import requests
from pandas.io.json import json_normalize
base_url = 'https://turo.com'
url = 'https://turo.com/api/search?'
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3578.98 Safari/537.36',
'Accept': '*/*',
'Accept-Encoding': 'gzip, deflate, br',
'Accept-Language': 'en-US,en;q=0.9',
'Connection': 'keep-alive',
'Host': 'turo.com',
'Referer': 'https://turo.com/search'}
params = {
'airportCode': 'EWR',
'customDelivery': 'true',
'defaultZoomLevel': '11',
'endDate': '04/05/2019',
'endTime': '11:00',
'international': 'true',
'isMapSearch': 'false',
'itemsPerPage': '200',
'location': 'EWR',
'locationType': 'Airport',
'maximumDistanceInMiles': '30',
'sortType': 'RELEVANCE',
'startDate': '03/05/2019',
'startTime': '10:00'}
response = requests.get(url, headers=headers, params=params)
data = response.json()
search_id = data['searchId']
print (search_id)
for ele in data['list']:
link = ele['vehicle']['url']
print (base_url + link)
links_list = [ base_url + ele['vehicle']['url'] for ele in data['list'] ]
# If you want to Manipulate a table of the data
df = json_normalize(data['list'])