What are the Features of Python?

Last updated: February 8, 2026Reviewed date: February 8, 2026Reading time: 11 min read
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Python is a programming language that is widely used in web applications, software development, data science, and machine learning (ML). Developers use Python because it is efficient and easy to learn and can run on many different platforms. Python software is free to download, integrates...

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Article Summary

Python is a programming language that is widely used in web applications, software development, data science, and machine learning (ML). Developers use Python because it is efficient and easy to learn and can run on many different platforms. Python software is free to download, integrates well with all types of systems, and increases development speed. What are the benefits of Python? Benefits of Python include:...

Key Takeaways

  • This article explains What are the benefits of Python? in simple medical language.
  • This article explains How is Python used? in simple medical language.
  • This article explains What is the history of Python? in simple medical language.
  • This article explains What are the features of Python? in simple medical language.
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  • New weakness, severe pain, high fever, or symptoms after a serious injury.
  • Any symptom that feels urgent, unusual, or unsafe for the patient.
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2

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Definition

Python is a programming language that is widely used in web applications, software development, data science, and machine learning (ML). Developers use Python because it is efficient and easy to learn and can run on many different platforms. Python software is free to download, integrates well with all types of systems, and increases development speed.

What are the benefits of Python?

Benefits of Python include:

  • Developers can easily read and understand a Python program because it has basic, English-like syntax.
  • Python makes developers more productive because they can write a Python program using fewer lines of code compared to many other languages.
  • Python has a large standard library that contains reusable codes for almost any task. As a result, developers do not have to write code from scratch.
  • Developers can easily use Python with other popular programming languages such as Java, C, and C++.
  • The active Python community includes millions of supportive developers around the globe. If you face an issue, you can get quick support from the community.
  • Plenty of helpful resources are available on the internet if you want to learn Python. For example, you can easily find videos, tutorials, documentation, and developer guides.
  • Python is portable across different computer operating systems such as Windows, macOS, Linux, and Unix.

How is Python used?

The Python language has several use cases in application development, including the following examples:

Server-side web development

Server-side web development includes the complex backend functions that websites perform to display information to the user. For example, websites must interact with databases, talk to other websites, and protect data when sending it over the network.

Python is useful for writing server-side code because it offers many libraries that consist of prewritten code for complex backend functions. Developers also use a wide range of Python frameworks that provide all the necessary tools to build web applications faster and more easily. For example, developers can create the skeleton web application in seconds because they don’t need to write it from scratch. They can then test it using the framework’s testing tools, without depending on external testing tools.

Automation with Python scripts

A scripting language is a programming language that automates tasks that humans normally perform. Programmers widely use Python scripts to automate many day-to-day tasks such as the following:

  • Renaming a large number of files at once
  • Converting a file to another file type
  • Removing duplicate words in a text file
  • Performing basic mathematical operations
  • Sending email messages
  • Downloading content
  • Performing basic log analysis
  • Finding errors in multiple files

Data science and machine learning

Data science is extracting valuable knowledge from data, and machine learning (ML) teaches computers to automatically learn from the data and make accurate predictions. Data scientists use Python for data science tasks such as the following:

  • Fixing and removing incorrect data, which is known as data cleaning
  • Extracting and selecting various features of data
  • Data labeling, which is adding meaningful names for the data
  • Finding different statistics from data
  • Visualizing data by using charts and graphs such as line charts, bar graphs, histograms, and pie charts
Data scientists use Python ML libraries to train ML models and build classifiers that accurately classify data. People in different fields use Python-based classifiers to do classification tasks such as image, text, and network traffic classification; speech recognition; and facial recognition. Data scientists also use Python for deep learning, an advanced ML technique.

Software development

Software developers often use Python for different development tasks and software applications such as the following:

  • Keeping track of bugs in the software code
  • Automatically building the software
  • Handling software project management
  • Developing software prototypes
  • Developing desktop applications using Graphical User Interface (GUI) libraries
  • Developing simple text-based games to more complex video games

Software test automation

Software testing is the process of checking whether the actual results from the software match the expected results to ensure that the software is error-free.

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

Developers can use several tools to automatically run test scripts. These tools are known as Continuous Integration/Continuous Deployment (CI/CD) tools. Software testers and developers use CI/CD tools such as Travis CI and Jenkins to automate tests. The CI/CD tool automatically runs the Python test scripts and reports the test results whenever developers introduce new code changes.

What is the history of Python?

Guido Van Rossum, a computer programmer in the Netherlands, created Python. He started it in 1989 at Centrum Wiskunde & Informatica (CWI), initially as a hobby project to stay busy during Christmastime. The name for the language was inspired by the BBC TV show Monty Python’s Flying Circus because Guido Van Rossum was a big fan of the show.

History of Python releases

  • Guido Van Rossum published the first version of the Python code (version 0.9.0) in 1991. It already included good features such as some data types and functions for error handling.
  • Python 1.0 was released in 1994 with new functions to easily process a list of data, such as map, filter, and reduce.
  • Python 2.0 was released on October 16, 2000, with new useful features for programmers, such as support for Unicode characters and a shorter way to loop through a list.
  • On December 3, 2008, Python 3.0 was released. It included features such as the print function and more support for number division and error handling.

What are the features of Python?

Following features of the Python programming language make it unique:

An interpreted language

Python is an interpreted language, which means it directly runs the code line by line. If there are errors in the program code, it will stop running. Therefore, programmers can quickly find errors in the code.

An easy-to-use language

Python uses English-like words. Unlike other programming languages, Python doesn’t use curly brackets. Instead, it uses indentation.

A dynamically typed language

Programmers do not have to declare variable types when writing code because Python determines them at runtime. Because of this, you can write Python programs more quickly.

A high-level language

Python is closer to human languages than some other programming languages. Therefore, programmers do not have to worry about its underlying functionalities such as architecture and memory management.

An object-oriented language

Python considers everything to be an object, but it also supports other types of programming such as structured and functional programming.

What are Python libraries?

A library is a collection of frequently used codes that developers can include in their Python programs to avoid writing code from scratch. By default, Python comes with the Standard Library, which contains a lot of reusable functions. In addition, more than 137,000 Python libraries are available for various applications, including web development, data science, and machine learning (ML).

Matplotlib

Developers use Matplotlib to plot data in high-quality two- and three-dimensional (2D and 3D) graphics. It is often used in scientific applications. With Matplotlib, you can visualize data by displaying it in different charts such as bar charts and line charts. You can also plot multiple charts at once, and the graphics are portable across all platforms.

Pandas

Pandas provides optimized and flexible data structures that you can use to manipulate time-series data and structured data, such as tables and arrays. For example, you can use Pandas to read, write, merge, filter, and group data. Many people use it for data science, data analysis, and ML tasks.

NumPy

NumPy is a popular library that developers use to easily create and manage arrays, manipulate logical shapes, and perform linear algebra operations. NumPy supports integration with many languages such as C and C++.

Requests

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

OpenCV-Python

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

Keras

Keras is Python’s deep neural network library with excellent support for data processing, visualization and much more. Keras supports many neural networks. It has a modular structure that offers flexibility in writing innovation applications.

What are Python frameworks?

A Python framework is a collection of packages and modules. A module is a set of related code, and a package is a set of modules. Developers can use Python frameworks to build Python applications more quickly because they do not have to worry about low-level details such as how communications happen in the web application or how Python will make the program faster. Python has two types of frameworks:

  • A full-stack framework includes almost everything that is required to build a large application.
  • A microframework is a basic framework that provides minimal functionalities for building simple Python applications. It also provides extensions if applications need more sophisticated functions.

Developers can use multiple Python frameworks to make their development efficient, including the following frameworks:

Django

Django is one of the most widely used full-stack 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 to build the website frontend, 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 testing, and a built-in web server. It also provides extensions for validation support, database mapping layers, and web security.

TurboGears

TurboGears is a framework designed to build web applications faster and easier. These are some of its popular features:

  • A specific database table structure
  • Tools for creating and managing projects
  • A template engine to build the databases
  • A template engine to build the frontend
  • Mechanisms to handle web security

Apache MXNet

Apache MXNet is a fast, flexible, and scalable deep learning framework that developers use to build research prototypes and deep learning applications. It supports multiple programming languages, including Java, C++, R, and Perl. It provides a rich set of tools and libraries to support development. For example, you can find an interactive machine learning (ML) book, computer vision toolkits, and deep learning models for Natural Language Processing (NLP), which processes natural language such as text and speech.

PyTorch

PyTorch is a framework for ML that has been built on top of the Torch library, which is another open-source ML library.  Developers use it for applications such as NLP, robotics, and computer vision, finding meaningful information in images and videos. They also use it to run those applications in CPUs and GPUs.

What are Python IDEs?

An integrated development environment (IDE) is software that gives developers the tools they need to write, edit, test, and debug code in one place.

PyCharm

JetBrains, a Czech company that develops software tools, created PyCharm. It has a free community edition that is suitable for small Python applications and a paid professional edition that is suitable for building large-scale Python applications, with the following full set of features:

  • Automatic code completion and code inspection
  • Error handling and quick fixes
  • Code cleaning without changing the functionality
  • Support for web application frameworks such as Django and Flask
  • Support for other programming languages, such as JavaScript, CoffeeScript, TypeScript, AngularJS, and Node
  • Scientific tools and libraries such as Matplotlib and NumPy
  • Ability to run, debug, test, and deploy applications in remote virtual machines
  • A debugger to find errors in the code, a profiler to identify performance issues in the code, and a test runner for running unit tests
  • Support for databases

IDLE

Integrated Development and Learning Environment (IDLE) is the Python IDE installed by default. It has been developed only with Python using the Tkinter GUI toolkit and offers the following features:
  • Works across many operating systems such as Windows, Unix, and macOS
  • Provides a shell window to run commands and display the output
  • Offers a multiple-window text editor that provides code syntax highlighting and automatic code completion
  • Has its own debugger

Spyder

Spyder is an open-source IDE that many scientists and data analysts use. It provides a comprehensive development experience with features for advanced data analysis, data visualization, and debugging. It also includes the following features:

  • A rich code editor that supports multiple languages
  • An interactive IPython console
  • A basic debugger
  • Scientific libraries such as Matplotlib, SciPy, and NumPy
  • Ability to explore variables in the code
  • Ability to view documentation in real time

Atom

Atom is a free editor developed by GitHub that supports coding in many programming languages, including Python. Using Atom, developers can directly work with GitHub, the website where you can save your code centrally. Atom offers the following features:

  • Ability to use with many operating systems
  • Easy installation or creation of new packages
  • Faster automatic code completion
  • Ability to search files and projects
  • Easy customization of the interface

What are Python SDKs?

A software development kit (SDK) is a collection of software tools that developers can use to create software applications in a particular language. Most SDKs are specific to different hardware platforms and operating systems. Python SDKs include many tools such as libraries, code samples, and developer guides that developers find helpful when writing applications.

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A simple rural-patient checklist to help you explain symptoms clearly, ask better questions, and avoid unsafe self-treatment.

Safety note: This is not a prescription or diagnosis. For severe symptoms, pregnancy danger signs, children with serious illness, chest pain, breathing difficulty, stroke-like weakness, or major injury, seek urgent care.

Which doctor may help?

Start with a registered doctor or the nearest qualified health center.

What to tell the doctor

  • Write when the problem started and how it changed.
  • Bring old prescriptions, investigation reports, and current medicines.
  • Write allergies, pregnancy status, diabetes, kidney/liver disease, and major past illnesses.
  • Bring one family member if the patient is weak, elderly, confused, or a child.

Questions to ask

  • What is the most likely cause of my symptoms?
  • Which danger signs mean I should go to hospital quickly?
  • Which tests are necessary now, and which can wait?
  • How should I take medicines safely and what side effects should I watch for?
  • When should I come for follow-up?

Tests to discuss

  • Vital signs: temperature, pulse, blood pressure, oxygen saturation
  • Basic physical examination by a clinician
  • CBC, urine test, blood sugar, or imaging only when clinically needed

Avoid these mistakes

  • Do not use antibiotics, steroid tablets/injections, or strong painkillers without proper medical advice.
  • Do not hide pregnancy, kidney disease, ulcer, allergy, or blood thinner use.
  • Do not delay emergency care when danger signs are present.

Medicine safety and first-aid guide

This section is for patient education only. It does not replace a doctor, pharmacist, or emergency care.

Safe first steps

  • Rest, drink safe water, and observe symptoms carefully.
  • Keep a written note of symptoms, duration, temperature, medicines already taken, and allergy history.
  • Seek medical care quickly if symptoms are severe, worsening, or unusual for the patient.

OTC medicine safety

  • For mild pain or fever, ask a registered pharmacist or doctor before using common over-the-counter pain/fever medicines.
  • Do not combine multiple pain medicines without advice, especially if you have kidney disease, liver disease, stomach ulcer, asthma, pregnancy, or take blood thinners.
  • Do not give adult medicines to children unless a qualified clinician advises it.

Avoid these mistakes

  • Do not start antibiotics without a proper medical decision.
  • Do not use steroid tablets or injections casually for quick relief.
  • Do not delay emergency care because of home remedies.

Get urgent help if

  • Severe symptoms, confusion, fainting, breathing difficulty, chest pain, severe dehydration, or sudden weakness need urgent medical care.
Medicine names, dose, and timing must be decided by a qualified clinician or pharmacist after checking age, pregnancy, allergy, other diseases, and current medicines.

For rural patients and family caregivers

Patient health record and symptom diary

Write your symptoms, medicines already taken, test results, and questions before visiting a doctor. This note stays on your device unless you print or copy it.

Doctor to discuss: Doctor / qualified healthcare provider
Tests to discuss with doctor
  • Basic vital signs: temperature, pulse, blood pressure, oxygen level if needed
  • Relevant blood, urine, imaging, or specialist tests only after clinical assessment
Questions to ask
  • What is the most likely cause of my symptoms?
  • Which warning signs mean I should go to emergency care?
  • Which tests are really needed now?
  • Which medicines are safe for my age, pregnancy status, allergy, kidney/liver/stomach condition, and current medicines?

Emergency warning signs such as chest pain, severe breathing difficulty, sudden weakness, confusion, severe dehydration, major injury, or loss of bladder/bowel control need urgent medical care. Do not wait for online information.

Safe pathway to proper treatment

Care roadmap for: What are the Features of Python?

Use this simple roadmap to understand the next safe steps. It is educational and does not replace examination by a doctor.

Go to emergency care if you notice:
  • Severe or rapidly worsening symptoms
  • Breathing difficulty, chest pain, fainting, confusion, severe weakness, major injury, or severe dehydration
Doctor / service to discuss: Qualified healthcare provider; specialist depends on symptoms and examination.
  1. Step 1

    Check danger signs first

    If danger signs are present, seek emergency care and do not wait for online information.

  2. Step 2

    Record the symptom story

    Write when symptoms started, severity, medicines already taken, allergies, pregnancy status, and test results.

  3. Step 3

    Visit a qualified clinician

    A doctor, nurse, or qualified healthcare provider can examine you and decide which tests or treatment are needed.

  4. Step 4

    Do only useful tests

    Do tests after clinical assessment. Avoid unnecessary tests, random antibiotics, or repeated medicines without diagnosis.

  5. Step 5

    Follow up and return early if worse

    If symptoms worsen, new warning signs appear, or treatment is not helping, return for review quickly.

Rural patient practical tips
  • Take a written symptom diary and all previous prescriptions/test reports.
  • Do not hide medicines already taken, even herbal or over-the-counter medicines.
  • Ask which warning signs mean urgent referral to hospital.

This roadmap is for education. A real diagnosis and treatment plan requires history, examination, and clinical judgment.

RX Patient Help

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Write your symptom story. A health professional or site editor can review it before any answer is prepared. This box is not for emergency care.

Emergency first: Severe chest pain, breathing trouble, unconsciousness, stroke signs, severe injury, heavy bleeding, or rapidly worsening symptoms need urgent local medical care now.

Frequently Asked Questions

What are the benefits of Python?

Benefits of Python include: Developers can easily read and understand a Python program because it has basic, English-like syntax. Python makes developers more productive because they can write a Python program using fewer lines of code compared to many other languages. Python has a large standard library that contains reusable codes for almost any task. As a result, developers do not have to write code from scratch. Developers can easily use Python with other popular programming languages such as Java,…

How is Python used?

The Python language has several use cases in application development, including the following examples:

Server-side web development Server-side web development includes the complex backend functions that websites perform to display information to the user. For example, websites must interact with databases, talk to other websites, and protect data when sending it over the network. Python is useful for writing server-side code because it offers many libraries that consist of prewritten code for complex backend functions. Developers also use a wide range of Python frameworks that provide all the necessary tools to build web applications faster and more easily. For example, developers can create the skeleton web application in seconds because they don’t need to write it from scratch. They can then test it using the framework’s testing tools, without depending on external testing tools. Automation with Python scripts A scripting language is a programming language that automates tasks that humans normally perform. Programmers widely use Python scripts to automate many day-to-day tasks such as the following: Renaming a large number of files at once Converting a file to another file type Removing duplicate words in a text file Performing basic mathematical operations Sending email messages Downloading content Performing basic log analysis Finding errors in multiple files Data science and machine learning Data science is extracting valuable knowledge from data, and machine learning (ML) teaches computers to automatically learn from the data and make accurate predictions. Data scientists use Python for data science tasks such as the following: Fixing and removing incorrect data, which is known as data cleaning Extracting and selecting various features of data Data labeling, which is adding meaningful names for the data Finding different statistics from data Visualizing data by using charts and graphs such as line charts, bar graphs, histograms, and pie charts Data scientists use Python ML libraries to train ML models and build classifiers that accurately classify data. People in different fields use Python-based classifiers to do classification tasks such as image, text, and network traffic classification; speech recognition; and facial recognition. Data scientists also use Python for deep learning, an advanced ML technique. Software development Software developers often use Python for different development tasks and software applications such as the following: Keeping track of bugs in the software code Automatically building the software Handling software project management Developing software prototypes Developing desktop applications using Graphical User Interface (GUI) libraries Developing simple text-based games to more complex video games Software test automation Software testing is the process of checking whether the actual results from the software match the expected results to ensure that the software is error-free. Developers use Python unit test frameworks, such as Unittest, Robot, and PyUnit, to test the functions they write. Software testers use Python to write test cases for various test scenarios. For example, they use it to test the user interface of a web application, multiple software components, and new features. Developers can use several tools to automatically run test scripts. These tools are known as Continuous Integration/Continuous Deployment (CI/CD) tools. Software testers and developers use CI/CD tools such as Travis CI and Jenkins to automate tests. The CI/CD tool automatically runs the Python test scripts and reports the test results whenever developers introduce new code changes. What is the history of Python?

Guido Van Rossum, a computer programmer in the Netherlands, created Python. He started it in 1989 at Centrum Wiskunde & Informatica (CWI), initially as a hobby project to stay busy during Christmastime. The name for the language was inspired by the BBC TV show Monty Python’s Flying Circus because Guido Van Rossum was a big fan of the show.

History of Python releases Guido Van Rossum published the first version of the Python code (version 0.9.0) in 1991. It already included good features such as some data types and functions for error handling. Python 1.0 was released in 1994 with new functions to easily process a list of data, such as map, filter, and reduce. Python 2.0 was released on October 16, 2000, with new useful features for programmers, such as support for Unicode characters and a shorter way to loop through a list. On December 3, 2008, Python 3.0 was released. It included features such as the print function and more support for number division and error handling. What are the features of Python?

Following features of the Python programming language make it unique:

An interpreted language Python is an interpreted language, which means it directly runs the code line by line. If there are errors in the program code, it will stop running. Therefore, programmers can quickly find errors in the code. An easy-to-use language Python uses English-like words. Unlike other programming languages, Python doesn’t use curly brackets. Instead, it uses indentation. A dynamically typed language Programmers do not have to declare variable types when writing code because Python determines them at runtime. Because of this, you can write Python programs more quickly. A high-level language Python is closer to human languages than some other programming languages. Therefore, programmers do not have to worry about its underlying functionalities such as architecture and memory management. An object-oriented language Python considers everything to be an object, but it also supports other types of programming such as structured and functional programming. What are Python libraries?

A library is a collection of frequently used codes that developers can include in their Python programs to avoid writing code from scratch. By default, Python comes with the Standard Library, which contains a lot of reusable functions. In addition, more than 137,000 Python libraries are available for various applications, including web development, data science, and machine learning (ML).

What are the most popular Python libraries?

Matplotlib Developers use Matplotlib to plot data in high-quality two- and three-dimensional (2D and 3D) graphics. It is often used in scientific applications. With Matplotlib, you can visualize data by displaying it in different charts such as bar charts and line charts. You can also plot multiple charts at once, and the graphics are portable across all platforms. Pandas Pandas provides optimized and flexible data structures that you can use to manipulate time-series data and structured data, such as tables…

What are Python frameworks?

A Python framework is a collection of packages and modules. A module is a set of related code, and a package is a set of modules. Developers can use Python frameworks to build Python applications more quickly because they do not have to worry about low-level details such as how communications happen in the web application or how Python will make the program faster. Python has two types of frameworks: A full-stack framework includes almost everything that is required to build…

What are the most popular Python frameworks?

Developers can use multiple Python frameworks to make their development efficient, including the following frameworks: Django Django is one of the most widely used full-stack 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 to build the website frontend, 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…

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