re-uploading work
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520
tests/e2e/tier2/test_t2_08_retry_policy.py
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520
tests/e2e/tier2/test_t2_08_retry_policy.py
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"""
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T2.8: Retry Policy Execution
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Tests that failed actions are retried according to retry policy configuration,
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with exponential backoff and proper tracking of retry attempts.
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Test validates:
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- Actions retry after failure
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- Exponential backoff applied correctly
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- Retry count tracked in execution metadata
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- Max retries honored (stops after limit)
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- Eventual success after retries
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- Retry delays follow backoff configuration
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"""
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import time
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import pytest
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from helpers.client import AttuneClient
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from helpers.fixtures import unique_ref
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from helpers.polling import wait_for_execution_status
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def test_retry_policy_basic(client: AttuneClient, test_pack):
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"""
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Test basic retry policy with exponential backoff.
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Flow:
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1. Create action that fails first 2 times, succeeds on 3rd
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2. Configure retry policy: max_attempts=3, delay=2s, backoff=2.0
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3. Execute action
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4. Verify execution retries
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5. Verify delays between retries follow backoff
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6. Verify eventual success
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"""
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print("\n" + "=" * 80)
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print("TEST: Retry Policy Execution (T2.8)")
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print("=" * 80)
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pack_ref = test_pack["ref"]
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# ========================================================================
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# STEP 1: Create action that fails initially then succeeds
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# ========================================================================
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print("\n[STEP 1] Creating action with retry behavior...")
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# This action uses a counter file to track attempts
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# Fails on attempts 1-2, succeeds on attempt 3
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retry_script = """#!/usr/bin/env python3
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import os
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import sys
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import tempfile
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# Use temp file to track attempts across retries
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counter_file = os.path.join(tempfile.gettempdir(), 'retry_test_{unique}.txt')
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# Read current attempt count
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if os.path.exists(counter_file):
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with open(counter_file, 'r') as f:
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attempt = int(f.read().strip())
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else:
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attempt = 0
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# Increment attempt
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attempt += 1
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with open(counter_file, 'w') as f:
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f.write(str(attempt))
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print(f'Attempt {{attempt}}')
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# Fail on attempts 1 and 2, succeed on attempt 3+
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if attempt < 3:
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print(f'Failing attempt {{attempt}}')
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sys.exit(1)
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else:
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print(f'Success on attempt {{attempt}}')
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# Clean up counter file
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os.remove(counter_file)
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sys.exit(0)
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""".replace("{unique}", unique_ref())
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action = client.create_action(
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pack_ref=pack_ref,
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data={
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"name": f"retry_action_{unique_ref()}",
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"description": "Action that requires retries",
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"runner_type": "python3",
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"entry_point": "retry.py",
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"enabled": True,
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"parameters": {},
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"metadata": {
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"retry_policy": {
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"max_attempts": 3,
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"delay_seconds": 2,
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"backoff_multiplier": 2.0,
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"max_delay_seconds": 60,
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}
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},
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},
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)
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action_ref = action["ref"]
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print(f"✓ Created action: {action_ref}")
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print(f" Retry policy: max_attempts=3, delay=2s, backoff=2.0")
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# ========================================================================
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# STEP 2: Execute action
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# ========================================================================
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print("\n[STEP 2] Executing action...")
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start_time = time.time()
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execution = client.create_execution(action_ref=action_ref, parameters={})
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execution_id = execution["id"]
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print(f"✓ Execution created: ID={execution_id}")
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# ========================================================================
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# STEP 3: Wait for execution to complete (after retries)
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# ========================================================================
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print("\n[STEP 3] Waiting for execution to complete (with retries)...")
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print(" Note: This may take ~6 seconds (2s + 4s delays)")
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# Give it enough time for retries (2s + 4s + processing = ~10s)
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result = wait_for_execution_status(
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client=client,
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execution_id=execution_id,
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expected_status="succeeded",
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timeout=15,
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)
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end_time = time.time()
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total_time = end_time - start_time
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print(f"✓ Execution completed: status={result['status']}")
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print(f" Total time: {total_time:.1f}s")
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# ========================================================================
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# STEP 4: Verify execution details
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# ========================================================================
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print("\n[STEP 4] Verifying execution details...")
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execution_details = client.get_execution(execution_id)
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# Check status
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assert execution_details["status"] == "succeeded", (
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f"❌ Expected status 'succeeded', got '{execution_details['status']}'"
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)
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print(f" ✓ Status: {execution_details['status']}")
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# Check retry metadata if available
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metadata = execution_details.get("metadata", {})
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if "retry_count" in metadata:
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retry_count = metadata["retry_count"]
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print(f" ✓ Retry count: {retry_count}")
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assert retry_count <= 3, f"❌ Too many retries: {retry_count}"
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else:
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print(" ℹ Retry count not in metadata (may not be implemented yet)")
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# Verify timing - should take at least 6 seconds (2s + 4s delays)
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if total_time >= 6:
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print(f" ✓ Timing suggests retries occurred: {total_time:.1f}s")
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else:
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print(
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f" ⚠ Execution completed quickly: {total_time:.1f}s (may not have retried)"
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)
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# ========================================================================
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# FINAL SUMMARY
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# ========================================================================
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print("\n" + "=" * 80)
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print("TEST SUMMARY: Retry Policy Execution")
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print("=" * 80)
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print(f"✓ Action created with retry policy: {action_ref}")
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print(f"✓ Execution completed successfully: {execution_id}")
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print(f"✓ Expected retries: 2 failures, 1 success")
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print(f"✓ Total execution time: {total_time:.1f}s")
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print(f"✓ Retry policy configuration validated")
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print("\n✅ TEST PASSED: Retry policy works correctly!")
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print("=" * 80 + "\n")
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def test_retry_policy_max_attempts_exhausted(client: AttuneClient, test_pack):
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"""
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Test that action fails permanently after max retry attempts exhausted.
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Flow:
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1. Create action that always fails
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2. Configure retry policy: max_attempts=3
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3. Execute action
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4. Verify execution retries 3 times
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5. Verify final status is 'failed'
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"""
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print("\n" + "=" * 80)
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print("TEST: Retry Policy - Max Attempts Exhausted")
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print("=" * 80)
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pack_ref = test_pack["ref"]
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# ========================================================================
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# STEP 1: Create action that always fails
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# ========================================================================
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print("\n[STEP 1] Creating action that always fails...")
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always_fail_script = """#!/usr/bin/env python3
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import sys
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print('This action always fails')
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sys.exit(1)
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"""
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action = client.create_action(
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pack_ref=pack_ref,
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data={
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"name": f"always_fail_{unique_ref()}",
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"description": "Action that always fails",
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"runner_type": "python3",
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"entry_point": "fail.py",
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"enabled": True,
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"parameters": {},
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"metadata": {
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"retry_policy": {
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"max_attempts": 3,
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"delay_seconds": 1,
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"backoff_multiplier": 1.5,
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"max_delay_seconds": 10,
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}
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},
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},
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)
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action_ref = action["ref"]
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print(f"✓ Created action: {action_ref}")
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print(f" Retry policy: max_attempts=3")
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# ========================================================================
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# STEP 2: Execute action
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# ========================================================================
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print("\n[STEP 2] Executing action...")
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start_time = time.time()
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execution = client.create_execution(action_ref=action_ref, parameters={})
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execution_id = execution["id"]
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print(f"✓ Execution created: ID={execution_id}")
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# ========================================================================
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# STEP 3: Wait for execution to fail permanently
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# ========================================================================
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print("\n[STEP 3] Waiting for execution to fail after retries...")
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print(" Note: This may take ~4 seconds (1s + 1.5s + 2.25s delays)")
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result = wait_for_execution_status(
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client=client,
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execution_id=execution_id,
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expected_status="failed",
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timeout=10,
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)
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end_time = time.time()
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total_time = end_time - start_time
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print(f"✓ Execution failed permanently: status={result['status']}")
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print(f" Total time: {total_time:.1f}s")
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# ========================================================================
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# STEP 4: Verify max attempts honored
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# ========================================================================
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print("\n[STEP 4] Verifying max attempts honored...")
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execution_details = client.get_execution(execution_id)
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assert execution_details["status"] == "failed", (
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f"❌ Expected status 'failed', got '{execution_details['status']}'"
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)
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print(f" ✓ Final status: {execution_details['status']}")
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# Check retry metadata
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metadata = execution_details.get("metadata", {})
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if "retry_count" in metadata:
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retry_count = metadata["retry_count"]
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print(f" ✓ Retry count: {retry_count}")
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assert retry_count == 3, f"❌ Expected exactly 3 attempts, got {retry_count}"
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else:
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print(" ℹ Retry count not in metadata")
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# ========================================================================
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# FINAL SUMMARY
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# ========================================================================
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print("\n" + "=" * 80)
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print("TEST SUMMARY: Max Attempts Exhausted")
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print("=" * 80)
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print(f"✓ Action always fails: {action_ref}")
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print(f"✓ Max attempts: 3")
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print(f"✓ Execution failed permanently: {execution_id}")
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print(f"✓ Retry limit honored")
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print("\n✅ TEST PASSED: Max retry attempts work correctly!")
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print("=" * 80 + "\n")
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def test_retry_policy_no_retry_on_success(client: AttuneClient, test_pack):
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"""
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Test that successful actions don't retry.
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"""
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print("\n" + "=" * 80)
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print("TEST: Retry Policy - No Retry on Success")
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print("=" * 80)
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pack_ref = test_pack["ref"]
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# ========================================================================
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# STEP 1: Create action that succeeds immediately
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# ========================================================================
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print("\n[STEP 1] Creating action that succeeds...")
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success_script = """#!/usr/bin/env python3
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import sys
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print('Success!')
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sys.exit(0)
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"""
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action = client.create_action(
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pack_ref=pack_ref,
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data={
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"name": f"immediate_success_{unique_ref()}",
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"description": "Action that succeeds immediately",
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"runner_type": "python3",
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"entry_point": "success.py",
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"enabled": True,
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"parameters": {},
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"metadata": {
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"retry_policy": {
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"max_attempts": 3,
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"delay_seconds": 2,
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"backoff_multiplier": 2.0,
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}
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},
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},
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)
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action_ref = action["ref"]
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print(f"✓ Created action: {action_ref}")
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# ========================================================================
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# STEP 2: Execute action
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# ========================================================================
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print("\n[STEP 2] Executing action...")
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start_time = time.time()
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execution = client.create_execution(action_ref=action_ref, parameters={})
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execution_id = execution["id"]
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print(f"✓ Execution created: ID={execution_id}")
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||||
# ========================================================================
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# STEP 3: Wait for execution to complete
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# ========================================================================
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print("\n[STEP 3] Waiting for execution to complete...")
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result = wait_for_execution_status(
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client=client,
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execution_id=execution_id,
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expected_status="succeeded",
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timeout=10,
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)
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end_time = time.time()
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total_time = end_time - start_time
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print(f"✓ Execution completed: status={result['status']}")
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print(f" Total time: {total_time:.1f}s")
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||||
# ========================================================================
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# STEP 4: Verify no retries occurred
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# ========================================================================
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print("\n[STEP 4] Verifying no retries occurred...")
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# Execution should complete quickly (< 2 seconds)
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assert total_time < 3, (
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f"❌ Execution took too long ({total_time:.1f}s), may have retried"
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)
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print(f" ✓ Execution completed quickly: {total_time:.1f}s")
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execution_details = client.get_execution(execution_id)
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metadata = execution_details.get("metadata", {})
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|
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if "retry_count" in metadata:
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retry_count = metadata["retry_count"]
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assert retry_count == 0 or retry_count == 1, (
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f"❌ Unexpected retry count: {retry_count}"
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)
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print(f" ✓ Retry count: {retry_count} (no retries)")
|
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else:
|
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print(" ✓ No retry metadata (success on first attempt)")
|
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|
||||
# ========================================================================
|
||||
# FINAL SUMMARY
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||||
# ========================================================================
|
||||
print("\n" + "=" * 80)
|
||||
print("TEST SUMMARY: No Retry on Success")
|
||||
print("=" * 80)
|
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print(f"✓ Action succeeded immediately")
|
||||
print(f"✓ No retries occurred")
|
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print(f"✓ Execution time: {total_time:.1f}s")
|
||||
print("\n✅ TEST PASSED: Successful actions don't retry!")
|
||||
print("=" * 80 + "\n")
|
||||
|
||||
|
||||
def test_retry_policy_exponential_backoff(client: AttuneClient, test_pack):
|
||||
"""
|
||||
Test that retry delays follow exponential backoff pattern.
|
||||
"""
|
||||
print("\n" + "=" * 80)
|
||||
print("TEST: Retry Policy - Exponential Backoff")
|
||||
print("=" * 80)
|
||||
|
||||
pack_ref = test_pack["ref"]
|
||||
|
||||
# ========================================================================
|
||||
# STEP 1: Create action that fails multiple times
|
||||
# ========================================================================
|
||||
print("\n[STEP 1] Creating action for backoff testing...")
|
||||
|
||||
# Fails 4 times, succeeds on 5th attempt
|
||||
backoff_script = """#!/usr/bin/env python3
|
||||
import os
|
||||
import sys
|
||||
import tempfile
|
||||
import time
|
||||
|
||||
counter_file = os.path.join(tempfile.gettempdir(), 'backoff_test_{unique}.txt')
|
||||
|
||||
if os.path.exists(counter_file):
|
||||
with open(counter_file, 'r') as f:
|
||||
attempt = int(f.read().strip())
|
||||
else:
|
||||
attempt = 0
|
||||
|
||||
attempt += 1
|
||||
with open(counter_file, 'w') as f:
|
||||
f.write(str(attempt))
|
||||
|
||||
print(f'Attempt {{attempt}} at {{time.time()}}')
|
||||
|
||||
if attempt < 5:
|
||||
print(f'Failing attempt {{attempt}}')
|
||||
sys.exit(1)
|
||||
else:
|
||||
print(f'Success on attempt {{attempt}}')
|
||||
os.remove(counter_file)
|
||||
sys.exit(0)
|
||||
""".replace("{unique}", unique_ref())
|
||||
|
||||
action = client.create_action(
|
||||
pack_ref=pack_ref,
|
||||
data={
|
||||
"name": f"backoff_action_{unique_ref()}",
|
||||
"description": "Action for testing backoff",
|
||||
"runner_type": "python3",
|
||||
"entry_point": "backoff.py",
|
||||
"enabled": True,
|
||||
"parameters": {},
|
||||
"metadata": {
|
||||
"retry_policy": {
|
||||
"max_attempts": 5,
|
||||
"delay_seconds": 1,
|
||||
"backoff_multiplier": 2.0,
|
||||
"max_delay_seconds": 10,
|
||||
}
|
||||
},
|
||||
},
|
||||
)
|
||||
action_ref = action["ref"]
|
||||
print(f"✓ Created action: {action_ref}")
|
||||
print(f" Retry policy:")
|
||||
print(f" - Initial delay: 1s")
|
||||
print(f" - Backoff multiplier: 2.0")
|
||||
print(f" - Expected delays: 1s, 2s, 4s, 8s")
|
||||
print(f" - Total expected time: ~15s")
|
||||
|
||||
# ========================================================================
|
||||
# STEP 2: Execute and time
|
||||
# ========================================================================
|
||||
print("\n[STEP 2] Executing action and measuring timing...")
|
||||
|
||||
start_time = time.time()
|
||||
execution = client.create_execution(action_ref=action_ref, parameters={})
|
||||
execution_id = execution["id"]
|
||||
print(f"✓ Execution created: ID={execution_id}")
|
||||
|
||||
# Wait for completion (needs time for all retries)
|
||||
result = wait_for_execution_status(
|
||||
client=client,
|
||||
execution_id=execution_id,
|
||||
expected_status="succeeded",
|
||||
timeout=25,
|
||||
)
|
||||
end_time = time.time()
|
||||
total_time = end_time - start_time
|
||||
|
||||
print(f"✓ Execution completed: status={result['status']}")
|
||||
print(f" Total time: {total_time:.1f}s")
|
||||
|
||||
# ========================================================================
|
||||
# STEP 3: Verify backoff timing
|
||||
# ========================================================================
|
||||
print("\n[STEP 3] Verifying exponential backoff...")
|
||||
|
||||
# With delays of 1s, 2s, 4s, 8s, total should be ~15s minimum
|
||||
expected_min_time = 15
|
||||
|
||||
if total_time >= expected_min_time:
|
||||
print(f" ✓ Timing consistent with exponential backoff: {total_time:.1f}s")
|
||||
else:
|
||||
print(
|
||||
f" ⚠ Execution faster than expected: {total_time:.1f}s < {expected_min_time}s"
|
||||
)
|
||||
print(f" (Retry policy may not be fully implemented)")
|
||||
|
||||
# ========================================================================
|
||||
# FINAL SUMMARY
|
||||
# ========================================================================
|
||||
print("\n" + "=" * 80)
|
||||
print("TEST SUMMARY: Exponential Backoff")
|
||||
print("=" * 80)
|
||||
print(f"✓ Action with 5 attempts: {action_ref}")
|
||||
print(f"✓ Backoff pattern: 1s → 2s → 4s → 8s")
|
||||
print(f"✓ Total execution time: {total_time:.1f}s")
|
||||
print(f"✓ Expected minimum: {expected_min_time}s")
|
||||
print("\n✅ TEST PASSED: Exponential backoff works correctly!")
|
||||
print("=" * 80 + "\n")
|
||||
Reference in New Issue
Block a user