This package provides tools for working with the basic calculus operations of differentiation and integration. The Calculus package produces approximate derivatives by several forms of finite differencing or produces exact derivative using symbolic differentiation. It can also be used to compute definite integrals by different numerical methods.

This package provides a framework for implementing statically sized arrays in Julia, using the abstract type StaticArraySize,T,N <: AbstractArrayT,N. Subtypes of StaticArray will provide fast implementations of common array and linear algebra operations.

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

This package provides zlib codecs for TranscodingStreams.jl.

This package provides an interface to line search algorithms implemented in Julia.

This minimalistic package serves as the foundation for other SIMD packages in Julia.

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.

This package provides the @OptionalData macro and the corresponding OptData type which is a thin wrapper around a nullable value (of type UnionT, Nothing where T). It allows you to load and access globally available data at runtime in a type-stable way.

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.

This package provides a documentation generator for Julia.

This package provides a collection of useful extensions for Julia's built-in docsystem. These are features that are not yet mature enough to be considered for inclusion in Base, or that have sufficiently niche use cases that including them with the default Julia installation is not seen as valuable enough at this time.

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.

URIs.jl is a Julia package that allows parsing and working with URIs, as defined in RFC 3986.

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.

Jive.jl is a Julia package to help with writing tests.

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

The Tables.jl package provides simple, yet powerful interface functions for working with all kinds tabular data.

This package provides SentinelArrayT that wraps an AbstractArray of type T, and accepts a sentinel and value argument.

ReferenceTests.jl is a Julia package that adds a couple of additional macros to your testing toolbox. In particular, it focuses on functionality for testing values against reference files, which in turn the package can help create and update if need be.

This package generates formatted output from timings made in different sections of a program.

This package provides primitive differentiation rules that can be composed via various formulations of the chain rule. Using DiffRules, new differentiation rules can defined, query whether or not a given rule exists, and symbolically apply rules to simple Julia expressions.

This is a twin package to ImageCore with functions that are used among many of the packages in JuliaImages. The main purpose of this package is to reduce unnecessary compilation overhead from external dependencies.

This package provides Julia implementation of C-style interface to CFITSIO functions with following features:

• Function names closely mirror the C interface (e.g., fits_open_file()).

• Functions operate on FITSFile, a thin wrapper for fitsfile C struct (FITSFile has concept of "current HDU", as in CFITSIO).

• Wrapper functions do check the return status from CFITSIO and throw an error with the appropriate message.

TableTraits defines a generic interface for tabular data.