Alternatives to Jupyter Notebook for Python and more!
Jupyter emerged and gained respect for being an easy-to-install solution, in addition to bringing the proposed use to facilitate coding and visualization of the code, a form of interactive computing aimed at usability. With the success of Python, other market tools started to support this language and compete directly with Jupyter.
Now that I spoke well about jupyter, let’s go to the competition… :)
The company Jetbrains developed Pycharm, a Python development solution containing a development wizard, support for Django, Flask, Google App Engine, Pyramid, and web2py web frameworks, support for other languages such as JavaScript, CoffeeScript, TypeScript, Cython, SQL, HTML / CSS, template languages, AngularJS, Node.js, test and debugger solution, in addition to the ability to integrate and deploy with remote environments, Docker and Vagrant, integrated database manager.
As a disadvantage, PyCharm can take a long time to load; depending on the project, your settings when creating the project need to be changed. Its free version could offer more functionality to compete with other market solutions.
PyCharm is generally used for AI development due to its easy integration with other Jetbrains solutions and its assistant who will put an AI to learn how each person develops code and offer a much better autocomplete, but it will improve the development experience.
If you are a university student, teacher, or going to do a Bootcamp, you can try to win the license of the paid version of all Jetbrains software for free (FREE!)! > Happy link <:)
Another alternative for AI development in Visual Studio Code, a free and open-source project from Microsoft that in addition to native Python support, also supports JavaScript, JSON, HTML, CSS, SCSS, Less, TypeScript, Markdown, PowerShell, C ++, Java, PHP, Go, T-SQL, C # and .NET Core, have a large number of extensions, maintained by your community that enables development in Clojure and Scala and integration with the most diverse cloud solutions such as Azure and Google cloud and recently started offering support for files in notebook format. Depending on the number of extensions installed, Visual Studio code may experience slow loading or an error in its execution.
VS Code, every day that passes, Microsoft or its community improves it or creates a new extension that will make life easier or copy the idea of its competitors. It is a very light tool and highly attachable to more diverse environments.
Recently, RStudio also started to support the Python language, normally used for R development and offered support for Julia. Although it is a complete tool, it still needs to improve the debugger part, and at times during its use, it can be slow.
RStudio has numerous data visualization tools to assist the user in plotting. It comes with various interesting features, such as a customizable console, searchable history for previous code, keyboard shortcuts, cross-platform compatibility, help section, and more.
All other software will already copy most features in some way…
At the same time that already established and widely used IDEs like RStudio are renewed and provide support for new languages, other solutions appear almost out of nowhere and are adopted by the market as is the case of nteract, an open-source project to be the next interactive development experience adopted by Netflix, in practice it has support for Python, node.JS, R, Julia, C ++, Scala and .NET, in addition to coming with a set of libraries to offer the functionality of configurations and automation of the environment of work like the papermill.
I installed to see and addict… very simple, intuitive and happy… :)
These are some of the many alternatives to Jupyter Notebook for data sciences; even though some have only recently supported Python-like RStudio, others gain more functionality and integrations every day, as is the case with Visual Studio Code, and even companies like Jetbrains have been concerned with supporting Python and creating integrated environments with their other solutions and market solutions to expand their share of the Artificial Intelligence (AI) development market.
I put in this list only the software that I have used and recommend!
References:
https://medium.com/lica-ufal/a-beleza-do-jupyter-notebook-d9dd8a689289
https://analyticsindiamag.com/top-5-alternatives-jupyter-notebook/
https://www.programiz.com/python-programming/ide
https://www.guru99.com/python-ide-code-editor.html
https://www.kdnuggets.com/2018/11/best-python-ide-data-science.html
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