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 supports SI units and also many other unit system.

This package enables the Markdown / MkDocs backend of Documenter.jl.

This package provides a Julia interface defining a collection of types (without instances) for implementing conventions about the scientific interpretation of data. This package makes a distinction between the machine type and the scientific type of a Julia object. A machine type refers to the Julia type being used to represent the object, for instance Float64. The scientific type refers to how the object should be interpreted, for instance Continuous or Multiclass3.

This package aims at establishing common ground for Optim.jl, LineSearches.jl, and NLsolve.jl. The common ground is mainly the types used to hold objective related callables, information about the objectives, and an interface to interact with these types.

Millboard.jl provides a library for getting data in a tablized format to arrange into rows and columns of cells.

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.

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.

StackViews provides only one array type: StackView. There are multiple ways to understand StackView:

• inverse of eachslice

• cat variant

• view object

• lazy version of repeat special case

The is package provides a variety of common utilities that can be used by downstream automatic differentiation (AD) tools to define and execute forward-, reverse-, and mixed-mode primitives.

FuzzyCompletions provides fuzzy completions for a Julia runtime session.

This package provides a Julia wrapper for astronomical library ERFA.

This package intends to provide a simple RNG with stable streams, suitable for tests in packages which need reproducible streams of random numbers across Julia versions. Indeed, the Julia RNGs provided by default are documented to have non-stable streams (which for example enables some performance improvements).

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.

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

This package exports following operations over bit vectors with extremely fast speed while keeping extra memory usage small:

• getindex(bv::IndexableBitVectors, i::Integer): i-th element of bv

• rank(b::Bool, bv::AbstractIndexableBitVector, i::Integer): the number of occurrences of bit b in bv[1:i]

• select(b::Bool, bv::AbstractIndexableBitVector, i::Integer): the index of i-th occurrence of b in bv.

and other shortcuts or types.

This module provides a Julia interface to GR, a framework for visualisation applications.

This package provides tools to help you develop code. Juno is built on the Atom text editor. Juno consists of both Julia and Atom packages in order to add Julia-specific enhancements, such as syntax highlighting, a plot pane, integration with Julia's debugger, a console for running code, and much more.

Consider that the package is “maintenance-only mode” and only receives bug fixes. The Julia IDE effort is pointed to extension for VSCode.

This package enables the Julia compiler to generate efficient code when running test cases. Test cases are typically run with flags that prevent efficient code generation. This package detects those flags and instead spawns a separate Julia process without the flags in which to run the test cases.

This package is designed to help in testing ChainRulesCore.frule and ChainRulesCore.rrule methods. The main entry points are ChainRulesTestUtils.frule_test, ChainRulesTestUtils.rrule_test, and ChainRulesTestUtils.test_scalar. Currently this is done via testing the rules against numerical differentiation (using FiniteDifferences.jl).

ChainRulesTestUtils.jl is separated from ChainRulesCore.jl so that it can be a test-only dependency, allowing it to have potentially heavy dependencies, while keeping ChainRulesCore.jl as light-weight as possible.

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.

Various special functions based on log and exp moved from StatsFuns.jl into a separate package, to minimize dependencies. These functions only use native Julia code, so there is no need to depend on librmath or similar libraries.

This package introduces the type StructArray which is an AbstractArray whose elements are struct (for example NamedTuples, or ComplexF64, or a custom user defined struct). While a StructArray iterates structs, the layout is column based (meaning each field of the struct is stored in a separate Array).

This package provides a pooled representation of arrays for purposes of compression when there are few unique elements.