This package provides macros for defining the required behaviours of Julia interfaces, and stating that an object implements them.

BSON.jl is a Julia package for working with the Binary JSON serialisation format. It can be used as a general store for Julia data structures.

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 provides consistent and extensible functional programming infrastructures, and metaprogramming facilities.

AstroTime.jl provides a high-precision, time-scale aware, DateTime-like data type which supports all commonly used astronomical time scales.

The Tables.jl package provides simple, yet powerful interface functions for working with all kinds tabular data.

ArnoldiMethod.jl provides an iterative method to find a few approximate solutions to the eigenvalue problem in standard form with main goals:

• Having a native Julia implementation of the eigs function that performs as well as ARPACK. With native we mean that its implementation should be generic and support any number type. Currently the partialschur function does not depend on LAPACK, and removing the last remnants of direct calls to BLAS is in the pipeline.

• Removing the dependency of the Julia language on ARPACK. This goal was already achieved before the package was stable enough, since ARPACK moved to a separate repository Arpack.jl.

This package provides a namespace for data-related generic function definitions to solve the optional dependency problem; packages wishing to share and/or extend functions can avoid depending directly on each other by moving the function definition to DataAPI.jl and each package taking a dependency on it.

This package provides representations for infinity and negative infinity in Julia.

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

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.

Julia macros for suppressing and/or capturing output (stdout), warnings (stderr) or both streams at the same time.

The SortingAlgorithms package provides three sorting algorithms that can be used with Julia's standard sorting API: heapsort, timsort and radixsort.

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

HTTP.jl is a Julia library for HTTP Messages, implementing both a client and a server.

This package will provide a library of functions useful for machine learning, such as softmax, sigmoid, convolutions and pooling. It doesn't provide any other "high-level" functionality like layers or AD.

This package provides primitive differentiation rules that can be composed via various formulations of the chain rule. Using DiffRules, new differentiation rules can defined, query whether or not a given rule exists, and symbolically apply rules to simple Julia expressions.

This package provides various examples.

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

This package allows you to reduce the latency of the first execution of Julia code. It is applicable to both package developers and end users in their personal workflows.

This is a Julia interface to libquadmath, providing a Float128 type corresponding to the IEEE754 binary128 floating point format.

OffsetArrays.jl provides Julia users with arrays that have arbitrary indices, similar to those found in some other programming languages like Fortran.

This package allows multiple FFT packages to co-exist with the same underlying fft(x) and plan_fft(x) interface. It is mainly not intended to be used directly. Instead, developers of packages that implement FFTs (such as FFTW.jl or FastTransforms.jl) extend the types/functions defined in AbstractFFTs.

This package only contains and exports a single function realdot(x, y). It computes real(LinearAlgebra.dot(x, y)) while avoiding computing the imaginary part of LinearAlgebra.dot(x, y) if possible. The real dot product is useful when one treats complex numbers as embedded in a real vector space.