import io
import pandas as pd
data_spring = pd.read_csv('spring.csv',encoding='CP949')
data_summer = pd.read_csv('summer.csv',encoding='CP949')
data_fall = pd.read_csv('fall.csv',encoding='CP949')
data_winter = pd.read_csv('winter.csv',encoding='CP949')

df_spring = df_spring.fillna(0)
df_summer = df_summer.fillna(0)
df_fall = df_fall.fillna(0)
df_winter = df_winter.fillna(0)
df_spring_test = df_spring_test.fillna(0)

df_sp=df_spring.drop(['지점','일시'],axis=1)
df_su=df_summer.drop(['지점','일시'],axis=1)
df_fa=df_fall.drop(['지점','일시'],axis=1)
df_wi=df_winter.drop(['지점','일시'],axis=1)
df_spring_test=df_spring_test.drop(['지점','일시'],axis=1)

train_spring = df_sp.drop('지점명', axis=1)
train_summer = df_su.drop('지점명', axis=1)
train_fall = df_fa.drop('지점명', axis=1)
train_winter = df_wi.drop('지점명', axis=1)
test_spring = df_spring_test.drop('지점명',axis=1)

from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(train_spring, y_label_spring, test_size=0.3, random_state=42)

from socket import *
from datetime import datetime, timedelta
import numpy as np
HOST = ""
PORT = 12000
s = socket(AF_INET, SOCK_STREAM)
print ('Socket created')
s.bind((HOST, PORT))
print ('Socket bind complete')
s.listen(1)
print ('Socket now listening')

#접속 승인
conn, addr = s.accept()
print("Connected by ", addr)

#데이터 수신
rc = conn.recv(1024)
rc = rc.decode("utf8").strip()
if not rc: break
print("Received: " + rc)
date=rc[0:8]
time=rc[8:]
print('date:',date)
print('time:',time)

#현재 날짜 정보
time1 = datetime.now() 
#원하는 날짜 정보 
want_day_s = datetime(int(rc[0:4]),int(rc[4:6]),int(rc[6:8]),int(rc[8:10]),0,0) 

# 오늘과 원하는 날짜의 차이 
# 2면 모레, 1이면 내일, 0이면 오늘 날씨 선택한 것
interval = (want_day_s - time1).days 

#모레를 선택했는데 현재 시각이 새벽 여섯시 전이면 오류 메시지 보내기
if(interval == 2) and (int(time1[12:14]) <= int(6)): 
    res = "새벽 6시 이후 모레 날씨 정보가 업데이트 됩니다!"
    conn.sendall(res.encode("utf-8"))
    conn.close()
    s.close()
    exit()

#오늘, 내일, 모레 이외의 선택을 했을 시 오류 메시지 보내기
if(interval != 1) and (interval != 0) and (interval != 2): 
    res = "오늘, 내일, 모레의 예보만을 지원합니다!"
    conn.sendall(res.encode("utf-8"))
    conn.close()
    s.close()
    exit()

#하루 전날 날짜 정보 받기
pre_day_s = want_day_s + timedelta(days=-1) 

pre_day_s=str(pre_day_s)
pre_day_s=pre_day_s[:11]
pre_day_s=pre_day_s.replace('-','')

want_day_s=str(want_day_s)

#원하는 pre_day의 형태로 변환
pre_day = pre_day_s + "00" 
print('pre_day_s',pre_day_s)

#원하는 want_day 형태로 변환
want_day = want_day_s[:16] 
print('want_day', want_day)

import pandas as pd
from pandas import json_normalize
import json
import requests
from bs4 import BeautifulSoup

url = 'http://apis.data.go.kr/1360000/TourStnInfoService/getTourStnVilageFcst'

x_test = pd.DataFrame(columns=['tm','spotName','th3','wd','ws','sky','rhm','pop'])

for ID in range(1,439):
    No = [29, 248, 249, 250]
    if ID in No:
        continue
    course_id = str(ID)
    queryString = "?" + \
      "ServiceKey=" + "0000000000000000" + \
      "&pageNo=" + "1"+ \
      "&numOfRows=" + "140" + \
      "&dataType=" + "JSON" + \
      "&CURRENT_DATE=" + pre_day + \
      "&HOUR=" + "24" + \
      "&COURSE_ID=" + course_id
      
    queryURL = url + queryString
    response = requests.get(queryURL)

    r_dict = json.loads(response.content)
    data = json_normalize(r_dict['response']['body']['items']['item'])

    li = ['tm','spotName','th3','wd','ws','sky','rhm','pop']
    
    #tm : 선택한 시각으로 부터 3시간 기온 (예 : 09면 09-12)
    #wd : 풍향
    #ws : 풍속
    #sky: 하늘 상태
    # 1: 맑음, 2: 구름 조금, 3: 구름많이, 4:흐림, 5: 비, 6:비눈, 7:눈비, 8:눈
    #rhm: 습도
    #pop: 강수확률

    #필요한 column만 data에 저장
    data = data.loc[:,li]
    
    #오전 오후 저녁 시간선택에 맞는 데이터만 추출
    List = []
    for i in range(0,len(data['tm'])):
        if want_day not in data.loc[i,'tm']:
                List.append(i)
    data = data.drop(List,axis = 0)
    x_test = x_test.append(data,ignore_index=True)
x_test = x_test.drop_duplicates(['spotName'], keep='first')