from anomalyarmor import Client

client = Client()

# 1. Check current freshness status
freshness = client.freshness.status("asset-uuid")
print(f"Status: {freshness.status}")
print(f"Last Update: {freshness.last_updated_at}")
print(f"Expected: {freshness.expected_at}")

# 2. Get upstream lineage
lineage = client.lineage.get("asset-uuid", direction="upstream", depth=2)
print(f"\nUpstream Dependencies ({len(lineage.upstream)} tables):")
for node in lineage.upstream:
    print(f"  {node.qualified_name}")

# 3. Check upstream freshness
for node in lineage.upstream:
    try:
        upstream_status = client.freshness.status(node.asset_id)
        if upstream_status.status == "stale":
            print(f"  WARNING: {node.qualified_name} is also stale!")
    except Exception:
        pass

# 4. Ask AI for analysis
response = client.intelligence.ask(
    question="Why is the orders table stale and what should I do?",
    asset_ids=["asset-uuid"]
)
print(f"\nAI Analysis: {response.answer}")

# Get alert details
alerts = client.alerts.list(
    asset_id="asset-uuid",
    status="triggered",
    limit=5
)

for alert in alerts:
    print(f"Alert: {alert.message}")
    print(f"  Severity: {alert.severity}")
    print(f"  Triggered: {alert.triggered_at}")
    print(f"  Asset: {alert.qualified_name}")

# Ask AI about the alert
response = client.intelligence.ask(
    question=f"Explain this alert and what caused it: {alerts[0].message}",
    asset_ids=["asset-uuid"]
)
print(f"\nAI Explanation: {response.answer}")

# Get schema baseline and changes
baseline = client.schema.baseline("asset-uuid")
print(f"Schema Status: {baseline.status}")

# Check for recent changes
if baseline.unacknowledged_changes:
    print("\nUnacknowledged Changes:")
    for change in baseline.unacknowledged_changes:
        print(f"  {change.change_type}: {change.column_name}")
        print(f"    Detected: {change.detected_at}")

# Get downstream impact
lineage = client.lineage.get("asset-uuid", direction="downstream", depth=2)
print(f"\nDownstream Impact ({len(lineage.downstream)} tables may be affected):")
for node in lineage.downstream:
    print(f"  {node.qualified_name}")

Investigation: orders table is stale

Freshness Status:
  Status: STALE
  Last Update: 2026-01-30 06:00:00
  Expected: 2026-01-31 06:00:00
  Delay: 24 hours

Upstream Dependencies (3 tables):
  raw.events - FRESH
  staging.orders_raw - STALE (root cause)
  staging.customers - FRESH

Root Cause: staging.orders_raw has not updated since 2026-01-30

AI Analysis:
  The orders table is stale because its upstream dependency staging.orders_raw
  has not received new data in 24 hours. This appears to be related to the
  ETL job failure at 2026-01-30 05:45. Recommended action: Check the Airflow
  logs for the orders_etl DAG.

Related Alerts:
  [CRITICAL] Freshness SLA breach - orders
  [WARNING] ETL job failed - staging.orders_raw