Choose Best Python Compiler For Your Machine Learning Project – Detailed Overview

Akshay Last Updated : 06 Jun, 2023
7 min read

This article was published as a part of the Data Science Blogathon.

Introduction

Python is one of the most famous programming languages. Python is an interpreted programming language and has different execution environments. It has a wide range of compilers to execute the python programs eg. PyCharm, PyDev, Jupyter Notebook, Visual Studio Code, and many more. The compiler is a special program that is written in a specific programming language to convert the human-readable language i.e. high-level language to machine-readable language i.e. low-level language.

Python Compiler  image

Image Source

So in this blog, I am going to cover my personal favorite top 6 python compilers that are useful for Python developers and data scientists. So let’s get started!

If you want to check more articles, click here

Python Compiler

Image Source

List of Python Compilers

Here is a wide range of compilers to execute the python programs.

  • PyCharm
  • Spyder
  • Visual Studio Code
  • PyDev
  • Jupyter Notebook
  • Sublime Text

PyCharm

It is created by Jet Brains and it is one of the best and broadly utilized Integrated Development Environment (IDE). Developers utilize this IDE for creating gainful Python and creates perfect and viable code. The PyCharm IDE assists engineers with making greater profitability and gives savvy help to the developers. It helps developers to write good quality code correctly. It saves the developers time by performing the fast compilation.

  1. Price: Free
  2. Language Supported: English
  3. Supported Platform: Microsoft Windows, Mac, Linux
  4. Developed by: Jet Brains
Python Compiler PyCharm

Image Source

Features of PyCharm

  • It supports more than 1100 plugins
  • Provides an option to write own plugin
  • It has a code navigator, code editor, and fast & safe refactoring
  • It provides developers with an option to detect errors, fast fix errors and to complete auto code, etc.
  • It can be easily integrated with an IPython notebook.
  • It provides functionality to integrate debugging, deployments, testing, etc

Pros

  • It is very easy to use
  • Installation is very easy
  • Very helpful and supportive community

Cons

  • In the case of large data, it becomes slow
  • Not beginners friendly

Check the official page here: PyCharm

Spyder

It is another open-source IDE that can be utilized as a python compiler for python code advancement. The principle justification for building up this IDE is to give a huge scientific environment to python, which researchers and developers use. It includes features such as editing, debugging and has an API and plugin system. It is a blend of different Python stacks like NumPy, pandas, IPython, and so on, and is delivered under the MIT permit.

  1. Price: Free
  2. Language Supported: English
  3. Supported Platform: Microsoft Windows, Mac, Linux
  4. Developed by: Pierre Raybaut
Spyder Python Compiler

Image Source

Features

  • Provides auto-code completion and syntax highlighting feature
  • It supports multiple IPython consoles
  • With the help of GUI, it can edit and explore the variables
  • It provides a debugger to check the step by step execution
  • User can see the command history in the console

Pros

  • It is open-source and free
  • To improve the functionalities, it supports additional plugins
  • Provide support for strong debugger

Cons

  • The very old style interface
  • Difficult to find the terminal in this compiler

Check the official page here: Spyder

Visual Studio Code

This IDE is developed by Microsoft in 2015. It is free and open-source. It is lightweight and very powerful. It provides features such as unit testing, debugging, fast code completion, and more. It has a large number of extensions for different uses, for example, if you want to use C++, then install C++ extension, similarly install the different extension for different programming languages.

  1. Price: Free
  2. Language Supported: English
  3. Supported Platform: Microsoft Windows, Mac, Linux
  4. Developed by: Microsoft
Visual Studio Code

Image Source

Features

  • It has an inbuilt Command Line Interface
  • It has an integrated Git that allows users to commit, add, pull and push changes to a remote Git repository utilizing a straightforward GUI.
  • It has an API for debugging
  • Visual Studio Code Live Share is an element that empowers you to share your VS Code case, and permit somebody distant to control and run different things like debuggers.

Pros

  • It supports multiple programming languages eg. Python, C/C++, Java etc
  • Provides auto-code feature
  • It has built-in plugins

Cons

  • Sometimes, it crashes and shutdowns
  • The interface isn’t all that great and it required some time to begin

Check the official page here: Visual Studio Code

PyDev

PyDev is an IDE for Eclipse and is utilized in the advancement of Python, JPython, and IronPython. It is presently the best Python environment for coding. For as long as 8 years, the community is dealing with it to improve it for Python clients.

PyDev is free and open-source, people can introduce it from the web and begin utilizing it. It is perhaps the most usable IDE and liked by a large portion of developers.

  1. Price: Free
  2. Language Supported: English
  3. Supported Platform: Microsoft Windows, Mac, Linux
  4. Developed by: Appcelerator
PyDev

Image Source

Features

  • It provides functionalities such as debugging, code analysis, refactoring, etc
  • Provides error parsing, folding of code, and syntax for highlighting code.
  • It supports black formatted, virtual environment, PyLint, etc
  • Offers help for PyLint execution, application keys, online screen, Unittest advancement, graphical interfaces, and f-string evaluation

Pros

  • It supports Jython, Django Framework, etc
  • It offers supports for different programming languages like Python, Java, C/C++, etc
  • Provides auto-code completion and syntax highlighting feature

Cons

  • When multiple plugins are installed, the performance of PyDev diminishes

Check the official page here: PyDev

Jupyter Notebook

It is one of the most widely used python IDE for data science and machine learning environments. It is an open-source and web-based interactive environment. It permits us to create and share documents that have mathematical equations, plots, visuals, live code, and readable text. It supports many languages such as Python, R, Julia, etc but it is mostly used for Python.

  1. Price: Free
  2. Language Supported: English
  3. Supported Platform: Microsoft Windows, Mac, Linux
  4. Developed by: Brian Granger, Fernando Perez
Jupyter Notebook

Image Source

Features

  • Easy collaboration
  • Provides the option to download jupyter notebook in many formats like PDF, HTML file etc
  • It provides presentation mode
  • Provides easy editing
  • Provides cell level and selection code execution that is helpful for data science

Pros

  • It is beginners friendly and perfect for data science newbies.
  • It supports multiple languages like Python, R, Julia, and many more
  • With the help of data visualization libraries such as matpotlib and seaborn, we can visualize graphs within the IDE
  • It has a browser-based interface

Cons

  • It doesn’t provide a good security
  • It doesn’t provide code correction
  • Not effective in real-world projects – use only for dummy projects

Check the official page here: Jupyter Notebook

Sublime Text

Sublime Text is an IDE that comes in two renditions for example free and paid. The paid variant contains additional highlights features. It has different plugins and is kept up under free software licenses. It upholds numerous other programming languages, for instance, Java, C/C++, and so on not just Python.

Sublime Text is very quick when contrasted with other text compilers. One can likewise introduce different bundles like debugger, code linting, and code completion.

  1. Price: Free
  2. Language Supported: English
  3. Supported Platform: Microsoft Windows, Mac, Linux
  4. Developed by: Jon Skinner
Sublime Text

Image Source

Features

  • Provides option for customization
  • Instant switch between different projects
  • It provides split editing
  • It has a Goto Anything option, that allows user to jump the cursor wherever they want
  • It supports multiple languages such as Python, java, C/C++
  • It provides Command Palette
  • It has a distraction-free mode too

Pros

  • Very interactive interface – very handy for beginners
  • Provide plugin which is very helpful in debugging and tet highlighting.
  • Provide time to time suggestion for accurate syntax
  • It provides a free version
  • Working on different projects are possible at the same time

Cons

  • Not wors well in case of large documents
  • One of the most annoying things is, it doesn’t save documents automatically.
  • At some time, plugins are difficult to handle.

Check the official page here: Sublime Text

Frequently Asked Questions

Q1. Which compiler is best for Python?

A. Python is an interpreted language, and it does not require compilation like traditional compiled languages. However, popular Python interpreters include CPython (the reference implementation), PyPy (a just-in-time compiler), and Anaconda (a distribution that includes the conda package manager and various scientific computing libraries).

Q2. What is a Python compiler?

A. In the context of Python, a compiler is a software tool that translates Python code written in high-level human-readable form into low-level machine code or bytecode that can be executed directly by a computer. The compiled code is typically more efficient and faster to execute than the original Python source code. Python compilers can optimize the code, perform static type checking, and generate standalone executable files or bytecode files that can be run on a specific platform or within a virtual machine. Examples of Python compilers include Cython, Nuitka, and Shed Skin.

Conclusion

So in this article, we have covered the top 6 Python Compilers For Data Scientists in 2021. I hope you learn something from this blog and it will turn out best for your project. Thanks for reading and your patience. Good luck!

You can check my articles here: Articles

Email id: gakshay1210@gmail.com

Connect me on LinkedIn: LinkedIn

The media shown in this article are not owned by Analytics Vidhya and is used at the Author’s discretion. 

Responses From Readers

Clear

Suresh
Suresh

Disparity between title and content . Title says compiler but talks of IDEs. So please change the title . Misleading

jago
jago

the website is very good Great article.

whoever
whoever

This is laughable. IDEs are called compilers

Congratulations, You Did It!
Well Done on Completing Your Learning Journey. Stay curious and keep exploring!

We use cookies essential for this site to function well. Please click to help us improve its usefulness with additional cookies. Learn about our use of cookies in our Privacy Policy & Cookies Policy.

Show details