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GetData.py
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# coding:utf-8
import pandas as pd
import os
import datetime
import http.client
import urllib
import json
from io import *
from .. import config
#最终数据写入地址
DATAPATH = config.Config.DATAPATH
print(DATAPATH)
GET = 'GET'
POST = 'POST'
CITY_CODE = "370100"
url = 'jngffp.cn'
'''
通过请求的方式调用api接口
date:2017-8-3 14:40:01
'''
def getJsonData(method, uri, body=None):
connection = http.client.HTTPConnection('jngffp.cn') # 设置请求主机地址，如果不是80端口，后面多加一个参数
requestHeaders = {'Content-Type': 'text/html;charset=UTF-8',
'Accept': 'text/html,application/xhtml+xml, */*'} # 设置返回值类型
connection.request(method, uri, body, requestHeaders) # 开始请求
response = connection.getresponse() # 接收返回值
print("状态:", response.status) # 返回状态
datas = response.read(); # 读取返回值
return datas
'''
获取所有电站ID和经纬度信息
获取内容：
stationCode：电站编码，
changZhanId：电站ID，
titile：电站名称，
还有最后经纬度，
最后把数据保存到本地
'''
def getPositionAll():
urlPosition = 'http://jngffp.cn/getMapController/mapData?StationStat=0&provinceIds=284'
print(urlPosition)
result = getJsonData(POST, urlPosition) # 调用请求函数
# print(type(BytesIO(result)))
# dataWeatherInfo = json.load(StringIO(result))["data"] # 请求返回的字符串转换为json字符串,result必须是str or none
dataPosition = json.load(BytesIO(result))["attributes"]["mapdata"] # 请求返回的字符串转换为json字符串
#取得信息，并保存到本地
df = pd.DataFrame(dataPosition)
df = df.sort_values(by='changZhanId')
df = df.reset_index()
df.drop(['index'], axis=1)
station = df[['stationCode', 'changZhanId', 'title']]
# 把Series转为list获取其中的字典
list_temp = df['position'].values.tolist()
temp = pd.DataFrame(list_temp)
station['longitude'] = temp['lng']
station['latitude'] = temp['lat']
file = os.path.join(DATAPATH, 'station.csv')
station.to_csv(file, index=False)
'''
根据相应条件获取天气
date:2017-8-3 15:12:06
'''
def getWeatherInfo(nowDate, cityID):
paramWeatherInfo = {"city_Code": cityID, "startTime": nowDate + " 07",
"endTime": nowDate + " 18"} # 传递参数 为什么时间选择7点到18点，因为这个数据库存储的时间是天气更新时间
bodyWeatherInfo = urllib.parse.urlencode(paramWeatherInfo) # 参数转码
urlWeatherInfo = 'http://' + url + '/getSolarDataByPython/getWeatherList?' + bodyWeatherInfo
print(urlWeatherInfo)
result = getJsonData(POST, urlWeatherInfo) # 调用请求函数
# dataWeatherInfo = json.load(StringIO(result))["data"] # 请求返回的字符串转换为json字符串,result必须是str or none
dataWeatherInfo = json.load(BytesIO(result))["data"] # 请求返回的字符串转换为json字符串
# print(dataWeatherInfo)
return dataWeatherInfo
'''
获取日电量
date:2017-8-3 14:40:01
'''
def getPower(forecastDate, regionId):
paramPower = {"regionType": 5, "regionId": regionId, "dataType": 2, "batchType": 0,
"dayTime": forecastDate} # 传递参数 为什么时间选择7点到18点，因为这个数据库存储的时间是天气更新时间
bodyPower = urllib.parse.urlencode(paramPower) # 参数转码
urlPower = 'http://' + url + '/getSolarDataByPython/getSimilardayPower?' + bodyPower
print(urlPower)
result = getJsonData(POST, urlPower) # 调用请求函数
if (len(result) > 2): # 返回为{}len(result)=2
# print(result)
data = json.load(BytesIO(result))["data"] # 请求返回的字符串转换为json字符串
return data
else:
print("为空")
return None
'''
获取所有电站2017-1-1 至 2020-3-1的日发电量
获取内容：电站ID，time，日发电量，容量
'''
def getPowerAll():
station=pd.read_csv(file,encoding='GB2312')
regionId=station['changZhanId']
startDate='2017-1-1 22'
endDate='2020-3-1 22'
startDate = datetime.datetime.strptime(startDate, '%Y-%m-%d %H')
endDate = datetime.datetime.strptime(endDate, '%Y-%m-%d %H')
for id in regionId:
print(id)
#if(id<400):
#continue
i = datetime.timedelta(days=1)
dayPowerAll=pd.DataFrame(columns=['id','time','dayPower','Capacity'])
while i <= (endDate - startDate + datetime.timedelta(days=1)):
listdata = startDate + i-datetime.timedelta(days=1)#在date1的基础上加i天
date=(listdata).strftime('%Y-%m-%d %H')
#print(date)
dayPower=getPower(date,id)
if(dayPower==None):
#默认值
dayPower=pd.DataFrame([[str(id),date,0,50]],columns=['id','time','dayPower','Capacity'])
i += datetime.timedelta(days=1)#i++
dayPowerAll=pd.concat([dayPowerAll,dayPower])
else:
dayPower=pd.DataFrame(dayPower)[['id','time','dayPower','Capacity']]
i += datetime.timedelta(days=1)#i++
dayPowerAll=pd.concat([dayPowerAll,dayPower])
dayPowerAll=dayPowerAll[['id','time','dayPower']]
dayPowerAll.to_csv('../datasets/PowerData/station' + str(id) + '.csv',index=False)
'''
获得所有天气信息
获取内容：
city_Code:城市编码
city_Name:城市名字
weatherCode:天气编码
weatherTypeName:天气别称
humidity:湿度
temperature:温度
wind:风向和风速
'''
def getWeatherAll():
weatherInfo = pd.DataFrame(
columns=['city_Code', 'city_Name', 'time', 'weatherCode', 'weatherTypeName', 'humidity', 'temperature', 'wind'])
startDate = '2017-1-1'
endDate = '2020-3-1'
startDate = datetime.datetime.strptime(startDate, '%Y-%m-%d')
endDate = datetime.datetime.strptime(endDate, '%Y-%m-%d')
i = datetime.timedelta(days=1)
while i <= (endDate - startDate + datetime.timedelta(days=1)):
listdata = startDate + i - datetime.timedelta(days=1) # 在date1的基础上加i天
date = (listdata).strftime('%Y-%m-%d')
i += datetime.timedelta(days=1) # i++
historyWeather = getWeatherInfo(date, '370100')
if len(historyWeather) == 0:
print(date, '没有数据')
historyWeather = pd.DataFrame([['370100', '济南', date, 0, 0, 0, 0, 0]],
columns=['city_Code', 'city_Name', 'time', 'weatherCode', 'weatherTypeName',
'humidity', 'temperature', 'wind'])
historyWeather = historyWeather[
['city_Code', 'city_Name', 'time', 'weatherCode', 'weatherTypeName', 'humidity', 'temperature', 'wind']]
weatherInfo = pd.concat([weatherInfo, historyWeather])
continue
else:
historyWeather = pd.DataFrame(historyWeather)
historyWeather = historyWeather[
['city_Code', 'city_Name', 'time', 'weatherCode', 'weatherTypeName', 'humidity', 'temperature', 'wind']]
weatherInfo = pd.concat([weatherInfo, historyWeather])
weatherInfo.to_csv('../datasets/weather.csv', index=False)
#getWeatherAll()