This package provides some common helper functions that make it easier to implement various Base.show functions for types that participate in the TableTraits.jl ecosystem.

This package provides a method to ensure that arguments to a function conform to a specification.

This package provides special mathematical functions, including Bessel, Hankel, Airy, error, Dawson, exponential (or sine and cosine) integrals, eta, zeta, digamma, inverse digamma, trigamma, and polygamma functions.

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.

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

Inflate provides a pure Julia implementation of zlib decompression functionality, with both in- memory and streaming interfaces. This covers decompression of the Deflate algorithm and the Zlib and Gzip wrapper formats, as specified in RFC 1950, RFC 1951, and RFC 1952.

This minimalistic package serves as the foundation for working with colors in Julia. It defines basic color types and their constructors, and sets up traits and show methods to make them easier to work with.

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 set of custom string types of various fixed sizes. Each inline string is a custom primitive type and can benefit from being stack friendly by avoiding allocations/heap tracking in the GC. When used in an array, the elements are able to be stored inline since each one has a fixed size. Currently support inline strings from 1 byte up to 255 bytes.

This package is intended as a lightweight foundation for tensor operations across the Julia ecosystem. Currently it exports three operations: hadamard, tensor, and boxdot.

This package provides a lightweight string parsing and representation of angles.

Static.jl defines a limited set of statically parameterized types and a common interface that is shared between them.

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.

MsgPack.jl is a MessagePack implementation in pure Julia, with type-driven, overloadable packing/unpacking functionality.

This package implements OrderedDicts and OrderedSets, which are similar to containers in base Julia. However, during iteration the Ordered* containers return items in the order in which they were added to the collection.

This package provides a minimal String type for Julia that allows for efficient string representation and transfer

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

This package provides number datatypes which store their values in type parameters, making them runtime constants.

This package generates formatted output from timings made in different sections of a program.

Extents.jl is a small package that defines an Extent object that can be used by the different Julia spatial data packages. Extent is a wrapper for a NamedTuple of tuples holding the lower and upper bounds for each dimension of a object.

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

This package is the counterpart of AbstractArray interface, but for GPU array types. It provides functionality and tooling to speed-up development of new GPU array types. This package is not intended for end users; instead, you should use one of the packages that builds on GPUArrays.jl, such as CUDA.jl, oneAPI.jl or AMDGPU.jl.

This package provides various examples.

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.