CoordinateTransformations is a Julia package to manage simple or complex networks of coordinate system transformations. Transformations can be easily applied, inverted, composed, and differentiated (both with respect to the input coordinates and with respect to transformation parameters such as rotation angle). Transformations are designed to be light-weight and efficient enough for, e.g., real-time graphical applications, while support for both explicit and automatic differentiation makes it easy to perform optimization and therefore ideal for computer vision applications such as SLAM (simultaneous localization and mapping).

This small package supports the representation of images as AxisArrays to endow the axes with "meaning," and makes programming with such arrays easy via traits.

The purpose of this library is to solidify extensions to the current AbstractArray interface, which are put to use in package ecosystems like DifferentialEquations.jl. Since these libraries are live, this package will serve as a staging ground for ideas before they are merged into Base Julia. For this reason, no functionality is exported so that if such functions are added and exported in a future Base Julia, there will be no issues with the upgrade.

This package provides tools to help you develop code. Juno is built on the Atom text editor. Juno consists of both Julia and Atom packages in order to add Julia-specific enhancements, such as syntax highlighting, a plot pane, integration with Julia's debugger, a console for running code, and much more.

Consider that the package is “maintenance-only mode” and only receives bug fixes. The Julia IDE effort is pointed to extension for VSCode.

This package provides a type stable and efficient wrapper of arbitrary functions.

The Compat package is designed to ease interoperability between older and newer versions of the Julia language. The Compat package provides a macro that lets you use the latest syntax in a backwards-compatible way.

Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.

libwhich is like which, but for dynamic libraries. It is also a bit like ldd and otool -L.

This package provides the backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications.

This package provides a Jupyter Server extension for serving Mathjax, the JavaScript display engine for mathematics.

Leveraging the Jupyter interactive widgets framework, ipympl enables the interactive features of matplotlib in the Jupyter notebook and in JupyterLab.

The jupyterlite-core package provides the core functionality for building JupyterLite websites, the jupyter-lite CLI, and extension points for authoring custom addons.

This package contains a syntax coloring theme for pygments making use of the JupyterLab CSS variables.

This package provides a Qt-based console for Jupyter with support for rich media output.

This package provides a multi-language server WebSocket proxy for Jupyter Notebook/Lab server. It provides coding assistance for JupyterLab (code navigation, hover suggestions, linters, autocompletion, and rename) using the Language Server Protocol.

This package provides a Jupyter Server extension providing terminals.

This package opens a notebook, strips its output, and writes the outputless version to the original file.

This project provides a way for JupyterLab and other frontends to switch to Jupyter Server for their Python Web application backend.

This module installs a Jupyter kernel for SPARQL. It allows sending queries to an SPARQL endpoint, fetching and presenting the results in a notebook.

This package provides a hatch plugin to help build Jupyter packages.

This package provides a set of widgets to help facilitate reuse of large datasets across widgets.

This package provides tools to help build and install Jupyter Python packages that require a pre-build step that may include JavaScript build steps.

xeus is a library meant to facilitate the implementation of kernels for Jupyter. It takes the burden of implementing the Jupyter Kernel protocol so developers can focus on implementing the interpreter part of the kernel.

Several Jupyter kernels are built upon xeus, such as xeus-cling, a kernel for the C++ programming language, and xeus-python, an alternative Python kernel for Jupyter.

This package provides the IPython kernel for Jupyter.