This package provides macros for defining the required behaviours of Julia interfaces, and stating that an object implements them.

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 contains the testset from Julia, packaged into a loadable module.

This package was factored out of Plots.jl to allow any other plotting package to use the recipe pipeline. In short, the extremely lightweight RecipesBase.jl package can be depended on by any package to define "recipes": plot specifications of user-defined types, as well as custom plot types. RecipePipeline.jl contains the machinery to translate these recipes to full specifications for a plot.

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 compiles regular expressions into Julia code, which is then compiled into low-level machine code by the Julia compiler. The package is designed to generate very efficient code to scan large text data, which is often much faster than handcrafted code. Automa.jl can insert arbitrary Julia code that will be executed in state transitions. This makes it possible, for example, to extract substrings that match a part of a regular expression.

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

This package implements image show methods suitable for graphical platforms such as IJulia. It is intended to provide convenient inline presentation of greyscale or color images.

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

This package determines tabular file formats based on file extensions. It is intended to be the base both for TableIO.jl and for the Pluto.jl tabular data import functionality.

FuzzyCompletions provides fuzzy completions for a Julia runtime session.

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.

This package provides a lightweight string parsing and representation of angles.

This Julia package provides the adapt(T, x) function acts like convert(T, x), but without the restriction of returning a T. This allows you to "convert" wrapper types like Adjoint to be GPU compatible without throwing away the wrapper.

This package implements handy macros @recipe and @series which will define a custom transformation and attach attributes for user types. Its design is an attempt to simplify and generalize the summary and display of types and data from external packages. With this package it is possible to describe visualization routines that can be used as components in more complex visualizations.

This package provides a simple Julian API to use the libsass library to compile scss and sass files to css.

BufferedStreams.jl provides buffering for IO operations. It can wrap any IO type automatically making incremental reading and writing faster.

This package provides the IOCapture.capture(f) function, which captures the standard output and standard error, and returns it as a string together with the return value.

This package allows programmers to explicitly SIMD-vectorize their Julia code. By exposing SIMD vector types and corresponding operations, the programmer can explicitly vectorize their code. While this does not guarantee that the generated machine code is efficient, it relieves the compiler from determining whether it is legal to vectorize the code, deciding whether it is beneficial to do so, and rearranging the code to synthesize vector instructions.

This package provides support for the Woodbury matrix identity for the Julia programming language. This is a generalization of the Sherman-Morrison formula. Note that the Woodbury matrix identity is notorious for floating-point roundoff errors, so be prepared for a certain amount of inaccuracy in the result.

FixedPointNumbers.jl implements fixed-point number types for Julia. A fixed-point number represents a fractional, or non-integral, number. In contrast with the more widely known floating-point numbers, with fixed-point numbers the decimal point doesn't "float": fixed-point numbers are effectively integers that are interpreted as being scaled by a constant factor. Consequently, they have a fixed number of digits (bits) after the decimal (radix) point.

This package defines the BFloat16 data type. The only currently available hardware implementation of this datatype are Google's Cloud TPUs. As such, this package is suitable to evaluate whether using TPUs would cause precision problems for any particular algorithm, even without access to TPU hardware. Note that this package is designed for functionality, not performance, so this package should be used for precision experiments only, not performance experiments.

This is a small package to make it easier to type LaTeX equations in string literals in the Julia language.

This package supports SI units and also many other unit system.