Web Applications with Python: What You Need to Know

Web Applications with Python

Web Applications with Python: What You Need to Know

Python did not get its fame by luck or chance; there are some big brands that have built their web applications with Python. Python is a programming language widely used in web applications, software development, data science, and machine learning.

Developers use Python because it’s efficient and easy to learn, and it runs on many different platforms. Python software is free to download and integrates well with various systems to improve development speed.

Advantages of Developing Web Applications with Python

The advantages of Python include:

  • Developers can easily read and understand Python programs thanks to its basic English-like syntax.
  • It makes developers more productive because they can write Python programs using fewer lines of code than many other languages.
  • It has a large standard library that contains reusable code for almost any task. That way, developers won’t have to rewrite the code.
  • Developers can easily combine Python with other popular programming languages such as Java, C, and C++.
  • There’s an active Python community, so, if you’re having trouble, you can get help from the local community.
  • If you want to learn to make web applications with Python, there are many useful resources on the Internet. For example, you can easily find videos, tutorials, and programming guides.
  • Python is compatible with many OSs such as Windows, macOS, Linux, and Unix.

There are many cases of development of web applications with Python that we can go through and that we’ll cover below.

Server-Side Web Development

Server-side web development involves the complex back-end functions that websites perform to display information to users.

For example, websites must interact with databases, communicate with other websites, and protect data when it is sent over the internet.

Python is useful for writing server-side code because it provides several libraries consisting of prewritten code to create complex back-end functions.

Developers also use a variety of Python frameworks that provide all the tools they need to make building web applications faster and easier. For example, they can create basic web applications with Python in seconds because they don’t have to write the code from scratch.

They can test it using the framework’s testing tools without relying on external testing tools.

Web Applications with Python: Automation Using Python Scripts

A scripting language is a programming language that automates tasks normally performed by humans. Python scripts are widely used by programmers to automate many everyday tasks, such as:

  • Rename a large number of files at once.
  • Convert a file to another file format.
  • Remove duplicate words from text files.
  • Perform basic mathematical operations.
  • Send a message by email.
  • Download content.
  • Perform basic registry analysis.
  • Find errors in multiple files.

Perform Data Science and Machine Learning Tasks

Automation extracts valuable insights from data while teaching computers to automatically learn from data and make accurate predictions. Data scientists use Python to perform data science tasks like:

  • Correction and removal of incorrect data, called data cleansing.
  • Extract and select various features of the data, including adding meaningful names to the data.
  • Find various statistics from that data.
  • Visualize data using tables and graphs such as line charts, bar charts, pie charts, and histograms.

Data scientists use the Python ML library to train ML models and create classifiers that can accurately classify data. People working in various fields use Python-based classifiers to perform classification tasks such as image, text, and network traffic classification, speech recognition, and facial recognition. Data scientists also use Python to perform deep learning tasks, an advanced ML technique.

Web Applications with Python: Software Development

Software developers often use Python for a variety of applications and software development tasks, such as:

  • Track bugs in software code.
  • Create software automatically.
  • Manage software projects.
  • Develop software prototypes.
  • Develop desktop applications using graphical user interface (GUI) libraries.
  • Evolve simple text games into more complex video games.

Software Test Automation

This software testing is the process of checking whether the actual results of the software match the expected results to ensure that the software is free of bugs.

  • Developers use Python unit testing frameworks such as Unittest, Robot, and PyUnit to test the functionality they write.
  • Software testers use Python to write test cases for various scenarios. For example, they use it to test the user interface of web applications, various software components, and new features.

Various tools can be used to automate the execution of test scripts. These tools are known as continuous integration and deployment (CI/CD) tools.

Software testers and developers use CI/CD tools like Travis CI and Jenkins to automate testing.

Web Applications with Python
Web Applications with Python

Web Applications with Python: What Are Python Libraries?

A library is a set of commonly used code that developers can include in their web applications with Python to avoid having to rewrite the code.

By default, Python includes a standard library that contains a large number of reusable functions.

What Are the Most Popular Python Libraries?

There are over 137,000 Python libraries available for a variety of applications, including web development, data science, and machine learning (ML).

  • Matplotlib

Developers use Matplotlib to display data in high-quality two-dimensional and three-dimensional (2D and 3D) plots. It is often used in scientific applications. With Matplotlib, you can visualize data by displaying it in a variety of graphs, such as bar and line graphs. You can also draw multiple graphics at once, making it portable between platforms.

  • Panda

Panda provides flexible and optimized data structures that can be used to manipulate time series data and structured data such as tables and matrices. For example, you can use Panda to read, write, merge, filter, and group data. Lots of people use it for data science, data analysis, and ML tasks.

  • NumPy

NumPy is a popular library that allows developers to easily create and manage matrices, manipulate logical forms, and perform linear algebra operations. NumPy supports integration into multiple languages such as C and C++.

  • Requests

The Requests library provides useful functions needed for web development. You can use it to send HTTP requests, add headers, URL parameters and data, and perform many other tasks when communicating with web applications.

  • OpenCVPython

OpenCV-Python is a library that developers use to process images for machine vision applications. It provides many functions for image processing tasks, such as simultaneously reading and writing images, creating 3D environments from 2D environments, and capturing, and analyzing video images.

  • Keras

Keras is a deep neural network library for Python with great support for data processing, data visualization, and more. Keras supports many neural networks. It has a modular structure that provides flexibility to write innovative applications.

Web Applications with Python: What Is a Python Framework?

A Python framework is a collection of packages and modules. A module is a group of related code, and a package is a group of modules.

Developers can use Python frameworks to build Python applications faster because they don’t have to worry about the lower-level details of how web applications communicate, or how Python makes them run faster.

Python has two types of frameworks:

Full-stack frameworks include almost everything needed to build large applications. A microframework is a basic framework that provides minimal functionality for building simple Python applications. It also provides extensions if the application requires more complex functionality.

What Are the Most Famous Python Frameworks?

Developers can use a variety of Python frameworks to increase development productivity, including:

  • Django

Django is one of the most widely used full-featured Python web frameworks for developing large-scale web applications. It provides several useful features, including a web server for development and testing, a template engine for building front-end sites, and various security mechanisms.

  • Flask

Flask is a micro-framework for developing small web applications. Its features include strong community support, well-written documentation, a template engine, unit tests, and an integrated web server. It also provides extensions for authentication support, database mapping layer, and network security.

  • TurboGears

TurboGears is a framework designed to make building web applications faster and easier. Here are some of its key features:

  • Specific structure of a database table.
  • Tools for the creation and management of projects.
  • A template engine for creating databases.
  • A template engine for creating arcs.
  • Network security management mechanisms.
  • Apache MXNet

Apache MXNet is a fast, flexible, and scalable deep learning framework that developers can use to build research prototypes and deep learning applications. It supports several programming languages, including Java, C, R, and Perl.

It provides a complete set of tools and libraries to support development. For example, you can find interactive machine learning (ML) books, computer vision toolkits, and deep learning models for natural language processing (NLP) such as text and speech.

  • PyTorch

PyTorch is a machine learning framework based on the Torch library, another open source machine learning library. Developers use it in applications like NLP, robotics, and computer vision to find meaningful information in images and videos. They also use it to run these applications on the CPU and GPU.


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