10 Best Python IDEs and Code Editors – IQCode

Python IDEs: Top 10 Options for Developers

Python IDEs are important tools for programmers. Below we present the top 10 Python IDEs:

1. Pycharm
2. Vim
3. Spyder
5. Sublime Text 3
6. Visual Studio Code
7. Atom
8. Jupyter
9. PyDev
10. Thonny


Choosing the right Python IDE for you helps increase productivity and efficiency. The FAQs below answer some common questions about Python IDEs.


Q.1: What is the best IDE to run Python?
A: PyCharm is often considered the best Python IDE by professionals.

Q.2: Is IDE mandatory for Python?
A: No, it’s not mandatory, but using an IDE can make coding easier and quicker.

Q.3: Is PyCharm good for machine learning?
A: Yes, PyCharm has built-in support for machine learning libraries and frameworks.

Q.4: What is the most common Python IDE?
A: IDLE is the most common Python IDE, as it comes pre-installed with the Python interpreter.

Additional Resources:

If you want to learn more about Python IDEs, check out these resources:

– “Python IDEs: Top 10 Options for Developers” by Real Python: https://realpython.com/python-ides-code-editors-guide/
– “The Best Python IDEs” by PythonForBeginners: https://www.pythonforbeginners.com/ides/the-best-python-ides

Python IDEs – All You Need to Know

Python IDEs (Integrated Development Environments) are a software package that provides developers with a comprehensive set of tools in a single environment. These tools include auto code completion, syntax highlighting, easy navigation, and more, eliminating the need to install separate Python packages for different functions.

IDEs are specifically designed to work with application-specific platforms, removing obstacles faced during software development. Python IDE makes it easy to create web pages, applications, and software.

The Importance of IDEs in Python Development

IDEs play a crucial role in developing projects, regardless of the programming language. Python comes with basic tools and a text editor, but it lacks helpful features to create applications. IDEs enhance your coding, debugging, and testing process, simplifying tasks and saving time. There are various Python IDEs available, including free options for beginners, and advanced versions for larger projects. The more intelligent the IDE, the less effort required to code.

Top 10 Python IDEs

# Code to print Top 10 Python IDEs
print("1. PyCharm")
print("2. Spyder")
print("3. Jupyter Notebook")
print("4. IDLE")
print("5. Visual Studio Code")
print("6. Sublime Text")
print("7. Atom")
print("8. Wing")
print("9. Eric")
print("10. Thonny")

These are the most popular Python Integrated Development Environments (IDEs) used by developers. Each one has its own strengths and features that make it unique.

Python IDEs: Pycharm


Pycharm is a widely used cross-platform Python IDE that works with Windows, Linux and macOS. It offers a productive environment for Python developers with features like smart navigation and quick code refactoring. The IDE has three versions including the free Apache-licensed Community version, the free Educational (Edu) version and the paid proprietary Professional version.

– Direct database access from the IDE
– Large active community support
– Customizable interface for ease of use
– Plug-ins to improve project functionality

– Expensive paid version compared to other IDEs
– Slow loading times
– Requires more space than other IDEs
– Not recommended for beginners due to complicated virtual environment setup

# Code for accessing database from Pycharm IDE
import database

db = database.connect(‘localhost’)

Pycharm is a great tool for Python development, though it may not be the best fit for beginners or those with limited storage space. Additionally, loading times can be slow, but the customizable interface and active community support make it a popular choice among developers.


Vim is a free open-source IDE based on the Vi editor, pre-installed in Linux and macOS. It is highly configurable and supports non-programming applications. Vim has three modes: insert mode, command mode, and command-line mode. It provides a vibrant plugin environment and supports multiple tabs and buffers.


  • Supports multiple programming languages
  • Powerful integration functionality
  • Scripting language


  • Difficult for beginners to learn
  • Requires high effort for customization

Spyder IDE for Python

Spyder is a widely used, open-source IDE and a powerful analytical environment employed by developers in data science projects. It is included with the Anaconda distribution, making it easy to use and trace each step of your Python code. Its salient features include code auto-completion, integration with several libraries, and syntax highlighting, among others.


* Provides plugins to enhance code performance.
* Allows creation of charts for data visualization.
* Has strong community support.
* Strong debugger for tracking code and identifying errors.


* Performance may be affected when many plugins are added at once.
* Suitable only for Python language.
* Not recommended for collaborative work.

IDLE: Integrated Development and Learning Environment

IDLE is a user-friendly text editor that comes as part of the Python installation package. It is the ideal choice for beginners in Python programming.

Primary features include code coloring, smart indentation, syntax highlighting, compatibility across various operating systems, and an interactive interpreter.


  • Easily create and modify Python scripts.
  • Has an intuitive graphical interface.
  • Debugger boasts a breakpoint feature, enabling developers to debug code efficiently.
  • It is highly configurable.


  • It lacks a line numbering feature making it hard for developers to track their code.
  • Only basic code debugging features are available.
  • It does not offer data science-specific notebooks.

Overall, IDLE is an excellent text editor for learning and prototyping projects.

Sublime Text 3: A Comprehensive Python Editor

This cross-platform Python IDE supports various programming languages and offers built-in support for Flask, Django, and scientific development. It has a customizable, reliable, and powerful API. Sublime Text 3 provides many shortcuts to navigate and work with your code and offers a built-in plugin for code linters to detect errors early.


  • Highly performant with a powerful API
  • Easy to open large files
  • Effective auto-completion with colour-coded syntax definitions for better readability


  • Difficult to use the auto-comparison feature
  • Weak GIT plugin
  • License required to use all the main features

Visual Studio Code

Visual Studio Code is a lightweight, free and open-source text editor designed by Microsoft for Windows, Linux, and macOS. It offers several enhanced features such as code completion, syntax highlighting, unit testing, extensions addon, and a user-friendly interface. Developers can easily customize it to suit their preferences.


  • Easy GIT integration
  • Automatic handling of common python variable declarations and syntaxes
  • Multi-window split and auto-save functionality
  • Supports multiple languages


  • Difficult to change settings in some cases
  • High CPU usage that sometimes freezes the system
  • Slow searching

Overall, Visual Studio Code is a great choice for developers, especially those who prefer an easy-to-use and customizable text editor.

ATOM – Open-source Code Editor

Atom is a customizable text editor with a built-in file browser and package manager. It can be used for data science projects with R and Python. Atom provides auto-completion, good customer support, and allows for project collaboration. However, Atom uses a lot of RAM, stability issues may arise, and setting up Git integration can be complicated.

Jupyter Code Editor for Machine Learning and Data Science

Jupyter is a popular code editor for implementing machine learning and data science code. It supports multiple programming languages, numerical calculations, and includes rich text elements such as links and equations. You can easily run and edit your code notebooks in your browser and add breakpoints to navigate throughout the code.


  • Easy to use
  • Integrated machine learning libraries
  • Simple conversion of notebooks to PDFs
  • Easy server hosting for notebooks


  • No support for integrating third-party applications
  • No IDE integration support
  • Less secure

PyDev: An IDE for Python Development

PyDev is a popular IDE for Python development that functions as a third-party plugin of Eclipse. It offers an advanced interpreter along with code analysis and code completion functionality. PyDev also comes with key features such as debugging, syntax highlighting, multi-language support, and a comprehensive outline view.

– Efficient Django integration configuration
– Excellent web development support for Python
– User-friendly and easily comprehensible
– Supports Mypy, black formatter, and virtual environments

– Plugins may become unstable and affect development
– Unattractive UI
– Performance may degrade for large applications

Thonny: A Beginner-Friendly Python IDE

Thonny is a python-based IDE designed for beginners to learn the programming language effectively. Its features include syntax error highlighting, code completion, simple debugger, and step through expression evaluation. Thonny provides a user-friendly GUI and a detailed view of Python variables without high memory usage. However, it lacks support for templates and is not recommended for experienced developers. Furthermore, quick fixes for some issues are not available.

Choosing a Python IDE: Factors to Consider

This blog covers different Python IDEs and how to choose the most appropriate one based on your field of work, team size, collaboration needs, business scale, and knowledge of Python. No IDE is perfect, and the selection process may benefit from professional advice for a better programming experience.

Best IDEs for Python Programming

There is no single best IDE for Python programming. Each has its advantages and disadvantages, and one’s choice depends on their needs and preferences. Some popular options include PyCharm, Atom, IDLE, and Jupyter.

# Example
import pandas as pd
data = pd.read_csv("data.csv")

Python Programming and IDE

It is preferable to work with an IDE if you want a great programming experience. IDEs have built-in features and user-friendly interfaces that make coding easier. It’s a good practice to use an IDE when coding in Python or any other language.

PyCharm for Machine Learning

PyCharm is an excellent tool for Machine Learning as it provides support for various ML libraries such as NumPy, Matplotlib, and Pandas. Many big tech giants use PyCharm for their ML projects. Therefore, PyCharm is a reliable option for Machine Learning projects.

Most Common Python IDE

The most commonly used Python IDEs are Jupyter, preferred for Machine Learning tasks in Python, and Atom and PyCharm as commonly used Python code editors.

Additional Resources

For those interested in becoming a Python developer, the following resources may be helpful:

  • Python MCQs: Test your knowledge with these multiple choice questions
  • Python Projects: Get inspired with project ideas for Python developers
  • Python Interview Questions: Prepare for interviews with these commonly asked questions
  • Python Developer Salary: Learn about the average salary for Python developers in India
  • Features of Python: Discover the unique features that make Python a popular programming language
  • Difference Between Python 2 and 3: Understand the differences between the two major versions of Python
  • Python Frameworks: Explore popular frameworks for building web applications with Python
  • Python Books: Find beginner-friendly books for learning Python
  • Python Developer Resume: Get tips for creating a strong resume for Python development jobs
  • Applications of Python: Learn about the various industries and use cases where Python is applied
  • Python Developer Skills: Identify the essential skills required for a career in Python development
  • Python Libraries: Check out useful libraries for extending the capabilities of Python
  • Python vs Java: Compare Python and Java to make an informed decision about which language to learn

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