请求未能解码响应

Question

I want to use python requests to get response from API. In postman this works. I use headers Content-Type application/json and in body raw JSON. How I can make this in python?

Now I get the following contentDecodingError

'Received response with content-encoding: gzip, but failed to decode it.', error('Error -3 while decompressing data: incorrect data check')

Example Code

import requests
url = "http://api.semstorm.com/api-v3/monitoring/monitoring-keyword/get-list"
key = "xxxx"
dat = {'services_token' : key, 'campaign_id' : 43174}
hed = {'Content-Type': 'application/json'}


POST = requests.post(url, json = dat, headers = hed)

Answer 1

Your module expects gzip but the server doesn't return gzip. You could try to add an Encoding-Type. I cannot guarantee the type, this depends on your api.

import requests
url = "http://api.semstorm.com/api-v3/monitoring/monitoring-keyword/get-list"
key = "xxxx"
dat = {'services_token' : key, 'campaign_id' : 43174}
hed = {'Content-Type': 'application/json', 'Accept-Encoding': 'deflate'}

POST = requests.post(url, json = dat, headers = hed)

Answer 2

如果我添加encode = c（'json'），这对我来说是有效的。

Answer 3

Were you able to solve the problem at the python level? Because I was able to download only the basic data about the campaign, but it does not display the data to me as in php

import requests
import urllib3
import json
urllib3.disable_warnings()
import zlib
import gzip


    url = 'http://api.semstorm.com/api-v3/monitoring/monitoring-campaign/'
    headers = {
    'Content-Type': 'application/json',
    'Accept-Encoding': 'gzip',
}

campaign_id = xxxxx

hed = {'Content-Type': 'application/json', 'Accept-Encoding': 'deflate'}
data = {
    'services_token': 'xxxxx', 
    'campaign_id':campaign_id,
    "datemin": "20211101",
    "datemax": "20211130",
    "gap": "monthly"
    
}
url_new = url + str(campaign_id) +'.json'
from pandas import json_normalize
r= requests.get(url_new, headers=headers, json = data,   allow_redirects=False, verify=False,params=data
             )
jsonResponse = json.loads(r.text)
json_normalize(jsonResponse['results'])