Request all data from next day for once

[Caiocoelho07]

I'm trying to retrieve the next day forecast. There is any way of getting all values for once or only requesting hour per hour?

[jagoosw]

It would appear I made it only do one time at a time. Because of the format of the API it would be non-trivial to request a range of times as one request, but you could easily iterate through a set of times and turn it into an array. If you do this it would be great if you could add a wrapper for it to this library!

[Caiocoelho07]

I create a loop to request this values to the next day but after some interaction i'm retriving the same values. ` horarios =['00:00','01:00','02:00','03:00', '04:00','05:00','06:00','07:00', '08:00','09:00','10:00','11:00', '12:00','13:00','14:00','15:00', '16:00','17:00','18:00','19:00', '20:00','21:00','22:00','23:00']

#Dia de interesse
t1 = date.today()
t2 = date.today()+timedelta(days=1)
t3 = date.today()+timedelta(days=2)
t4 = date.today()+timedelta(days=3)
t5 = date.today()+timedelta(days=4)


t1 = t1.strftime("%Y%m%d")
t2 = t2.strftime("%Y%m%d")
t3 = t3.strftime("%Y%m%d")
t4 = t4.strftime("%Y%m%d")
t5 = t5.strftime("%Y%m%d")

#Coordenadas grid 0.25 AS1
lat=['-5.25','-5.25']

long=['-35.00','-35.75']

parque=['REN1','VSM']

f=getgfs.Forecast("0p25",'1hr')

list_parques=['REN1','REN2','REN3','REN4','VSM']
df = pd.DataFrame(columns=list_parques)

datas = [t1,t2,t3,t4,t5]
for p in range(len(parque)):
    lista_aux=[]
    for d in range(len(datas)):
        dia=[datas[d]]*len(horarios)
        for j in range(len(horarios)):
            res=f.get(["gustsfc"],dia[j] +' '+ horarios[j], lat[p],long[p])
            print("gustsfc" + dia[j] +' '+ horarios[j] + lat[p] + long[p])
            lista_aux.append(res.variables["gustsfc"].data)
    lista_aux = np.array(lista_aux).flatten()
    df[parque[p]] = lista_aux 

`

[lgblkb]

The same. Getting repeated data for forecasted dates.

[YannChemin]

Is it possible that current date is hardcoded somewhere?

import getgfs
import numpy as np
from datetime import datetime, timedelta
# Getting the current date and time
dt = datetime.now()
print("Date and time is:", dt)
today = dt.strftime("%Y%m%d")
#Create the list of 3 dates from now
dates = []
for i in range(3):
	newdate = datetime.today() + timedelta(days=i)
	dates.append(newdate.strftime("%Y%m%d"))
f = getgfs.Forecast("0p25")
f.search("precipitation")
# ROIs search
xy = [["Gilgit", '[35.0:36.0]', '[74.0:75.0]']]
for i in range(len(xy)):
	print("++++++++++++")
	print(xy[i][0])
	print("++++++++++++")
	for d in dates:
		for t in [12]:
			timestamp = d+" "+str(t)+":00"
			res = f.get(["apcpsfc"],timestamp, xy[i][1], xy[i][2])
			val = res.variables["apcpsfc"].data
			for y in range(len(val[0])):
				for x in range(len(val[0][y])): 
					if (val[0][y][x] > 9999):
						val[0][y][x] = np.nan 
			print(timestamp)
			print(val[0])

The result is repeating even if the query is for a different day

Date and time is: 2023-03-22 06:56:49.299838
20230322
++++++++++++
Gilgit
++++++++++++
20230322 12:00
[[1.5625 1.9375 1.75   1.5625 0.375 ]
 [0.6875 0.3125 2.3125 3.6875 0.8125]
 [0.25   0.1875 0.25   0.5    0.625 ]
 [2.     0.9375 0.1875 0.     0.1875]
 [0.8125 0.0625 0.1875 0.5    0.75  ]]
20230323 12:00
[[1.5625 1.9375 1.75   1.5625 0.375 ]
 [0.6875 0.3125 2.3125 3.6875 0.8125]
 [0.25   0.1875 0.25   0.5    0.625 ]
 [2.     0.9375 0.1875 0.     0.1875]
 [0.8125 0.0625 0.1875 0.5    0.75  ]]
20230324 12:00
[[1.5625 1.9375 1.75   1.5625 0.375 ]
 [0.6875 0.3125 2.3125 3.6875 0.8125]
 [0.25   0.1875 0.25   0.5    0.625 ]
 [2.     0.9375 0.1875 0.     0.1875]
 [0.8125 0.0625 0.1875 0.5    0.75  ]]

Is it possible that only the current day is hardcoded in the lib?