So let’s look at those first!Functions returning functionsSay you have one function, greet() - it greets whatever object you pass it. As you start using them, you’ll notice how they don’t overcomplicate things and make your code neat and snazzy.Before anything else: higher-order functionsIn a nutshell, decorators are a neat way to handle higher-order functions. It does take a while to wrap your head around, but it’s worth it. But as the language started getting used for more and more things, Python developers felt the need for more and more features, without cluttering the landscape and making code unreadable.Decorators are a prime-time example of a perfectly implemented feature. It’s also not beginner-friendly then - a novice getting boggled by unreadable code won’t attempt writing its own one day.Python was already readable and beginner-friendly before decorators came around. Everything else hinges on that: if code is unreadable, it’s hard to maintain. To get started writing your own, check out the VS Code renderer api documentation.Īnalyze, test, and re-use your code with little more than an symbolIf there’s one thing that makes Python incredibly successful, that would be its readability. Although the Jupyter extension comes with a comprehensive set of the most commonly used renderers for output, the marketplace supports installable custom renderers to make working with your notebooks even more productive.Extensions can now add their own specific language or runtime to notebooks, such as the. Extensibility beyond what the Jupyter extension provides.Includes a notebook diff tool, which makes it easy to compare and visualize differences between code cells, results and metadata.Any notebook file is loaded and rendered as quickly as possible, while execution-related operations are initialized behind the scenes. Fast load times for Jupyter notebook (.ipynb) files.Deep integration with the general workbench and file-based features of VS Code, such as outline view (table of contents), breadcrumbs, and other operations.Editor extensions such as VIM, bracket coloring, linters and many more are available while editing a cell.Out-of-the-box support for VS Code's wide range of basic code editing functions, such as hot output, search and replace, and code folding.This interface offers a number of advantages to notebook users: The Jupyter Extension uses VS code's built-in notebook support. To enable advanced features, modifications to the VS Code language extensions may be necessary. Many language kernels will work without any modifications. A Visual Studio Code extension that provides basic notebook support for language kernels that are compatible with Jupyter Notebooks today.
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