.NET Interactive combines the power of .NET with many other languages to create notebooks, REPLs, and embedded coding experiences. Share code, explore data, write, and learn across your apps in ways you couldn't before.
Les fonctionnalités principales de dotnet/interactive sont : Interactive Notebooks, Interactive Programming.
Les alternatives open-source à dotnet/interactive incluent : velocidex/velociraptor — Velociraptor is a digital forensics and incident response platform, endpoint detection and response system, and… vaexio/vaex — Vaex is a high-performance Apache Arrow DataFrame library and out-of-core data processing engine designed to handle… kotlin/dataframe — This library is a data processing framework for the JVM that provides a type-safe environment for manipulating… jupyter/notebook — This project is a browser-based interactive computing environment and data science IDE. It serves as a literate… nteract/papermill — Papermill is a Jupyter notebook execution engine and parameterization framework designed to run notebooks… marimo-team/marimo — Marimo is a reactive Python notebook environment and data science integrated development environment. It functions as…
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
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
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
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