


Python Server Programming: Building Web Applications with Jupyter Notebook
In recent years, Python has become the language of choice for more and more developers. In the field of back-end development, Python is also a very practical tool. Due to Python's easy-to-learn and easy-to-use characteristics and its large collection of third-party libraries, Python has great advantages in server-side development. In this article, we will explore how to build web applications using Jupyter Notebook.
Jupyter Notebook is a powerful web application that allows users to program in Python in an integrated environment. It can be used not only for data analysis and scientific computing, but also for server-side development. Using Jupyter Notebook, we can quickly build a web application.
We first need to install Jupyter Notebook. We can install Jupyter Notebook using Anaconda, or download it directly from Jupyter's official website.
After successful installation, we can start Jupyter Notebook with the following command:
jupyter notebook
After startup, we can see the following interface:
We can click the "New" button to create a new Notebook, select Python3 or Python2, and then start programming.
Next, we will demonstrate how to use Jupyter Notebook to build a web application through an example. Suppose we want to build a simple web application that converts user-entered text into lowercase letters.
We can use the flask framework in Python to build this application. First, we need to install the flask framework:
pip install Flask
After successful installation, we can write code in Jupyter Notebook to build this application. The following is the complete code:
from flask import Flask, request app = Flask(__name__) @app.route('/', methods=['GET', 'POST']) def index(): res = '' if request.method == 'POST': res = request.form['text'].lower() return ''' <html> <body> <h1>Input some text:</h1> <form method="post"> <input type="text" name="text"> <input type="submit" value="Submit"> </form> <h2>Lowercase text:</h2> <h3>{}</h3> </body> </html> '''.format(res) if __name__ == '__main__': app.run(debug=True)
The above code builds the simplest web application. On the homepage of the program, we can enter a piece of text. After submission, it will convert the entered text into lowercase letters and display it on the interface. We can use the @app.route decorator in the flask framework to create a function to handle user requests. In this function, we use the request object to obtain the text entered by the user, convert it into lowercase letters, and return the result to the user.
At the end of the program, we use the app.run() method to start the Web server and start listening for Web requests. When a user accesses our web application, the server can receive the request and return a response.
Finally, we can use the browser to visit http://127.0.0.1:5000 to see the effect of this application. In the browser, we can see the following interface:
We can enter a piece of text, and after clicking the "Submit" button, the program will convert the entered text into lowercase letters and display the result on the web page .
Summary:
In this article, we introduced how to use Jupyter Notebook to build web applications. We used the flask framework and built a simple web application that demonstrates how to convert user-entered text into lowercase letters. By writing programs in Jupyter Notebook, we can quickly build a web application, test and debug it. Jupyter Notebook's ease of use and powerful features make it an indispensable tool for server-side Python programming.
The above is the detailed content of Python Server Programming: Building Web Applications with Jupyter Notebook. For more information, please follow other related articles on the PHP Chinese website!

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

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics











PHP is mainly procedural programming, but also supports object-oriented programming (OOP); Python supports a variety of paradigms, including OOP, functional and procedural programming. PHP is suitable for web development, and Python is suitable for a variety of applications such as data analysis and machine learning.

PHP is suitable for web development and rapid prototyping, and Python is suitable for data science and machine learning. 1.PHP is used for dynamic web development, with simple syntax and suitable for rapid development. 2. Python has concise syntax, is suitable for multiple fields, and has a strong library ecosystem.

To run Python code in Sublime Text, you need to install the Python plug-in first, then create a .py file and write the code, and finally press Ctrl B to run the code, and the output will be displayed in the console.

PHP originated in 1994 and was developed by RasmusLerdorf. It was originally used to track website visitors and gradually evolved into a server-side scripting language and was widely used in web development. Python was developed by Guidovan Rossum in the late 1980s and was first released in 1991. It emphasizes code readability and simplicity, and is suitable for scientific computing, data analysis and other fields.

Python is more suitable for beginners, with a smooth learning curve and concise syntax; JavaScript is suitable for front-end development, with a steep learning curve and flexible syntax. 1. Python syntax is intuitive and suitable for data science and back-end development. 2. JavaScript is flexible and widely used in front-end and server-side programming.

Golang is better than Python in terms of performance and scalability. 1) Golang's compilation-type characteristics and efficient concurrency model make it perform well in high concurrency scenarios. 2) Python, as an interpreted language, executes slowly, but can optimize performance through tools such as Cython.

Writing code in Visual Studio Code (VSCode) is simple and easy to use. Just install VSCode, create a project, select a language, create a file, write code, save and run it. The advantages of VSCode include cross-platform, free and open source, powerful features, rich extensions, and lightweight and fast.

Running Python code in Notepad requires the Python executable and NppExec plug-in to be installed. After installing Python and adding PATH to it, configure the command "python" and the parameter "{CURRENT_DIRECTORY}{FILE_NAME}" in the NppExec plug-in to run Python code in Notepad through the shortcut key "F6".
