julia  1.1.1 About: Julia is a high-level, high-performance dynamic programming language for technical computing. It provides distributed parallel execution, numerical accuracy, and an extensive mathematical function library.  Fossies Dox: julia-1.1.1.tar.gz  ("inofficial" and yet experimental doxygen-generated source code documentation)
julia Documentation

### Some Fossies usage hints in advance:

1. To see the Doxygen generated documentation please click on one of the items in the steelblue colored "quick index" bar above or use the side panel at the left which displays a hierarchical tree-like index structure and is adjustable in width.
2. If you want to search for something by keyword rather than browse for it you can use the client side search facility (using Javascript and DHTML) that provides live searching, i.e. the search results are presented and adapted as you type in the Search input field at the top right.
3. Doxygen doesn't incorporate all member files but just a definable subset (basically the main project source code files that are written in a supported language). So to search and browse all member files you may visit the Fossies
4. julia-1.1.1.tar.gz contents page and use the Fossies standard member browsing features (also with source code highlighting and additionally with optional code folding).

Build status:

Code coverage:

## The Julia Language

Julia is a high-level, high-performance dynamic language for technical computing. The main homepage for Julia can be found at julialang.org. This is the GitHub repository of Julia source code, including instructions for compiling and installing Julia, below.

## Resources

New developers may find the notes in CONTRIBUTING helpful to start contributing to the Julia codebase.

## Currently Supported Platforms

Julia is built and tested regularly on the following platforms:

Operating System Architecture CI Binaries Support Level
Linux 2.6.18+ x86-64 (64-bit) Official
i686 (32-bit) Official
ARM v7 (32-bit) Official
ARM v8 (64-bit) Community
PowerPC (64-bit) Community
PTX (64-bit) External
macOS 10.8+ x86-64 (64-bit) Official
Windows 7+ x86-64 (64-bit) Official
i686 (32-bit) Official
FreeBSD 11.0+ x86-64 (64-bit) Official

All systems marked with ✓ for CI are tested using continuous integration for every commit. Systems with ✓ for binaries have official binaries available on the downloads page and are tested regularly. The PTX backend needs the CUDAnative.jl package. The systems listed here with neither CI nor official binaries are known to build and work, but ongoing support for those platforms is dependent on community efforts. It is possible that Julia will build and work on other platforms too, and we're always looking to improve our platform coverage. If you're using Julia on a platform not listed here, let us know!

First, make sure you have all the required dependencies installed. Then, acquire the source code by cloning the git repository:

git clone git://github.com/JuliaLang/julia.git


(If you are behind a firewall, you may need to use the https protocol instead of the git protocol:

git config --global url."https://".insteadOf git://

Be sure to also configure your system to use the appropriate proxy settings, e.g. by setting the https_proxy and http_proxy variables.)

By default you will be building the latest unstable version of Julia. However, most users should use the most recent stable version of Julia, which is currently the 1.0 series of releases. You can get this version by changing to the Julia directory and running

git checkout v1.0.2


Now run make to build the julia executable. To perform a parallel build, use make -j N and supply the maximum number of concurrent processes. (See Platform Specific Build Notes for details.) When compiled the first time, it will automatically download and build its external dependencies. This takes a while, but only has to be done once. If the defaults in the build do not work for you, and you need to set specific make parameters, you can save them in Make.user, and place the file in the root of your Julia source. The build will automatically check for the existence of Make.user and use it if it exists. Building Julia requires 5GiB of disk space and approximately 2GiB of virtual memory.

You can create out-of-tree builds of Julia by specifying make O=<build-directory> configure on the command line. This will create a directory mirror, with all of the necessary Makefiles to build Julia, in the specified directory. These builds will share the source files in Julia and deps/srccache. Each out-of-tree build directory can have its own Make.user file to override the global Make.user file in the top-level folder.

If you need to build Julia on a machine without internet access, use make -C deps getall to download all the necessary files. Then, copy the julia directory over to the target environment and build with make.

Note: The build process will fail badly if any of the build directory's parent directories have spaces or other shell meta-characters such as $ or : in their names (this is due to a limitation in GNU make). Once it is built, you can run the julia executable after you enter your julia directory and run ./julia  To run julia from anywhere you can: • add an alias (in bash: echo "alias julia='/path/to/install/folder/bin/julia'" >> ~/.bashrc && source ~/.bashrc), or • add a soft link to the julia executable in the julia directory to /usr/local/bin (or any suitable directory already in your path), or • add the julia directory to your executable path for this shell session (in bash: export PATH="$(pwd):$PATH" ; in csh or tcsh: set path= ($path $cwd ) ), or • add the julia directory to your executable path permanently (e.g. in .bash_profile), or • write prefix=/path/to/install/folder into Make.user and then run make install. If there is a version of Julia already installed in this folder, you should delete it before running make install. Now you should be able to run Julia like this: julia  If everything works correctly, you will see a Julia banner and an interactive prompt into which you can enter expressions for evaluation. (Errors related to libraries might be caused by old, incompatible libraries sitting around in your PATH. In this case, try moving the julia directory earlier in the PATH). Note that most of the instructions above apply to unix systems. Your first test of Julia determines whether your build is working properly. From the UNIX/Windows command prompt inside the julia source directory, type make testall. You should see output that lists a series of running tests; if they complete without error, you should be in good shape to start using Julia. You can read about getting started in the manual. If you are building a Julia package for distribution on Linux, OS X, or Windows, take a look at the detailed notes in DISTRIBUTING.md. ### Updating an existing source tree If you have previously downloaded julia using git clone, you can update the existing source tree using git pull rather than starting anew: cd julia git pull && make Assuming that you had made no changes to the source tree that will conflict with upstream updates, these commands will trigger a build to update to the latest version. #### General troubleshooting 1. Over time, the base library may accumulate enough changes such that the bootstrapping process in building the system image will fail. If this happens, the build may fail with an error like  *** This error is usually fixed by running 'make clean'. If the error persists, try 'make cleanall' *** As described, running make clean && make is usually sufficient. Occasionally, the stronger cleanup done by make cleanall is needed. 2. New versions of external dependencies may be introduced which may occasionally cause conflicts with existing builds of older versions. a. Special make targets exist to help wipe the existing build of a dependency. For example, make -C deps clean-llvm will clean out the existing build of llvm so that llvm will be rebuilt from the downloaded source distribution the next time make is called. make -C deps distclean-llvm is a stronger wipe which will also delete the downloaded source distribution, ensuring that a fresh copy of the source distribution will be downloaded and that any new patches will be applied the next time make is called. b. To delete existing binaries of julia and all its dependencies, delete the ./usr directory in the source tree. 3. If you've updated OS X recently, be sure to run xcode-select --install to update the command line tools. Otherwise, you could run into errors for missing headers and libraries, such as ld: library not found for -lcrt1.10.6.o. 4. If you've moved the source directory, you might get errors such as CMake Error: The current CMakeCache.txt directory ... is different than the directory ... where CMakeCache.txt was created., in which case you may delete the offending dependency under deps 5. In extreme cases, you may wish to reset the source tree to a pristine state. The following git commands may be helpful:  git reset --hard #Forcibly remove any changes to any files under version control git clean -x -f -d #Forcibly remove any file or directory not under version control To avoid losing work, make sure you know what these commands do before you run them. git will not be able to undo these changes! ## Uninstalling Julia Julia does not install anything outside the directory it was cloned into. Julia can be completely uninstalled by deleting this directory. Julia packages are installed in ~/.julia by default, and can be uninstalled by deleting ~/.julia. ## Platform-Specific Build Notes ### Linux #### General • GCC version 4.7 or later is required to build Julia. • To use external shared libraries not in the system library search path, set USE_SYSTEM_XXX=1 and LDFLAGS=-Wl,-rpath,/path/to/dir/contains/libXXX.so in Make.user. • Instead of setting LDFLAGS, putting the library directory into the environment variable LD_LIBRARY_PATH (at both compile and run time) also works. • The USE_SYSTEM_* flags should be used with caution. These are meant only for troubleshooting, porting, and packaging, where package maintainers work closely with the Julia developers to make sure that Julia is built correctly. Production use cases should use the officially provided binaries. Issues arising from the use of these flags will generally not be accepted. • See also the external dependencies. #### Architecture Customization Julia can be built for a non-generic architecture by configuring the ARCH Makefile variable. See the appropriate section of Make.inc for additional customization options, such as MARCH and JULIA_CPU_TARGET. For example, to build for Pentium 4, set MARCH=pentium4 and install the necessary system libraries for linking. On Ubuntu, these may include lib32gfortran-6-dev, lib32gcc1, and lib32stdc++6, among others. You can also set MARCH=native for a maximum-performance build customized for the current machine CPU. #### Ubuntu The julia-deps PPA contains updated packages for Julia dependencies if you want to use system libraries instead of having them downloaded and built during the build process. See System Provided Libraries. #### RHEL/CentOS 6 On RHEL/CentOS 6 systems, the default compiler (gcc 4.4) is too old to build Julia. Install or contact your systems administrator to install a more recent version of gcc. The Scientific Linux Developer Toolset works well. #### Linux Build Troubleshooting Problem Possible Solution OpenBLAS build failure Set one of the following build options in Make.user and build again: • OPENBLAS_TARGET_ARCH=BARCELONA (AMD CPUs) or OPENBLAS_TARGET_ARCH=NEHALEM (Intel CPUs) Set OPENBLAS_DYNAMIC_ARCH = 0 to disable compiling multiple architectures in a single binary. • OPENBLAS_NO_AVX2 = 1 disables AVX2 instructions, allowing OpenBLAS to compile with OPENBLAS_DYNAMIC_ARCH = 1 using old versions of binutils • USE_SYSTEM_BLAS=1 uses the system provided libblas • Set LIBBLAS=-lopenblas and LIBBLASNAME=libopenblas to force the use of the system provided OpenBLAS when multiple BLAS versions are installed. If you get an error that looks like ../kernel/x86_64/dgemm_kernel_4x4_haswell.S:1709: Error: no such instruction: vpermpd$ 0xb1,%ymm0,%ymm0', then you need to set OPENBLAS_DYNAMIC_ARCH = 0 or OPENBLAS_NO_AVX2 = 1, or you need a newer version of binutils (2.18 or newer). (Issue #7653)

Illegal Instruction error Check if your CPU supports AVX while your OS does not (e.g. through virtualization, as described in this issue).

### OS X

You need to have the current Xcode command line utilities installed: run xcode-select --install in the terminal. You will need to rerun this terminal command after each OS X update, otherwise you may run into errors involving missing libraries or headers. You will also need a 64-bit gfortran to compile Julia dependencies. The gfortran-4.7 (and newer) compilers in Brew, Fink, and MacPorts work for building Julia.

Clang is now used by default to build Julia on OS X 10.7 and above. On OS X 10.6, the Julia build will automatically use gcc. On current systems, we recommend that you install the command line tools as described above. Older systems do not have a separate command line tools package from Apple, and will require a full Xcode install. On these, you will need at least Xcode 4.3.3. In Xcode prior to v5.0, you can alternatively go to Preferences -> Downloads and select the Command Line Utilities. These steps will ensure that clang v3.1 is installed, which is the minimum version of clang required to build Julia.

If you have set LD_LIBRARY_PATH or DYLD_LIBRARY_PATH in your .bashrc or equivalent, Julia may be unable to find various libraries that come bundled with it. These environment variables need to be unset for Julia to work.

If you see build failures in OpenBLAS or if you prefer to experiment, you can use the Apple provided BLAS in vecLib by building with USE_SYSTEM_BLAS=1. Julia does not use the Apple provided LAPACK, as it is too old.

When building Julia, or its dependencies, libraries installed by third party package managers can redirect the compiler to use an incompatible version of the software it is looking for. One example of this happening is when a piece of software called the "linker" gives an error involving "Undefined symbols." If that happens, you can usually figure out what software package is causing the error from the names in the error text. This sort of error can be bypassed by, temporarily, uninstalling the offending package. If the offending package cannot be uninstalled by itself, it may be possible to just uninstall the development headers (for example: a package ending in "-dev" in Fink).

### FreeBSD

Clang is the default compiler on FreeBSD 11.0-RELEASE and above. The remaining build tools are available from the Ports Collection, and can be installed using pkg install git gcc gmake cmake pkgconf. To build Julia, simply run gmake. (Note that gmake must be used rather than make, since make on FreeBSD corresponds to the incompatible BSD Make rather than GNU Make.)

As mentioned above, it is important to note that the USE_SYSTEM_* flags should be used with caution on FreeBSD. This is because many system libraries, and even libraries from the Ports Collection, link to the system's libgcc_s.so.1, or to another library which links to the system libgcc_s. This library declares its GCC version to be 4.6, which is too old to build Julia, and conflicts with other libraries when linking. Thus it is highly recommended to simply allow Julia to build all of its dependencies. If you do choose to use the USE_SYSTEM_* flags, note that /usr/local is not on the compiler path by default, so you may need to add LDFLAGS=-L/usr/local/lib and CPPFLAGS=-I/usr/local/include to your Make.user, though doing so may interfere with other dependencies.

Note that the x86 architecture does not support threading due to lack of compiler runtime library support, so you may need to set JULIA_THREADS=0 in your Make.user if you're on a 32-bit system.

### Windows

In order to build Julia on Windows, see README.windows.

### Vagrant

Julia can be developed in an isolated Vagrant environment. See the Vagrant README for details.

## Required Build Tools and External Libraries

Building Julia requires that the following software be installed:

• GNU make — building dependencies.
• gcc & g++ (>= 4.7) or Clang (>= 3.1, Xcode 4.3.3 on OS X) — compiling and linking C, C++.
• libatomic — provided by gcc and needed to support atomic operations.
• python (>=2.7) — needed to build LLVM.
• gfortran — compiling and linking Fortran libraries.
• perl — preprocessing of header files of libraries.
• wget, curl, or fetch (FreeBSD) — to automatically download external libraries.
• m4 — needed to build GMP.
• awk — helper tool for Makefiles.
• patch — for modifying source code.
• cmake (>= 3.4.3) — needed to build libgit2.
• pkg-config — needed to build libgit2 correctly, especially for proxy support.

On Debian-based distributions (e.g. Ubuntu), you can easily install them with apt-get:

sudo apt-get install build-essential libatomic1 python gfortran perl wget m4 cmake pkg-config


Julia uses the following external libraries, which are automatically downloaded (or in a few cases, included in the Julia source repository) and then compiled from source the first time you run make:

• LLVM (6.0 + patches) — compiler infrastructure (see note below).
• FemtoLisp — packaged with Julia source, and used to implement the compiler front-end.
• libuv (custom fork) — portable, high-performance event-based I/O library.
• OpenLibm — portable libm library containing elementary math functions.
• DSFMT — fast Mersenne Twister pseudorandom number generator library.
• OpenBLAS — fast, open, and maintained basic linear algebra subprograms (BLAS) library, based on Kazushige Goto's famous GotoBLAS (see note below).
• LAPACK (>= 3.5) — library of linear algebra routines for solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue problems, and singular value problems.
• MKL (optional) – OpenBLAS and LAPACK may be replaced by Intel's MKL library.
• SuiteSparse (>= 4.1) — library of linear algebra routines for sparse matrices.
• PCRE (>= 10.00) — Perl-compatible regular expressions library.
• GMP (>= 5.0) — GNU multiple precision arithmetic library, needed for BigInt support.
• MPFR (>= 4.0) — GNU multiple precision floating point library, needed for arbitrary precision floating point (BigFloat) support.
• libgit2 (>= 0.23) — Git linkable library, used by Julia's package manager.
• curl (>= 7.50) — libcurl provides download and proxy support for Julia's package manager.
• libssh2 (>= 1.7) — library for SSH transport, used by libgit2 for packages with SSH remotes.
• mbedtls (>= 2.2) — library used for cryptography and transport layer security, used by libssh2
• utf8proc (>= 2.1) — a library for processing UTF-8 encoded Unicode strings.
• libosxunwind — clone of libunwind, a library that determines the call-chain of a program.

### Notes for distribution package maintainers

We understand that package maintainers will typically want to make use of system libraries where possible. Please refer to the above version requirements and additional notes below. It is strongly advised that package maintainers apply the patches included in the Julia repo for LLVM and other libraries, should they choose to use SYSTEM versions. A list of maintained Julia packages for various platforms is available at https://julialang.org/downloads/platform.html.

### System Provided Libraries

If you already have one or more of these packages installed on your system, you can prevent Julia from compiling duplicates of these libraries by passing USE_SYSTEM_...=1 to make or adding the line to Make.user. The complete list of possible flags can be found in Make.inc.

Please be aware that this procedure is not officially supported, as it introduces additional variability into the installation and versioning of the dependencies, and is recommended only for system package maintainers. Unexpected compile errors may result, as the build system will do no further checking to ensure the proper packages are installed.

### LLVM

The most complicated dependency is LLVM, for which we require additional patches from upstream (LLVM is not backward compatible).

For packaging Julia with LLVM, we recommend either:

• bundling a Julia-only LLVM library inside the Julia package, or
• adding the patches to the LLVM package of the distribution.
• A complete list of patches is available in deps/llvm.mk, and the patches themselves are in deps/patches/.
• The only Julia-specific patch is the lib renaming (llvm-symver-jlprefix.patch), which should not be applied to a system LLVM.
• The remaining patches are all upstream bug fixes, and have been contributed into upstream LLVM.

Using an unpatched or different version of LLVM will result in errors and/or poor performance. Though Julia can be built with newer LLVM versions, support for this should be regarded as experimental and not suitable for packaging.

### libuv

Julia uses a custom fork of libuv. It is a small dependency, and can be safely bundled in the same package as Julia, and will not conflict with the system library. Julia builds should not try to use the system libuv.

### BLAS and LAPACK

As a high-performance numerical language, Julia should be linked to a multi-threaded BLAS and LAPACK, such as OpenBLAS or ATLAS, which will provide much better performance than the reference libblas implementations which may be default on some systems.

### Intel MKL

For a 64-bit architecture, the environment should be set up as follows:

# bash
source /path/to/intel/bin/compilervars.sh intel64

Add the following to the Make.user file:

USE_INTEL_MKL = 1


It is highly recommended to start with a fresh clone of the Julia repository.

## Source Code Organization

The Julia source code is organized as follows:

base/          source code for the Base module (part of Julia's standard library)
stdlib/        source code for other standard library packages
contrib/       editor support for Julia source, miscellaneous scripts
deps/          external dependencies
doc/src/manual source for the user manual
doc/src/stdlib source for standard library function reference
src/           source for Julia language core
test/          test suites
ui/            source for various front ends
usr/           binaries and shared libraries loaded by Julia's standard libraries


## Binary Installation

If you would rather not compile the latest Julia from source, platform-specific tarballs with pre-compiled binaries are also available for download.

You can either run the julia executable using its full path in the directory created above, or add that directory to your executable path so that you can run the Julia program from anywhere (in the current shell session):

export PATH="$(pwd)/julia:$PATH"

Now you should be able to run Julia like this:

julia


On Windows, double-click usr/bin/julia.exe.

If everything works correctly, you will see a Julia banner and an interactive prompt into which you can enter expressions for evaluation. You can read about getting started in the manual.

Note: Although some system package managers provide Julia, such installations are neither maintained nor endorsed by the Julia project. They may be outdated and/or unmaintained. We recommend you use the official Julia binaries instead.

## Editor and Terminal Setup

Currently, Julia editing mode support is available for a number of editors. While Julia modes for Emacs, Sublime Text, and Vim have their own repos, others such as Textmate, Notepad++, and Kate, are in contrib/.

Two major IDEs are supported for Julia: Juno which is based on Atom and julia-vscode based on VS Code. A Jupyter notebooks interface is available through IJulia.

In the terminal, Julia makes great use of both control-key and meta-key bindings. To make the meta-key bindings more accessible, many terminal emulator programs (e.g., Terminal, iTerm, xterm`, etc.) allow you to use the alt or option key as meta. See the section in the manual on the Julia REPL for more details.