Detailed introduction to three methods of using Python string connection and their efficiency and applicable scenarios

高洛峰
Release: 2017-03-19 15:27:16
Original
1335 people have browsed it

pythonThere are generally three ways to connect strings:

Method 1: Directly through the plus sign (+)operatorConnection

website = 'python' + 'tab' + '.com'
Copy after login

Method 2: join method

listStr = ['python', 'tab', '.com'] 
website = ''.join(listStr)
Copy after login

Method 3: Replacement

website = '%s%s%s' % ('python', 'tab', '.com')
Copy after login

Let’s talk about the differences between the three methods

Method 1 , simple and direct to use, but many people on the Internet say that this method is inefficient

The reason why using + for string connection in python is inefficient is because strings in python are immutable types. When using + to connect two strings, a new string will be generated. To generate a new string, you need to apply for memory again. When there are many strings that are continuously added (a+b+c+d+e+f+.. .), low efficiency is inevitable

Method 2 is slightly complicated to use, but it is efficient when connecting multiple characters, and there will only be one memory application. And if you are connecting characters in a list, this method must be the first choice

Method 3: String formatting, this method is very commonly used, and I also recommend this method

The following experiments are used to illustrate the efficiency of string concatenation.

比较对象:加号连接 VS join连接
python版本: python2.7
系统环境:CentOS
Copy after login

Experiment one:

# -*- coding: utf-8 -*-
from time import time
def method1():
    t = time()
    for i in xrange(100000):
        s = 'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'+'pythontab'
    print time() - t
def method2():
    t = time()
    for i in xrange(100000):
        s = ''.join(['pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab','pythontab'])
    print time() -t
method1()
method2()
Copy after login

Result:

0.641695976257
0.341440916061
Copy after login

Experiment two:

# -*- coding: utf-8 -*-
from time import time
def method1():
    t = time()
    for i in xrange(100000):
        s = 'pythontab'+'pythontab'+'pythontab'+'pythontab'
    print time() - t
def method2():
    t = time()
    for i in xrange(100000):
        s = ''.join(['pythontab','pythontab','pythontab','pythontab'])
    print time() -t
method1()
method2()
Copy after login

Result:

0.0265691280365
0.0522091388702
Copy after login

The above two experiments appeared Completely different results were obtained. The only difference between the two experiments is: the number of string connections.

Conclusion: The low efficiency of plus sign connection occurs when multiple string connections are performed continuously. If the number of connections is small, the efficiency of plus sign connection is higher than that of join connection

The above is the detailed content of Detailed introduction to three methods of using Python string connection and their efficiency and applicable scenarios. For more information, please follow other related articles on the PHP Chinese website!

Related labels:
source:php.cn
Statement of this Website
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
Popular Tutorials
More>
Latest Downloads
More>
Web Effects
Website Source Code
Website Materials
Front End Template
About us Disclaimer Sitemap
php.cn:Public welfare online PHP training,Help PHP learners grow quickly!