_ _ _ _(_)_ | (_) | (_) (_) | A fresh approach to technical computing _ _ _| |_ __ _ | | | | | | | |/ _` | | http://julialang.org | | |_| | | | (_| | | julia-users@googlegroups.com _/ |\__'_|_|_|\__'_| | #julia on freenode |__/ | [![Build Status](https://api.travis-ci.org/JuliaLang/julia.png?branch=master)](https://travis-ci.org/JuliaLang/julia) ## 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](http://julialang.org/). This is the GitHub repository of Julia source code, including instructions for compiling and installing Julia, below. - **Homepage:** - **Binaries:** - **Documentation:** - **Packages:** - **Source code:** - **Git clone URL:** - **Mailing lists:** - **IRC:** The mailing list for developer discussion is . 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](https://github.com/JuliaLang/julia/blob/master/CONTRIBUTING.md) 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](#Required-Build-Tools-External-Libraries). 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. If you need to build Julia in an environment that does not allow access to the outside world, 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 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](http://julialang.org/manual/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](http://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](https://github.com/JuliaLang/julia/blob/master/README.windows.md). ### Vagrant Julia can be developed in an isolated Vagrant environment. See [the Vagrant README](https://github.com/JuliaLang/julia/blob/master/contrib/vagrant/README.md) for details. ## Required Build Tools and External Libraries Building Julia requires that the following software be installed: - **[GNU make]** — building dependencies. - **[gcc & g++][gcc]** or **[Clang][clang]** — compiling and linking C, C++ (if clang, need at least v3.1, Xcode 4.3.3 on OS X) - **[gfortran][gcc]** — 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)](http://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms) library, based on [Kazushige Goto's](http://en.wikipedia.org/wiki/Kazushige_Goto) famous [GotoBLAS](http://www.tacc.utexas.edu/tacc-projects/gotoblas2/). 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. [GNU make]: http://www.gnu.org/software/make/ [patch]: http://www.gnu.org/software/patch/ [wget]: http://www.gnu.org/software/wget/ [m4]: http://www.gnu.org/software/m4/ [gcc]: http://gcc.gnu.org/ [clang]: http://clang.llvm.org/ [curl]: http://curl.haxx.se/ [git]: http://git-scm.com/ [perl]: http://www.perl.org/ [OpenLibm]: https://github.com/JuliaLang/openlibm [DSFMT]: http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/SFMT/#dSFMT [OpenBLAS]: https://github.com/xianyi/OpenBLAS [LAPACK]: http://www.netlib.org/lapack/ [MKL]: http://software.intel.com/en-us/articles/intel-mkl/ [SuiteSparse]: http://www.cise.ufl.edu/research/sparse/SuiteSparse/ [AMOS]: http://netlib.org/amos [ARPACK]: http://forge.scilab.org/index.php/p/arpack-ng/ [FFTW]: http://www.fftw.org/ [PCRE]: http://www.pcre.org/ [LLVM]: http://www.llvm.org/ [FemtoLisp]: https://github.com/JeffBezanson/femtolisp [readline]: http://cnswww.cns.cwru.edu/php/chet/readline/rltop.html [GMP]: http://gmplib.org/ [MPFR]: http://www.mpfr.org/ [double-conversion]: http://double-conversion.googlecode.com/ [Rmath]: http://cran.r-project.org/doc/manuals/R-admin.html#The-standalone-Rmath-library [libuv]: https://github.com/JuliaLang/libuv ### 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](http://julialang.org/downloads/). 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](http://julialang.org/manual/getting-started) in the manual. The following distributions include julia, but the versions may be out of date due to rapid development: * [Arch Linux package](https://aur.archlinux.org/packages.php?ID=56877) * [Debian GNU/Linux](http://packages.debian.org/sid/julia) * [Ubuntu](http://packages.ubuntu.com/raring/julia) * [OS X Homebrew](http://mxcl.github.com/homebrew/) ## Editor and Terminal Setup Currently, Julia editing mode support is available for Emacs, Vim, Textmate, Sublime Text, 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