TimerOutputs is a small Julia package that is used to generate formatted output from timings made in different sections of a program. It's main functionality is the @timeit macro, similar to the @time macro in Base except one also assigns a label to the code section being timed. Multiple calls to code sections with the same label (and in the same "scope") will accumulate the data for that label. After the program has executed, it is possible to print a nicely formatted table presenting how much time, allocations and number of calls were made in each section. The output can be customized as to only show the things you are interested in.

TerminalLoggers provides a logger type TerminalLogger which can format your log messages in a richer way than the default ConsoleLogger which comes with the julia standard Logging library.

This package provides basic arithmetic, integration, differentiation, evaluation, and root finding over dense univariate polynomials.

LoggingExtras is designs around allowing you to build arbitrarily complicated systems for "log plumbing". That is to say basically routing logged information to different places. It is built around the idea of simple parts which are composed together, to allow for powerful and flexible definition of your logging system.

An alternative to the @__DIR__ macro. Packages that wish to reference paths in their project directory run into issues with relocatability when used in conjunction with PackageCompiler.

Update deeply nested immutable structs.

This is what I wish Base.BufferStream was.

This is a slightly modified version of the standalone Rmath library from R, built to be used with the Rmath.jl Julia package. The main difference is that it is built to allow defining custom random number generating functions via C function pointers (see include/callback.h). When using the library, these should be defined before calling any of the random functions.

This implementation of Glob is based on the IEEE Std 1003.1, 2004 Edition (Open Group Base Specifications Issue 6) for fnmatch and glob.

This package allows one to use conda as a cross-platform binary provider for Julia for other Julia packages, especially to install binaries that have complicated dependencies like Python.

Easy regression testing for visual packages. Automated tests compare similarity between a newly generated image and a reference image using the Images package. While in interactive mode, the tests can optionally pop up a Gtk GUI window showing a side-by-side comparison of the test and reference image, and then optionally overwrite the reference image with the test image. This allows for straightforward regression testing of image data, even when the "correct" images change over time.

HTTP.jl is a Julia library for HTTP Messages, implementing both a client and a server.

This package provides an archive of functions that emulate R's d-p-q-r functions for probability distributions. It is a wrapper around rmath for Julia.

julia-jwas is an open-source software tool written in Julia for Bayesian multiple regression methods applied to genomic prediction and genome-wide association studies.

Packages are installed to a Prefix; a folder that acts similar to the /usr/local directory on Unix-like systems, containing a bin folder for binaries, a lib folder for libraries, etc... Prefix objects can have tarballs install()'ed within them, uninstall()'ed from them, etc...

Makie is a data visualization ecosystem for the Julia programming language.

This package provides a math library with extended precision floats and complex types.

This package contains simple routines for finding roots, or zeros, of scalar functions of a single real variable using floating-point math.

This package provides an enhancement to Julia piping syntax.

This package provides package developers an alternative option to delay package loading until used. If some dependency is not used, then users don't need to pay for its latency.

SnoopCompile observes the Julia compiler, causing it to record the functions and argument types it's compiling. From these lists of methods, you can generate lists of precompile directives that may reduce the latency between loading packages.

Easy memoization for Julia.