Configurations.jl provides a macro @option to let you define structs to represent options/configurations, and serialize between different option/configuration file formats such as TOML.

This package provides a wide array of functions for dealing with color. This includes conversion between colorspaces, measuring distance between colors, simulating color blindness, parsing colors, and generating color scales for graphics.

This package provides a documentation generator for Julia.

This is a small package to make it easier to type LaTeX equations in string literals in the Julia language.

Measurements.jl is an error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations, operations with arrays, and numerical integration. The linear error propagation theory is employed to propagate the errors.

The package provides a light-weight dependency for defining sensitivities for functions without the need to depend on ChainRules itself.

This package provides a collection of useful bit-twiddling tricks, ready to use as functions, with detailed documentation and example real-world use cases.

This package has the purpose to print data in matrices in a human-readable format.

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

The VersionParsing package implements flexible parsing of version-number strings into Julia's built-in VersionNumber type, via the vparse(string) function. Unlike the VersionNumber(string) constructor, vparse(string) can handle version-number strings in a much wider range of formats than are encompassed by the semver standard. This is useful in order to support VersionNumber comparisons applied to "foreign" version numbers from external packages.

ImageCore is the lowest-level component of the system of packages designed to support image processing and computer vision.

This package contains generic helper algorithms for building plotting components.

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

Showoff provides an interface for consistently formatting an array of n things, e.g. numbers, dates, unitful values. It's used in Gadfly, Plots and Makie to label axes and keys.

This package implements handy macros @recipe and @series which will define a custom transformation and attach attributes for user types. Its design is an attempt to simplify and generalize the summary and display of types and data from external packages. With this package it is possible to describe visualization routines that can be used as components in more complex visualizations.

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.

Tracker.jl previously provided Flux.jl with automatic differentiation for its machine learning platform.

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

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

This package implements a variety of data structures, including, CircularBuffer, Queue, Stack, Accumulators, LinkedLists, SortedDicts and many others.

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

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

This package implements "lazy" in-place elementwise transformations of arrays for the Julia programming language. Explicitly, it provides a "view" M of an array A so that M[i] = f(A[i]) for a specified (but arbitrary) function f, without ever having to compute M explicitly (in the sense of allocating storage for M). The name of the package comes from the fact that M == map(f, A).

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.