Ejemplo n.º 1
0
        '86': 22,
        '66': 10,
        '67': 11,
        '56': 10,
        '57': 11,
        '95': 25
    }

    return condicodes.get(str(code), None)


# Create new task
task = Routine('import.dwd.hourly.model')

# Get counter value
counter = task.get_var('station_counter')
skip = 0 if counter is None else int(counter)

# Get MOSMIX stations
try:
    stations = pd.read_csv(MOSMIX_PATH,
                           dtype='str',
                           skiprows=skip,
                           nrows=STATIONS_PER_CYCLE,
                           names=['id', 'mosmix'])
except pd.errors.EmptyDataError:
    stations = None
    pass

# Update counter
if stations is None or len(stations.index) < STATIONS_PER_CYCLE:
Ejemplo n.º 2
0
        pass

    return file


# Create task
task = Routine('import.dwd.hourly.national')

# Connect to DWD FTP server
ftp = FTP(DWD_FTP_SERVER)
ftp.login()
ftp.cwd('/climate_environment/CDC/observations_germany/climate/hourly/' +
        BASE_DIR)

# Get counter value
counter = task.get_var(f'station_counter_{MODE}')
counter = int(counter) if counter is not None else 0
skip = 3 if counter is None else 3 + counter

# Get all files in directory
try:
    endpos = STATIONS_PER_CYCLE + skip
    stations = ftp.nlst()[skip:endpos]
except BaseException:
    stations = None
    pass

# Update counter
if stations is None or len(stations) < STATIONS_PER_CYCLE:
    task.set_var(f'station_counter_{MODE}', 0)
    exit()
Ejemplo n.º 3
0
USAF_WBAN_PATH = os.path.abspath(
    os.path.join(os.path.dirname(__file__), '../../..',
                 'resources')) + '/usaf_wban.csv'
CURRENT_YEAR = datetime.now().year

# Required columns
usecols = [0, 1, 2, 3, 4, 5, 6, 7, 8, 10]

# Column names
NAMES = ['time', 'temp', 'dwpt', 'pres', 'wdir', 'wspd', 'prcp']

# Create new task
task = Routine('import.noaa.hourly.global')

# Get counter value
counter = task.get_var('station_counter_' + MODE)
skip = 0 if counter is None else int(counter)

# Get year
if MODE == 'historical':
    year = task.get_var('year')
    year = 1901 if year is None else int(year)

# Get ISD Lite stations
try:
    stations = pd.read_csv(USAF_WBAN_PATH,
                           dtype='str',
                           skiprows=skip,
                           nrows=STATIONS_PER_CYCLE,
                           names=['id', 'usaf', 'wban'])
except pd.errors.EmptyDataError: