Sublime Text vs Jupyter

Sublime Text has a minimap on the side that provides a top-down view of the file and keyboard shortcuts for most actions. It also supports a large number of languages and general text editing features out of the box.

Sublime Text is very lightweight by default. Customization occurs on the fly thanks to Package Control.

Sublime Text uses TextMate's syntax declaration files to support new languages, it has all its menus and keybindings generated from JSON files, and it can be scripted to add new features using Python.
If Sublime Text doesn't support a desired language or feature, it's usually not long before someone implements it themselves - examples include the plugin package manager and the 'open in browser' command.

When you start using Sublime Text, it doesn't drown you in keyboard shortcuts or non-intuitive use-concepts. However, high-level functionality can still be easily accessed when the need for it arises.

Multiple cursors and column selection allows for versatile ways of editing.
ctrl + d will select the current word and each time the command is repeated, it adds the next occurrence of the word to the selection.
ctrl + click or middle-mouse click will place another cursor in the place that's clicked. Cursors can then be controlled together. This also permits selecting vertically.
ctrl + shift + l will place a cursor on every highlighted line.

Sublime Text looks consistently the same across Windows, OS X, and Linux.

Sublime Text allows for all sorts of customization to help users change almost everything in the editor: Key Bindings, Menus, Snippets, Macros, Completions, and many more. Essentially, just about everything in Sublime Text is customizable with simple JSON files. This system gives the user flexibility as settings can be specified on a per-file type and per-project basis.

Sublime is quick to start and never slows down. The UI is always responsive and you know what is happening in the background.

The package manager is a plugin and can be swapped with something else custom.

Sublime Text, while being lighter-weight than an IDE, still supports many IDE features.

• Text from the current file is used to provide autocomplete.
• Project Support (folder browsing, scoped history, build-system declarations).
• Refactoring support is emulated through multi-select, project-wide find and replace, and regular expression search.
• Syntax-aware selection and GoTo for quickly jumping to locations in the project.
• Snippets and Macros.
• A Python console for everything else.

Command Palette allows for fuzzy searching all available settings, snippets, etc.

All you need to do when starting up is to install a package manager and modify user configuration.

Regex commands help describe a certain amount of text.

From menus to commands, assign key maps to almost anything.

Settings are modular and can be shared.

Distraction free editing takes over your screen and removes every UI element so you can focus on code.

Choose from many build systems or craft your own.

A Sublime license can be bought but it can still be used for free. However, a pop-up appears when you save multiple times.

Open Goto Anything by pressing Ctrl or Command + P and by using fuzzy search you can look for a file in your project. The file will load even without pressing enter, so you can make sure you've found the correct file without committing.

Both of these programming interfaces are cross-platform, open source, and easy to use.

Provides command line shortcut for server upload.

Vintage mode is Vim-style editing that's already built into the text editor.

Sublime Text compatibility with Textmate bundles is good, but excludes commands, which are incompatible. In general, Sublime Text syntax definitions are compatible with Textmate language files (.tmLanguage extension).

Create your own theme with online editor.

With lot of functionalities, where other editor even not think to provide.

Because the editor is a web app (the Jupyter Notebook program is a web server that you run on the host machine), it is possible to use this on quite literally any machine. Morever, you can have Jupyter Notebook run on one machine (like a VM that you have provisioned in the cloud) and access the web page / do your editing from a different machine (like a Chromebook).

Most IDEs require you to separately run Python to see the output of a particular piece of code. By contrast, Jupyter Notebook can evaluate Python statements inline, giving you the immediate feedback of interactive use of the interpreter while keeping your changes saved.

The interactive editor is able to display complex equations, charts, graphs, etc. making this particular editor very well-regarded among data scientists.

Because it is open source, you can review the source code and also propose extensions and fixes to it. It is also possible to fork the repository and make changes to it to customize it for your specific use case.

Jupyter Notebook, formerly known as ipython, used to be specific to Python; however, in recent iterations, it has become capable of general purpose usage for any programming language. Thus it is possible to use this and have a consistent developer workflow, regardless of language.