Automate Google Indexing API with Python to bypass 'Discovered - Currently Not Indexed'. Fast, scalable indexing for new content.
The “Discovered - Currently Not Indexed” status in Google Search Console is one of the most frustrating bottlenecks for content sites. Google has discovered your pages but hasn’t yet decided they are important enough to crawl and index.
The most effective solution is to proactively request indexing through the Google Indexing API using an automated Python worker.
I built this system for a large content platform. It dramatically reduced the time from publishing to being indexed from days to minutes for priority pages.
The Production-Grade Worker
Here is the complete, robust implementation:
import asyncio
import json
import logging
from pathlib import Path
from urllib.parse import urlparse, urljoin
from google.oauth2 import service_account
from googleapiclient.discovery import build
logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
class GoogleProductionIndexer:
def __init__(self, credentials_path: str, base_site_url: str, state_file: str = "indexed_registry.json"):
self.base_url = urlparse(base_site_url).geturl().rstrip('/')
self.state_file = Path(state_file)
self.submitted_cache = self._load_state()
self.credentials = service_account.Credentials.from_service_account_file(
credentials_path,
scopes=["https://www.googleapis.com/auth/indexing"]
)
self.service = build("indexing", "v3", credentials=self.credentials)
def _load_state(self) -> set:
"""Load previously submitted URLs to respect the 200-request daily quota limits."""
if self.state_file.exists():
try:
with open(self.state_file, 'r', encoding='utf-8') as f:
return set(json.load(f))
except Exception:
return set()
return set()
def _save_state(self) -> None:
"""Persist state cache back to disk safely."""
with open(self.state_file, 'w', encoding='utf-8') as f:
json.dump(list(self.submitted_cache), f, indent=2)
def _normalize_url(self, input_url: str) -> str:
"""Sanitize paths and complete absolute constraints defensively."""
if input_url.startswith('http'):
return input_url
return urljoin(self.base_url, input_url.lstrip('/'))
async def request_indexing(self, raw_url: str) -> bool:
"""Request indexing cleanly via non-blocking asynchronous thread pools."""
target_url = self._normalize_url(raw_url)
# Idempotency barrier protecting quota integrity
if target_url in self.submitted_cache:
logging.info(f"[-] Skipping {target_url} - Already processed within active window.")
return False
body = {
"url": target_url,
"type": "URL_UPDATED"
}
try:
# Correct Execution: Construct payload synchronously, defer network I/O execution to thread pool
api_request = self.service.urlNotifications().publish(body=body)
response = await asyncio.to_thread(api_request.execute)
logging.info(f"✅ Google Indexing API confirmed: {target_url}")
self.submitted_cache.add(target_url)
self._save_state()
return True
except Exception as e:
logging.error(f"❌ Failed processing request target {target_url}: {e}")
return False
async def process_batch(self, urls: list, batch_concurrency: int = 4):
"""Throttle bursts to avoid triggering HTTP 429 Too Many Requests from Google gateways."""
semaphore = asyncio.Semaphore(batch_concurrency)
async def worker_wrapper(url):
async with semaphore:
success = await self.request_indexing(url)
if success:
# Courteous pacing to guarantee network pipeline stability
await asyncio.sleep(0.75)
tasks = [worker_wrapper(u) for u in urls]
await asyncio.gather(*tasks)
# Sample Execution Lifecycle
# if __name__ == "__main__":
# indexer = GoogleProductionIndexer("credentials.json", "https://news-todaytrends.com")
# asyncio.run(indexer.process_batch(["/priority-page-1", "https://news-todaytrends.com/priority-page-2"]))The Mathematics of Quota Throttling: Token Bucket Analogy
When bursting hundreds of indexing requests simultaneously from a production CMS pipeline, you run directly into Google's rate-limiting firewalls. Google monitors incoming traffic using a variation of the Token Bucket Algorithm.
The maximum allowable transmission rate ( R ) can be mathematically represented as:
Where Q_{\text{daily}} = 200. This breaks down to roughly 1 request every 432 seconds if perfectly distributed. However, Google allows brief bursts of execution up to a burst capacity ( B ) (typically around 5 to 10 concurrent connections).
By binding our queue using an asyncio.Semaphore(4) paired with an explicit sleep decay
Delta t = 0.75s , we ensure our operational loop satisfies the systemic bound:
Final Thoughts
Relying blindly on standard discovery loops means putting your platform's organic growth at the mercy of unpredictable crawl schedules. By implementing an idempotent, thread-safe asynchronous worker around the Google Indexing API, you transition your tech SEO architecture from a passive architecture to an aggressive, deterministic data pipeline. It forces search crawlers to align with your platform's immediate deployment priorities, maximizing crawling efficiency and securing rapid indexing returns.
For more details on the Indexing API, see the official Google Indexing API Documentation and Search Console API Quotas.