This package provides another JSON package for Julia, with a focus on speed and slick struct mapping.

This package provides a summary of available CPU features in Julia.

This package provides string distances in Julia. Distances are defined for AbstractStrings, and any iterator that define length(). The package also defines Distance "modifiers" that can be applied to any distance.

This Julia package provides several utilities for working with tree-like data structures. Most importantly, it defines the children method that any package that contains such a data structure may import and extend in order to take advantage of any generic tree algorithm in this package.

Astronomical https://www.atnf.csiro.au/people/mcalabre/WCS/ library for Julia. This package wraps the WCSLIB C library.

This package supports representing block-banded and banded-block-banded matrices by only storing the entries in the non-zero bands. A BlockBandedMatrix is a subtype of BlockMatrix of BlockArrays.jl whose layout of non-zero blocks is banded.

This package provides a Julia interface to the Matplotlib plotting library from Python, and specifically to the matplotlib.pyplot module. PyPlot uses the Julia PyCall package to call Matplotlib directly from Julia with little or no overhead (arrays are passed without making a copy).

BenchmarkTools.jl makes performance tracking of Julia code easy by supplying a framework for writing and running groups of benchmarks as well as comparing benchmark results.

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 the @cse macro, which performs common subexpression elimination.

Zygote provides source-to-source automatic differentiation (AD) in Julia, and is the next-generation AD system for the Flux differentiable programming framework.

The purpose of this package is to provide test problems for JuliaNLSolvers packages.

This package supports SI units and also many other unit system.

Various special functions based on log and exp moved from StatsFuns.jl into a separate package, to minimize dependencies. These functions only use native Julia code, so there is no need to depend on librmath or similar libraries.

A Julia package to contain non-standard matrix factorizations. At the moment it implements the QL, RQ, and UL factorizations, a combined Cholesky factorization with inverse, and polar decompositions. In the future it may include other factorizations such as the LQ factorization.

This package provides a framework for implementing statically sized arrays in Julia, using the abstract type StaticArraySize,T,N <: AbstractArrayT,N. Subtypes of StaticArray will provide fast implementations of common array and linear algebra operations.

This package provides an alternative interface for dictionaries in Julia, for improved productivity and performance.

This library generalizes and unifies the notion of measures used in Compose, Compose3D, and Escher. It allows building up and representing expressions involving differing types of units that are then evaluated, resolving them into absolute units.

This package provides a set of tools for working with tabular data in Julia. Its design and functionality are similar to those of Pandas from Python or data.frame, data.table and dplyr from R, making it a great general purpose data science tool, especially for those coming to Julia from R or Python.

The Schur decomposition is the workhorse for eigensystem analysis of dense matrices. The diagonal eigen-decomposition of normal (especially Hermitian) matrices is an important special case, but for non-normal matrices the Schur form is often more useful.

This package provides the @muladd macro. It automatically converts expressions with multiplications and additions or subtractions to calls with muladd which then fuse via FMA when it would increase the performance of the code. The @muladd macro can be placed on code blocks and it will automatically find the appropriate expressions and nest muladd expressions when necessary. In mixed expressions summands without multiplication will be grouped together and evaluated first but otherwise the order of evaluation of multiplications and additions is not changed.

This package is intended to implement a "minimal" foundation for intervals upon which other packages might build. In particular, we encourage type-piracy for the reason that only one interval package can unambiguously define the .. and ± operators.

This package provides an implementation of shifted arrays for Julia.

An IndirectArray is one that encodes data using a combination of an index and a value table. Each element is assigned its own index, which is used to retrieve the value from the value table. Among other uses, IndirectArrays can represent indexed images, sometimes called "colormap images" or "paletted images."