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.

Optimisers.jl defines many standard gradient-based optimisation rules, and tools for applying them to deeply nested models.

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.

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.

The aim of this package is to provide users with a set of small generic routines useful above all in astronomical and astrophysical context, written in Julia.

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.

This package provides a functionality to calculate Earth orientation parameters with data retrieved from IERS.

This package supports representing banded matrices by only the entries on the bands.

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

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

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.

Crayons is a package that makes it simple to write strings in different colors and styles to terminals. It supports the 16 system colors, both the 256 color and 24 bit true color extensions, and the different text styles available to terminals.

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 simple and flexible IR format, expressive enough to work with both lowered and typed Julia code, as well as external IRs. It can be used with Julia metaprogramming tools such as Cassette.

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

This package provides a fast, extensible progress bar for Julia. This can help users track the progress of long-running tasks.

This package is intended to implement a "minimal" foundation for intervals upon which other packages might build. In particular, we encourage type-piracy for the reason that only one interval package can unambiguously define the .. and ± operators.

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

This package provides definitions for most of the primary types and functions in StaticArrays.jl. This enables downstream packages to implement new methods on these types without depending on the entirety of StaticArrays.jl.

This package provides the StructTypes.StructType trait for Julia types to declare the kind of "struct" they are, providing serialization/deserialization packages patterns and strategies to automatically construct objects.

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

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.

This package is made to be included into packages that just need the ffmpeg binaries + executables, and don't want the overhead of VideoIO.jl.

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.