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A Concise Guide of 10+ Awesome Python Editors and How To Choose Which Editor Suits You The Best…

A concise guide to help you choose between the various development environments for python

Photo by Rob Lambert on Unsplash
Photo by Rob Lambert on Unsplash

Introduction:

The integrated Development Environment (IDE) is a software that provides comprehensive facilities for the compilation and interpretation of programs. It provides a platform for coders, enthusiasts, and developers to experiment and interpret code/programs with source code editors, automation tools, and also a debugger. An IDE can either support a single programming language like Pycharm which, is a Python exclusive, or can support a multitude of programming languages as in the case of Visual Studio Code.

Since python is a popular language of the modern era, it has a wide array of the development software available such as Pycharm, visual studio code, Jupyter notebooks, etc. Let us do a complete break down of each editor and when you should consider using them. I will be providing a more detailed guide about the editors I am more familiar with and what I consider more appealing. However, I will give a summary of some of the editors I have less experience with as well.

Note: Every editor mentioned in this article is absolutely fantastic and awesome. The list provides a concise guide based on my personal experience of using them. You may enjoy some a bit more than others. In the end, the choice to pick the editor or development environment is completely yours, and there is no wrong or right choice. Each of these has its pros and cons, and everything is amazing in its own way.


5 Editors I have the most experience with and have used a lot

1. Python IDLE

Screenshot By Author
Screenshot By Author

This is the default installation which you get after you install python on your system. This the most basic and simplistic mode for coding python programs. However, it is still a good choice for beginners to get started with programming and understanding the basics of python. It comes with features such as the python shell which is an interactive interpreter. It has extensive features such as auto-completion, syntax highlighting, smart indentation, and a basic integrated debugger.

Pros:

  • Lightweight.
  • Suitable for beginners.

Cons:

  • Not suitable for complex projects.
  • Lacks advanced features.

2. Sublime Text

Screenshot By Author
Screenshot By Author

Sublime Text is a free software with a wide community support capable of running multiple programming languages including python. You can use Sublime Text unregistered for most of the time but occasionally you will receive a pop up asking you to register to the product and acquire a license. It is highly customizable and various installations can be added to improve the quality of working of python language like debugging, auto-completion, code linting, etc.

Pros:

  • Easy to use and free for the most part.
  • Highly Customizable.
  • Compact and effective.

Cons:

  • Requires additional installations for a better experience with Python.

3. Visual Studio Code

Screenshot By Author
Screenshot By Author

Visual Studio Code is a free source-code editor made by Microsoft for Windows, Linux, and macOS. Features include support for debugging, syntax highlighting, intelligent code completion, snippets, code refactoring, and embedded Git. It supports various programming languages including python. You might need a few additional installations to get started with Python but it is quite simple. It has continuous updates and is one of the best platforms for Python and other programming languages. I use this a lot and would highly recommend it as well.

Pros:

  • Fantastic platform with continuous updates.
  • The consumption of software memory is quite low as compared to other bulky development tools.
  • Console terminal integration and easy to use.

Cons:

  • Sometimes the terminal can become a bit buggy and not run as desired.

4. Jupyter Notebooks

Screenshot By Author
Screenshot By Author

The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. The Jupyter Notebook is an absolutely fantastic option to get started with Data Science and machine learning. These Notebooks can be shared with anyone and helps to collaborate code more efficiently and effectively. I would highly recommend using the Jupyter Notebook as well because you can use each code block separately and you also have the option to use markdowns. It is widely used in lots of profitable companies.

Pros:

  • Best Platform for getting started with data science.
  • Easy to share notebooks and visualizations.
  • Availability of markdowns and other additional functionalities.

Cons:

  • Lack of powerful features which are included in some IDE’s.

5. Pycharm

Screenshot By Author
Screenshot By Author

PyCharm is an integrated development environment used in computer programming, specifically for the Python language. It is developed by the Czech company JetBrains. Since this is specifically developed for Python it has every extensive feature and additional support that you desire. These include code completion, code inspections, error-highlighting, and fixes, debugging, version control system and code refactoring. It is available on multiple platforms such as Microsoft Windows, Linux, and macOS. It comes with a free version and a paid professional version. The paid professional version has a few additional features but the free version is sufficient for most coding and programming related activities. I would highly recommend Pycharm if you have at least 8GB RAM and a high-quality PC.

Pros:

  • Stupendous in-built features.
  • Developed by a top-notch company with the best support for python.
  • Supports anaconda virtual environments as well.

Cons:

  • The main issue of Pycharm is if you have a personal computer or laptop which is low-end and does not have at least 8 GB RAM will lag a bit and is quite slow.

Other Awesome Editors:

1. Thonny Editor

Screenshot By Author
Screenshot By Author

The Thonny Integrated Development Environment (IDE), which comes pre-installed on the Linux and Linux based Platforms. However, you have to install it manually on the Windows platform. My experience with the Thonny editor is mainly on the Raspberry Pi. It is a great development environment and easy for beginners to get started with. It is extremely awesome for Raspberry Pi projects. Some of its features are syntax error highlighting, debugger, code completion, step through expression evaluation, etc.

Pros:

  • Interactive environment.
  • Suitable for Beginners.
  • Can be used for Raspberry Pi projects.

Cons:

  • Sometimes prone to issues.
  • Does not have extensive features.

2. Spyder

Screenshot By Author
Screenshot By Author

Spyder is an open-source cross-platform integrated development environment for scientific programming in the Python language. Spyder is a powerful scientific environment written in Python, for Python, and designed by and for scientists, engineers, and data analysts. It features a unique combination of the advanced editing, analysis, debugging, and profiling functionality of a comprehensive development tool with the data exploration, interactive execution, deep inspection, and beautiful visualization capabilities of a scientific package. The easy way to get up and running with Spyder on any of the Spyder supported platforms is to download it as part of the Anaconda distribution and use the conda package and environment manager to keep it and your other packages installed and up to date. The developers recommend the latest 64-bit Python 3 version unless you have specific requirements that dictate otherwise.

Pros:

  • Free Editor which you get with anaconda.
  • Nice Working Environment to see interpretations and code side by side.
  • Has a wide range of options exclusive to python.

Cons:

  • Slightly rusty interface.

3. Atom

Screenshot By Author
Screenshot By Author

This IDE is similar to the Sublime text editor with additional requirements for Python. It is highly customizable and supports many packages required for python. This is an alternative choice for sublime text. I have had less experience working with this, so I would recommend sublime text more than Atom, but viewers with more experience on both of them, do let me know which one you prefer. Some of the commonly used packages in Atom for Python development are autocomplete-python, linter-flake8, python-debugger, etc.

Pros:

  • Easy to use.
  • Supports python with additional installations.

Cons:

  • Requires additional plugins for python.
  • More suitable for git applications.

4. VIM

Screenshot By Author
Screenshot By Author

Vim is a text editor pre-installed in macOS and UNIX systems. However, you will need to download it manually on the Windows platform. Most experts absolutely love vim due to the high computation ability and lightweight compact development working environment. It is not recommended for beginners because it has a steep learning curve and you have to spend additional time and effort understanding the VIM software. You can add plugins for syntax highlighting, code completion, debugging, refactoring, etc. to Vim and use it as a Python IDE.

Pros:

  • Lightweight.
  • Effective.
  • Productive.

Cons:

  • You have to spend dedicated time to learn the entire editor and it has a steep learning curve.

5. Notepad ++

Screenshot By Author
Screenshot By Author

Notepad++ is a text and source code editor for use with Microsoft Windows. It supports tabbed editing, which allows working with multiple open files in a single window. The project’s name comes from the C increment operator. Notepad++ is distributed as free software. The notepad ++ supports many developing environments for various programming languages and can be a choice to consider. In my opinion, there are better options out there, and also you need to do some extra installations to make it fully functional for python.

Pros:

  • Easy to use similar to notepad.
  • Can be used for multiple programming languages including python.

Cons:

  • Requires some more setting up and tweaks to run python.
  • Not on my top list of recommendations since there are a lot of better options.

6. Other Online Editors

Programiz, tutorials point, w3schools, and few other websites have some awesome options for online editors. I have missed out a few but do check out all the online editors as most of them are free and fun to mess around with. If you are too lazy to go through with all the setting-up procedures of python, then jump into the world of online editors and explore them.

Pros:

  • No additional installations or extra setting up procedure.
  • Simple code can be run easily without much hassle.

Cons:

  • Not as powerful as other IDE.

Photo by Windows on Unsplash
Photo by Windows on Unsplash

Conclusion:

Phew! That was a long list. I have covered almost all of the python editors that I have worked with. However, the funny part is there is a chance I probably missed something or even lots of them because there are so many development environments out there. There are also a ton of editors that are being built to make it a more customizable and fun experience for the users. I hope this concise guide was able to help out the viewers. Feel free to let me know if I missed out something. There are so many options to choose, but don’t be overwhelmed. I would like to reiterate that there is no right or wrong choice.

In the end, Choose the editor you feel you are comfortable with and enjoy the most.

Check out my most recent article on the 5 common python errors which could be made by almost anyone and how you can avoid them.

5 Common Python Errors And How To Avoid Them!

Feel free to check out the article series that will cover the entire mastery of Machine Learning from scratch below. They will be updated consistently, and this series will cover every topic and algorithm related to machine learning with python from scratch.

Starting Your Journey to Master Machine Learning with Python

Basics of Python and its Library Modules Required for Machine Learning

Thank you all for reading this article. I wish you all a wonderful day!


References:

  1. https://www.spyder-ide.org/
  2. https://www.programiz.com/python-programming/ide
  3. https://notepad-plus-plus.org/downloads/
  4. https://www.vim.org/
  5. www.trustradius.com
  6. https://en.wikipedia.org/wiki/Wiki

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