy(), serie.id)
self.stdout.write("[OK]")
else:
self.stdout.write("[FAILED]")
def handle(self, *args, **options):
days = options['days']
daysgap = options['daysgap']
ps = SourceType.objects.get(code='cmems_wms')
for station in ps.station_set.filter(status='active'):
self.stdout.write(
"Loading DataSource/Station {} ... ".format(station))
apiclient = CMEMSWmsDataSource(station.uri)
self.stdout.write("\tLooking for registered layers/parameters ...")
for pm in station.parametermapping_set.all():
parameter = pm.parameter
source_uom = pm.source_parameter_uom
uom = parameter.uom
print(source_uom, uom, parameter)
layer = pm.source_parameter_label
self.stdout.write("\tLooking for registered series ...")
for series in station.serie_set.filter(
parameter=parameter).all():
location = series.location
# print(series)
self.stdout.write(
"\tLoading series {}. Layer {}. Location {} ... ".
format(series.id, layer, location),
ending='')
point = [location.geo.x, location.geo.y]
df = apiclient.get_df(layer,
point,
timedelta=days,
timegap=daysgap)
# convert uom if needed
if uom is not None and source_uom is not None and uom != source_uom:
df['value'] = Q_(df.value.array,
source_uom).to(uom).magnitude
if df.shape[0] > 0:
load_serie(df['value'].copy(), series.id)
self.stdout.write("nrecords {}".format(df.shape[0]),
ending='')
self.stdout.write("[OK]")
else:
self.stdout.write("[FAILED]")
def handle(self, *args, **options):
hours = options['hours']
ps = SourceType.objects.get(code='elmed')
for s in ps.station_set.filter(status='active'):
self.stdout.write("Loading station {} ... ".format(s), ending='')
keys = SOURCE_AUTH['elmed'][s.network.code]
elmedapi = ElmedAPI(None, keys['private_key'])
df = elmedapi.get_df(s.code, hours)
if df is not None and df.shape[0] > 0:
for k, _v in PARAMETER_MAP.items():
if not isinstance(_v, str):
v, height = _v
else:
v = _v
height = None
if k in df.columns:
serie = get_serie(s, v, height=height)
load_serie(df[k].copy(), serie.id)
self.stdout.write("[OK]")
else:
self.stdout.write("[FAILED]")