Extensions for Julia's docsystem.

Fast parsing machinery for basic types in Julia

Tools for building non-allocating pre-cached functions in Julia, allowing for GC-free usage of automatic differentiation in complex codes

Uniform Interface for positive definite matrices of various structures

Observable refs

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Functions generated at runtime without world-age issues or overhead

A framework for simulating viscous incompressible flows about arbitrary body shapes.

The Arnoldi Method with Krylov-Schur restart, natively in Julia.

Fast and differentiable implementations of matrix exponentials, Krylov exponential matrix-vector multiplications ("expmv"), KIOPS, ExpoKit functions, and more. All your exponential needs in SciML form.

Julia implementation of associative containers that preserve insertion order

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SparseArrays.jl is a Julia stdlib

This is what I wish `Base.@enum` was.

Simple, consistent interfaces for any codec.

Collective tools for metaprogramming on Julia Expr

Cunning tricks though the julia compiler internals

`@pack!` and `@unpack` macros

TAR files: create, list, extract them in pure Julia

Fixed point types for julia

Light-weight expression manipulation tools

Basic color definitions and traits

🏩🏠🌆🏨🌇🏦

A simple shared suite of common derivative definitions

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Julia package for various special functions based on `log` and `exp`.

Missing value support for Julia

A Julia package for calculating hypergeometric functions

Base library providing vectorization-tools (ie, SIMD) that other libraries are built off of.

Concatenated Array views in Julia.

Fast and simple nonlinear solvers for the SciML common interface. Newton, Broyden, Bisection, Falsi, and more rootfinders on a standard interface.

Translate Julia to JavaScript

Scratch spaces for all your persistent mutable data needs

A Julia package for representing block-banded matrices and banded-block-banded matrices

A Julia package for describing array layouts and more general fast linear algebra

Ask the CPU for cache sizes, SIMD feature support, a running hypervisor, and more.

Faster closure variable capture

Julia math built-ins which return NaN and accumulator functions which ignore NaN