Google News contains valuable data -- news articles, headlines, sources, publication dates, and more. Scraping this data directly means dealing with anti-bot detection, CAPTCHAs, IP rotation, and constantly breaking selectors. The Scavio API handles all of that and returns clean, structured JSON from a single POST request.
This tutorial shows you how to scrape Google News using Python and the Scavio API. By the end, you will have a working Python script that fetches real-time Google News data and parses the results.
Prerequisites
- Python installed on your machine
- A Scavio API key (free tier includes 50 credits on signup -- no credit card required)
Step 1: Install Dependencies
Install requests to make HTTP requests:
pip install requestsStep 2: Make Your First Google News Search
Send a POST request to the Scavio Google News API endpoint with your query. The API returns structured JSON with news articles, headlines, sources, and more.
# source is an object - read source.name, not source.
import requests
API_KEY = "sk_live_your_key"
query = "artificial intelligence regulation"
response = requests.post(
"https://api.scavio.dev/api/v2/google/news",
headers={
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json",
},
json={"query": query},
timeout=60,
)
response.raise_for_status()
data = response.json()
rows = data.get("news_results") or []
for row in rows[:5]:
print(row.get("title"))
print(" ", (row.get("source") or {}).get("name"), row.get("date"), row.get("link"))Step 3: Example Response
The API returns structured JSON. Here is an example response for a Google News search:
{
"search_parameters": { "engine": "google_news", "q": "openai", "hl": "en", "gl": "us" },
"news_results": [
{
"position": 1,
"title": "OpenAI Discovers New Way to Cut Inference Costs in Half",
"link": "https://www.theinformation.com/newsletters/ai-agenda/openai-discovers-new-way",
"source": { "name": "The Information", "authors": ["Stephanie Palazzolo"] },
"date": "21 hours ago",
"iso_date": "2026-06-30T14:06:00Z"
}
],
"response_time": 2260,
"credits_used": 1,
"credits_remaining": 4816
}Every field is structured and typed -- no HTML parsing, no CSS selectors, no regex extraction. Your Python code can access any field directly.
Step 4: Full Working Example
Here is a complete, runnable Python script that searches Google News and prints the results:
"""
Search Google News data with the Scavio API.
POST /api/v2/google/news - rows come back under news_results, 1 credit per call.
"""
import json
import os
import requests
# source is an object - read source.name, not source.
API_URL = "https://api.scavio.dev/api/v2/google/news"
API_KEY = os.environ["SCAVIO_API_KEY"]
def search_google_news(query: str) -> dict:
response = requests.post(
API_URL,
headers={
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json",
},
json={"query": query},
timeout=60,
)
response.raise_for_status()
return response.json()
if __name__ == "__main__":
data = search_google_news("artificial intelligence regulation")
print(json.dumps(data, indent=2))
rows = data.get("news_results") or []
for row in rows[:5]:
print(row.get("title"))
print(" ", (row.get("source") or {}).get("name"), row.get("date"), row.get("link"))Why Use Scavio Instead of Scraping Google News Directly?
- No proxy management. Direct scraping requires rotating proxies to avoid IP bans. Scavio handles all of this server-side.
- No CAPTCHA solving. Google News aggressively blocks automated requests. Scavio returns clean data every time.
- Structured JSON output. No HTML parsing or CSS selector maintenance. Get typed, consistent data from every request.
- Multi-platform in one API. Search Google, Amazon, YouTube, and Walmart from the same API key with the same authentication pattern.
- Free tier included. 50 credits on signup with no credit card required. Each search costs 1 credit.