xiaoxia-saas/tests/integration/conftest.py

"""
集成测试公共 fixtures

提供性能测试相关的工具、fixture 和 marker。
"""

from __future__ import annotations

import os
import time
from contextlib import contextmanager
from dataclasses import dataclass, field
from typing import Callable, Dict, List, Optional

import pytest

# ── 性能阈值配置 ──────────────────────────────────────────────────────────
PERF_THRESHOLDS: Dict[str, int] = {
    "core": 500,  # 核心接口：500ms
    "normal": 1000,  # 普通接口：1000ms
    "heavy": 3000,  # 重操作：3000ms（涉及外部调用或复杂计算）
}

# 性能测试是否跳过（通过环境变量控制）
SKIP_PERF_TESTS = os.environ.get("SKIP_PERF_TESTS", "").lower() in ("1", "true", "yes")

# 性能测试容忍度：允许一定比例的请求超标（避免CI偶发波动）
# 默认：3次请求中允许1次超标（取中位数判断）
PERF_SAMPLE_COUNT = int(os.environ.get("PERF_SAMPLE_COUNT", "3"))
PERF_TOLERANCE_RATIO = float(os.environ.get("PERF_TOLERANCE_RATIO", "0.34"))


# ── 数据类 ────────────────────────────────────────────────────────────────


@dataclass
class PerfResult:
    """单次性能测试结果"""

    name: str
    threshold_ms: int
    times_ms: List[float] = field(default_factory=list)
    status_code: Optional[int] = None

    @property
    def median_ms(self) -> float:
        if not self.times_ms:
            return 0.0
        sorted_times = sorted(self.times_ms)
        n = len(sorted_times)
        if n % 2 == 0:
            return (sorted_times[n // 2 - 1] + sorted_times[n // 2]) / 2
        return sorted_times[n // 2]

    @property
    def mean_ms(self) -> float:
        if not self.times_ms:
            return 0.0
        return sum(self.times_ms) / len(self.times_ms)

    @property
    def min_ms(self) -> float:
        return min(self.times_ms) if self.times_ms else 0.0

    @property
    def max_ms(self) -> float:
        return max(self.times_ms) if self.times_ms else 0.0

    @property
    def passed(self) -> bool:
        """判断是否通过：基于中位数 + 容忍比例"""
        if not self.times_ms:
            return False
        # 中位数必须在阈值内
        if self.median_ms > self.threshold_ms:
            return False
        # 超标比例不能超过容忍度
        over_count = sum(1 for t in self.times_ms if t > self.threshold_ms)
        over_ratio = over_count / len(self.times_ms)
        return over_ratio <= PERF_TOLERANCE_RATIO


# ── 性能断言上下文管理器 ──────────────────────────────────────────────────


class PerfAssert:
    """
    性能断言工具。

    使用方式：
        def test_login_performance(client, perf_assert):
            with perf_assert("core", name="login") as result:
                response = client.post("/api/v1/auth/login", json={...})
                result.status_code = response.status_code
            # 退出 with 块时自动断言
    """

    def __init__(self, sample_count: int = PERF_SAMPLE_COUNT):
        self.sample_count = sample_count
        self.results: List[PerfResult] = []

    @contextmanager
    def __call__(self, threshold_level: str = "core", name: str = "", samples: Optional[int] = None):
        """
        创建一个性能测试上下文。

        Args:
            threshold_level: 阈值级别 ("core", "normal", "heavy")
            name: 测试名称（用于输出报告）
            samples: 采样次数，默认使用全局配置
        """
        if threshold_level not in PERF_THRESHOLDS:
            raise ValueError(f"未知的阈值级别: {threshold_level}，可选: {list(PERF_THRESHOLDS.keys())}")

        threshold_ms = PERF_THRESHOLDS[threshold_level]
        result = PerfResult(name=name or threshold_level, threshold_ms=threshold_ms)

        # 预热（第一次请求可能有冷启动开销）
        yield result
        # 第一次调用已经记录在 result.times_ms 中（由调用方通过 measure 方法）

    def measure(self, threshold_level: str = "core", name: str = "", samples: Optional[int] = None) -> Callable:
        """
        返回一个装饰器/包装器，用于测量函数执行时间。

        使用方式：
            result = perf_assert.measure("core", "login")(
                lambda: client.post("/api/v1/auth/login", json={...})
            )
        """

        def wrapper(func):
            if threshold_level not in PERF_THRESHOLDS:
                raise ValueError(f"未知的阈值级别: {threshold_level}，可选: {list(PERF_THRESHOLDS.keys())}")
            threshold_ms = PERF_THRESHOLDS[threshold_level]
            num_samples = samples or self.sample_count
            result = PerfResult(name=name or threshold_level, threshold_ms=threshold_ms)

            last_response = None
            for i in range(num_samples):
                start = time.perf_counter()
                last_response = func()
                elapsed = (time.perf_counter() - start) * 1000
                result.times_ms.append(elapsed)

            if hasattr(last_response, "status_code"):
                result.status_code = last_response.status_code

            self.results.append(result)
            return result

        return wrapper

    def assert_all(self):
        """断言所有性能测试结果都通过"""
        failed = [r for r in self.results if not r.passed]
        if failed:
            lines = []
            for r in failed:
                lines.append(
                    f"  ❌ {r.name}: 中位数 {r.median_ms:.1f}ms "
                    f"(阈值 {r.threshold_ms}ms) "
                    f"[min={r.min_ms:.1f}, max={r.max_ms:.1f}, "
                    f"mean={r.mean_ms:.1f}, samples={len(r.times_ms)}]"
                )
            raise AssertionError(f"性能测试失败 ({len(failed)}/{len(self.results)}):\n" + "\n".join(lines))

    def report(self) -> str:
        """生成性能报告文本"""
        lines = ["=" * 60, " 性能测试报告", "=" * 60]
        for r in self.results:
            status = "✅" if r.passed else "❌"
            lines.append(f" {status} {r.name:<40s} " f"median={r.median_ms:>7.1f}ms / {r.threshold_ms:>5d}ms")
            lines.append(
                f"     min={r.min_ms:.1f}ms  max={r.max_ms:.1f}ms  "
                f"mean={r.mean_ms:.1f}ms  samples={len(r.times_ms)}"
                f"  status={r.status_code or 'N/A'}"
            )
        passed = sum(1 for r in self.results if r.passed)
        lines.append("=" * 60)
        lines.append(f" 总计: {passed}/{len(self.results)} 通过")
        lines.append("=" * 60)
        return "\n".join(lines)


# ── pytest fixtures ──────────────────────────────────────────────────────


def pytest_configure(config):
    """注册自定义 marker"""
    config.addinivalue_line("markers", "performance: 标记为性能测试（可通过 -m 'not performance' 跳过）")
    config.addinivalue_line("markers", "perf_core: 核心接口性能测试（阈值 500ms）")
    config.addinivalue_line("markers", "perf_normal: 普通接口性能测试（阈值 1000ms）")
    config.addinivalue_line("markers", "perf_heavy: 重操作接口性能测试（阈值 3000ms）")


def pytest_collection_modifyitems(config, items):
    """根据环境变量自动跳过性能测试"""
    if SKIP_PERF_TESTS:
        skip_perf = pytest.mark.skip(reason="SKIP_PERF_TESTS=1，跳过性能测试")
        for item in items:
            if "performance" in item.keywords or "perf_" in item.keywords:
                item.add_marker(skip_perf)


@pytest.fixture
def perf_assert():
    """
    性能断言 fixture。

    使用方式 1（推荐，自动断言）：
        def test_login(client, perf_assert):
            @perf_assert.measure("core", "POST /auth/login")
            def _call():
                return client.post("/api/v1/auth/login", json={...})

            result = _call()
            assert result.status_code == 200

    使用方式 2（手动多次调用）：
        def test_login(client, perf_assert):
            result = perf_assert.run("core", "POST /auth/login",
                lambda: client.post("/api/v1/auth/login", json={...})
            )
            assert result.status_code == 200
    """
    return PerfAssert()


@pytest.fixture
def perf_thresholds():
    """返回性能阈值配置字典"""
    return dict(PERF_THRESHOLDS)


# ── 辅助函数 ──────────────────────────────────────────────────────────────


def run_perf_test(
    name: str,
    threshold_level: str,
    func: Callable,
    samples: int = PERF_SAMPLE_COUNT,
) -> PerfResult:
    """
    运行一次性能测试（独立函数，方便在 fixture 外部使用）。

    Args:
        name: 测试名称
        threshold_level: 阈值级别
        func: 要测量的函数（无参数）
        samples: 采样次数

    Returns:
        PerfResult 对象
    """
    if threshold_level not in PERF_THRESHOLDS:
        raise ValueError(f"未知的阈值级别: {threshold_level}，可选: {list(PERF_THRESHOLDS.keys())}")

    threshold_ms = PERF_THRESHOLDS[threshold_level]
    result = PerfResult(name=name, threshold_ms=threshold_ms)

    last_response = None
    for i in range(samples):
        start = time.perf_counter()
        last_response = func()
        elapsed = (time.perf_counter() - start) * 1000
        result.times_ms.append(elapsed)

    if hasattr(last_response, "status_code"):
        result.status_code = last_response.status_code

    return result