def main(argv):
try:
job = GetWeatherDataJob()
lat = float(FLAGS.latitude)
lon = float(FLAGS.longitude)
UtilFunctions.validate_lat_lon(lat, lon)
# get weather data
job.get_weather_data(start_date=FLAGS.start_date, end_date=FLAGS.end_date, lat=float(FLAGS.latitude), lon=float(FLAGS.longitude))
except Exception as err:
if FLAGS.job_status_blob_sas_url:
writer = JobStatusWriter(FLAGS.job_status_blob_sas_url)
writer.set_success(False)
writer.flush()
JobError.write_to_status_file(err, FLAGS.job_status_blob_sas_url)
sys.exit(1)
def __get_weather_forecast_data_for_day(self, day, lat, lon):
'''
Gets weather data for a given day and pushes it to eventhub
'''
try:
# get data for given date range.
start_time = time.time()
LOG.info("Getting data for " + day.strftime("%m/%d/%Y, %H:%M:%S"))
weather_data = NoaaGfsWeather(day, day)
LOG.info("Successfully got data for " +
day.strftime("%m/%d/%Y, %H:%M:%S"))
# get the data into a pandas data frame, so we can filter and process
weather_data_df = weather_data.to_pandas_dataframe()
LOG.info("Took {} seconds to get the data.".format(time.time() -
start_time))
# out of the lat longs available get the nearest points
LOG.info(
"Finding the nearest latitude and longitude from the available data"
)
(nearest_lat,
nearest_lon) = UtilFunctions.find_nearest_lat_longs_in_data(
weather_data_df, lat, lon)
LOG.info("nearest lat, lon: [" + str(nearest_lat) + "," +
str(nearest_lon) + "]")
# filter the data to this lat and lon
LOG.info("Filtering the data to nearest lat, lon")
filtered_weather_data = weather_data_df[
(weather_data_df['latitude'] == nearest_lat)
& (weather_data_df['longitude'] == nearest_lon)]
LOG.info(filtered_weather_data)
# push the data to eventhub
LOG.info("Pushing data to eventhub")
wdl_id = self.__push_weather_data_to_farmbeats(
filtered_weather_data)
LOG.info("Successfully pushed data")
# Update the status for the job
if FLAGS.job_status_blob_sas_url:
msg = "Weather data pushed for start_date: {} to end_date: {}\n for nearest_lat: {}, nearest_lon: {}\n provided lat:{}, lon:{}".format(
FLAGS.start_date, FLAGS.end_date, nearest_lat, nearest_lon,
FLAGS.latitude, FLAGS.longitude)
writer = JobStatusWriter(FLAGS.job_status_blob_sas_url)
output_writer = writer.get_output_writer()
output_writer.set_prop("WeatherDataLocationId: ", wdl_id)
output_writer.set_prop("Message: ", msg)
writer.set_success(True)
writer.flush()
except Exception as err:
# Update the status in failure
if FLAGS.job_status_blob_sas_url:
writer = JobStatusWriter(FLAGS.job_status_blob_sas_url)
writer.set_success(False)
writer.flush()
raise JobError(str(err), JobConstants.INTERNAL_ERROR, False)
def validate_lat_lon(lat, lon):
'''
validates, if provided latitude and longitude are in range.
'''
if (lat > 90.0 or lat < -90.0 or lon > 180.0 or lon < -180.0):
raise JobError(
"Bad request: Please ensure that latitude[-90, 90]/longitude[-180, 180]",
'400', False)
def __get_weather_data_model_id(self, name):
'''
returns the weather data model id, given the name
'''
wsms = self.fb_api.get_weather_data_model_api().weather_data_model_get_all(names=[name], includes=[JobConstants.WEATHER_MEASURES, JobConstants.PROPERTIES]).to_dict()
if (wsms):
return wsms[JobConstants.ITEMS][0][JobConstants.ID]
else:
raise JobError("weather data model {} not found!".format(wsms), JobConstants.INTERNAL_ERROR, False)
def daterange(start_date, end_date):
'''
Generator to give one day at a time.
'''
if (start_date > end_date):
raise JobError(
"Bad request: Please ensure that start_date is prior to end_date",
'400', False)
for n in range(int((end_date - start_date).days) + 1):
yield start_date + timedelta(n)