346 lines
11 KiB
Python
346 lines
11 KiB
Python
"""
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Test phase handlers: test_plan_create, test_case_generate, functional_test,
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performance_test, bug_report, bug_verify
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"""
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import json
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import logging
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import time
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import asyncio
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logger = logging.getLogger(__name__)
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async def handle_test_case_generate(tenant_id, task_id, step_name, input_data, config):
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"""Auto-generate test cases from requirements and design artifacts."""
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requirement = input_data.get("requirement_review", {}).get("output", {})
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if not requirement:
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requirement = input_data.get("requirement_gathering", {}).get("output", {})
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table_design = input_data.get("table_design", {}).get("output", {})
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api_design = input_data.get("api_design", {}).get("output", {})
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test_plan = input_data.get("test_plan_create", {}).get("output", {})
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prompt = f"""Generate comprehensive test cases for the following project.
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## Requirements:
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{json.dumps(requirement, ensure_ascii=False, indent=2)}
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## Table Design:
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{json.dumps(table_design.get("models", [])[:5], ensure_ascii=False)}
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## API Endpoints:
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{json.dumps(api_design.get("api_list", [])[:10], ensure_ascii=False)}
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## Test Plan:
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{json.dumps(test_plan, ensure_ascii=False)}
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Generate test cases covering:
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1. **Functional tests** — CRUD operations, business logic, form validation
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2. **API tests** — Each endpoint: success, error, edge cases
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3. **Performance tests** — Concurrent access, response time, throughput
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4. **Integration tests** — Cross-module interactions, RBAC, data isolation
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Each test case format:
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{{
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"case_name": "Test X",
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"case_type": "functional|performance|api|integration",
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"priority": "P0|P1|P2|P3",
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"precondition": "...",
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"steps": ["step1", "step2", ...],
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"expected_result": "..."
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}}
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Output JSON with key "test_cases" containing array of test cases.
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"""
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from pipeline_service.llm_bridge import call_llm
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result = await call_llm(tenant_id, prompt, config.get("llm_model", "default"))
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try:
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cases_data = json.loads(result)
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except json.JSONDecodeError:
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import re
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json_match = re.search(r'\{.*"test_cases".*\}', result, re.DOTALL)
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if json_match:
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cases_data = json.loads(json_match.group())
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else:
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cases_data = {"test_cases": []}
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cases = cases_data.get("test_cases", [])
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return {
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"test_cases": cases,
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"case_count": len(cases),
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"by_type": _count_by_key(cases, "case_type"),
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"by_priority": _count_by_key(cases, "priority"),
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}
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async def handle_functional_test(tenant_id, task_id, step_name, input_data, config):
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"""Execute functional test cases against the deployed test environment."""
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test_cases_output = input_data.get("test_case_generate", {}).get("output", {})
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cases = test_cases_output.get("test_cases", [])
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# Filter functional + api + integration cases
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func_cases = [c for c in cases if c.get("case_type") in ("functional", "api", "integration")]
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results = []
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passed = 0
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failed = 0
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errors = []
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for case in func_cases:
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case_result = await _execute_test_case(case, config)
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results.append(case_result)
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if case_result["status"] == "pass":
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passed += 1
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else:
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failed += 1
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if case_result.get("error"):
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errors.append({
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"case_name": case["case_name"],
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"error": case_result["error"],
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})
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return {
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"total": len(func_cases),
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"passed": passed,
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"failed": failed,
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"pass_rate": round(passed / max(len(func_cases), 1) * 100, 1),
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"results": results,
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"errors": errors,
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}
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async def handle_performance_test(tenant_id, task_id, step_name, input_data, config):
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"""Execute performance test cases."""
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test_cases_output = input_data.get("test_case_generate", {}).get("output", {})
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cases = test_cases_output.get("test_cases", [])
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# Filter performance cases
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perf_cases = [c for c in cases if c.get("case_type") == "performance"]
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if not perf_cases:
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# Generate default performance tests if none specified
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perf_cases = _default_performance_cases(config)
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results = []
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for case in perf_cases:
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case_result = await _execute_performance_case(case, config)
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results.append(case_result)
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# Aggregate metrics
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avg_response = sum(r.get("avg_response_ms", 0) for r in results) / max(len(results), 1)
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max_response = max((r.get("max_response_ms", 0) for r in results), default=0)
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total_throughput = sum(r.get("requests_per_sec", 0) for r in results) / max(len(results), 1)
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return {
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"total": len(perf_cases),
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"results": results,
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"metrics": {
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"avg_response_ms": round(avg_response, 2),
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"max_response_ms": round(max_response, 2),
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"avg_throughput_rps": round(total_throughput, 2),
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},
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"passed": sum(1 for r in results if r.get("status") == "pass"),
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"failed": sum(1 for r in results if r.get("status") == "fail"),
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}
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async def handle_bug_report(tenant_id, task_id, step_name, input_data, config):
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"""Collect test results and generate bug reports."""
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func_output = input_data.get("functional_test", {}).get("output", {})
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perf_output = input_data.get("performance_test", {}).get("output", {})
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bugs = []
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# Bugs from functional test failures
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for error in func_output.get("errors", []):
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bugs.append({
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"title": f"[功能测试失败] {error['case_name']}",
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"description": error.get("error", "Unknown error"),
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"severity": "major",
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"priority": "P1",
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"reporter_type": "agent",
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"reporter_id": "system",
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"step_name": step_name,
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})
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# Bugs from performance test failures
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for result in perf_output.get("results", []):
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if result.get("status") == "fail":
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bugs.append({
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"title": f"[性能测试失败] {result.get('case_name', 'Unknown')}",
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"description": json.dumps(result.get("metrics", {}), ensure_ascii=False),
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"severity": "major",
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"priority": "P1",
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"reporter_type": "agent",
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"reporter_id": "system",
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"step_name": step_name,
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})
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return {
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"bugs": bugs,
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"bug_count": len(bugs),
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"by_severity": _count_by_key(bugs, "severity"),
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}
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async def handle_bug_verify(tenant_id, task_id, step_name, input_data, config):
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"""Verify bug fixes by re-running related test cases."""
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bug_fix_output = input_data.get("bug_fix", {}).get("output", {})
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fix_commit = bug_fix_output.get("commit_sha", "")
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if not fix_commit:
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raise ValueError("No fix commit provided from bug_fix step")
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# Re-run the failing test cases
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func_output = input_data.get("functional_test", {}).get("output", {})
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failed_cases = [
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r for r in func_output.get("results", [])
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if r.get("status") == "fail"
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]
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results = []
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for case in failed_cases:
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# Re-execute the test
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rerun = await _execute_test_case(
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{"case_name": case.get("case_name", ""), "steps": case.get("steps", [])},
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config,
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)
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results.append(rerun)
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verified = sum(1 for r in results if r.get("status") == "pass")
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still_failing = sum(1 for r in results if r.get("status") == "fail")
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return {
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"total_verified": len(results),
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"verified_passed": verified,
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"still_failing": still_failing,
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"fix_commit": fix_commit,
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"results": results,
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}
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# --- Helper functions ---
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def _count_by_key(items, key):
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counts = {}
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for item in items:
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val = item.get(key, "unknown")
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counts[val] = counts.get(val, 0) + 1
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return counts
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async def _execute_test_case(case, config):
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"""Execute a single test case. Returns result dict."""
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start_time = time.time()
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case_name = case.get("case_name", "Unknown")
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steps = case.get("steps", [])
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try:
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# Simulate test execution (real implementation would call endpoints)
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base_url = config.get("test_base_url", "http://localhost:9090")
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results = []
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for step in steps:
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# In real implementation, this would:
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# 1. Parse the step to determine HTTP action
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# 2. Execute the HTTP request
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# 3. Validate the response
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results.append({"step": step, "status": "pass"})
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elapsed_ms = int((time.time() - start_time) * 1000)
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all_passed = all(r["status"] == "pass" for r in results)
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return {
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"case_name": case_name,
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"status": "pass" if all_passed else "fail",
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"duration_ms": elapsed_ms,
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"steps": results,
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}
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except Exception as e:
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elapsed_ms = int((time.time() - start_time) * 1000)
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return {
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"case_name": case_name,
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"status": "fail",
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"duration_ms": elapsed_ms,
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"error": str(e),
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}
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async def _execute_performance_case(case, config):
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"""Execute a performance test case."""
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start_time = time.time()
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case_name = case.get("case_name", "Performance Test")
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try:
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base_url = config.get("test_base_url", "http://localhost:9090")
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concurrency = case.get("concurrency", 10)
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duration_sec = case.get("duration_sec", 30)
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endpoint = case.get("endpoint", "/health")
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# Simulate load testing
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# Real implementation would use aiohttp/locust
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request_count = concurrency * duration_sec
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avg_response_ms = 50.0 # simulated
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max_response_ms = 200.0 # simulated
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rps = request_count / duration_sec
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elapsed_ms = int((time.time() - start_time) * 1000)
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# Check thresholds
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threshold_rps = case.get("threshold_rps", 100)
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threshold_avg_ms = case.get("threshold_avg_ms", 500)
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passed = rps >= threshold_rps and avg_response_ms <= threshold_avg_ms
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return {
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"case_name": case_name,
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"status": "pass" if passed else "fail",
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"duration_ms": elapsed_ms,
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"metrics": {
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"requests": request_count,
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"avg_response_ms": avg_response_ms,
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"max_response_ms": max_response_ms,
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"requests_per_sec": rps,
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},
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}
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except Exception as e:
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return {
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"case_name": case_name,
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"status": "fail",
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"error": str(e),
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}
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def _default_performance_cases(config):
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"""Generate default performance test cases."""
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return [
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{
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"case_name": "API响应时间基准",
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"case_type": "performance",
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"endpoint": "/health",
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"concurrency": 10,
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"duration_sec": 30,
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"threshold_rps": 100,
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"threshold_avg_ms": 200,
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},
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{
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"case_name": "CRUD列表性能",
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"case_type": "performance",
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"endpoint": "/api/list",
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"concurrency": 20,
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"duration_sec": 60,
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"threshold_rps": 50,
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"threshold_avg_ms": 500,
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},
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{
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"case_name": "并发写入压力",
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"case_type": "performance",
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"endpoint": "/api/create",
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"concurrency": 5,
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"duration_sec": 30,
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"threshold_rps": 20,
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"threshold_avg_ms": 1000,
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},
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]
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