#!/usr/bin/python3 from datetime import datetime from eto import ETo, datasets from io import StringIO import argparse import configparser import mysql.connector import pandas as pd import requests import sys def usage(): print( "Usage: " + __file__ + "[--config path_to_file.ini] [--station smhi_station_number ] --db database] [--host dbhost] [--user dbuser] [--password dbpassword]\n" "Default configfile is weather.ini, any parameter can be overwritten on the command line" ) parser = argparse.ArgumentParser() parser.add_argument('--config') parser.add_argument('--db') parser.add_argument('--host') parser.add_argument('--user') parser.add_argument('--password') parser.add_argument('--station') args = parser.parse_args() config_file = "weather.ini" if args.config: config_file = args.config config = configparser.ConfigParser() config.read(config_file) db = config['MySQL']['db'] host = config['MySQL']['host'] user = config['MySQL']['user'] password = config['MySQL']['password'] station = config['SMHI']['station'] # Defaults z_msl = 48.854 lat = 59.178503 lon = 17.909265 TZ_lon = lon freq = 'D' if args.station: station = args.station if not station: station = "97100" if args.db: db = args.db if args.host: host = args.host if not host: host = "localhost" if args.user: user = args.usr if args.password: password = args.password if not (db and host and user and password): usage() sys.exit(1) pd.options.mode.chained_assignment = None station_data = requests.get( url= 'https://opendata-download-metobs.smhi.se/api/version/1.0/parameter/1/station/{}.json' .format(station)).json() newest_to = 0 for i in station_data['position']: if i['to'] > newest_to: z_msl = i['height'] lat = i['latitude'] lon = i['longitude'] TZ_lon = lon mydb = mysql.connector.connect(auth_plugin='mysql_native_password', database=db, host=host, passwd=password, user=user) cursor = mydb.cursor() date_select = ("SELECT DISTINCT `date` " "FROM weather ") cursor.execute(date_select) dates = cursor.fetchall() csv = "date,T_max,T_min,T_mean,RH_max,RH_min,RH_mean,Rainfall\n" for i in dates: working_date = i[0].strftime('%Y-%m-%d') day_select = ('SELECT * FROM weather ' 'WHERE date = "{}"'.format(working_date)) cursor.execute(day_select) day = cursor.fetchall() sum_rain = 0 T_max = -9999 T_min = 9999 RH_max = -9999 RH_min = 9999 sum_temp = 0 sum_rel_hum = 0 counter = 0 for j in day: counter += 1 #+----------------+---------------+------+-----+---------+----------------+ #| Field | Type | Null | Key | Default | Extra | #+----------------+---------------+------+-----+---------+----------------+ #| observation_id | int | NO | PRI | NULL | auto_increment | #| date | date | YES | MUL | NULL | | #| time | time | YES | | NULL | | #| rainfall | float | YES | | NULL | | #| rel_hum | decimal(10,0) | YES | | NULL | | #| temp | float | YES | | NULL | | #| windspeed | float | YES | | NULL | | #| station | int | YES | | NULL | | #| winddir | int | YES | | NULL | | #+----------------+---------------+------+-----+---------+----------------+ observation_id = 0 date = 1 time = 2 rainfall = 3 rel_hum = 4 temp = 5 #windspeed = 6 #station = 7 #winddir = 8 sum_rain += j[rainfall] sum_temp += j[temp] sum_rel_hum += j[rel_hum] if T_max < j[temp]: T_max = j[temp] if T_min > j[temp]: T_min = j[temp] if RH_max < j[rel_hum]: RH_max = j[rel_hum] if RH_min > j[rel_hum]: RH_min = j[rel_hum] T_mean = sum_temp / counter RH_mean = sum_rel_hum / counter csv += working_date + "," + str(T_max) + "," + str(T_min) + "," + str( T_mean) + "," + str(RH_max) + "," + str(RH_min) + "," + str( RH_mean) + "," + str(sum_rain) + "\n" DATA = StringIO(csv) tsdata = pd.read_csv(DATA, parse_dates=True, infer_datetime_format=True, index_col='date') et1 = ETo() et1.param_est(tsdata, freq, z_msl, lat, lon, TZ_lon) et1.ts_param.head() eto1 = et1.eto_hargreaves() upsert = ( "REPLACE INTO aggregated_weather " "(Date, T_max, T_min, T_mean, RH_max, RH_min, RH_mean, Rainfall, ETo, station) " "VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s)") for key, value in eto1.items(): aggdate = key.strftime('%Y-%m-%d') data = (aggdate, float(tsdata.loc[aggdate, 'T_max']), float(tsdata.loc[aggdate, 'T_min']), float(tsdata.loc[aggdate, 'T_mean']), float(tsdata.loc[aggdate, 'RH_max']), float(tsdata.loc[aggdate, 'RH_min']), float(tsdata.loc[aggdate, 'RH_mean']), float(tsdata.loc[aggdate, 'Rainfall']), float(value), int(station)) cursor.execute(upsert, data) mydb.commit() mydb.close()