# create a local virtual environment, you can call it as you wish, here 'myenv' is used.
conda create -n myenv python=3.8 

# add repository channel
conda config --add channels conda-forge

# activate the local environment. 
conda activate myenv

# install the required packages
conda install -c conda-forge/label/main xarray cfgrib eccodes 
conda install cartopy netcdf4 matplotlib

# and the cdsapi
pip install cdsapi

import cdsapi
from datetime import datetime, timedelta


def get_monthsdays(start =[2019,1,1],end=[2019,12,31]):
    # reforecast time index
    start, end = datetime(*start),datetime(*end)
    days = [start + timedelta(days=i) for i in range((end - start).days + 1)]
    monthday = [d.strftime("%B-%d").split("-")  for d in days if d.weekday() in [0,3] ]   

    return monthday

# get date index
MONTHSDAYS = get_monthsdays() 

if __name__ == '__main__':
    c = cdsapi.Client()


    # set station coordinates (lat,lon)
    COORDS = {
            "Thames":[51.35,-0.45],
            "Po":[44.85, 11.65]
            }
        
    # select all years
    YEARS  = ['%d'%(y) for y in range(1999,2019)]
    
    # select all leadtime hours
    LEADTIMES = ['%d'%(l) for l in range(24,1128,24)]
    
    # loop over date index
    for md in MONTHSDAYS:

        month = md[0].lower()
        day = md[1]
        
		# loop over coordinates
        for station in COORDS:

            station_point_coord = COORDS[station]*2 # coordinates input for the area keyword
            
            c.retrieve(
                'cems-glofas-reforecast',
                {
                    'system_version': 'version_2_2',
                    'variable': 'river_discharge_in_the_last_24_hours',
                    'format': 'grib',
                    'hydrological_model': 'htessel_lisflood',
                    'product_type': 'control_reforecast',
                    'area':station_point_coord, 
                    'hyear': YEARS,
                    'hmonth': month ,
                    'hday': day ,
                    'leadtime_hour': LEADTIMES,
                },
                f'glofas_reforecast_{station}_{month}_{day}.grib')