Best Ide for Python on Mac

What is Python? It’s a simple, easy-to-learn programming language. And despite its name, pretty much everything you have seen in the movies has been written in Python! The reason for that is it’s a very readable and versatile programming language. Python was designed with the aim to be as “simple and clean” as possible and it did just that and more!

Python is a programming language that has been popularly used for developing websites and creating apps on a number of platforms including Android, PC, and Mac. It has a syntax that relies on indentation instead of enclosing code blocks in brackets or braces. Below are some free Python IDEs for Mac users worth checking out.

PyCharm. One of the best (and only) full-featured, dedicated IDEs for Python is PyCharm. Available in both paid (Professional) and free open-source (Community) editions, PyCharm installs quickly and easily on Windows, Mac OS X, and Linux platforms. Out of the box, PyCharm supports Python development directly.

What is Python IDE used for

IDE stands for Integrated Development Environment. It’s a coding tool which allows you to write, test, and debug your code in an easier way, as they typically offer code completion or code insight by highlighting, resource management, debugging tools,… And even though the IDE is a strictly defined concept, it’s starting to be redefined as other tools such as notebooks start gaining more and more features that traditionally belong to IDEs. For example, debugging your code is also possible in Jupyter Notebook.

You can probably most clearly see this evolution in the results of the Stack Overflow Developer Survey below, which also includes these new tools, next to the traditional IDEs that you might already know; They all fall under the section “development environment”.

Because of all the features that IDEs have to offer, they are extremely useful for development: they make your coding more comfortable and this is no different for data science.

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However, given the fact that there aren’t only the traditional IDEs to consider, but also new tools, such as notebooks, you might be wondering which development environment to use when you’re just starting out with data science.

Spyder (IDE)

Spyder is a Python-specific IDE designed for data scientists and ML engineers. It’s included with the Anaconda distribution that includes other popular Python libraries like Scikit-learn, Mumpy, Matplotlib, Scipy, and Pandas.

It includes great features like autocompletion, a powerful debugger, iPython shell, and limited data visualization tools. Spyder is specifically optimized for data science and therefore interfaces perfectly with all the top tools.

Spyder has fewer features than extensive IDEs like PyDev and rather focuses on providing a straightforward, easy-to-use tool for non-developers.

Pros:

  • Simple to install and integrate with top libraries
  • Tailored to data science tools and needs
  • Powerful debugging tools to help non-developers

Cons:

  • Limited functionality outside of data science
  • Few customization options

Use Case:

You use Python solely for data science or machine learning and want an IDE with tools tailored to your coding needs.

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PyDev (IDE)

PyDev is an open-source IDE plugin available for Eclipse, a popular Java IDE for open source development. PyDev comes with all of Eclipse’s built-in control and adds support for Python autocompletion, an interactive console, and debugging.

It is also integrated with Django with many tools suited for web development. It is one of the few IDEs that include support for Jython and Cython.

While not as featured or customizable as other Python IDEs, PyDev lets those already familiar with Eclipse get started in a fraction of the time it would take to learn a new tool. Those inexperienced with Eclipse will have a noticeable learning curve.

Pros:

  • Quick to pick up for current Eclipse users
  • Optimized for Django web dev
  • Includes support for Jython and Cython

Cons:

  • Limited in functionality as a simple plugin
  • Noticeable learning curve due to Eclipse
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Use Case:

You use Python as a secondary language for web development or open-source contributions and have some experience with Eclipse already.

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Thonny

The next IDE is Thonny: an IDE for learning and teaching programming. It’s software developed at The University of Tartu, which you can download for free on the Bitbucket repository for Windows, Linux, and Mac.
Among its features, Thonny supports code completion and highlights syntax errors, but it also provides a simple debugger, which you can run your program step-by-step. This is very nice for beginners, as they can step through statements and expressions. While editing a function, a new window is opened with local variables and the code being shown separately from your main code. The purpose of Thonny is to give you a good understanding of how Python works under the hood.
Atom

An open-source text editor developed by Github. That sounds great, right?
That’s exactly what Atom is.
You should try it out because… Although this text editor is available for many popular programming languages such as Ruby on Rails, PHP, Java, and so on, Atom has interesting features that create a good experience for Python developers.

Features One of the best advantages of Atom is its community, chiefly due to the constant enhancements and plugins that they develop in order to customize your IDE and improve your workflow.
For instance, One of these plugins – called “Packages” – is the Data Atom, which allows you to write and execute SQL queries. It supports PostgreSQL, Microsoft SQL Server, and MySQL. Besides that, you can also visualize your results on Atom, without opening any other window.

Additionally, you also have a plugin called “Markdown Preview Plus”, which provides you with built-in support for editing and visualizing Markdown files and which allows you to open a preview, render LaTeX equations, and much more!
As you could have already expected, Atom’s integration with git is awesome. And, as with other IDEs, it allows you to use multiple panes, themes, and colors, managing multiple projects.
Do you want to know one of the downsides? Atom might have a weak performance on older CPUs.
Data science enthusiasts say…
“I’m using hydrogen for Atom, it’s very fast and useful, it’s worthwhile tryout. […] Very recommended.”
Tip Use Atom in combination with Hydrogen, a package that lets you run your code directly in Atom using any Jupyter kernels you have installed.

Download Based in Electron – also known as Atom Shell, a cross-platform desktop applications framework by using Chromium -, Atom is available for free for Windows, OS X, and Linux.

Jupyter Notebook

Jupyter Notebook was born out of IPython in 2014. It is a web application based on the server-client structure, and it allows you to create and manipulate notebook documents – or just “notebooks”.
You should try it out because… Jupyter Notebook provides you with an easy-to-use, interactive data science environment across many programming languages that doesn’t only work like an IDE, but also as a presentation or educational tool. It’s perfect for those who are just starting out with data science!
Features The Jupyter Notebook supports markdowns, allowing you to add HTML components from images to videos. Thanks to Jupyter, you can easily see and edit your code in order to create compelling presentations. For instance, you can use data visualization libraries like Matplotlib and Seaborn and show your graphs in the same document where your code is. Besides all of this, you can export your final work to PDF and HTML files, or you can just export it as a .py file. In addition, you can also create blogs and presentations from your notebooks.
Data science enthusiasts say…
“Jupyter Notebook should be an integral part of any Python data scientist’s toolbox. It’s great for prototyping and sharing notebooks with visualizations.”
Tip If you want to know everything about the Jupyter Notebook, the installation process, and how to get started with this tool, check out this tutorial that will guide you through this awesome data science tool.

Pycharm

Pycharm

Platform: Linux/macOS/Windows

Official websitehttps://www.jetbrains.com/pycharm/

Type: IDE

Pycharm is an integrated development environment developed by JetBrains. It stands out from the competition because of its productivity tools, such as quick fixes. Available in three versions, the Apache-licensed Community version, the Educational (Edu) version, and the proprietary Professional version. The first two versions are open source and therefore free of charge, while the Professional version is paid

The Community version is very interesting because it has different features such as syntax highlighting, auto-completion, and live code verification. The paid version has more advanced features such as full database management and a multitude of more important Frameworks than the community version such as Django, Flask, Google App, Engine, Pyramid, and web2py.

Advantage:

  • Active community support
  • Live code verification and syntax highlighting
  • Executes edits and debugs Python code without any external requirements

Disadvantage:

  • Slow loading time
  • The default setting may require adjustment before existing projects can be used.
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Eclipse + PyDev

Category: IDE
Website: www.eclipse.org
Python tools: PyDev, www.pydev.org

If you’ve spent any amount of time in the open-source community, you’ve heard about Eclipse. Available for Linux, Windows, and OS X at, Eclipse is the de-facto open-source IDE for Java development. It has a rich marketplace of extensions and add-ons, which makes Eclipse useful for a wide range of development activities.

One such extension is PyDev, which enables Python debugging, code completion, and an interactive Python console. Installing PyDev into Eclipse is easy: from Eclipse, select Help, Eclipse Marketplace, then search for PyDev. Click Install and restart Eclipse if necessary.

Pros: If you’ve already got Eclipse installed, adding PyDev will be quicker and easier. PyDev is very accessible for the experienced Eclipse developer.

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Cons: If you’re just starting out with Python, or with software development in general, Eclipse can be a lot to handle. Remember when I said IDEs are larger and require more knowledge to use properly? Eclipse is all that and a bag of (micro)chips.

Conclusion

Developers like to use an Integrated Development Environment (IDE) for various reasons. Some may prefer IDEs because of their ease-of-use while some will prefer IDEs because of their advanced features. Whatever the reason you want to select an IDE for your Python development, there are still some things you need to look out for when trying to find the best IDE for Python.

A window of opportunity has appeared for Python developers on macOS, thanks to PyCharm’s recent price change. The pricing change puts the full strength of PyCharm Professional Edition on par with JetBrains’ own Python IDE, PyCharm Community Edition—free for open source projects, and now for everyone else as well.

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