As a followup to this question, how can I locate the XHR request which is used to retrieve the data from the back-end API on CNBC News in order to be able to scrape this CNBC search query?
The end goal is to have a doc with: headline, date, full article and url.
I have found this: https://api.sail-personalize.com/v1/personalize/initialize?pageviews=1&isMobile=0&query=coronavirus&qsearchterm=coronavirus
Which tells me I don't have access. Is there a way to access information anyway?
Actually my previous answer for you were addressing your question regarding the XHR request:
But here we go with a screenshot:
import requests
params = {
"queryly_key": "31a35d40a9a64ab3",
"query": "coronavirus",
"endindex": "0",
"batchsize": "100",
"callback": "",
"showfaceted": "true",
"timezoneoffset": "-120",
"facetedfields": "formats",
"facetedkey": "formats|",
"facetedvalue":
"!Press Release|",
"needtoptickers": "1",
"additionalindexes": "4cd6f71fbf22424d,937d600b0d0d4e23,3bfbe40caee7443e,626fdfcd96444f28"
}
goal = ["cn:title", "_pubDate", "cn:liveURL", "description"]
def main(url):
with requests.Session() as req:
for page, item in enumerate(range(0, 1100, 100)):
print(f"Extracting Page# {page +1}")
params["endindex"] = item
r = req.get(url, params=params).json()
for loop in r['results']:
print([loop[x] for x in goal])
main("https://api.queryly.com/cnbc/json.aspx")
Pandas DataFrame version:
import requests
import pandas as pd
params = {
"queryly_key": "31a35d40a9a64ab3",
"query": "coronavirus",
"endindex": "0",
"batchsize": "100",
"callback": "",
"showfaceted": "true",
"timezoneoffset": "-120",
"facetedfields": "formats",
"facetedkey": "formats|",
"facetedvalue":
"!Press Release|",
"needtoptickers": "1",
"additionalindexes": "4cd6f71fbf22424d,937d600b0d0d4e23,3bfbe40caee7443e,626fdfcd96444f28"
}
goal = ["cn:title", "_pubDate", "cn:liveURL", "description"]
def main(url):
with requests.Session() as req:
allin = []
for page, item in enumerate(range(0, 1100, 100)):
print(f"Extracting Page# {page +1}")
params["endindex"] = item
r = req.get(url, params=params).json()
for loop in r['results']:
allin.append([loop[x] for x in goal])
new = pd.DataFrame(
allin, columns=["Title", "Date", "Url", "Description"])
new.to_csv("data.csv", index=False)
main("https://api.queryly.com/cnbc/json.aspx")
Output: view online
