VS CODE vs JUPYTER NOTEBOOK
Visual Studio Code (VS Code) and Jupyter Notebook are two popular tools used by developers and data scientists. While they have some similarities, they are designed for different purposes and are suitable for different types of work.
VS Code is a general-purpose code editor developed by Microsoft. It is available for Windows, Mac, and Linux, and can be used for a wide variety of programming languages and tasks. VS Code has a large selection of extensions, which are add-ons that enable users to customize the editor and add new features. Some popular extensions for VS Code include debugging tools, language support, and integration with other tools such as Git.
One of the main advantages of VS Code is its support for large projects. It has features such as code completion, linting, and refactoring that help developers write and maintain code more efficiently. It also has a built-in debugger that allows users to identify and fix errors in their code. Additionally, VS Code integrates with Git, which is a version control system that allows developers to track changes to their code and collaborate with others.
VS Code also has a number of features that make it easier to work with large projects. It has a built-in search function that allows users to quickly find files and symbols within their codebase. It also has support for multiple cursors, which allows users to make simultaneous edits in different parts of their code. This can be particularly useful for making global changes or refactoring code.
Another advantage of VS Code is its customization options. Users can customize the appearance of the editor by selecting from a range of color themes and font styles. They can also customize the layout and arrangement of the editor by docking and undocking windows, or by using the built-in terminal. This allows users to tailor the environment to their specific needs and preferences.
Jupyter Notebook, on the other hand, is an open-source web-based interactive computing platform. It was originally developed for Python, but now supports a wide variety of languages including R, Julia, and Haskell. Jupyter Notebook allows users to write and run code blocks, view visualizations, and document their work using markdown all in one place.
One of the main advantages of Jupyter Notebook is its interactive nature. It allows users to explore and experiment with code in a flexible and interactive environment. This makes it particularly well-suited for data science and machine learning workflows, where users may want to quickly test out different ideas and see the results. Jupyter Notebook also allows users to easily combine code, visualizations, and text in a single document, which makes it easy to document and share their work.
Jupyter Notebook has a number of features that make it well-suited for data science and machine learning workflows. It has support for inline plotting, which allows users to view visualizations directly within the notebook. It also has support for rich media, such as HTML, LaTeX, and images, which allows users to include a wide range of content in their notebooks. Additionally, Jupyter Notebook has support for kernels, which are executors that allow users to run code in different languages within the same notebook.
Another advantage of Jupyter Notebook is its ability to be used in a collaborative environment. Users can share their notebooks with others, either by sharing the file directly or by using a cloud-based service such as JupyterHub. This allows multiple users to work on the same notebook simultaneously and see each other’s changes in real-time.
In summary, VS Code is a powerful and feature-rich code editor that is suitable for a wide range of developing and researching.
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— TANUJ SHARMA