+ # List of year-months to consider
+ historical = []
+ date_end = datetime.now()
+ for year in range(1996, date_end.year+1):
+ for month in range(1,13):
+ date = datetime(year, month, 1)
+ if date <= date_end:
+ historical.append(date.strftime("%Y%m"))
+
+ # We download all csv files from meteofrance that are not in
+ # the data repository
+ meteo_data = self._data_directory / 'historical'
+ p = Path(meteo_data)
+ p.mkdir(exist_ok=True, parents=True)
+ for date in historical:
+ if not isfile(meteo_data / ('synop.'+date+'.csv')):
+ link = 'https://donneespubliques.meteofrance.fr/donnees_libres/Txt/Synop/Archive/synop.'
+ link += date + '.csv.gz'
+ download_path = meteo_data / basename(link)
+ urlretrieve(link, download_path)
+ with gzip.open(download_path, 'rb') as f:
+ csv_file = meteo_data / basename(link[:-3])
+ with open(csv_file, 'w') as g:
+ g.write(f.read().decode())
+ remove(meteo_data / basename(link))
+
+
+
+ def update(self):
+ '''
+ Update the MeteoFrance features with the last available data
+ '''
+ # We collect archive files from MeteoFrance, until the current month
+ # by using the same method than for data generation : this is currently
+ # based on the presence of a synop.+date+.csv' file in the
+ # data/meteo_france/historical directory. The file corresponding to the
+ # current month is deleted first, so that its most recent version will
+ # be downloaded by calling self._collect_historical_data
+
+ logger.info('Update historical csv files from MeteoFrance, if needed')
+ today = datetime.now()
+ todel = 'synop.'+today.strftime("%Y%m")+".csv"
+ try:
+ remove(self._data_directory / 'historical' / todel)
+ except:
+ logger.warning(f"{self._data_directory / 'historical' / todel} not found")
+ system("touch "+todel)
+ self._collect_historical_data()
+
+
+
+ @property
+ def dated_features(self):
+ '''
+ '''
+ if self._dated_features == None:
+ csv_file = Path.cwd() / 'config' / 'features' / 'meteofrance' / 'meteofrance_features.csv'
+ logger.info(f'Collecting meteo feature information from {csv_file}')
+ # A dictionary for the features
+ with open(csv_file, "r") as f:
+ reader = DictReader(f, delimiter=',')
+ next(reader)
+ dico_features = {row["abbreviation"]:
+ {
+ 'name': row['name'], # feature name
+ 'type': row['type'] # qualitative (2) or quantitative (1)
+ }
+ for row in reader}
+
+ dir_data = Path.cwd() / 'data' / 'meteo_france' / 'historical'
+ self._dated_features = {}
+ for csv_meteo in listdir(dir_data):
+ logger.info(f'Inserting {csv_meteo} in intervention dictionary')
+ with open(dir_data / csv_meteo, "r") as f:
+ reader = DictReader(f, delimiter=';')
+ for row in reader:
+ if row['numer_sta'] in self._stations:
+ self._dated_features.setdefault(row['date'],{}).update({dico_features[feat]['name']+'_'+str(self._stations.index(row['numer_sta'])): eval(row[feat].replace('mq','None')) for feat in dico_features})
+ return self._dated_features
+
