Python IDE’s
In this article, I will talk about Python Programming environments. I will tell you what I’m using and the existing IDEs. I’ll start with brief information about Python.
Python is a general-purpose programming language for building anything; from backend web development, data analysis, artificial intelligence to scientific computing. It can also be used for developing productivity software, games, desktop apps and beyond.
It’s easy to learn, has a clean syntax and mark structure. And an IDE (Integrated Development Environment) can, to some extent, determine one's programming experience when it comes to learning or developing using any language.
Now we can talk about IDEs.
PyCharm is a powerful, cross-platform, highly customizable and pluggable Python IDE, which integrates all developments tools in one place. It is feature rich and comes in the community (free and open source) as well as professional editions.
It provides smart code completion, code inspections functionalities and has remarkable error highlighting and quick-fixes. It also ships in with automated code refactoring and excellent navigation capabilities. It is very popular among Python programmers and designed for professional developers.
Also you can download PyCharm from here:
Spyder is a scientific Python IDE with many features for research, data analysis, and scientific package creation. It ships with a multi-language editor with function/class browser, code analysis features (with support for pyflakes and pylint), code completion, horizontal and vertical splitting as well as goto definition feature.
Powerful Python IDE with advanced editing, interactive testing, debugging and introspection features.
It has an interactive console, documentation viewer, variable explorer, and a file explorer. Spyder allows for searching queries across multiple files in your project, with complete support for regular expressions.
Also you can download Spyder from here:
PyDev, 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.
is a Python IDE for Eclipse with Django support, code completion, code analysis, navigation, remote debugging, the interactive console and much more. You can install it as a plugin for Eclipse or by installing LiCipse, an advanced Eclipse distribution.
Also you can download PyDev from here:
Visual Studio, Built by Microsoft, Visual Studio is a full-featured IDE, in many ways comparable to Eclipse. Built for Windows and Mac OS only, VS comes in both free (Community) and paid (Professional and Enterprise) versions. Visual Studio enables development for a variety of platforms and comes with its own marketplace for extensions.
Python Tools for Visual Studio (aka PTVS) enables Python coding in Visual Studio, as well as IntelliSense for Python, debugging, and other tools.
Note: If you already have Visual Studio installed for other development activities, adding PTVS is quicker and easier. Also, Visual Studio is a big download for just Python. Plus, if you’re on Linux, you’re out of luck: there’s no Visual Studio install for that Platform.
Also you can download Visual Studio from here:
Visual Studio Code, not to be confused with full Visual Studio, Visual Studio Code (aka VS Code) is a full-featured code editor available for Linux, Mac OS X, and Windows platforms. Small and light-weight, but full-featured, VS Code is open-source, extensible and configurable for almost any task. Like Atom, VS Code is built on Electron, so it has the same advantages and disadvantages that brings.
Also you can download Visual Studio Code from here:
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 as an IDE, but also as a presentation or education 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.
Jupyter Notebook is also my favorite environment. I generally develop my project on this IDE.
Also you can download Jupyter Notebook from here:
Komodo is an IDE for dynamic languages such as Python, PHP, and Ruby. The new version has many improvements such as code refactoring, multiple selections, better UI interface, open fast dialog, and much more.
Also you can download Komodo from here:
Python IDLE, An IDE that is part of Python standard library. It is quite helpful to try out small Python snippets and experiment with different features in Python.
Also you can download Python IDLE from here:
Anaconda Navigator is a desktop graphical user interface (GUI) included in Anaconda distribution that allows you to launch applications and easily manage conda packages, environments, and channels without using command-line commands. Navigator can search for packages on Anaconda Cloud or in a local Anaconda Repository. It is available for Windows, macOS, and Linux.
Why Use Navigator?
In order to run, many scientific packages depend on specific versions of other packages. Data scientists often use multiple versions of many packages and use multiple environments to separate these different versions.
The command line program conda is both a package manager and an environment manager, to help data scientists ensure that each version of each package has all the dependencies it requires and works correctly.
Navigator is an easy, point-and-click way to work with packages and environments without needing to type conda commands in a terminal window. You can use it to find the packages you want, install them in an environment, run the packages and update them, all inside Navigator.
What applications can I access using Navigator?
The following applications are available by default in Navigator:
- JupyterLab
- Jupyter Notebook
- QTConsole
- Spyder
- VSCode
- Glueviz
- Orange 3 App
- RStudio
How can I run code with Navigator?
The simplest way is with Spyder. From the Navigator Home tab, click Spyder, and write and execute your code.
You can also use Jupyter Notebooks the same way. Jupyter Notebooks are an increasingly popular system that combines your code, descriptive text, output, images, and interactive interfaces into a single notebook file that is edited, viewed and used in a web browser.
Also you can download Anaconda Navigator from here:
You can also run Anaconda Navigator typing ‘anaconda-navigator’ on the Anaconda prompt.
You can search your environments and Packages in this section.
You can create a new Python File, Text File, Folder and Terminal and upload in this page.
Hopefully, it benefits you..
