### Making List of rain forecasting pixels
rain = processor.rainbar(img)
logger.info('rain bars ready')
### Checking if rain forecasted
if rain:
logger.info('There is some rain!')
### Getting location for each pixel
rain = processor.pixelcoding(rain, img)
logger.info('Pixel coding done')
### Gettiung forecast
barish = processor.get_forecast(rain, img, dates)
logger.info('Getting forecast')
else:
barish = processor.no_rain(img, dates)
logger.info('No rain and df ready')
barish['created_at'] = datetime.now()
barish['forecast'] = barish['forecast'].apply(lambda x: int(1)
if x > 0 else int(0))
logger.info('DF ready to go')
# processor.store_forecast(barish)
conn = pymysql.connect("139.59.42.147", "dummy", "dummy123",
"energy_consumption")
mycursor = conn.cursor()
query = "INSERT INTO meteo_data(`date`, `time`, `forecast`, `horizon`, `created_at`) VALUES ('{}','{}','{}','{}','{}') ON DUPLICATE KEY UPDATE forecast='{}', horizon='{}', created_at='{}'"
for row in barish.values:
mycursor.execute(
query.format(row[0], row[1], row[2], row[3], row[4], row[2],
row[3], row[4]))
