AstroTime.jl provides a high-precision, time-scale aware, DateTime-like data type which supports all commonly used astronomical time scales.

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

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

The @unpack and @pack! macros work to unpack types, modules, and dictionaries.

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.

This package provides generic methods and modules used in many of the other BioJulia packages. This package defines IO, exceptions, and other types or methods used by other BioJulia packages.

This module provides support for reading and writing ZIP archives in Julia.

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

RecursiveArrayTools.jl is a set of tools for dealing with recursive arrays like arrays of arrays.

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

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.

A block array is a partition of an array into blocks or subarrays. This package has two purposes. Firstly, it defines an interface for an AbstractBlockArray block arrays that can be shared among types representing different types of block arrays. The advantage to this is that it provides a consistent API for block arrays. Secondly, it also implements two different type of block arrays that follow the AbstractBlockArray interface. The type BlockArray stores each block contiguously while the type PseudoBlockArray stores the full matrix contiguously. This means that BlockArray supports fast non copying extraction and insertion of blocks while PseudoBlockArray supports fast access to the full matrix to use in in for example a linear solver.

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.

This package supports representing block-banded and banded-block-banded matrices by only storing the entries in the non-zero bands. A BlockBandedMatrix is a subtype of BlockMatrix of BlockArrays.jl whose layout of non-zero blocks is banded.

This package allows a few "forward" definitions for the DataValues.jl package that other packages can utilize for integration without having to take direct dependencies.

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.

ItemGraphs is a simple wrapper around LightGraphs that enables most common use case for graph-like data structures: with collection of items that are in relations between each other providing the shortest path between two items.

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.

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 allows you to reduce the latency of the first execution of Julia code. It is applicable to both package developers and end users in their personal workflows.

StatsBase.jl is a Julia package that provides basic support for statistics. Particularly, it implements a variety of statistics-related functions, such as scalar statistics, high-order moment computation, counting, ranking, covariances, sampling, and empirical density estimation.

The Compat package is designed to ease interoperability between older and newer versions of the Julia language. The Compat package provides a macro that lets you use the latest syntax in a backwards-compatible way.

SoftGlobalScope is a package for the Julia language that simplifies the variable scoping rules for code in global scope. It is intended for interactive shells to make it easier to work interactively with Julia, especially for beginners.

This package will provide a library of functions useful for machine learning, such as softmax, sigmoid, convolutions and pooling. It doesn't provide any other "high-level" functionality like layers or AD.