This package defines the BFloat16 data type. The only currently available hardware implementation of this datatype are Google's Cloud TPUs. As such, this package is suitable to evaluate whether using TPUs would cause precision problems for any particular algorithm, even without access to TPU hardware. Note that this package is designed for functionality, not performance, so this package should be used for precision experiments only, not performance experiments.

This package provides tools for working with categorical variables, both with unordered (nominal variables) and ordered categories (ordinal variables), optionally with missing values.

JSON.jl is a pure Julia module which supports parsing and printing JSON documents.

This package allows you to query the availability of specific CPU features with low run-time cost.

SplitApplyCombine.jl provides high-level, generic tools for manipulating data - particularly focussing on data in nested containers. An emphasis is placed on ensuring split-apply-combine strategies are easy to apply, and work reliably for arbitrary iterables and in an optimized way with the data structures included in Julia's standard library.

This package defines functions for getting multiple indices out of dictionaries, tuples, etc, extending this ability beyond AbstractArray.

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.

This package implements image show methods suitable for graphical platforms such as IJulia. It is intended to provide convenient inline presentation of greyscale or color images.

This package aims to offer a standard set of Geometry types, which easily work with metadata, query frameworks on geometries and different memory layouts. The aim is to create a solid basis for Graphics/Plotting, finite elements analysis, Geo applications, and general geometry manipulations - while offering a Julian API, that still allows performant C-interop.

This package supports lazy analogues of array operations like vcat, hcat, and multiplication. This helps with the implementation of matrix-free methods for iterative solvers.

This package provides the IOCapture.capture(f) function, which captures the standard output and standard error, and returns it as a string together with the return value.

This package provides Julia implementations of the Standard Clausen functions and Glaisher-Clausen functions of integer order for real or complex arguments.

This package contains utilities for setting up documentation generation with Documenter.jl.

This package implements various 3D rotation parameterizations and defines conversions between them. At their heart, each rotation parameterization is a 3×3 unitary (orthogonal) matrix (based on the StaticArrays.jl package), and acts to rotate a 3-vector about the origin through matrix-vector multiplication.

This package takes a string or buffer containing Julia code, performs lexical analysis and returns a stream of tokens.

This package implements a trait-based framework for describing array layouts such as column major, row major, etc. that can be dispatched to appropriate BLAS or optimised Julia linear algebra routines. This supports a much wider class of matrix types than Julia's in-built StridedArray.

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.

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

AxisAlgorithms is a collection of filtering and linear algebra algorithms for multidimensional arrays. For algorithms that would typically apply along the columns of a matrix, you can instead pick an arbitrary axis (dimension).

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 package implements a variety of interpolation schemes for the Julia language. It has the goals of ease-of-use, broad algorithmic support, and exceptional performance.

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

This package provides reader/writer for delimited text data, as comma-delimited (csv), tab-delimited (tsv), or otherwise.

This package allows programmers to explicitly SIMD-vectorize their Julia code. By exposing SIMD vector types and corresponding operations, the programmer can explicitly vectorize their code. While this does not guarantee that the generated machine code is efficient, it relieves the compiler from determining whether it is legal to vectorize the code, deciding whether it is beneficial to do so, and rearranging the code to synthesize vector instructions.