Fast parsing machinery for basic types in Julia

Extensions for Julia's docsystem.

Mike's Little Intermediate Representation

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

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Functions generated at runtime without world-age issues or overhead

Interval Sets for Julia

Random Number Generators for the Julia Language.

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

A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers

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

Julia-based implementation of ellipsis array indexing notation `..`

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

Fixed point types for julia

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

Light-weight expression manipulation tools

Basic color definitions and traits

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A simple shared suite of common derivative definitions

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

Optimisers.jl defines many standard optimisers and utilities for learning loops.

A Julia package for describing domains as continuous sets of elements

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.

A library of noise processes for stochastic systems like stochastic differential equations (SDEs) and other systems that are present in scientific machine learning (SciML)

Resizeable multi-dimensional arrays for Julia

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

Scratch spaces for all your persistent mutable data needs