python @mylog.timer 裝飾器的使用

更新時(shí)間：2026年03月22日 10:08:26 作者：Yorlen_Zhang

本文詳細(xì)介紹了Python計(jì)時(shí)裝飾器@mylog.timer的實(shí)現(xiàn)與應(yīng)用,文中通過示例代碼介紹的非常詳細(xì),對(duì)大家的學(xué)習(xí)或者工作具有一定的參考學(xué)習(xí)價(jià)值,需要的朋友們下面隨著小編來一起學(xué)習(xí)學(xué)習(xí)吧

1. 基礎(chǔ)版本：簡易計(jì)時(shí)裝飾器

import time
import functools

def timer(func):
    """基礎(chǔ)計(jì)時(shí)裝飾器"""
    @functools.wraps(func)
    def wrapper(*args, **kwargs):
        start_time = time.perf_counter()
        result = func(*args, **kwargs)
        end_time = time.perf_counter()
        print(f"[TIMER] {func.__name__} 執(zhí)行時(shí)間: {end_time - start_time:.4f} 秒")
        return result
    return wrapper

# 使用方式
@timer
def slow_function():
    time.sleep(1)
    return "完成"

slow_function()
# 輸出: [TIMER] slow_function 執(zhí)行時(shí)間: 1.0023 秒

2. 進(jìn)階版本：集成日志系統(tǒng)（推薦）

實(shí)際項(xiàng)目中，我們通常需要專業(yè)的日志管理：

import logging
import time
import functools
from typing import Callable, Any
# 配置日志
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
    datefmt='%Y-%m-%d %H:%M:%S'
)
class MyLog:
    """日志工具類，包含計(jì)時(shí)裝飾器"""
    def __init__(self, name: str = "MyLog"):
        self.logger = logging.getLogger(name)
    def timer(self, level: int = logging.INFO):
        """
        帶日志級(jí)別的計(jì)時(shí)裝飾器
        用法:
        @mylog.timer()
        @mylog.timer(logging.DEBUG)
        """
        def decorator(func: Callable) -> Callable:
            @functools.wraps(func)
            def wrapper(*args, **kwargs) -> Any:
                # 記錄開始時(shí)間
                start_time = time.perf_counter()
                try:
                    # 執(zhí)行函數(shù)
                    result = func(*args, **kwargs)
                    # 計(jì)算耗時(shí)
                    end_time = time.perf_counter()
                    duration = end_time - start_time
                    # 獲取函數(shù)參數(shù)信息
                    args_repr = [repr(a) for a in args]
                    kwargs_repr = [f"{k}={v!r}" for k, v in kwargs.items()]
                    signature = ", ".join(args_repr + kwargs_repr)
                    # 記錄日志
                    self.logger.log(
                        level,
                        f"[TIMER] {func.__name__}({signature}) -> {duration:.4f}s"
                    )
                    return result
                except Exception as e:
                    # 異常時(shí)也記錄耗時(shí)
                    end_time = time.perf_counter()
                    duration = end_time - start_time
                    self.logger.error(
                        f"[TIMER] {func.__name__} 執(zhí)行失敗，耗時(shí): {duration:.4f}s, 錯(cuò)誤: {e}"
                    )
                    raise
            return wrapper
        return decorator
# 實(shí)例化
mylog = MyLog()
# 使用示例
@mylog.timer()
def calculate_sum(n: int):
    """計(jì)算 1 到 n 的和"""
    return sum(range(1, n + 1))
@mylog.timer(logging.DEBUG)
def fetch_data(url: str):
    """模擬獲取數(shù)據(jù)"""
    time.sleep(0.5)
    return f"Data from {url}"
# 測試
calculate_sum(1000000)
fetch_data("https://api.example.com")

3. 高級(jí)版本：帶配置和統(tǒng)計(jì)功能

import logging
import time
import functools
import statistics
from typing import Dict, List
from collections import defaultdict

class AdvancedMyLog:
    """高級(jí)日志類，支持統(tǒng)計(jì)多次調(diào)用的性能數(shù)據(jù)"""
    
    _stats: Dict[str, List[float]] = defaultdict(list)
    
    def __init__(self, name: str = "AdvancedLog"):
        self.logger = logging.getLogger(name)
        handler = logging.StreamHandler()
        formatter = logging.Formatter(
            '%(asctime)s | %(name)s | %(levelname)s | %(message)s'
        )
        handler.setFormatter(formatter)
        self.logger.addHandler(handler)
        self.logger.setLevel(logging.DEBUG)
    
    def timer(self, log_args: bool = True, alert_threshold: float = None):
        """
        高級(jí)計(jì)時(shí)裝飾器
        
        Args:
            log_args: 是否記錄函數(shù)參數(shù)
            alert_threshold: 超時(shí)警告閾值（秒）
        """
        def decorator(func):
            @functools.wraps(func)
            def wrapper(*args, **kwargs):
                func_name = func.__qualname__
                start = time.perf_counter()
                
                result = func(*args, **kwargs)
                
                duration = time.perf_counter() - start
                
                # 保存統(tǒng)計(jì)數(shù)據(jù)
                self._stats[func_name].append(duration)
                
                # 構(gòu)建日志消息
                if log_args and (args or kwargs):
                    args_str = ", ".join(
                        [repr(a) for a in args[1:]] +  # 排除 self/cls
                        [f"{k}={v!r}" for k, v in kwargs.items()]
                    )
                    msg = f"[TIMER] {func_name}({args_str}) 耗時(shí): {duration:.4f}s"
                else:
                    msg = f"[TIMER] {func_name} 耗時(shí): {duration:.4f}s"
                
                # 檢查閾值
                if alert_threshold and duration > alert_threshold:
                    self.logger.warning(f"[SLOW] {msg} (超過閾值 {alert_threshold}s)")
                else:
                    self.logger.info(msg)
                
                return result
            return wrapper
        return decorator
    
    @classmethod
    def get_stats(cls, func_name: str = None):
        """獲取性能統(tǒng)計(jì)報(bào)告"""
        if func_name:
            times = cls._stats.get(func_name, [])
            if not times:
                return f"{func_name}: 無數(shù)據(jù)"
            return {
                "函數(shù)": func_name,
                "調(diào)用次數(shù)": len(times),
                "平均耗時(shí)": statistics.mean(times),
                "最大耗時(shí)": max(times),
                "最小耗時(shí)": min(times),
            }
        
        return {name: cls.get_stats(name) for name in cls._stats}

# 使用示例
adv_log = AdvancedMyLog()

class DataProcessor:
    @adv_log.timer(alert_threshold=1.0)  # 超過1秒警告
    def process(self, data: list):
        time.sleep(0.8)  # 模擬處理
        return len(data)

processor = DataProcessor()
processor.process([1, 2, 3])
processor.process([4, 5, 6])

# 查看統(tǒng)計(jì)
print(AdvancedMyLog.get_stats("DataProcessor.process"))

4. 異步函數(shù)支持

現(xiàn)代 Python 常使用 async/await，需要特殊處理：

import asyncio
import time
import functools

class AsyncTimerLog:
    def __init__(self):
        self.logger = logging.getLogger("AsyncLog")
    
    def timer(self, func):
        """支持異步函數(shù)的計(jì)時(shí)裝飾器"""
        @functools.wraps(func)
        async def async_wrapper(*args, **kwargs):
            start = time.perf_counter()
            result = await func(*args, **kwargs)
            duration = time.perf_counter() - start
            self.logger.info(f"[ASYNC TIMER] {func.__name__} 耗時(shí): {duration:.4f}s")
            return result
        
        @functools.wraps(func)
        def sync_wrapper(*args, **kwargs):
            start = time.perf_counter()
            result = func(*args, **kwargs)
            duration = time.perf_counter() - start
            self.logger.info(f"[SYNC TIMER] {func.__name__} 耗時(shí): {duration:.4f}s")
            return result
        
        # 自動(dòng)判斷是否是協(xié)程函數(shù)
        if asyncio.iscoroutinefunction(func):
            return async_wrapper
        return sync_wrapper

# 使用
mylog = AsyncTimerLog()

@mylog.timer
async def async_fetch():
    await asyncio.sleep(1)
    return "data"

@mylog.timer
def sync_fetch():
    time.sleep(0.5)
    return "data"

# 運(yùn)行
sync_fetch()
asyncio.run(async_fetch())

5. 使用場景與最佳實(shí)踐

5.1 性能監(jiān)控

# 監(jiān)控 API 接口響應(yīng)時(shí)間
@mylog.timer(alert_threshold=2.0)
def api_endpoint():
    # 數(shù)據(jù)庫查詢等操作
    pass

5.2 算法優(yōu)化對(duì)比

@mylog.timer()
def algorithm_v1(data):
    # 舊算法
    pass

@mylog.timer()
def algorithm_v2(data):
    # 新算法
    pass

# 對(duì)比兩者的執(zhí)行時(shí)間

5.3 上下文管理器（替代方案）

import time
from contextlib import contextmanager

@contextmanager
def timer_context(name: str):
    start = time.perf_counter()
    yield
    duration = time.perf_counter() - start
    print(f"[BLOCK TIMER] {name}: {duration:.4f}s")

# 使用
with timer_context("代碼塊 A"):
    time.sleep(1)

6. 注意事項(xiàng)

注意點(diǎn)	說明
functools.wraps	必須保留原函數(shù)的元數(shù)據(jù)（`__name__`, `__doc__`）
異常處理	確保即使函數(shù)拋出異常也能記錄耗時(shí)
性能開銷	日志本身有開銷，生產(chǎn)環(huán)境建議設(shè)置開關(guān)
線程安全	多線程環(huán)境下統(tǒng)計(jì)數(shù)據(jù)需要加鎖

完整使用模板

# config.py 或 utils.py
import logging
import time
import functools

class MyLog:
    _instance = None
    
    def __new__(cls, *args, **kwargs):
        if not cls._instance:
            cls._instance = super().__new__(cls)
        return cls._instance
    
    def __init__(self, name="MyApp"):
        if not hasattr(self, 'logger'):
            self.logger = logging.getLogger(name)
            self.logger.setLevel(logging.INFO)
            if not self.logger.handlers:
                handler = logging.StreamHandler()
                handler.setFormatter(
                    logging.Formatter('%(asctime)s - %(message)s')
                )
                self.logger.addHandler(handler)
    
    def timer(self, level=logging.INFO):
        def decorator(func):
            @functools.wraps(func)
            def wrapper(*args, **kwargs):
                start = time.perf_counter()
                try:
                    result = func(*args, **kwargs)
                    duration = time.perf_counter() - start
                    self.logger.log(
                        level, 
                        f"[?? TIMER] {func.__name__} completed in {duration:.4f}s"
                    )
                    return result
                except Exception as e:
                    duration = time.perf_counter() - start
                    self.logger.error(
                        f"[?? TIMER] {func.__name__} failed after {duration:.4f}s: {e}"
                    )
                    raise
            return wrapper
        return decorator

# 全局實(shí)例
mylog = MyLog()

# 業(yè)務(wù)代碼中使用
@mylog.timer()
def your_function():
    pass

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