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Back to dotnet/interactive

Open-source alternatives to Interactive

13 open-source projects similar to dotnet/interactive, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Interactive alternative.

  • velocidex/velociraptorAvatar Velocidex

    Velocidex/velociraptor

    3,769Vezi pe GitHub↗

    Velociraptor is a digital forensics and incident response platform, endpoint detection and response system, and visibility tool. It provides a query engine and remote forensic collector used to hunt for indicators of compromise and perform triage across a fleet of hosts. The system is distinguished by its specialized query language for interrogating host state and parsing binary files. It features a notebook environment that combines markdown documentation with executable query cells to standardize investigative workflows and enable collaborative reporting. The platform covers a wide range o

    Godigital-forensicsendpoint-discoveryendpoint-protection
    Vezi pe GitHub↗3,769
  • vaexio/vaexAvatar vaexio

    vaexio/vaex

    8,506Vezi pe GitHub↗

    Vaex is a high-performance Apache Arrow DataFrame library and out-of-core data processing engine designed to handle billion-row tabular datasets in Python. It functions as a lazy evaluation framework that defers computations and transformations until results are required, enabling the processing of datasets that exceed available system RAM by mapping files directly from disk. The project distinguishes itself as a tool for big data visualization and exploration, specifically integrated for use within interactive notebooks. It provides specialized capabilities for machine learning feature engin

    Python
    Vezi pe GitHub↗8,506
  • kotlin/dataframeAvatar Kotlin

    Kotlin/dataframe

    1,049Vezi pe GitHub↗

    This library is a data processing framework for the JVM that provides a type-safe environment for manipulating structured tabular data. It functions as a comprehensive toolset for performing complex data transformations, aggregations, and statistical analysis, while leveraging compile-time schema validation to ensure structural integrity across data pipelines. The project distinguishes itself through its deep integration with interactive notebook environments and its use of compile-time code generation. By automatically deriving and enforcing schemas from raw inputs, it generates type-safe ac

    Kotlindata-analysisdata-sciencedataframe
    Vezi pe GitHub↗1,049

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  • marimo-team/marimoAvatar marimo-team

    marimo-team/marimo

    21,468Vezi pe GitHub↗

    Marimo is a reactive Python notebook environment and data science integrated development environment. It functions as a scripting tool that maintains state consistency by automatically tracking variable dependencies and re-executing downstream code blocks whenever upstream inputs are modified. The platform distinguishes itself by storing notebooks as standard, portable Python scripts rather than proprietary formats, ensuring compatibility with version control systems. It integrates artificial intelligence to assist with code generation and debugging based on the current execution context, whi

    Pythonartificial-intelligencedagdata-science
    Vezi pe GitHub↗21,468
  • nteract/papermillAvatar nteract

    nteract/papermill

    6,451Vezi pe GitHub↗

    Papermill is a Jupyter notebook execution engine and parameterization framework designed to run notebooks programmatically. It allows users to inject custom input values into notebooks to execute the same logic across different datasets, transforming interactive notebooks into reproducible data science pipelines. The project functions as a language-agnostic notebook runner and orchestrator, supporting kernels for Python, R, Julia, and Scala. It is distinguished by its cloud-integrated runner capabilities, featuring built-in handlers to read and write notebooks directly to storage providers su

    Python
    Vezi pe GitHub↗6,451
  • ploomber/ploomberAvatar ploomber

    ploomber/ploomber

    3,623Vezi pe GitHub↗

    The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️

    Pythondata-engineeringdata-sciencejupyter
    Vezi pe GitHub↗3,623
  • polynote/polynoteAvatar polynote

    polynote/polynote

    4,595Vezi pe GitHub↗

    Polynote is a polyglot notebook environment and interactive document system designed for executing code in multiple languages within a single document. It functions as a cross-language data analysis tool and a JVM language IDE, allowing users to combine executable code, rich text, and data visualizations to prototype and document technical workflows. The system is distinguished by its ability to share data and variables between different language runtimes, such as Python and the JVM. It uses cross-language object conversion and data wrapping to pass objects between runtimes, enabling multi-la

    Jupyter Notebook
    Vezi pe GitHub↗4,595
  • rstudio/rmarkdownAvatar rstudio

    rstudio/rmarkdown

    3,021Vezi pe GitHub↗

    rmarkdown is a dynamic document generator and markdown rendering engine used to create reproducible reports, analysis, and websites. It functions as a literate programming tool that weaves narrative text with live executable code and data, ensuring that visual results are tied directly to the source code. The project serves as a multi-format rendering engine and content publisher, utilizing a Pandoc-based conversion framework to transform a single source file into diverse outputs such as PDFs, HTML pages, and presentation slides. It integrates with Knitr to execute code blocks and capture out

    Rliterate-programmingmarkdownpandoc
    Vezi pe GitHub↗3,021
  • stencila/stencilaAvatar stencila

    stencila/stencila

    888Vezi pe GitHub↗

    Documents with Scientific Intelligence

    Rust
    Vezi pe GitHub↗888
  • apache/zeppelinAvatar apache

    apache/zeppelin

    6,629Vezi pe GitHub↗

    Apache Zeppelin is a web-based notebook platform for interactive data analytics that supports executing code in over 20 languages within a single notebook. It provides a plugin-based interpreter architecture that allows the notebook to be extended with new languages and data sources, and includes a JDBC connector abstraction for connecting to any JDBC-compliant database. The platform also features session-isolated interpreter contexts, enabling separate interpreter instances per notebook or user with support for dependency injection and user impersonation. The platform distinguishes itself th

    Java
    Vezi pe GitHub↗6,629
  • voila-dashboards/voilaAvatar voila-dashboards

    voila-dashboards/voila

    5,935Vezi pe GitHub↗

    Voilà is a tool that converts Jupyter notebooks into standalone interactive web applications. It renders notebook cells as HTML web components, preserving live widgets while stripping source code by default, and gives each viewer a dedicated Jupyter kernel for isolated widget state and callback execution. The project runs as a Jupyter server extension, reusing existing server infrastructure for notebook serving and authentication. It supports directory-based notebook hosting, serving all notebooks in a folder as a browsable collection of web applications from a single command. Voilà also prov

    Python
    Vezi pe GitHub↗5,935
  • deepnote/deepnoteAvatar deepnote

    deepnote/deepnote

    2,930Vezi pe GitHub↗

    Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time collaboration, Deepnote agent, and deployable data apps. https://deepnote.com/

    TypeScript
    Vezi pe GitHub↗2,930
  • jupyter/notebookAvatar jupyter

    jupyter/notebook

    13,204Vezi pe GitHub↗

    This project is a browser-based interactive computing environment and data science IDE. It serves as a literate programming tool that allows users to create documents combining live code, mathematical equations, visualizations, and narrative text. As a polyglot notebook interface, it connects to various language kernels to execute code and render output within a single interface. The application distinguishes itself by separating the frontend interface from a remote compute engine through a language-agnostic kernel interface. This allows it to support multiple programming languages while main

    Jupyter Notebookclosemberjupyterjupyter-notebook
    Vezi pe GitHub↗13,204