search
HomeBackend DevelopmentPython TutorialHow to crawl ajax in python

How to crawl ajax in python

Jul 01, 2019 am 10:22 AM
python

Use python package: requests.

How to crawl ajax in python

Specific method: (Recommended learning: Python video tutorial)

First, define your own headers. Note that the User-Agent field in the headers can be used to design a list according to your own needs for random replacement.

Web page features of ajax data: There are some ajax requests in the XHR network flow in NetWork, among which their request_url must be an ajax request interface, and the referer in the headers is the url before the jump. When constructing itself The referer field needs to be set in the headers.

Take the search for "java" on Lagou.com's homepage as an example:

How to crawl ajax in python The ajax data crawler and the ordinary web crawler have one more url, one is the url of the referer. Placed in headers. The other one is ajax_url, which is also the main access url.

The most important point is that ajax generally returns json data, so the parsing form of the captured data is different. Simply convert the result set into a json result set, and the access method is ordinary dictionary or list access.

The other one is the access parameter. If the request contains param, it will be constructed. If not, ignore it. There are parameters in this example, pay attention to the parameter dictionary construction method

A simple complete code is shown below

from urllib.request import quote,unquote
import random
import requests
 
keyword = quote('java').strip()
print(keyword, type(keyword))
city = quote('郑州').strip()
print(unquote(city))
 
refer_url = 'https://www.lagou.com/jobs/list_%s?city=%s&cl=false&fromSearch=true&labelWords=&suginput=' % (keyword, city)
ajax_url = 'https://www.lagou.com/jobs/positionAjax.json?city=%s&needAddtionalResult=false' %city
user_agents=[
    'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2883.87 Safari/537.36',
    'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3325.181 Safari/537.36',
    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36 Edge/16.16299',
]
 
data ={
    'first': 'true',
    'pn': '1',
    'kd': keyword,
}
headers={
    'Accept': 'application/json, text/javascript, */*; q=0.01',
    'Accept-Encoding': 'gzip, deflate, br',
    'Accept-Language': 'zh-CN,zh;q=0.9',
    'Connection': 'keep-alive',
    'Content-Length': '46',
    'Content-Type': 'application/x-www-form-urlencoded; charset=UTF-8',
    'Host': 'www.lagou.com',
    'Origin': 'https://www.lagou.com',
    'Referer': refer_url,
    'User-Agent': user_agents[random.randrange(0,3)],
    'X-Anit-Forge-Code': '0',
    'X-Anit-Forge-Token': 'None',
    'X-Requested-With': 'XMLHttpRequest',
}
resp = requests.post(ajax_url,data=data, headers=headers)
 
result = resp.json()
print(result)
# print(result)
#result 就是最终获得的json格式数据
item = result['content']['positionResult']['result'][0]
print(item)
#item就是单个招聘条目信息
print("程序结束")

For more Python related technical articles, please visitPython tutorial Column for learning!

The above is the detailed content of How to crawl ajax 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
Python vs. C  : Learning Curves and Ease of UsePython vs. C : Learning Curves and Ease of UseApr 19, 2025 am 12:20 AM

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.

Python vs. C  : Memory Management and ControlPython vs. C : Memory Management and ControlApr 19, 2025 am 12:17 AM

Python and C have significant differences in memory management and control. 1. Python uses automatic memory management, based on reference counting and garbage collection, simplifying the work of programmers. 2.C requires manual management of memory, providing more control but increasing complexity and error risk. Which language to choose should be based on project requirements and team technology stack.

Python for Scientific Computing: A Detailed LookPython for Scientific Computing: A Detailed LookApr 19, 2025 am 12:15 AM

Python's applications in scientific computing include data analysis, machine learning, numerical simulation and visualization. 1.Numpy provides efficient multi-dimensional arrays and mathematical functions. 2. SciPy extends Numpy functionality and provides optimization and linear algebra tools. 3. Pandas is used for data processing and analysis. 4.Matplotlib is used to generate various graphs and visual results.

Python and C  : Finding the Right ToolPython and C : Finding the Right ToolApr 19, 2025 am 12:04 AM

Whether to choose Python or C depends on project requirements: 1) Python is suitable for rapid development, data science, and scripting because of its concise syntax and rich libraries; 2) C is suitable for scenarios that require high performance and underlying control, such as system programming and game development, because of its compilation and manual memory management.

Python for Data Science and Machine LearningPython for Data Science and Machine LearningApr 19, 2025 am 12:02 AM

Python is widely used in data science and machine learning, mainly relying on its simplicity and a powerful library ecosystem. 1) Pandas is used for data processing and analysis, 2) Numpy provides efficient numerical calculations, and 3) Scikit-learn is used for machine learning model construction and optimization, these libraries make Python an ideal tool for data science and machine learning.

Learning Python: Is 2 Hours of Daily Study Sufficient?Learning Python: Is 2 Hours of Daily Study Sufficient?Apr 18, 2025 am 12:22 AM

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Python for Web Development: Key ApplicationsPython for Web Development: Key ApplicationsApr 18, 2025 am 12:20 AM

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python vs. C  : Exploring Performance and EfficiencyPython vs. C : Exploring Performance and EfficiencyApr 18, 2025 am 12:20 AM

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Tools

SublimeText3 English version

SublimeText3 English version

Recommended: Win version, supports code prompts!

Dreamweaver Mac version

Dreamweaver Mac version

Visual web development tools

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

EditPlus Chinese cracked version

EditPlus Chinese cracked version

Small size, syntax highlighting, does not support code prompt function