Medium and low priority tiers were generating full static date ranges (150 and 185 dates) every day. With a queue limit of 200, high (31) + medium (150) consumed the entire budget, leaving only ~19 slots for low priority — causing the observed ~6 month cap. Medium now selects the 60 oldest-scraped (or never-scraped) dates from the days 31-180 window; low selects the 30 oldest from days 181-365. Per-run budget drops from ~365 to ~121 dates, and coverage naturally cycles through the full year: medium every ~2-3 days, low every ~6-7 days. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
212 lines
7.2 KiB
Python
212 lines
7.2 KiB
Python
"""
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Scheduled Booking.com Rate Scraping Job
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Tiered scheduling for 365-day coverage:
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- High (priority 10): next 30 days — all 31 dates scraped every day
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- Medium (priority 5): days 31-180 — up to 60 oldest-scraped dates per day
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- Low (priority 2): days 181-365 — up to 30 oldest-scraped dates per day
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Per-run budget: ~121 dates (30 high + 60 medium + 30 low).
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Medium and low tiers select whichever dates in their window have the oldest
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(or missing) scrape data first, naturally distributing coverage across the
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full year without hammering all 365 dates every day.
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Approximate refresh cadence:
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- High: daily
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- Medium (150 dates / 60 per day): every ~2-3 days
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- Low (185 dates / 30 per day): every ~6 days
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Uses a queue-based approach:
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1. Populate the queue with the selected dates and priorities
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2. Process the queue in priority order
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3. Failed dates are retried (up to 3 attempts)
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4. On blocking, the queue pauses and resumes after cooldown
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Schedule: Daily at configurable time (default 05:30)
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"""
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import asyncio
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import logging
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from datetime import date, timedelta
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from sqlalchemy import text
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from sqlalchemy.orm import Session
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from database import SyncSessionLocal
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from services.booking_scraper import (
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populate_queue,
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process_queue,
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clear_old_queue_items,
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cleanup_stale_batches,
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get_scrape_config,
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)
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logger = logging.getLogger(__name__)
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# Priority levels (higher = processed first)
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PRIORITY_HIGH = 10 # 0-30 days
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PRIORITY_MEDIUM = 5 # 31-180 days
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PRIORITY_LOW = 2 # 181-365 days
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# Per-run date budget for medium and low tiers
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MEDIUM_DATES_PER_RUN = 60 # out of ~150 in window
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LOW_DATES_PER_RUN = 30 # out of ~185 in window
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def get_high_priority_dates() -> list[date]:
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"""High priority: all of today through +30 days, scraped every run."""
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today = date.today()
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return [today + timedelta(days=i) for i in range(31)]
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def _get_oldest_scraped_dates(db: Session, start: date, end: date, limit: int) -> list[date]:
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"""
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From the date window [start, end], return up to `limit` dates ordered by
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oldest last-scrape first (never-scraped dates come first via NULLS FIRST).
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Joining against booking_com_rates means we naturally pick whichever dates
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in the window are most stale or have no data yet.
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"""
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rows = db.execute(
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text("""
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SELECT s.rate_date::date AS rate_date,
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MAX(r.scraped_at) AS last_scraped
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FROM generate_series(:start::date, :end::date, '1 day'::interval) AS s(rate_date)
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LEFT JOIN booking_com_rates r ON r.rate_date = s.rate_date::date
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GROUP BY s.rate_date
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ORDER BY last_scraped ASC NULLS FIRST
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LIMIT :limit
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"""),
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{'start': start, 'end': end, 'limit': limit}
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).fetchall()
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return [row.rate_date for row in rows]
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def get_medium_priority_dates(db: Session, limit: int = MEDIUM_DATES_PER_RUN) -> list[date]:
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"""Medium priority: up to `limit` oldest-scraped dates in the days 31-180 window."""
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today = date.today()
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return _get_oldest_scraped_dates(
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db,
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start=today + timedelta(days=31),
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end=today + timedelta(days=180),
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limit=limit,
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)
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def get_low_priority_dates(db: Session, limit: int = LOW_DATES_PER_RUN) -> list[date]:
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"""Low priority: up to `limit` oldest-scraped dates in the days 181-365 window."""
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today = date.today()
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return _get_oldest_scraped_dates(
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db,
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start=today + timedelta(days=181),
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end=today + timedelta(days=365),
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limit=limit,
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)
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def compute_next_scrape_for_date(target_date: date) -> tuple[str, date | None]:
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"""
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For a target date, determine its priority tier and approximate next scrape date.
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Returns (tier, next_scrape_date) where tier is 'high'/'medium'/'low'/'none'.
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High dates are scraped every run; medium/low estimates reflect typical cadence
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based on the per-run budget vs window size.
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"""
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today = date.today()
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offset = (target_date - today).days
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if offset < 0:
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return ('none', None)
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if offset > 365:
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return ('none', None)
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if offset <= 30:
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# Scraped every day
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return ('high', today)
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elif offset <= 180:
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# ~150 dates, 60/day → ~2-3 day cadence
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return ('medium', today + timedelta(days=3))
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else:
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# ~185 dates, 30/day → ~6-7 day cadence
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return ('low', today + timedelta(days=7))
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def run_scheduled_booking_scrape():
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"""
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Main scheduled job: populate queue with today's dates, then process.
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"""
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db = SyncSessionLocal()
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try:
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# Check if scraper is enabled
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result = db.execute(
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text("SELECT config_value FROM system_config WHERE config_key = 'booking_scraper_enabled'")
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).fetchone()
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if not result or result.config_value != 'true':
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logger.debug("Scheduled booking scrape skipped (disabled)")
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return
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if not get_scrape_config(db):
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logger.warning("Scheduled booking scrape skipped (no location configured)")
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return
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# Clean up stale running batches and old queue items
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cleanup_stale_batches(db, max_age_minutes=120)
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clear_old_queue_items(db, days=3)
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# Gather dates with priorities — medium/low select oldest-scraped first
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high = get_high_priority_dates()
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medium = get_medium_priority_dates(db)
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low = get_low_priority_dates(db)
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priorities = {}
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for d in high:
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priorities[d] = PRIORITY_HIGH
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for d in medium:
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priorities[d] = max(priorities.get(d, 0), PRIORITY_MEDIUM)
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for d in low:
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priorities[d] = max(priorities.get(d, 0), PRIORITY_LOW)
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all_dates = sorted(priorities.keys())
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if not all_dates:
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logger.info("Scheduled booking scrape: no dates to scrape today")
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return
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logger.info(
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f"Scheduled booking scrape: queuing {len(all_dates)} dates "
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f"(high={len(high)}, medium={len(medium)}, low={len(low)})"
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)
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# Populate queue
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populate_queue(db, all_dates, priorities)
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# Process queue
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loop = asyncio.new_event_loop()
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asyncio.set_event_loop(loop)
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try:
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result = loop.run_until_complete(process_queue(db))
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if result.get('success'):
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logger.info(
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f"Scheduled booking scrape completed: "
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f"{result.get('dates_completed', 0)} dates, "
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f"{result.get('rates_scraped', 0)} rates"
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)
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elif result.get('blocked'):
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logger.warning(
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f"Scheduled booking scrape blocked: {result.get('block_reason')}. "
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f"Completed {result.get('dates_completed', 0)} dates. "
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f"Remaining dates stay queued for retry."
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)
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else:
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logger.error(f"Scheduled booking scrape failed: {result.get('error')}")
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finally:
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loop.close()
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except Exception as e:
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logger.error(f"Scheduled booking scrape error: {e}", exc_info=True)
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finally:
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db.close()
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async def run_scheduled_booking_scrape_async():
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"""Async wrapper for APScheduler."""
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loop = asyncio.get_event_loop()
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await loop.run_in_executor(None, run_scheduled_booking_scrape)
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