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               _
   _       _ _(_)_     |
  (_)     | (_) (_)    |   A fresh approach to technical computing
   _ _   _| |_  __ _   |
  | | | | | | |/ _` |  |          http://julialang.org
  | | |_| | | | (_| |  |       [email protected]
 _/ |\__'_|_|_|\__'_|  |           #julia on freenode
|__/                   |

Build Status

## 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.

The mailing list for developer discussion is http://groups.google.com/group/julia-dev/. All are welcome, but the volume of messages is higher, and the discussions tend to be more esoteric. New developers may find the notes in CONTRIBUTING helpful to start contributing to the Julia codebase.

## Currently Supported Platforms
  • GNU/Linux
  • Darwin/OS X
  • FreeBSD
  • Windows

All systems are supported with both x86/64 (64-bit) and x86 (32-bit) architectures.

 ## Source Download and Compilation

First, acquire the source code by cloning the git repository:

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

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

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

Next, enter the julia/ directory and run make to build the julia executable. To perform a parallel build, use make -j N and supply the maximum number of concurrent processes. 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. The build will automatically check for the existence of Make.user and use it if it exists. Building Julia requires 1.5GiB of diskspace and approximately 700MiB of virtual memory.

Note: the build process will not work if any of the build directory's parent directories have spaces in their names (this is due to a limitation in GNU make).

Once it is built, 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):

In bash:

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

In csh / tcsh:

set path= ( $path $cwd )

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. You can read about getting started in the manual.

## Uninstalling Julia

Julia does not install anything outside the directory it was cloned into. Julia can be completely uninstalled by deleting this directory.

 ## Platform-Specific Notes

Linux

GCC version 4.6 or later is recommended to build Julia.

If the build fails trying to compile OpenBLAS, set one of the following build options in Make.user and build again. Use OPENBLAS_TARGET_ARCH=BARCELONA on AMD CPUs, and OPENBLAS_TARGET_ARCH=NEHALEM on Intel CPUs.

On some Linux distributions you may need to change how the readline library is linked. If you get a build error involving readline, set USE_SYSTEM_READLINE=1 in Make.user.

On Ubuntu or Debian systems, if you get any errors related to ncurses, you need to apt-get install libncurses5-dev.

On CentOS 5 systems, the default compiler (gcc 4.1) is too old to build Julia.

OS X

It is essential to use a 64-bit gfortran to compile Julia dependencies. The gfortran-4.7 (and newer) compilers in brew and macports work for building Julia. If you do not use brew or macports, you can download and install gfortran and gcc from hpc.sf.net. The HPC gfortran requires gcc to function properly.

Clang is now used by default to build Julia on OS X (10.7 and above). Make sure to update to at least Xcode 4.3.3, and update to the latest command line tools from the Xcode preferences. This will ensure that clang v3.1 is installed, which is the minimum version of clang required to build Julia. On older systems, the Julia build will attempt to use gcc. The build also detects Snow Leopard and sets USE_SYSTEM_LIBM=1, USE_SYSTEM_BLAS=1, and USE_SYSTEM_LAPACK=1.

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.

FreeBSD

On FreeBSD Release 9.0, install the gcc46, git, and gmake packages/ports, and compile Julia with the command:

$ gmake FC=gfortran46

You must use the gmake command on FreeBSD instead of make.

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++ — compiling and linking C, C++
  • clang — clang is the default compiler on OS X (Need at least v3.1, Xcode 4.3.3 on OS X)
  • gfortran — compiling and linking fortran libraries
  • git — version control and package management.
  • perl — preprocessing of header files of libraries.
  • wget, curl, or fetch (FreeBSD) — to automatically download external libraries.
  • m4 — needed to build GMP.
  • patch — for modifying source code.

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 — compiler infrastructure.
  • FemtoLisp — packaged with Julia source, and used to implement the compiler front-end.
  • readline — library allowing shell-like line editing in the terminal, with history and familiar key bindings.
  • libuv — portable, high-performance event-based I/O library
  • OpenLibm — a portable libm library containing elementary math functions.
  • DSFMT — a fast Mersenne Twister pseudorandom number generator library.
  • OpenBLAS — a fast, open, and maintained basic linear algebra subprograms (BLAS) library, based on Kazushige Goto's famous GotoBLAS. The system provided BLAS and LAPACK are used on OS X.
  • LAPACK — a 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.
  • AMOS — subroutines for computing Bessel and Airy functions.
  • SuiteSparse — a library of linear algebra routines for sparse matrices.
  • ARPACK — a collection of subroutines designed to solve large, sparse eigenvalue problems.
  • FFTW — library for computing fast Fourier transforms very quickly and efficiently.
  • PCRE — Perl-compatible regular expressions library.
  • GMP — the GNU multiple precision arithmetic library, needed for bigint support.
  • MPFR — the GNU multiple precision floating point library, needed for arbitrary precision floating point support.
  • double-conversion — efficient number-to-text conversion.
  • Rmath — basic RNGs and distributions.

Build options for make

If you already have one or more of these packages installed on your system, it is possible to pass USE_SYSTEM_...=1 to make to prevent Julia from compiling duplicates of these libraries. 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 variablity 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.

SuiteSparse

SuiteSparse is a special case, since it is typically only installed as a static library, while USE_SYSTEM_SUITESPARSE=1 requires that it is a shared library. Running the script contrib/repackage_system_suitesparse4.make will copy your static system SuiteSparse installation into the shared library format required by Julia.

Intel Math Kernel Libraries

To use the Intel MKL BLAS and LAPACK libraries, edit the following settings in Make.inc:

USE_MKL = 1
MKLLIB = /path/to/mkl/lib/arch

MKLLIB points to the directory containing libmkl_rt.so. MKL version 10.3 or greater is required. To rebuild a pre-built Julia source install with MKL support, delete the OpenBLAS, ARPACK, and SuiteSparse dependencies from deps, and run make cleanall testall.

## Source Code Organization

The Julia source code is organized as follows:

base/          source code for Julia's standard library
contrib/       editor support for Julia source, miscellaneous scripts
deps/          external dependencies
examples/      example Julia programs
extras/        useful optional libraries
src/           source for Julia language core
test/          unit and functional test cases
ui/            source for various front ends
usr/           binaries and shared libraries loaded by Julia's standard libraries
## Binary Installation

Because of the rapid pace of development at this point, we recommend installing the latest Julia from source, but 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 julia.bat.

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.

The following distributions include julia, but the versions may be out of date due to rapid development:

## Editor and Terminal Setup

Currently, Julia editing mode support is available for Emacs, Vim, Textmate, Notepad++, and Kate, in contrib/

Adjusting your terminal bindings is optional; everything will work fine without these key bindings. For the best interactive session experience, however, make sure that your terminal emulator (Terminal, iTerm, xterm, etc.) sends the ^H sequence for Backspace (delete key) and that the Shift-Enter key combination sends a \n newline character to distinguish it from just pressing Enter, which sends a \r carriage return character. These bindings allow custom readline handlers to trap and correctly deal with these key sequences; other programs will continue to behave normally with these bindings. The first binding makes backspacing through text at the prompt behave more intuitively. The second binding allows Shift-Enter to insert a newline without evaluating the current expression, even when the current expression is complete. (Pressing an unmodified Enter inserts a newline if the current expression is incomplete, evaluates the expression if it is complete, or shows an error if the syntax is irrecoverably invalid.)

On Linux systems, the Shift-Enter binding can be set by placing the following line in the file .xmodmaprc in your home directory:

keysym Return = Return Linefeed