This package provides definitions for common functions that are useful for symbolic expression manipulation in Julia. Its purpose is to provide a shared interface between various symbolic programming packages, for example SymbolicUtils.jl, Symbolics.jl, and Metatheory.jl.

A Julia package to contain non-standard matrix factorizations. At the moment it implements the QL, RQ, and UL factorizations, a combined Cholesky factorization with inverse, and polar decompositions. In the future it may include other factorizations such as the LQ factorization.

ArnoldiMethod.jl provides an iterative method to find a few approximate solutions to the eigenvalue problem in standard form with main goals:

• Having a native Julia implementation of the eigs function that performs as well as ARPACK. With native we mean that its implementation should be generic and support any number type. Currently the partialschur function does not depend on LAPACK, and removing the last remnants of direct calls to BLAS is in the pipeline.

• Removing the dependency of the Julia language on ARPACK. This goal was already achieved before the package was stable enough, since ARPACK moved to a separate repository Arpack.jl.

Showoff provides an interface for consistently formatting an array of n things, e.g. numbers, dates, unitful values. It's used in Gadfly, Plots and Makie to label axes and keys.

Inflate provides a pure Julia implementation of zlib decompression functionality, with both in- memory and streaming interfaces. This covers decompression of the Deflate algorithm and the Zlib and Gzip wrapper formats, as specified in RFC 1950, RFC 1951, and RFC 1952.

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

CommonSolve.jl provides solve, init, solve!, and step! commands. By using the same definition, solver libraries from other completely different ecosystems can extend the functions and thus not clash with SciML if both ecosystems export the solve command.

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

This package provides a macro-based implementation of traits. The main idea behind traits is to group types outside the type-hierarchy and to make dispatch work with that grouping. The difference to Union-types is that types can be added to a trait after the creation of the trait, whereas Union types are fixed after creation.

This package provides tools for transcoding data streams which are:

• fast: small overhead and specialized methods

• consistent: basic I/O operations work as expected

• generic: support any I/O objects like files, buffers, pipes, etc.

• extensible: easy definition for new codec to transcode data

PaddedViews provides a simple wrapper type, PaddedView, to add "virtual" padding to any array without copying data. Edge values not specified by the array are assigned a fillvalue. Multiple arrays may be "promoted" to have common indices using the paddedviews function.

This package provides some common helper functions that make it easier to implement various Base.show functions for types that participate in the TableTraits.jl ecosystem.

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.

An IndirectArray is one that encodes data using a combination of an index and a value table. Each element is assigned its own index, which is used to retrieve the value from the value table. Among other uses, IndirectArrays can represent indexed images, sometimes called "colormap images" or "paletted images."

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 very lightweight package provides primitive functions for construction of objects.

MutableArithmetics is a Julia package which allows:

• mutable types to implement mutable arithmetics

• algorithms that could exploit mutable arithmetics to exploit them while still being completely generic

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 provides an interface to line search algorithms implemented in Julia.

This package provides a documentation generator for Julia.

The purpose of this library is to solidify extensions to the current AbstractArray interface, which are put to use in package ecosystems like DifferentialEquations.jl. Since these libraries are live, this package will serve as a staging ground for ideas before they are merged into Base Julia. For this reason, no functionality is exported so that if such functions are added and exported in a future Base Julia, there will be no issues with the upgrade.

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 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 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.