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Jupyter

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Jupyter vs Org Mode: What are the differences?

Key Differences Between Jupyter and Org Mode

Jupyter and Org Mode are both popular tools for organizing and documenting code and data, but they have some key differences. Here are the six main differences between Jupyter and Org Mode:

  1. File format and structure: Jupyter notebooks are stored in .ipynb file format, which is a JSON-based format that can be easily shared and version controlled. Org Mode, on the other hand, uses a plain text format with a hierarchy of headings and subheadings to organize content.

  2. User interface: Jupyter provides a web-based interface that allows users to edit and run code cells, view output, and create interactive visualizations. Org Mode is primarily used within the Emacs text editor, providing a powerful and extensible environment for editing and managing documents.

  3. Code execution: Jupyter allows code cells to be executed in a variety of programming languages, including Python, R, and Julia. Org Mode also supports code execution, but is typically used with Emacs' built-in scripting language, Emacs Lisp.

  4. Inline documentation: Jupyter notebooks allow for the inclusion of Markdown cells, which can contain rich text, images, and mathematical formulas. Org Mode includes support for a similar syntax called org-mode markup, but also provides additional features like tables, to-do lists, and code blocks with syntax highlighting.

  5. Interactivity: Jupyter notebooks enable users to interact with code cells, making it easy to experiment and explore data interactively. Org Mode, while it supports code execution, is primarily designed for organizing and documenting content, and does not have the same level of interactivity as Jupyter.

  6. Community and ecosystem: Jupyter has a large and active community, with extensive documentation, numerous libraries, and a wide range of third-party extensions and integrations. Org Mode also has a dedicated user base, particularly within the Emacs community, but may have less extensive resources and support compared to Jupyter.

In summary, Jupyter and Org Mode differ in their file format and structure, user interface, code execution capabilities, inline documentation features, interactivity, and community and ecosystem.

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Pros of Jupyter
Pros of Org Mode
  • 19
    In-line code execution using blocks
  • 11
    In-line graphing support
  • 8
    Can be themed
  • 7
    Multiple kernel support
  • 3
    LaTex Support
  • 3
    Best web-browser IDE for Python
  • 3
    Export to python code
  • 2
    HTML export capability
  • 1
    Multi-user with Kubernetes
  • 1
    Agenda and Calendar
  • 1
    Suitable for long documents
  • 1
    Portable across platforms
  • 1
    Works in CLI via Emacs
  • 1
    Export to md, html, odt, LaTeX etc
  • 1
    GTD Concept
  • 1
    To-Do-Lists/Organiser
  • 1
    Note-taking
  • 1
    Intuitive
  • 1
    Easy formatting

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Cons of Jupyter
Cons of Org Mode
    Be the first to leave a con
    • 1
      Not many editors have org mode support other then Emacs

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    What is Jupyter?

    The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media.

    What is Org Mode?

    It is used for keeping notes, maintaining TODO lists, planning projects, and authoring documents with a fast and effective plain-text system

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    What companies use Jupyter?
    What companies use Org Mode?
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    What tools integrate with Jupyter?
    What tools integrate with Org Mode?

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    What are some alternatives to Jupyter and Org Mode?
    Apache Zeppelin
    A web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more.
    PyCharm
    PyCharm’s smart code editor provides first-class support for Python, JavaScript, CoffeeScript, TypeScript, CSS, popular template languages and more. Take advantage of language-aware code completion, error detection, and on-the-fly code fixes!
    IPython
    It provides a rich architecture for interactive computing with a powerful interactive shell, a kernel for Jupyter. It has a support for interactive data visualization and use of GUI toolkits. Flexible, embeddable interpreters to load into your own projects. Easy to use, high performance tools for parallel computing.
    Spyder
    It is a powerful scientific environment written in Python, for Python, and designed by and for scientists, engineers and data analysts.
    Anaconda
    A free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda.
    See all alternatives