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 provides the ability to directly call and fully interoperate with Python from the Julia language. You can import arbitrary Python modules from Julia, call Python functions (with automatic conversion of types between Julia and Python), define Python classes from Julia methods, and share large data structures between Julia and Python without copying them.

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 set of tools for working with tabular data in Julia. Its design and functionality are similar to those of Pandas from Python or data.frame, data.table and dplyr from R, making it a great general purpose data science tool, especially for those coming to Julia from R or Python.

This package provides bit twiddling convenience functions in Julia. These are useful for going to the next or previous mask size or for calculating corresponding shifts.

This package provides a namespace for data-related generic function definitions to solve the optional dependency problem; packages wishing to share and/or extend functions can avoid depending directly on each other by moving the function definition to StatsAPI.jl and each package taking a dependency on it.

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 a documentation generator for Julia.

The goal of RangeArrays is to provide efficient and convenient array data structures where the columns of the arrays are generated (on the fly) by Ranges.

This package provides an implementation of shifted arrays for Julia.

This package provides string distances in Julia. Distances are defined for AbstractStrings, and any iterator that define length(). The package also defines Distance "modifiers" that can be applied to any distance.

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

This package just exports one type: the InvertedIndex, or Not for short. It can wrap any supported index type and may be used as an index into any AbstractArray subtype, including OffsetArrays.

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.

This package provides information about the features of the host CPU in Julia.

This package is the counterpart of AbstractArray interface, but for GPU array types. It provides functionality and tooling to speed-up development of new GPU array types. This package is not intended for end users; instead, you should use one of the packages that builds on GPUArrays.jl, such as CUDA.jl, oneAPI.jl or AMDGPU.jl.

This package defines the Bijection data type. A Bijection data structure behaves similar to a Dict, however it prevents assigning the same value to two different keys.

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 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 package provides support for decoding and encoding texts between multiple character encodings. It is currently based on the iconv interface, and supports all major platforms using GNU libiconv.

This package implements various 3D rotation parameterizations and defines conversions between them. At their heart, each rotation parameterization is a 3×3 unitary (orthogonal) matrix (based on the StaticArrays.jl package), and acts to rotate a 3-vector about the origin through matrix-vector multiplication.

Minimal package which enables to add custom gradients to Zygote, without depending on Zygote itself.

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 is intended as a lightweight foundation for tensor operations across the Julia ecosystem. Currently it exports three operations: hadamard, tensor, and boxdot.