How to track Google Hotels prices with Python (no browser, no API key)

I built this actor; it's a paid tool on Apify with a free trial credit.

Google Hotels shows you a price for every hotel in a city, but there's no official API for it. If you want to watch how prices move over a few weeks, compare a hotel against its neighbours, or feed prices into a trip planner, you end up copying numbers by hand.

I'm an 18-year-old engineering student, and I wrote a scraper for this called Google Hotels Scraper. This post shows how to call it from Python and Node, what the data looks like, and one small project: logging Charlotte hotel prices to a Google Sheet once a day.

How it works, briefly

Google Hotels pages already carry their result data inside AF_initDataCallback script blobs. The actor fetches the page over plain HTTP (no headless browser), parses those blobs and picks out anything shaped like a hotel record. That's why a 50-hotel query usually finishes in well under a minute.

Python example

pip install apify-client

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")

run = client.actor("rel8ble/google-hotels-scraper").call(run_input={
    "queries": ["hotels in Charlotte"],
    "checkIn": "2026-10-15",
    "checkOut": "2026-10-18",
    "adults": 2,
    "currency": "USD",
    "maxResults": 50,
})

for hotel in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(hotel["name"], hotel["pricePerNight"], hotel["rating"], hotel.get("deal"))

Node example

npm install apify-client

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "<YOUR_APIFY_TOKEN>" });

const run = await client.actor("rel8ble/google-hotels-scraper").call({
  queries: ["hotels in Charlotte"],
  checkIn: "2026-10-15",
  checkOut: "2026-10-18",
  maxResults: 50,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.map((h) => `${h.name}: $${h.pricePerNight}/night`));

What comes back

One item per property. This is a real row from a test run (Charlotte, 3 nights, 15-18 Oct 2026), trimmed:

{
  "query": "hotels in Charlotte",
  "position": 1,
  "name": "Sonesta Select Charlotte University Research Park",
  "pricePerNight": 75,
  "pricePerNightWithTaxes": 88,
  "totalPrice": 263,
  "totalTaxesAndFees": 54.5,
  "currency": "USD",
  "deal": "DEAL 19% less than usual",
  "nights": 3,
  "rating": 3.9,
  "reviewCount": 915,
  "hotelClass": 3,
  "latitude": 35.3072356,
  "longitude": -80.7534261,
  "checkInTime": "4:00 PM",
  "checkOutTime": "11:00 AM",
  "entityToken": "ChYIl4r5ruWLqpcWGgovbS8wejlfbDlqEAE",
  "googleMapsUrl": "https://www.google.com/maps?cid=16387801168794899843",
  "scrapedAt": "2026-09-23T23:01:40.083Z"
}

You also get amenities, nearby places with travel times, photos, a short description and the official website. Turn on includeDetails and you get the street address and phone number too (one extra request per hotel).

The field I lean on most is entityToken. It stays the same across runs, so it's the key for joining today's price to yesterday's.

Use case: log Charlotte hotel prices to Google Sheets every day

The goal: one row per hotel per day, so after a couple of weeks you can chart how prices move for a fixed stay.

I use gspread with a Google service account (share the sheet with the service account's email first).

pip install apify-client gspread

import datetime
import gspread
from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
sheet = gspread.service_account(filename="service-account.json").open("Charlotte hotel prices").sheet1

run = client.actor("rel8ble/google-hotels-scraper").call(run_input={
    "queries": ["hotels in Charlotte"],
    "checkIn": "2026-11-20",
    "checkOut": "2026-11-22",
    "currency": "USD",
    "maxResults": 50,
})

today = datetime.date.today().isoformat()
rows = []
for h in client.dataset(run["defaultDatasetId"]).iterate_items():
    rows.append([
        today,
        h["entityToken"],
        h["name"],
        h.get("pricePerNight"),
        h.get("totalPrice"),
        h.get("rating"),
        h.get("deal") or "",
    ])

sheet.append_rows(rows, value_input_option="USER_ENTERED")
print(f"appended {len(rows)} rows")

Run it once a day with cron, Task Scheduler or a GitHub Actions schedule. You could also skip the script: set up a Schedule in the Apify Console and use the Google Sheets integration there. After a week, a pivot table on entityToken × date shows you which hotels are dropping and which aren't.

Keep the check-in and check-out dates fixed. If you change them, you're comparing different stays, not watching one stay's price move.

What it costs

Pricing is $3.50 per 1,000 results, and one result is one hotel saved. You aren't charged for duplicates or failed requests.

• The daily job above: 50 hotels × 30 days = 1,500 results ≈ $5.25/month
• A one-off market scan of 1,000 hotels = $3.50
• Apify's free plan gives $5 of monthly credit, which covers roughly 1,400 hotels

Limits

These come straight from my testing:

• About 150-250 unique hotels per query. After that Google only serves vacation rentals or repeats. For a big city, split it up: "hotels in Shinjuku", "hotels in Shibuya".
• Prices are Google's "from" price: the lowest rate across booking partners for your dates and guests. Properties with no rooms for your dates return pricePerNight: null (about 9% in a 300-hotel test).
• No per-partner price list (Booking.com vs Expedia vs direct) and no review texts in this version.
• Address and phone need includeDetails, which is slower.
• Google reshuffles results between pages, so a page sometimes adds fewer than 20 new hotels after dedup.

If something breaks or a field is wrong, the Issues tab on the actor page reaches me directly.

Google Hotels Scraper on Apify

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This article was drafted with AI and published by me.