Home >Backend Development >Python Tutorial >Comprehensive analysis of log (logging module) performance and multi-process in python

Comprehensive analysis of log (logging module) performance and multi-process in python

黄舟
黄舟Original
2017-07-18 11:26:512313browse

使用Python来写后台任务时,时常需要使用输出日志来记录程序运行的状态,并在发生错误时将错误的详细信息保存下来,以别调试和分析。Python的logging模块就是这种情况下的好帮手。本文就介绍了python中日志logging模块性能及多进程的相关资料,需要的朋友可以参考下。

前言

Java 中最通用的日志模块莫过于 Log4j 了,在 python 中,也自带了 logging 模块,该模块的用法其实和 Log4j 类似。日志是记录操作的一种好方式。但是日志,基本都是基于文件的,也就是要写到磁盘上的。这时候,磁盘将会成为一个性能瓶颈。对于普通的服务器硬盘(机械磁盘,非固态硬盘),Python日志的性能瓶颈是多少呢?今天我们就来测一下。下面话不多说,来一起看看详细的介绍:

测试代码如下:


#! /usr/bin/env python 
#coding=utf-8 
 
# ============================ 
# Describe : 给平台提供的日志 
# D&P Author By:  常成功 
# Create Date:  2016/08/01 
# Modify Date:  2016/08/01 
# ============================ 
 
import time 
import os 
import logging 
 
 
print "Start test ...." 
s_tm = time.time() 
test_time = 10.0 # 测试时间10秒 
e_tm = s_tm + 10 
j = 0 
 
pid = str(os.getpid()) 
while 1: 
 now_time = time.time() 
 j += 1 
 if now_time > e_tm: 
  break 
 # 生成文件夹 
 lujing = "d:\\test_log" 
 if not os.path.exists(lujing): 
  os.mkdir(lujing) 
 
 fm2 = '%Y%m%d' 
 YMD = time.strftime(fm2, time.localtime(now_time)) 
 
 filename = 'recharge_' + YMD + '.log' 
 log_file = os.path.join(lujing, filename) 
 t = "\t" 
 log_msg = str(j) +t+ str(now_time) +t+ pid 
 
 the_logger = logging.getLogger('recharge_log') 
 f_handler = logging.FileHandler(log_file) 
 the_logger.addHandler(f_handler) 
 the_logger.setLevel(logging.INFO) 
 # To pass exception information, use the keyword argument exc_info with a true value 
 the_logger.info(log_msg, exc_info=False) 
 the_logger.removeHandler(f_handler) 
 
rps = j/test_time 
print rps, "rows per second"

结果为:

Start test ....

2973.0 rows per second


Python的logging性能:

7200转的机械磁盘,测了几次,每秒的能写入日志的行数(每行就是一条日志),数量基本在 2800-3000 之间。此时,磁盘IO基本已经跑满。(在3.3Ghz的CPU上,CPU占用大约40%)。

Python的logging多进程:

python 的 logging模块,是线程安全的。但对于多进程的程序来说,怎么去写日志文件呢?我的解决办法是,每个进程的PID,写一个单独的日志文件。再用算法把所有进程的日志合并起来,生成新的日志。

提示:由于磁盘IO已经到达瓶颈,所以多进程并不能提高日志性能。高性能日志,需要用缓存,或者分布式日志。

总结

The above is the detailed content of Comprehensive analysis of log (logging module) performance and multi-process in python. For more information, please follow other related articles on the PHP Chinese website!

Statement:
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn