Python 将多个URL传递到dict并提取数据_Python_Api_Loops_Dictionary_Url

Python 将多个URL传递到dict并提取数据

python api loops dictionary url

Python 将多个URL传递到dict并提取数据,python,api,loops,dictionary,url,Python,Api,Loops,Dictionary,Url,我生成了以下代码，其中我通过API传递多个URL，并要求将输出写入不同的数据帧。它（有点）起作用，但结果是不正确的 1）它似乎进入功能并以“成功”的方式打印太多次。为什么? 2）所有数据帧的输出相同；不确定错误在哪里请参见功能： def data_extract(url): payload = {'limit':'200000'} # Persists parameters across requests s = requests.Session() # To determine su

我生成了以下代码，其中我通过API传递多个URL，并要求将输出写入不同的数据帧。它（有点）起作用，但结果是不正确的

1）它似乎进入功能并以“成功”的方式打印太多次。为什么?

2）所有数据帧的输出相同；不确定错误在哪里

请参见功能：

def data_extract(url):
payload = {'limit':'200000'}

# Persists parameters across requests
s = requests.Session()

# To determine success of request, and error code
for url in url:
    try:
        response = s.get(url)      
        # If the response was successful, no Exception will be raised 
        response.raise_for_status()
    except HTTPError as http_err:
        print(f'HTTP error occurred: {http_err}')
    except Exception as err:
        print(f'Other error occurred: {err}')
    else:
        # Ret
        jsonData = s.get(url, params=payload).json()
        print('Success!')

df_tmr = pd.DataFrame(jsonData['records'])
return df_tmr

    urls = {
    # Rainfall data
    'tot_rain_mth': 'https://data.gov.sg/dataset/5942f8bd-4240-4f68-acd2-a5a276958237/resource/778814b8-1b96-404b-9ac9-68d6c00e637b/data',
    'no_days_rain_mth': 'https://data.gov.sg/dataset/rainfall-monthly-number-of-rain-days/resource/8b94f596-91fd-4545-bf9e-7a426493b674/data',
    'max_rain_mth': 'https://data.gov.sg/dataset/rainfall-monthly-maximum-daily-total/resource/df4d391e-6950-4fc6-80cd-c9b9ef6354fe/data',
    # Temperature Data
    'mean_sun_dur_mth': 'https://data.gov.sg/dataset/sunshine-duration-monthly-mean-daily-duration/resource/0230819f-1c83-4980-b738-56136d6dc300/data',
    'wet_bulb_hr': 'https://data.gov.sg/dataset/wet-bulb-temperature-hourly/resource/0195dc7a-2f49-4107-ac7c-3112ca4a09a8/data',
    'min_air_temp_day': 'https://data.gov.sg/dataset/surface-air-temperature-mean-daily-minimum/resource/ad0d8a97-9321-42e9-ac6f-46bf12845d44/data',
    'min_air_temp_mth': 'https://data.gov.sg/dataset/surface-air-temperature-monthly-absolute-extreme-minimum/resource/0c5b9752-2488-46cc-ae1c-42318d0f8865/data',
    'mean_air_temp_mth': 'https://data.gov.sg/dataset/surface-air-temperature-monthly-mean/resource/07654ce7-f97f-49c9-81c6-bd41beba4e96/data',
    'max_air_temp_day': 'https://data.gov.sg/dataset/surface-air-temperature-mean-daily-maximum/resource/c7a7d2fd-9d32-4508-92ef-d1019e030a2f/data',
    'max_air_temp_mth': 'https://data.gov.sg/dataset/air-temperature-absolute-extremes-maximum/resource/96e66346-68bb-4ca9-b001-58bbf39e36a7/data',
    # Humidity Data
    'min_hum_mth': 'https://data.gov.sg/dataset/relative-humidity-monthly-absolute-extreme-minimum/resource/585c24a5-76cd-4c48-9341-9223de5adc1d/data',
    'mean_hum_mth': 'https://data.gov.sg/dataset/relative-humidity-monthly-mean/resource/4631174f-9858-463d-8a88-f3cb21588c67/data',
    'mean_hum_yr': 'https://data.gov.sg/dataset/relative-humidity-annual-mean/resource/77b9059f-cc9a-4f4f-a495-9c268945191b/data' 
}

df={}
for i in range(len(urls.keys())):
    df[str(i)] = pd.DataFrame()
#print('Name of Dataframe:', df)
    df[str(i)] = data_extract(urls.values())
print (df['0'])
print (df['1'])

请参见对函数的调用：

def data_extract(url):
payload = {'limit':'200000'}

# Persists parameters across requests
s = requests.Session()

# To determine success of request, and error code
for url in url:
    try:
        response = s.get(url)      
        # If the response was successful, no Exception will be raised 
        response.raise_for_status()
    except HTTPError as http_err:
        print(f'HTTP error occurred: {http_err}')
    except Exception as err:
        print(f'Other error occurred: {err}')
    else:
        # Ret
        jsonData = s.get(url, params=payload).json()
        print('Success!')

df_tmr = pd.DataFrame(jsonData['records'])
return df_tmr

    urls = {
    # Rainfall data
    'tot_rain_mth': 'https://data.gov.sg/dataset/5942f8bd-4240-4f68-acd2-a5a276958237/resource/778814b8-1b96-404b-9ac9-68d6c00e637b/data',
    'no_days_rain_mth': 'https://data.gov.sg/dataset/rainfall-monthly-number-of-rain-days/resource/8b94f596-91fd-4545-bf9e-7a426493b674/data',
    'max_rain_mth': 'https://data.gov.sg/dataset/rainfall-monthly-maximum-daily-total/resource/df4d391e-6950-4fc6-80cd-c9b9ef6354fe/data',
    # Temperature Data
    'mean_sun_dur_mth': 'https://data.gov.sg/dataset/sunshine-duration-monthly-mean-daily-duration/resource/0230819f-1c83-4980-b738-56136d6dc300/data',
    'wet_bulb_hr': 'https://data.gov.sg/dataset/wet-bulb-temperature-hourly/resource/0195dc7a-2f49-4107-ac7c-3112ca4a09a8/data',
    'min_air_temp_day': 'https://data.gov.sg/dataset/surface-air-temperature-mean-daily-minimum/resource/ad0d8a97-9321-42e9-ac6f-46bf12845d44/data',
    'min_air_temp_mth': 'https://data.gov.sg/dataset/surface-air-temperature-monthly-absolute-extreme-minimum/resource/0c5b9752-2488-46cc-ae1c-42318d0f8865/data',
    'mean_air_temp_mth': 'https://data.gov.sg/dataset/surface-air-temperature-monthly-mean/resource/07654ce7-f97f-49c9-81c6-bd41beba4e96/data',
    'max_air_temp_day': 'https://data.gov.sg/dataset/surface-air-temperature-mean-daily-maximum/resource/c7a7d2fd-9d32-4508-92ef-d1019e030a2f/data',
    'max_air_temp_mth': 'https://data.gov.sg/dataset/air-temperature-absolute-extremes-maximum/resource/96e66346-68bb-4ca9-b001-58bbf39e36a7/data',
    # Humidity Data
    'min_hum_mth': 'https://data.gov.sg/dataset/relative-humidity-monthly-absolute-extreme-minimum/resource/585c24a5-76cd-4c48-9341-9223de5adc1d/data',
    'mean_hum_mth': 'https://data.gov.sg/dataset/relative-humidity-monthly-mean/resource/4631174f-9858-463d-8a88-f3cb21588c67/data',
    'mean_hum_yr': 'https://data.gov.sg/dataset/relative-humidity-annual-mean/resource/77b9059f-cc9a-4f4f-a495-9c268945191b/data' 
}

df={}
for i in range(len(urls.keys())):
    df[str(i)] = pd.DataFrame()
#print('Name of Dataframe:', df)
    df[str(i)] = data_extract(urls.values())
print (df['0'])
print (df['1'])

-->抱歉，格式错误；这么快就弄不好了


import requests
import pandas as pd
def data_extract(url):
  print(url)
  payload = {'limit':'200000'}
  s = requests.Session()
  try:
      response = s.get(url)      
      response.raise_for_status()
      jsonData = s.get(url, params=payload).json()
      print('Success!')
  except Exception as err:
      print(f'Other error occurred: {err}')      

  df_tmr = pd.DataFrame(jsonData['records'])
  return df_tmr

urls = {
    # Rainfall data
    'tot_rain_mth': 'https://data.gov.sg/dataset/5942f8bd-4240-4f68-acd2-a5a276958237/resource/778814b8-1b96-404b-9ac9-68d6c00e637b/data',
    'no_days_rain_mth': 'https://data.gov.sg/dataset/rainfall-monthly-number-of-rain-days/resource/8b94f596-91fd-4545-bf9e-7a426493b674/data',
    'max_rain_mth': 'https://data.gov.sg/dataset/rainfall-monthly-maximum-daily-total/resource/df4d391e-6950-4fc6-80cd-c9b9ef6354fe/data',
    # Temperature Data
    'mean_sun_dur_mth': 'https://data.gov.sg/dataset/sunshine-duration-monthly-mean-daily-duration/resource/0230819f-1c83-4980-b738-56136d6dc300/data',
    'wet_bulb_hr': 'https://data.gov.sg/dataset/wet-bulb-temperature-hourly/resource/0195dc7a-2f49-4107-ac7c-3112ca4a09a8/data',
    'min_air_temp_day': 'https://data.gov.sg/dataset/surface-air-temperature-mean-daily-minimum/resource/ad0d8a97-9321-42e9-ac6f-46bf12845d44/data',
    'min_air_temp_mth': 'https://data.gov.sg/dataset/surface-air-temperature-monthly-absolute-extreme-minimum/resource/0c5b9752-2488-46cc-ae1c-42318d0f8865/data',
    'mean_air_temp_mth': 'https://data.gov.sg/dataset/surface-air-temperature-monthly-mean/resource/07654ce7-f97f-49c9-81c6-bd41beba4e96/data',
    'max_air_temp_day': 'https://data.gov.sg/dataset/surface-air-temperature-mean-daily-maximum/resource/c7a7d2fd-9d32-4508-92ef-d1019e030a2f/data',
    'max_air_temp_mth': 'https://data.gov.sg/dataset/air-temperature-absolute-extremes-maximum/resource/96e66346-68bb-4ca9-b001-58bbf39e36a7/data',
    # Humidity Data
    'min_hum_mth': 'https://data.gov.sg/dataset/relative-humidity-monthly-absolute-extreme-minimum/resource/585c24a5-76cd-4c48-9341-9223de5adc1d/data',
    'mean_hum_mth': 'https://data.gov.sg/dataset/relative-humidity-monthly-mean/resource/4631174f-9858-463d-8a88-f3cb21588c67/data',
    'mean_hum_yr': 'https://data.gov.sg/dataset/relative-humidity-annual-mean/resource/77b9059f-cc9a-4f4f-a495-9c268945191b/data' 
}

df={}
temp = list(urls.values())
for i in range(len(temp)):
    df[str(i)] = data_extract(temp[i])

print(df['0'])
print(df['1'])

if len(df) == len(temp):
  print('success')

我想这对你有帮助。您可以在其中迭代所有项并只返回最后一项。只需要从数据提取方法中删除for循环。

Hello@SahilDesai，太好了，谢谢你这么快-我会在检查完所有数据是否准确后更新此帖子