This package provides basic arithmetic, integration, differentiation, evaluation, and root finding over dense univariate polynomials.

Minimal package which enables to add custom gradients to Zygote, without depending on Zygote itself.

This package provides a functionality of files download with cURL, wget or HTTP.jl backends.

This package provides the DiffResult type, which can be passed to in-place differentiation methods instead of an output buffer.

This package provides the Observables type in Julia, which are like Refs but you can listen to changes.

Quaternions are best known for their suitability as representations of 3D rotational orientation. They can also be viewed as an extension of complex numbers.

This package provides a wrapper around ImageMagick version 6. It was split off from Images.jl to make image I/O more modular.

The goal of RangeArrays is to provide efficient and convenient array data structures where the columns of the arrays are generated (on the fly) by Ranges.

This package implements methods to take derivatives, gradients, Jacobians, Hessians, and higher-order derivatives of native Julia functions (or any callable object, really) using forward mode automatic differentiation (AD).

This package provides package developers an alternative option to delay package loading until used. If some dependency is not used, then users don't need to pay for its latency.

This package provides the StructTypes.StructType trait for Julia types to declare the kind of "struct" they are, providing serialization/deserialization packages patterns and strategies to automatically construct objects.

This package provides generic methods and modules used in many of the other BioJulia packages. This package defines IO, exceptions, and other types or methods used by other BioJulia packages.

This package contains Julia macros that enable JLL packages to generate themselves. It is not intended to be used by users, but rather is used in autogenerated packages via BinaryBuilder.jl.

This package provides a development environment and REPL interaction package for Julia in the spirit of Common Lisp’s SLIME and Clojure’s CIDER. It enables convenient and dynamic REPL-driven development.

This package provides a wrapper for libsass. It is an autogenerated source package constructed using BinaryBuilder.jl. The originating build_tarballs.jl script can be found on the community build tree Yggdrasil.

LightGraphs offers both (a) a set of simple, concrete graph implementations -- Graph (for undirected graphs) and DiGraph (for directed graphs), and (b) an API for the development of more sophisticated graph implementations under the AbstractGraph type.

ReverseDiff.jl is a fast and compile-able tape-based reverse mode AD, that implements methods to take gradients, Jacobians, Hessians, and higher-order derivatives of native Julia functions (or any callable object, really).

The DualNumbers Julia package defines the Dual type to represent dual numbers, and supports standard mathematical operations on them. Conversions and promotions are defined to allow performing operations on combinations of dual numbers with predefined Julia numeric types.

LeapSeconds provides a functionality to return the difference between TAI and UTC or vice versa for a given date. For dates after 1972-01-01, this is the number of leap seconds.

CommonSolve.jl provides solve, init, solve!, and step! commands. By using the same definition, solver libraries from other completely different ecosystems can extend the functions and thus not clash with SciML if both ecosystems export the solve command.

When visualizing images, it is not uncommon to provide a 2D view of different image sources. For example, comparing multiple images of different sizes, getting a preview of machine learning dataset. This package aims to provide easy-to-use tools for such tasks.

TypedTables.jl provides two column-based storage containers: Table and FlexTable, both of which represent an array of NamedTuples. This package is designed to be lightweight, easy-to-use and fast, and presents a very minimal new interface to learn.

PaddedViews provides a simple wrapper type, PaddedView, to add "virtual" padding to any array without copying data. Edge values not specified by the array are assigned a fillvalue. Multiple arrays may be "promoted" to have common indices using the paddedviews function.

This holds the common solve, init, step!, and solve! commands. By using the same definition, solver libraries from other completely different ecosystems can extend the functions and thus not clash with SciML if both ecosystems export the solve command. The rules are that you must dispatch on one of your own types.