When we browse the Internet every day, we often see some good-looking pictures, and we want to save and download these pictures, or use them as desktop wallpapers, or as design materials.
Our most common method is to right-click the mouse and select Save As. However, some pictures do not have a save as option when you right-click the mouse. Another way is to capture them with a screenshot tool, but this will reduce the clarity of the picture. Okay~! In fact, you are very good. Right-click to view the page source code.
We can use python to implement such a simple crawler function and crawl the code we want locally. Let's take a look at how to use python to implement such a function.
One, get the entire page data
First we can get the entire page information of the image to be downloaded.
getjpg.py
#coding=utf-8 import urllib def getHtml(url): page = urllib.urlopen(url) html = page.read() return html html = getHtml("http://tieba.baidu.com/p/2738151262") print html
The Urllib module provides an interface for reading web page data. We can read data on www and ftp just like reading local files. First, we define a getHtml() function:
urllib.urlopen() method is used to open a URL address.
read() method is used to read the data on the URL, pass a URL to the getHtml() function, and download the entire page. Executing the program will print out the entire web page.
Second, filter the data you want on the page
Python provides very powerful regular expressions. We need to know a little bit about python regular expressions first.
Suppose we find a few beautiful wallpapers in Baidu Tieba and go to the previous section to view the tools. Found the address of the picture, such as: src=”http://imgsrc.baidu.com/forum...jpg” pic_ext=”jpeg”
Modify the code as follows:
import re import urllib def getHtml(url): page = urllib.urlopen(url) html = page.read() return html def getImg(html): reg = r'src="(.+?\.jpg)" pic_ext' imgre = re.compile(reg) imglist = re.findall(imgre,html) return imglist html = getHtml("http://tieba.baidu.com/p/2460150866") print getImg(html)
We have also created the getImg() function, which is used to filter the required image links in the entire page obtained. The re module mainly contains regular expressions:
re.compile() can compile a regular expression into a regular expression object.
re.findall() method reads data containing imgre (regular expression) in html.
Running the script will get the URL address of the image contained in the entire page.
Three, save the page filtered data locally
Traverse the filtered image addresses through a for loop and save them locally. The code is as follows:
#coding=utf-8 import urllib import re def getHtml(url): page = urllib.urlopen(url) html = page.read() return html def getImg(html): reg = r'src="(.+?\.jpg)" pic_ext' imgre = re.compile(reg) imglist = re.findall(imgre,html) x = 0 for imgurl in imglist: urllib.urlretrieve(imgurl,'%s.jpg' % x) x+=1 html = getHtml("http://tieba.baidu.com/p/2460150866") print getImg(html)
The core here is to use the urllib.urlretrieve() method to directly download remote data to the local.
Traverse the obtained image connections through a for loop. In order to make the file name of the image look more standardized, rename it. The naming rule is to add 1 to the x variable. The save location defaults to the program's storage directory.
After the program is completed, you will see the files downloaded to the local directory.
Thanks for reading, I hope it can help everyone, thank you for your support of this site!

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

SecLists
SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.

WebStorm Mac version
Useful JavaScript development tools

Atom editor mac version download
The most popular open source editor

EditPlus Chinese cracked version
Small size, syntax highlighting, does not support code prompt function

DVWA
Damn Vulnerable Web App (DVWA) is a PHP/MySQL web application that is very vulnerable. Its main goals are to be an aid for security professionals to test their skills and tools in a legal environment, to help web developers better understand the process of securing web applications, and to help teachers/students teach/learn in a classroom environment Web application security. The goal of DVWA is to practice some of the most common web vulnerabilities through a simple and straightforward interface, with varying degrees of difficulty. Please note that this software