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).

This implements the notation .. for indexing arrays. It's similar to the Python ... in that it means "all of the columns before (or after)".

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

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

Common functional iterator patterns (formerly Iterators.jl).

ReverseDiff.jl is a fast and compile-able tape-based reverse mode AD, that implements methods to take gradients, Jacobians, Hessians, and higher-order derivatives of native Julia functions (or any callable object, really).

This package provides an interface for readable and writable references to an element of an array or dictionary in Julia.

This package provides a macro-based implementation of traits. The main idea behind traits is to group types outside the type-hierarchy and to make dispatch work with that grouping. The difference to Union-types is that types can be added to a trait after the creation of the trait, whereas Union types are fixed after creation.

This package provides a convenient function form of the conditional ifelse. It is similar to Core.ifelse but it is extendable.

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

The goal of RangeArrays is to provide efficient and convenient array data structures where the columns of the arrays are generated (on the fly) by Ranges.

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

This package provides a combinatorics library for Julia, focusing mostly (as of now) on enumerative combinatorics and permutations.

This package defines the Bijection data type. A Bijection data structure behaves similar to a Dict, however it prevents assigning the same value to two different keys.

This package provides the DiffResult type, which can be passed to in-place differentiation methods instead of an output buffer.

This package provides the @cse macro, which performs common subexpression elimination.

DeepDiffs.jl provides the deepdiff function, which finds and displays differences (diffs) between Julia data structures. It supports Vectors, Dicts, and Strings. When diffing dictionaries where values associated with a particular key may change, deepdiff will recurse into value to provide a more detailed diff.

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

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

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

LeapSeconds provides a functionality to return the difference between TAI and UTC or vice versa for a given date. For dates after 1972-01-01, this is the number of leap seconds.

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

This package provides manually managed memory buffers backed by NTuples in Julia.

ImageMetadata is a simple package providing utilities for working with images that have metadata attached. For example, you might want to associate an image with the date on which the picture was taken, or an MRI scan with patient data, or an astronomical image with sky coordinates and information about the detector used to acquire the image.