Need advice about which tool to choose?Ask the StackShare community!

IPython

503
109
+ 1
4
Jupyter

2.5K
1.3K
+ 1
57
Add tool

IPython vs Jupyter: What are the differences?

IPython and Jupyter are closely related interactive computing tools used in data science and scientific computing environments. Let's explore the key differences between them.

  1. IPython vs Jupyter Notebooks: IPython is an interactive command-line terminal for Python that provides enhanced features compared to the default Python shell. It includes features like tab completion, object introspection, and can execute code written in different programming languages. On the other hand, Jupyter Notebook is a web application that allows users to create and share documents containing live code, equations, visualizations, and narrative text. It supports multiple programming languages, including Python, R, and Julia. While IPython is a component of Jupyter Notebooks, Jupyter provides a more comprehensive interactive computing environment with additional features and support for multiple programming languages.

  2. Kernel-based architecture: IPython uses a single kernel for executing code written in different languages. However, Jupyter Notebooks utilize a kernel-based architecture that allows users to choose different kernels for executing code. This means that you can have notebooks with code written in Python, R, and other languages, all within the same Jupyter environment. Each kernel runs in a separate process and communicates with the Jupyter Notebook web application through a set of protocols. This architecture provides flexibility and enables users to work with different programming languages seamlessly.

  3. Notebook interface vs command-line interface: The primary interface of IPython is a command-line terminal, where users interact with the tool by entering commands and executing code. In contrast, Jupyter Notebooks provide a web-based interface with a notebook-like structure. Users can create notebooks, write code in cells, and execute them individually or all at once. The notebook interface allows for a more visual and interactive experience, as users can mix code with explanatory text, equations, and visualizations in a single document.

  4. Larger community and ecosystem: While IPython has a dedicated community, Jupyter Notebooks have a larger and more diverse user base. Jupyter Notebooks are widely adopted in academia, data science, and industry, with numerous resources, tutorials, and extensions available online. The larger community and ecosystem around Jupyter Notebooks make it easier to find support, discover new tools, and collaborate with other users.

  5. Extension ecosystem: Jupyter Notebooks have a rich extension ecosystem that allows users to enhance the functionality of the tool. Users can install various extensions to add features like table of contents, code formatting, spell checking, and more. These extensions can be customized and configured to match individual needs, providing a highly personalized and efficient workflow.

  6. Collaboration and sharing: While IPython does not have native support for collaboration and sharing, Jupyter Notebooks are designed with collaboration in mind. Jupyter Notebooks can be easily shared with others by exporting them in different formats like HTML, PDF, or Markdown. They can also be hosted on platforms like GitHub or Jupyter Notebook Viewer, allowing for seamless collaboration and sharing of interactive documents.

In summary, IPython is an interactive computing environment primarily used for Python programming, providing enhanced features like interactive shells and rich media display capabilities. Jupyter, on the other hand, is an open-source web application that allows users to create and share documents containing live code, equations, visualizations, and narrative text, supporting multiple programming languages beyond just Python.

Get Advice from developers at your company using StackShare Enterprise. Sign up for StackShare Enterprise.
Learn More
Pros of IPython
Pros of Jupyter
  • 1
    Interactive exploration then save to a script
  • 1
    Persistent history between sessions
  • 1
    It's magical are just that
  • 1
    Help in a keystroke
  • 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

Sign up to add or upvote prosMake informed product decisions

- No public GitHub repository available -

What is 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.

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.

Need advice about which tool to choose?Ask the StackShare community!

Jobs that mention IPython and Jupyter as a desired skillset
What companies use IPython?
What companies use Jupyter?
See which teams inside your own company are using IPython or Jupyter.
Sign up for StackShare EnterpriseLearn More

Sign up to get full access to all the companiesMake informed product decisions

What tools integrate with IPython?
What tools integrate with Jupyter?

Sign up to get full access to all the tool integrationsMake informed product decisions

Blog Posts

What are some alternatives to IPython and Jupyter?
Python
Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.
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.
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!
Spyder
It is a powerful scientific environment written in Python, for Python, and designed by and for scientists, engineers and data analysts.
JavaScript
JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles.
See all alternatives