Booking.com Full-Year Price Scraper — Deep Guide

Overview

This Actor is tailored to collect price and availability data from Booking.com hotel detail pages over an extended period (commonly 12 months). It is especially useful for pricing research, competitive intelligence, travel industry analytics, and revenue management teams who need historical or forward-looking price snapshots.

What it scrapes

• Hotel name and canonical URL
• Check-in and check-out dates (per row)
• Price value (optionally formatted to numeric)
• Currency (extracted when available)
• Scrape timestamp and source metadata

Key features

How the Actor works (pipeline)

[Input: startUrls, monthsForward, formatPrices, maxRetries] 
  ↓
For each URL:
  • open page (Playwright)
  • locate calendar / availability widget
  • iterate months (1..monthsForward)
  • extract visible prices for target dates
  • normalize (optional)
  • append record with source_url + scraped_at
After loop:
  • write Excel workbook (timestamped)
  • push records to Apify dataset
  • finish run with summary & attachments
      

Important implementation notes

• Prefer hotel *detail* pages (not search results) — they have more stable selectors.
• Use explicit waits for calendar elements; avoid blind sleeps.
• When sites change, update selectors; small pilot runs help catch locale differences.

Input JSON & configuration

Use the input object to control the run. Example below is the recommended starting point for a single-year sweep.

Copy{
  "startUrls": [
    "https://www.booking.com/hotel/xx/example-hotel-1.html",
    "https://www.booking.com/hotel/xx/example-hotel-2.html"
  ],
  "monthsForward": 12,
  "formatPrices": true,
  "maxRetries": 3,
  "datasetName": "booking_yearly_prices"
}

Field details

• startUrls — array of hotel detail page URLs (required).
• monthsForward — number of months to traverse from the current month (default 12).
• formatPrices — if true, strip currency symbols and return numeric price values.
• maxRetries — how many attempts per navigation/extract step.
• datasetName — optional dataset name to push results into.

Examples & snippets

Playwright + Python (pseudo-snippet)

Copyfrom playwright.sync_api import sync_playwright

def extract_prices(page):
    # Wait for calendar widget and iterate months
    page.wait_for_selector('.bui-calendar')
    for i in range(months):
        # click next month button
        page.click('.bui-calendar__control--next')
        # parse visible price cells
        # ... extract date and price

Price formatter (Python)

Copyimport re
def to_price_num(txt):
    if not txt: return None
    s = re.sub(r'[^0-9,.-]', '', txt)
    if ',' in s and '.' in s and s.find(',') < s.find('.'):
        s = s.replace(',', '')
    elif ',' in s and '.' not in s:
        s = s.replace(',', '.')
    try:
        return float(s)
    except:
        return None

Sample output (CSV/Excel row)

hotel_name,check_in,check_out,price_numeric,currency,source_url,scraped_at
Example Hotel,2025-01-01,2025-01-02,125,EUR,https://www.booking.com/hotel/xx/example-hotel-1.html,2025-08-13T10:22:00Z

Deploying & running on Apify

1. Open the Actor page on Apify Store and click Try for free.
2. Paste the input JSON, adjust parameters, and start a run.
3. Watch logs — Playwright actions, navigation steps, and any retries are logged.
4. Download the generated Excel from run attachments and access the dataset via API.

Scheduling & automation

Schedule this Actor weekly or monthly to keep a rolling dataset. Use Apify webhooks to trigger downstream ETL or reporting tasks when a run completes.

Troubleshooting & best practices

• Selector drift: Booking.com changes UI selectively by region; run a pilot and update selectors if elements are missing.
• Rate-limits & blocks: Use Apify proxy or platform anti-blocking options when scaling; still keep delays reasonable.
• Locale differences: Dates and price formats vary — include locale-aware parsing if you process many countries.
• Flaky runs: Increase maxRetries and add targeted waits for calendar animations.

Ethics, legal & respectful scraping

Always respect Booking.com's Terms of Service and robots.txt where applicable. Use scraped data for legitimate business purposes. Don’t republish or redistribute data in ways that violate site rules or copyrights.

In-browser extraction demo (client-side)

Tip: many sites block cross-origin requests — if fetch fails due to CORS paste page HTML into the box instead.

FAQ