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Reuses existing Supabase RPCs via execute_tool_rpc() — zero duplicated query logic.
Each evaluator function is a small unit (CC <= 4) dispatched by criteria_type.
"""
from datetime import datetime, timezone, timedelta
from config import ALERT_COOLDOWN_HOURS, SUPABASE_SERVICE_ROLE_KEY, SUPABASE_URL
from services.email_service import build_criteria_summary, send_alert_email
from services.observability import setup_logger
from services.supabase_service import execute_tool_rpc
logger = setup_logger(__name__)
def _get_service_client():
"""Lazy-import Supabase service client to avoid circular imports at module level."""
from supabase import create_client
return create_client(SUPABASE_URL, SUPABASE_SERVICE_ROLE_KEY)
def _is_in_cooldown(sub: dict, cooldown_hours: int = ALERT_COOLDOWN_HOURS) -> bool:
"""Check if subscription is in cooldown window."""
last_fired = sub.get("last_fired_at")
if not last_fired:
return False
fired_dt = datetime.fromisoformat(last_fired.replace("Z", "+00:00"))
return datetime.now(timezone.utc) - fired_dt < timedelta(hours=cooldown_hours)
async def _evaluate_spike(criteria: dict) -> tuple[bool, str]:
"""Check spike condition using get_spike_alerts RPC."""
market = criteria.get("market")
threshold = criteria.get("threshold_pct", 25)
result = await execute_tool_rpc("get_spike_alerts", {
"threshold_param": threshold,
"p_market": market,
"p_limit": 5,
"days_param": 1,
})
data = result.get("data", [])
if not data:
return False, ""
names = [f"{r.get('property_name', '?')} ({r.get('pct_change', '?')}%)" for r in data[:5]]
body = f"<h3>🔔 Price Spike Alert — {market or 'All Markets'}</h3>"
body += f"<p>{len(data)} properties spiked ≥{threshold}%:</p><ul>"
body += "".join(f"<li>{n}</li>" for n in names) + "</ul>"
return True, body
async def _evaluate_rate_change(criteria: dict) -> tuple[bool, str]:
"""Check rate change condition using get_market_rate_changes RPC."""
market = criteria.get("market")
direction = criteria.get("direction", "both")
result = await execute_tool_rpc("get_market_rate_changes", {
"p_market": market,
"p_days": 1,
"p_limit": 5,
})
data = result.get("data", result)
total = data.get("total_changes", 0) if isinstance(data, dict) else 0
if total == 0:
return False, ""
if direction == "up" and not data.get("increases", 0):
return False, ""
if direction == "down" and not data.get("decreases", 0):
return False, ""
body = f"<h3>🔔 Rate Change Alert — {market or 'All Markets'}</h3>"
body += f"<p>{total} properties had rate changes in the last scrape cycle.</p>"
examples = data.get("examples", [])
if examples:
body += "<ul>"
body += "".join(f"<li>{e.get('name', '?')}: {e.get('change', '?')}</li>" for e in examples[:5])
body += "</ul>"
return True, body
async def _evaluate_price_threshold(criteria: dict) -> tuple[bool, str]:
"""Check price threshold using get_property_snapshot RPC."""
prop = criteria.get("property_search", "")
operator = criteria.get("operator", "below")
value = criteria.get("value", 0)
result = await execute_tool_rpc("get_property_snapshot", {"p_property_search": prop})
data = result.get("data", result)
if isinstance(data, list) and data:
data = data[0]
rate = data.get("nightly_rate") or data.get("current_rate")
if rate is None:
return False, ""
rate = float(rate)
condition_met = (operator == "below" and rate < value) or (operator == "above" and rate > value)
if not condition_met:
return False, ""
name = data.get("property_name", prop)
body = f"<h3>🔔 Price Threshold Alert</h3>"
body += f"<p><strong>{name}</strong> is now at <strong>{rate}/night</strong> "
body += f"({operator} your threshold of {value}).</p>"
return True, body
async def _evaluate_availability(criteria: dict) -> tuple[bool, str]:
"""Check availability change using get_property_snapshot RPC."""
prop = criteria.get("property_search", "")
watch_for = criteria.get("watch_for", "any")
result = await execute_tool_rpc("get_property_snapshot", {"p_property_search": prop})
data = result.get("data", result)
if isinstance(data, list) and data:
data = data[0]
is_available = data.get("is_available")
if is_available is None:
return False, ""
if watch_for == "available" and not is_available:
return False, ""
if watch_for == "unavailable" and is_available:
return False, ""
status_text = "available" if is_available else "unavailable"
name = data.get("property_name", prop)
body = f"<h3>🔔 Availability Alert</h3>"
body += f"<p><strong>{name}</strong> is now <strong>{status_text}</strong>.</p>"
return True, body
async def _evaluate_new_listing(criteria: dict) -> tuple[bool, str]:
"""Check for new listings using get_recently_changed_tracking RPC."""
market = criteria.get("market")
result = await execute_tool_rpc("get_recently_changed_tracking", {"p_days": 1})
data = result.get("data", [])
added = [r for r in data if r.get("change_type") == "added"]
if market:
added = [r for r in added if market.lower() in (r.get("market", "") or "").lower()]
if not added:
return False, ""
body = f"<h3>🔔 New Listing Alert — {market or 'All Markets'}</h3>"
body += f"<p>{len(added)} new properties added to tracking:</p><ul>"
body += "".join(f"<li>{r.get('property_name', '?')}</li>" for r in added[:5]) + "</ul>"
return True, body
async def _evaluate_tracking_removed(criteria: dict) -> tuple[bool, str]:
"""Check for removed listings using get_recently_changed_tracking RPC."""
market = criteria.get("market")
result = await execute_tool_rpc("get_recently_changed_tracking", {"p_days": 1})
data = result.get("data", [])
removed = [r for r in data if r.get("change_type") == "removed"]
if market:
removed = [r for r in removed if market.lower() in (r.get("market", "") or "").lower()]
if not removed:
return False, ""
body = f"<h3>🔔 Tracking Removed Alert — {market or 'All Markets'}</h3>"
body += f"<p>{len(removed)} properties removed from tracking:</p><ul>"
body += "".join(f"<li>{r.get('property_name', '?')}</li>" for r in removed[:5]) + "</ul>"
return True, body
async def _evaluate_anomaly(criteria: dict) -> tuple[bool, str]:
"""Check for pricing anomalies using get_rate_anomaly_report RPC."""
prop = criteria.get("property_search", "")
threshold = criteria.get("deviation_threshold", 25)
result = await execute_tool_rpc("get_rate_anomaly_report", {
"p_property_search": prop,
"p_days": 7,
"p_deviation_threshold": threshold,
})
data = result.get("data", result)
if isinstance(data, list) and data:
data = data[0]
anomaly_count = data.get("anomaly_count", 0) if isinstance(data, dict) else 0
if not anomaly_count:
return False, ""
name = data.get("property_name", prop)
body = f"<h3>🔔 Pricing Anomaly Alert</h3>"
body += f"<p><strong>{name}</strong> has {anomaly_count} anomalous pricing events "
body += f"(≥{threshold}% deviation from baseline).</p>"
return True, body
async def _evaluate_volatility(criteria: dict) -> tuple[bool, str]:
"""Check volatility ranking using get_most_volatile_properties RPC."""
market = criteria.get("market")
top_n = criteria.get("top_n", 5)
result = await execute_tool_rpc("get_most_volatile_properties", {
"p_market": market,
"p_limit": top_n,
"p_days": 7,
})
data = result.get("data", [])
if not data:
return False, ""
body = f"<h3>🔔 Volatility Alert — {market or 'All Markets'}</h3>"
body += f"<p>Top {len(data)} most volatile properties:</p><ul>"
for r in data[:top_n]:
name = r.get("property_name", "?")
changes = r.get("change_count", r.get("rate_change_count", "?"))
body += f"<li>{name} — {changes} rate changes</li>"
body += "</ul>"
return True, body
async def _evaluate_trend_reversal(criteria: dict) -> tuple[bool, str]:
"""Check market trend direction using get_market_trend RPC."""
market = criteria.get("market")
watch_for = criteria.get("watch_for", "falling")
result = await execute_tool_rpc("get_market_trend", {
"p_market": market,
"p_days": 14,
})
data = result.get("data", [])
if not data or len(data) < 7:
return False, ""
recent_half = data[len(data) // 2:]
rates = [float(d.get("avg_rate", 0)) for d in recent_half if d.get("avg_rate")]
if len(rates) < 2:
return False, ""
slope = rates[-1] - rates[0]
direction = "falling" if slope < 0 else "rising"
if direction != watch_for:
return False, ""
body = f"<h3>🔔 Trend Reversal Alert — {market}</h3>"
body += f"<p>Market rates are now <strong>{direction}</strong> — "
body += f"average moved from {rates[0]:.0f} to {rates[-1]:.0f} over the last 7 days.</p>"
return True, body
_EVALUATORS = {
"spike": _evaluate_spike,
"rate_change": _evaluate_rate_change,
"price_threshold": _evaluate_price_threshold,
"availability_change": _evaluate_availability,
"new_listing": _evaluate_new_listing,
"tracking_removed": _evaluate_tracking_removed,
"anomaly": _evaluate_anomaly,
"volatility": _evaluate_volatility,
"trend_reversal": _evaluate_trend_reversal,
}
async def _evaluate_subscription(sub: dict) -> bool:
"""Evaluate a single subscription against live data. Returns True if alert was fired."""
criteria_type = sub["criteria_type"]
if criteria_type == "digest":
return False
evaluator = _EVALUATORS.get(criteria_type)
if not evaluator:
logger.warning(f"[evaluator] unknown criteria_type: {criteria_type}")
return False
if _is_in_cooldown(sub):
logger.info(f"[evaluator] sub {sub['id']} in cooldown, skipping")
return False
condition_met, alert_body = await evaluator(sub["criteria"])
if not condition_met:
return False
summary = build_criteria_summary(criteria_type, sub["criteria"])
subject = f"🔔 {summary}"
await send_alert_email(sub["email"], subject, alert_body, sub["unsubscribe_token"])
client = _get_service_client()
client.table("alert_subscriptions").update({
"last_fired_at": datetime.now(timezone.utc).isoformat(),
"last_checked_at": datetime.now(timezone.utc).isoformat(),
}).eq("id", sub["id"]).execute()
logger.info(f"[evaluator] fired alert for sub {sub['id']}: {criteria_type}")
return True
async def evaluate_all_active_subscriptions() -> dict:
"""Fetch all active subscriptions, evaluate each, fire if condition met."""
client = _get_service_client()
try:
result = (
client.table("alert_subscriptions")
.select("id, email, criteria_type, criteria, unsubscribe_token, last_fired_at")
.eq("status", "active")
.eq("confirmed", True)
.execute()
)
except Exception as exc:
logger.error(f"[evaluator] failed to fetch subscriptions: {exc}")
return {"status": "error", "message": str(exc)}
subs = result.data or []
logger.info(f"[evaluator] evaluating {len(subs)} active subscriptions")
fired_count = 0
checked_count = 0
now_iso = datetime.now(timezone.utc).isoformat()
for sub in subs:
checked_count += 1
try:
fired = await _evaluate_subscription(sub)
if fired:
fired_count += 1
else:
client.table("alert_subscriptions").update({
"last_checked_at": now_iso,
}).eq("id", sub["id"]).execute()
except Exception as exc:
logger.error(f"[evaluator] error evaluating sub {sub['id']}: {exc}")
logger.info(f"[evaluator] done: checked={checked_count}, fired={fired_count}")
return {
"status": "success",
"checked": checked_count,
"fired": fired_count,
}
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