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Kakoune VS Jupyter

Compare Kakoune VS Jupyter and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Kakoune logo Kakoune

Vim inspired — Faster as in less keystrokes — Multiple selections — Orthogonal design

Jupyter logo Jupyter

Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
  • Kakoune Landing page
    Landing page //
    2023-10-13
  • Jupyter Landing page
    Landing page //
    2023-06-22

Kakoune features and specs

  • Modal Editing
    Kakoune uses a modal editing style similar to Vim, which can be more efficient for experienced users who prefer to keep their hands on the keyboard.
  • Interactive and Asynchronous
    Kakoune is designed to be both interactive and asynchronous, providing immediate feedback for commands which can enhance the editing experience.
  • Selections
    Kakoune treats text editing as a multiple selections-oriented operation, enabling powerful, simultaneous edits across multiple text locations, which can speed up complex text manipulations.
  • Simplicity in Configuration
    Kakoune’s configuration files are written in a simple, declarative syntax, making it easier for users to customize their setup without extensive scripting.
  • Performance
    Kakoune is designed with performance in mind, resulting in a lightweight and fast editor even with large files.
  • Extensible Plugin System
    Kakoune supports various plugins and has a community-driven set of extensions, allowing users to extend functionality as needed.
  • Language Support
    Built-in support for syntax highlighting and other language-specific features for many programming languages.

Possible disadvantages of Kakoune

  • Learning Curve
    Kakoune has a steep learning curve, especially for users not familiar with modal editing or coming from different types of text editors.
  • Plugin Ecosystem
    While Kakoune has an extensible plugin system, its plugin ecosystem is not as mature or extensive as more established editors like Vim or Emacs.
  • Limited GUI Support
    Kakoune primarily operates in the terminal, with limited graphical user interface support, which might be a drawback for users who prefer more visual editing environments.
  • Smaller User Base
    Kakoune has a smaller user base compared to more mainstream editors, potentially resulting in fewer community resources, tutorials, and third-party tool integrations.
  • Reliance on Command Line
    Heavy reliance on command-line operations can be intimidating or cumbersome for users who are not comfortable with the terminal.
  • Limited IDE Features
    Kakoune lacks some of the advanced integrated development environment (IDE) features out-of-the-box, such as integrated debugging or project management tools.

Jupyter features and specs

  • Interactive Computing
    Jupyter allows real-time interaction with the data and code, providing immediate feedback and making it easier to experiment and iterate.
  • Rich Media Output
    It supports output in various formats including HTML, images, videos, LaTeX, and more, enhancing the ability to visualize and interpret results.
  • Language Agnostic
    Jupyter supports multiple programming languages through its kernel system (e.g., Python, R, Julia), allowing flexibility in the choice of tools.
  • Collaborative Features
    It enables collaboration through shared notebooks, version control, and platform integrations like GitHub.
  • Educational Tool
    Jupyter is widely used for teaching, thanks to its easy-to-use interface and ability to combine narrative text with code, making it ideal for assignments and tutorials.
  • Extensibility
    Jupyter is highly extensible with a large ecosystem of plugins and extensions available for various functionalities.

Possible disadvantages of Jupyter

  • Performance Issues
    For larger datasets and more complex computations, Jupyter can be slower compared to running scripts directly in a dedicated IDE.
  • Version Control Challenges
    Managing version control for Jupyter notebooks can be cumbersome, as they are not plain text files and include metadata that can make diffing and merging complex.
  • Resource Intensive
    Running Jupyter notebooks can be resource-intensive, especially when working with multiple large notebooks simultaneously.
  • Security Concerns
    Because Jupyter allows code execution in the browser, it can be a potential security risk if notebooks from untrusted sources are run without restrictions.
  • Dependency Management
    Managing dependencies and ensuring that the notebook runs consistently across different environments can be challenging.
  • Less Suitable for Production
    Jupyter is often considered more as a research and educational tool rather than a production environment; transitioning from a notebook to production code can require significant refactoring.

Kakoune videos

+ Add

Kakoune Is A More Efficient Text Editor

Jupyter videos

+ Add

What is Jupyter Notebook?

More videos:

  • Tutorial - Jupyter Notebook Tutorial: Introduction, Setup, and Walkthrough
  • Review - JupyterLab: The Next Generation Jupyter Web Interface

Category Popularity

0-100% (relative to Kakoune and Jupyter)

Kakoune

Jupyter

Text Editors
100 100%
Text Editors
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
IDE
100 100%
IDE
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Kakoune and Jupyter

Kakoune Reviews

We have no reviews of Kakoune yet.
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Jupyter Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Once you install nteract, you can open your notebook without having to launch the Jupyter Notebook or visit the Jupyter Lab. The nteract environment is similar to Jupyter Notebook but with more control and the possibility of extension via libraries like Papermill (notebook parameterization), Scrapbook (saving your notebook’s data and photos), and Bookstore (versioning).
Source: lakefs.io
7 best Colab alternatives in 2023
JupyterLab is the next-generation user interface for Project Jupyter. Like Colab, it's an interactive development environment for working with notebooks, code, and data. However, JupyterLab offers more flexibility as it can be self-hosted, enabling users to use their own hardware resources. It also supports extensions for integrating other services, making it a highly...
Source: deepnote.com
12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing
Jupyter Notebook is a widely popular tool for data scientists to work on data science projects. This article reviews the top 12 alternatives to Jupyter Notebook that offer additional features and capabilities.
Source: noteable.io
15 data science tools to consider using in 2021
Jupyter Notebook's roots are in the programming language Python -- it originally was part of the IPython interactive toolkit open source project before being split off in 2014. The loose combination of Julia, Python and R gave Jupyter its name; along with supporting those three languages, Jupyter has modular kernels for dozens of others.
Source: searchbusinessanalytics.techtarget.com
Top 4 Python and Data Science IDEs for 2021 and Beyond
Yep — it’s the most popular IDE among data scientists. Jupyter Notebooks made interactivity a thing, and Jupyter Lab took the user experience to the next level. It’s a minimalistic IDE that does the essentials out of the box and provides options and hacks for more advanced use.
Source: towardsdatascience.com

Social recommendations and mentions

Based on our record, Jupyter seems to be a lot more popular than Kakoune. While we know about 216 links to Jupyter, we've tracked only 10 mentions of Kakoune. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Kakoune mentions (10)

  • Show HN: Ki Editor
    Fascinating idea! To summarize for those who know [Kakoune](https://github.com/mawww/kakoune), the idea is that every command has the form ["selection mode" -> "movement" -> "action"](https://ki-editor.github.io/ki-editor/comparisons/modal-editors.html) instead of Kakoune's movement->action. So, instead of having separate commands for "next character", "next word", "next structural element", there is one command... - Source: Hacker News / 8 months ago
  • Helix: Release 24.03 Highlights
    Helix's modal editing is based on Kakoune's modal editing which is like an evolution to Vim's modal editing. You can think of it as being always in selection (visual) mode. https://github.com/mawww/kakoune?tab=readme-ov-file#selectio.... - Source: Hacker News / about 1 year ago
  • I don't need your query language
    You might like kakoune (https://github.com/mawww/kakoune), which does exactly that: first you select the range (which can even be disjoint, e.g. All words matching a regex), then you operate on it. By default, the selected range is the character under cursor, and multiple cursors work out of the box. It also generally follows the Unix philosophy, e.g. By using shell... - Source: Hacker News / almost 2 years ago
  • I use nano BTW.
    It might be worth checking out kakoune if you are experimenting with editors. It’s supposed to be equally powerful to vim but much easier to learn. Source: over 2 years ago
  • Mle is a small, flexible, terminal-based text editor written in C
    For that, try Kakoune[1], which is modal with a mostly-postfix language instead of vi's usually-prefix one and uses this to also be a multiple-selections editor with immediate visual feedback. It falls too much into the uncanny valley of almost-but-not-quite-vi for some people, though. [1] https://kakoune.org/, https://github.com/mawww/kakoune. - Source: Hacker News / over 2 years ago
View more

Jupyter mentions (216)

  • The 3 Best Python Frameworks To Build UIs for AI Apps
    Showcase and share: Easily embed UIs in Jupyter Notebook, Google Colab or share them on Hugging Face using a public link. - Source: dev.to / about 2 months ago
  • LangChain: From Chains to Threads
    LangChain wasn’t designed in isolation — it was built in the data pipeline world, where every data engineer’s tool of choice was Jupyter Notebooks. Jupyter was an innovative tool, making pipeline programming easy to experiment with, iterate on, and debug. It was a perfect fit for machine learning workflows, where you preprocess data, train models, analyze outputs, and fine-tune parameters — all in a structured,... - Source: dev.to / 3 months ago
  • Applied Artificial Intelligence & its role in an AGI World
    Leverage versatile resources to prototype and refine your ideas, such as Jupyter Notebooks for rapid iterations, Google Colabs for cloud-based experimentation, OpenAI’s API Playground for testing and fine-tuning prompts, and Anthropic's Prompt Engineering Library for inspiration and guidance on advanced prompting techniques. For frontend experimentation, tools like v0 are invaluable, providing a seamless way to... - Source: dev.to / 4 months ago
  • Jupyter Notebook for Java
    Lately I've been working on Langgraph4J which is a Java implementation of the more famous Langgraph.js which is a Javascript library used to create agent and multi-agent workflows by Langchain. Interesting note is that [Langchain.js] uses Javascript Jupyter notebooks powered by a DENO Jupiter Kernel to implement and document How-Tos. So, I faced a dilemma on how to use (or possibly simulate) the same approach in... - Source: dev.to / 8 months ago
  • JIRA Analytics with Pandas
    One of the most convenient ways to play with datasets is to utilize Jupyter. If you are not familiar with this tool, do not worry. I will show how to use it to solve our problem. For local experiments, I like to use DataSpell by JetBrains, but there are services available online and for free. One of the most well-known services among data scientists is Kaggle. However, their notebooks don't allow you to make... - Source: dev.to / 11 months ago
View more

What are some alternatives?

When comparing Kakoune and Jupyter, you can also consider the following products

Vim - Highly configurable text editor built to enable efficient text editing

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

VS Code - Build and debug modern web and cloud applications, by Microsoft

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

Light Table - Light Table is a new interactive IDE that lets you modify running programs and embed anything from...

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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