An Integrated Development Environment (IDE) serves as a comprehensive software application, offering computer programmers a wide array of software development tools. Typically, IDEs encompass a source code editor, build automation tools, and a debugger. Most modern IDEs boast intelligent code completion features. This article aims to explore the top Python IDEs currently accessible and prevalent in the market.

Understanding IDEs:

An IDE acts as a unifying platform for programmers, amalgamating various facets of crafting a computer program.

IDEs substantially augment programmer efficiency by integrating functionalities like source code editing, executable building, and debugging.

Differentiating IDEs and Code Editors:

IDEs and code editors function as tools employed by software developers for code writing and editing purposes.

IDEs, denoting Integrated Development Environments, generally offer a more extensive feature set, encompassing tools for debugging, code building, and deployment.

On the other hand, code editors maintain a more streamlined focus on code editing. Developers often interchangeably use IDEs and code editors, depending on the specific task at hand.

IDE vs. Code Editor: Distinct Characteristics:

An Integrated Development Environment (IDE) stands as a software application furnishing an array of tools and resources to facilitate code writing and debugging. Typically, an IDE encompasses:

A source code editor

A compiler or interpreter

An integrated debugger

A graphical user interface (GUI)

Contrarily, a code editor represents a text editor program primarily tailored for manipulating source code. It generally includes features aiding in code development, such as syntax highlighting, code completion, and debugging functionalities.

The primary discrepancy between an IDE and a code editor resides in the presence of a graphical user interface (GUI) in the former and its absence in the latter. Additionally, an IDE incorporates attributes like code completion, syntax highlighting, and debugging, which are notably absent in a code editor.

Code editors are typically simpler than IDEs, lacking many other components present in IDEs. Hence, experienced developers often prefer code editors, enabling them to manually configure their development environment to their preferences.

Top Python IDEs

Now that we’ve covered the concept of Integrated Development Environments, let’s explore a few renowned Python IDEs. It’s important to note that we won’t be ranking these IDEs arbitrarily. We firmly believe that each IDE serves distinct purposes tailored to different needs.

However, our aim is to guide you in selecting the most suitable IDE according to your specific requirements. This approach aims to dispel any uncertainties you might have, empowering you to choose an IDE that perfectly aligns with your objectives.


IDLE, short for Integrated Development and Learning Environment, comes as a default editor packaged with Python installations.

This particular IDE caters well to novice developers, offering ease of use and simplicity.

IDLE operates seamlessly across Mac OS, Windows, and Linux platforms.

Price: Free

Key Features of IDLE:

Multi-file search capabilities

Interactive interpreter equipped with syntax highlighting and error messaging

Intelligent indentation alongside basic text editing functions

Robust debugging tools

Ideal Python IDE for Windows


PyCharm, developed by JetBrains, stands as a highly favored Python IDE among professional developers, facilitating the management of extensive Python projects.

This IDE comes with a freemium model.

Key Features of PyCharm:

Support for JavaScript, CSS, and TypeScript

Intuitive code navigation tools

Quick and secure code restructuring options

Direct database access from the IDE

Great Python IDE for Windows

Visual Studio Code

Visual Studio Code, an open-source and free IDE crafted by Microsoft, boasts significant popularity within Python development circles.

VS Code impresses with its lightweight nature while offering powerful functionalities akin to some premium IDEs.

Price: Free

Key Features of Visual Studio Code:

Exceptional smart code completion based on diverse parameters

Seamless integration with Git

In-built code debugging capabilities

Extensive extension options for added features like code linting, themes, and more services

Sublime Text 3

Sublime Text stands as a highly favored code editor, boasting extensive language support, including Python.

This editor is celebrated for its exceptional customizability, offering rapid development speeds coupled with unwavering reliability.

Price: Free

Key Features of Sublime Text 3:

Comprehensive syntax highlighting

Personalized user commands enhancing IDE usability

Effective management of project directories

Support for supplementary packages catering to web and scientific Python development

An excellent Python IDE option for Windows


Atom, an open-source code editor curated by GitHub, stands as a robust supporter of Python development.

Similar to Sublime Text, Atom prioritizes speed and usability, providing a nearly equivalent feature set.

Price: Free

Key Features of Atom:

Extensive support for numerous plugins

Intelligent auto-completion capabilities

Custom command support for seamless user-editor interactions

Facilitates cross-platform development


Jupyter holds widespread usage within the domain of data science, lauded for its user-friendly interface and interactive functionalities enabling live code sharing and visualization.

Price: Free

Key Features of Jupyter:

Empowers numerical computations and facilitates the machine learning workflow

Integrates code, text, and visuals for an immersive user experience

Seamless incorporation of data science libraries such as NumPy, Pandas, and Matplotlib


Spyder, an open-source IDE, finds widespread utilization within the scientific development sphere.

Included in the Anaconda distribution renowned for its prowess in data science and machine learning, Spyder stands as a go-to choice.

Price: Free

Key Features of Spyder:

Automatic code completion and splitting functionalities

Extensive support for plotting diverse charts and data manipulation tasks

Seamless integration with data science libraries like NumPy, Pandas, and Matplotlib

An exceptional Python IDE catering to Windows users


PyDev, recognized for its robust Python interpreter, functions as a third-party plugin for the Eclipse IDE.

Its flexibility renders it a preferred open-source IDE among developers.

Price: Free

Key Features of PyDev:

Integration with Django, along with auto code completion and code coverage functionalities

Comprehensive support for type hinting, refactoring, debugging, and code analysis

Strong backing for Python web development tasks


Thonny, an IDE designed with an emphasis on teaching and learning Python programming, offers a user-friendly environment.

Price: Free

Key Features of Thonny:

Simplified debugger capabilities

Function evaluation tools

Automatic detection of syntax errors

Detailed display of variables used within Python programs or projects


Wing, a well-known IDE, fosters a highly productive development environment, ensuring seamless coding experiences.

Offering a 30-day trial version, Wing allows developers to explore and comprehend its feature set.

Price: US $95 – US$179 for a commercial license

Key Features of Wing:

Swift feedback mechanisms for Python code

Comprehensive support for test-driven development, encompassing unit tests, Pytest, and Django testing framework

Facilitation of remote development tasks

Auto code completion functionalities available


Vim, a versatile open-source terminal-based text editor, represents an evolution of the Vi text editor, aptly named Vi Improved.


Selecting the right code editor for Python development can be a nuanced decision. Emacs, encompassing a set of macro extensions for various code editors, found adoption into the GNU project in the early 1980s under the stewardship of Richard Stallman.


Dreamweaver stands out as one of the premier web development IDE tools, providing comprehensive support for creating, publishing, and managing websites. Its versatility extends to seamless uploads on any web server.


Functioning as a full-featured Python editor and IDE, Eric is constructed on the cross-platform Qt GUI development framework. Its notable strength lies in its excellent plug-in management support.

Visual Studio:

Microsoft’s Visual Studio serves as an integrated development environment, catering to the creation of diverse computer programs, including web services, web apps, and mobile applications.


Pyscripter encapsulates all the anticipated features of a modern Python IDE within a lightweight package. Natively compiled for Windows, it strikes a balance between minimal memory consumption and maximum performance.


Acknowledged as one of the premier IDEs for Python, Rodeo has been specifically designed for data science-related tasks. This includes extracting data from various sources, plotting, and supporting cross-platform functionality. Additionally, Rodeo doubles as an interactive IDE for experimental endeavors.

What Does Python Programming Entail?

Python programming represents an object-oriented, high-level programming language renowned for its dynamic semantics. Its appeal lies in the fusion of high-level built-in data structures with dynamic typing and binding, making it a compelling choice for application development. Additionally, Python serves as a scripting language, seamlessly connecting existing components with its user-friendly syntax, which contributes to reduced program maintenance costs.

Python places a strong emphasis on program modularity and code reuse. Its interpreter and extensive standard library, available in binary form or source, are freely distributable, further enhancing its accessibility.

Why Opt for Python?

Python garners favor among programmers due to its heightened productivity. With no compilation step required, the edit-test-debug cycle operates swiftly. Notably, debugging Python programs proves to be a straightforward task. In the event of an error, instead of causing a segmentation fault, the interpreter identifies the issue, raises an exception, and prints a stack trace.

The source-level debugger facilitates inspection of local and global variables, setting breakpoints, evaluating arbitrary expressions, and more. This debugger, exclusively written in Python, underscores Python’s introspective capabilities.

Moreover, the most expedient method for debugging involves adding a few print statements to the source code. This swift edit-test-debug cycle streamlines the process, enhancing its simplicity and effectiveness.

Acquiring Python:

Installing Python on your PC involves a series of steps to ensure a seamless setup process.

  • Choose the Python Version: Begin by selecting the appropriate version of Python for download. Opt for the full installer and proceed with the installation.
  • Download and Install Python Executable: Download the Python Executable Installer and initiate the installation process on your system.
  • Installation Process Completion: Allow the installation to progress until it successfully concludes. This step may require some patience.
  • Verification of Python Installation on Windows: Once the installation is finalized, verify that Python has been successfully installed on your Windows system.
  • Running Python: Run the Python application to confirm its functionality and proper installation.
  • Pip Verification: Ensure that Pip, the package installer for Python, has been successfully installed and is operational.

Python Shell, often referred to as REPL (Read, Evaluate, Print, Loop), provides a command-line interface to execute individual Python commands and display their results. This interactive Python shell is essential for testing code snippets and conducting quick evaluations. Easily accessible through a Google extension, Python Shell reads commands, evaluates them, prints the results, and loops back for further execution.

Understanding the Basics of Python:

To delve into Python programming, it’s crucial to grasp the fundamental concepts that underpin the language. Starting with the basic terminologies lays the groundwork for creating simple Python programs:

  • Foundations:
      • Syntax: Emphasizing the core programming syntax in Python.
      • Variables: Creating meaningful and concise variables.
      • Strings: Exploring string data and essential string operations.
      • Booleans: Understanding Boolean data types and truthy/falsy values.
      • Constants: Defining constants within Python programs.
      • Comments: Incorporating comments or notes within code.
      • Type Conversion: Learning how to convert values from one type to another, such as converting strings to numbers.
  • Operators:
      • Comparison Operators: Understanding and using operators to compare variables.
      • Logical Operators: Implementing logical operators to combine multiple conditions.
  • Control Flow:
    • If…Else Statements: Executing code blocks based on specific conditions.
    • Ternary Operator: Embracing the Python ternary operator for concise code.
    • Break: Exiting loops prematurely based on specific conditions.
    • Pass: Utilizing the pass statement as a placeholder within code blocks.


  • Functions:

Python Functions: Gain insights into the world of functions within Python, discovering how to define and reuse functions within your program effectively.

Keyword Arguments: Explore the utilization of keyword arguments to enhance the clarity and explicitness of function calls.

Recursive Functions: Learn the art of creating recursive functions in Python, enabling functions to call themselves within the code.

Docstrings: Understand the significance of docstrings and how to employ them effectively to document functions comprehensively.

  • Lists:

Tuples: Explore the concept of tuples, a list-like structure in Python that remains immutable throughout the program’s execution.

In-place List Sorting: Utilize the sort method to arrange elements within a list directly and in-place.

List Unpacking: Embrace the list unpacking technique to assign list elements to multiple variables simultaneously.

List Comprehensions: Master the art of generating a new list based on an existing one through list comprehensions.

Filtering List Elements with Filter: Implement the filter function to sift through and extract specific elements from a list.

Understanding Iterables: Grasp the distinction between an iterable and an iterator to enhance your understanding of Python’s data structures.

  • Dictionaries:

Introduction to Dictionaries: Familiarize yourself with dictionaries, a fundamental data type within Python known for its key-value pair structure.

Dictionary Comprehensions: Discover how to leverage dictionary comprehension to generate new dictionaries from existing ones efficiently.

  • Sets:

Introduction to Sets: Dive into the realm of sets, understanding their unique structure and effective manipulation of set elements.

Set Unions: Learn how to combine two or more sets using the union method to create a unified set.

Set Intersections: Explore techniques to intersect two or more sets, using methods like the intersection method or set intersection operator.

Symmetric Differences of Sets: Understand and identify the symmetric difference between sets, utilizing appropriate methods.

Subset Identification: Learn how to check if a set is a subset of another set, enabling efficient set comparisons and operations.

Exception Handling:

Try-Except: Explore the art of managing exceptions gracefully using the try-except statement, providing a robust approach to handling unexpected situations.

Try-Except-Else: Understand the extended capabilities of exception handling with the try-except-else statement, allowing effective control over the program flow even in the presence of exceptions.

More on Python Loops:

For-Else Statement: Gain a comprehensive understanding of the for-else statement, a valuable tool for executing specific actions after a for loop completes.

While-Else Statement: Delve into the intricacies of the while-else statement, providing insights into controlling program flow based on loop conditions.

More on Python Functions:

Unpacking Tuples: Learn the technique of unpacking tuples, enabling the assignment of individual tuple elements to multiple variables for enhanced flexibility.

Partial Functions: Explore the concept of partial functions, understanding how to define functions with predetermined arguments for simplified usage.

Type Hints: Incorporate type hints into your functions, enhancing code clarity and providing valuable information about expected parameter types.

Essential Python Learning Strategies:

Embark on your Python learning journey with these essential strategies:

Fundamental Coverage: Master the foundational aspects of Python programming.

Goal Setting: Establish clear goals for your learning journey to stay focused and motivated.

Resource Selection: Choose the best learning resources, combining interactive websites, non-interactive platforms, and video tutorials.

Library Exploration: Familiarize yourself with essential Python libraries to broaden your capabilities.

Efficient Installation: Expedite the Python installation process using tools like Anaconda for a seamless experience.

IDE Selection and Installation: Choose and install an Integrated Development Environment (IDE) that aligns with your preferences and needs.

Problem-Solving with Google: Harness the power of Google to troubleshoot coding issues and expand your problem-solving skills.

Different Ways of Coding in Python:
  • The Shell: Experience Python’s interpreter language capabilities through the Python Shell, executing code line by line for immediate results.
  • IDLE (Integrated Development and Learning Environment): Utilize the integrated IDE, IDLE, provided with Python installations, offering a user-friendly interface for code development.
  • Code Editor: Embrace the simplicity of a code editor, equipped with syntax highlighting and code formatting features, providing efficient code execution and debugger control.


Requirements for an Optimal Python Coding Environment

Several crucial elements contribute to creating an ideal Python coding environment:

A capable code editor is fundamental. This specialized text editor offers unique functionalities tailored for writing and editing code. Commonly used code editors for Python encompass Atom, Sublime Text, and Visual Studio Code.

Python interpreters are indispensable components in the Python environment. These interpreters execute Python code, enabling interactive code execution or running code from files.

A robust collection of libraries significantly enhances the environment’s capabilities. Libraries serve as repositories of code that expand Python’s functionality. Notable libraries for Python include the standard library, NumPy, and SciPy.

Effective debugging tools play a pivotal role. They are instrumental in identifying and rectifying errors within the codebase.

Version control is crucial within a Python environment. Utilizing version control systems such as Git and Subversion (SVN) ensures efficient management of code changes.

Tools are pivotal programs that aid in various development tasks, encompassing testing, debugging, and packaging. Essential Python tools comprise the Python debugger, Python package manager, and Python profiler. These tools streamline development processes and enhance overall productivity.

Classification Based on Skill Level and Objectives

Python IDEs can be categorized into two primary types: those tailored for seasoned developers and those designed for novices.

Experienced developers gravitate toward feature-rich IDEs that offer extensive customization options for their development environments.

Conversely, beginners often prefer simpler IDEs with fewer complexities, making them more approachable and user-friendly.

Among the top choices for proficient Python developers are PyCharm and Visual Studio Code. PyCharm boasts a comprehensive suite of features, including code completion, navigation, refactoring tools, and debugging capabilities. In contrast, Visual Studio Code is lauded for its simplicity, user-friendliness, and expandability.

For beginners venturing into Python, the prominent IDEs include IDLE, a straightforward tool bundled with the Python standard library, and Pythonista, a more comprehensive IDE encompassing a code editor, debugger, and interactive shell.

Online Compiler by Programiz

Programiz presents an easily accessible online compiler that simplifies code compilation without the need for software downloads or installations. This compiler swiftly compiles and runs code across various platforms, including Windows, Mac, Linux, and Android.


Vim stands out as a highly configurable text editor favored by programmers. It offers robust capabilities for file editing, search and replace operations, along with support for syntax highlighting, significantly enhancing code readability. Vim is particularly favored among seasoned coders for its robustness and flexibility, often hailed as one of the most potent text editors available.

GNU Emacs

GNU Emacs, a free and open-source text editor conceptualized by Richard Stallman in 1985, boasts extensive features. With a built-in Lisp interpreter, powerful editing tools, and support for various programming languages and file formats, it remains a versatile and powerful choice for developers.


ActivePython, a Python distribution by ActiveState, caters to Windows, Linux, and macOS X users. It includes additional packages beyond the standard Python distribution, encompassing scientific computing, data analysis, and web development tools. ActivePython is freely available for development purposes, providing a rich ecosystem for diverse Python applications.


In conclusion, the world of Python development offers a diverse array of IDEs, each tailored to specific needs and proficiency levels. Whether you’re a seasoned coder seeking a feature-rich environment or a newcomer preferring a simpler, user-friendly interface, the Python ecosystem accommodates both ends of the spectrum.

For adept developers, PyCharm and Visual Studio Code stand out, providing extensive features for comprehensive programming tasks. Meanwhile, beginners can start their Python journey with accessible tools like IDLE and Pythonista, easing their learning curve.

Beyond traditional IDEs, online compilers like Programiz offer hassle-free code execution, making coding more accessible across various platforms without the need for software installations.

Moreover, specialized text editors like Vim and GNU Emacs cater to advanced users, offering customization, powerful editing capabilities, and extensive language support.

ActivePython, a distribution by ActiveState, enriches the Python experience by extending its capabilities with additional packages, empowering developers in scientific computing, data analysis, and web development.

Regardless of your expertise or goals, the Python development environment presents an abundance of choices. This versatility ensures that whether you’re delving into coding basics or crafting intricate software, there’s an IDE or tool to suit your needs within the dynamic world of Python programming.


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