


How to use urllib.urlopen() function to send GET request in Python 2.x
Python is a popular programming language widely used in areas such as web development, data analysis, and automation tasks. In Python 2.x version, you can easily send GET requests and obtain response data using the urlopen() function of the urllib library. This article will introduce in detail how to use the urlopen() function to send a GET request in Python 2.x, and provide corresponding code examples.
Before using the urlopen() function to send a GET request, we first need to import the urllib library, using the following code:
import urllib
Next, we use the urlopen() function to send a GET request. The parameter of the urlopen() function can be a URL address string or a Request object. When sending a GET request, we only need to pass in the URL address. The following is a sample code that uses the urlopen() function to send a GET request and get the response:
response = urllib.urlopen('https://www.example.com') data = response.read() print(data)
In the above code, we use the urlopen() function to send a GET request, and the URL address is "https://www .example.com". The urlopen() function returns a file-like object, and we can obtain the response data by calling the read() method. Finally, we print out the obtained data.
It should be noted that the file-like object returned by the urlopen() function needs to be closed manually. In order to better manage resources, we can use the with statement to automatically close the object. The following is a sample code with a with statement:
with urllib.urlopen('https://www.example.com') as response: data = response.read() print(data)
When using the urlopen() function to send a GET request, we can also simulate the behavior of the browser sending a request by adding request header information. For example, we can add the User-Agent header to pretend to be a different browser. The following is a sample code for adding the User-Agent header:
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3'} req = urllib.urlopen('https://www.example.com', headers=headers) data = req.read() print(data)
In the above code, we define a dictionary type headers variable to store request header information. Then, we create a Request object and pass in the headers as parameters. Finally, we get the response data by calling the read() method.
In summary, the urllib library in Python 2.x provides a convenient urlopen() function, which can be used to send GET requests and obtain response data. When using the urlopen() function, we can simulate the behavior of the browser sending requests by passing in the URL address, adding request header information, etc. By mastering these methods, we can better handle related tasks such as web development, data analysis, and automation tasks. I wish you success in using Python!
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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.


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