Recently I am using python for interface testing and found that there are many http request methods in python. Today I will take some time to sort out the relevant content and share it with you. The specific content is as follows:
1. python’s own library---- urllib2
Python's own library urllib2 is used more often. A simple way to use it is as follows:
import urllib2
response = urllib2.urlopen('http://localhost:8080/jenkins/api/json?pretty=true')
print response.read()
Simple get request
import urllib2
import urllib
post_data = urllib.urlencode({})
response = urllib2.urlopen('http://localhost:8080/, post_data)
print response.read()
print response.getheaders()
This is the simplest example of urllib2 sending a post. There are a lot of codes
2. python’s own library - httplib
httplib is a relatively low-level http request module, and urlib is encapsulated based on httplib. The simple use is as follows:
import httplib conn = httplib.HTTPConnection("www.python.org") conn.request("GET", "/index.html") r1 = conn.getresponse() print r1.status, r1.reason data1 = r1.read() conn.request("GET", "/parrot.spam") r2 = conn.getresponse() data2 = r2.read() conn.close()
Simple get request
Let’s look at the post request
import httplib, urllib params = urllib.urlencode({'@number': 12524, '@type': 'issue', '@action': 'show'}) headers = {"Content-type": "application/x-www-form-urlencoded", "Accept": "text/plain"} conn = httplib.HTTPConnection("bugs.python.org") conn.request("POST", "", params, headers) response = conn.getresponse() data = response.read() print data conn.close()
Do you think it is too complicated? You have to read the document every time you write, let’s take a look at the third one
Third-party library--requests
Sending a get request is super simple:
print requests.get('http://localhost:8080).text
Just one sentence, let’s take a look at the post request
payload = {'key1': 'value1', 'key2': 'value2'} r = requests.post("http://httpbin.org/post", data=payload) print r.text
also Very simple.
Let’s take a look again if you want to authenticate:
url = 'http://localhost:8080' r = requests.post(url, data={}, auth=HTTPBasicAuth('admin', 'admin')) print r.status_code print r.headers print r.reason
Isn’t it much simpler than urllib2, and requests come with json parsing. This is great
http request in python
import urllib params = urllib.urlencode({key:value,key:value}) resultHtml = urllib.urlopen('[API or 网址]',params) result = resultHtml.read() print result

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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