These notes are for those wishing to compile a binary distribution of Julia for distribution on various platforms. We love users spreading Julia as far and wide as they can, trying it out on as wide an array of operating systems and hardware configurations as possible. As each platform has specific gotchas and processes that must be followed in order to create a portable, working Julia distribution, we have separated most of the notes by OS.
Note that while the code for Julia is MIT-licensed, with a few exceptions, the distribution created by the techniques described herein will be GPL licensed, as various dependent libraries such as
SuiteSparse are GPL licensed. We do hope to have a non-GPL distribution of Julia in the future.
The Makefile uses both the
VERSION file and commit hashes and tags from the git repository to generate the
base/version_git.jl with information we use to fill the splash screen and the
versioninfo() output. If you for some reason don't want to have the git repository available when building you should pregenerate the
base/version_git.jl file with:
make -C base version_git.jl.phony
Julia has lots of build dependencies where we use patched versions that has not yet been included by the popular package managers. These dependencies will usually be automatically downloaded when you build, but if you want to be able to build Julia on a computer without internet access you should create a full-source-dist archive with the special make target
that creates a julia-version-commit.tar.gz archive with all required dependencies.
When compiling a tagged release in the git repository, we don't display the branch/commit hash info in the splash screen. You can use this line to show a release description of up to 45 characters. To set this line you have to create a Make.user file containing:
override TAGGED_RELEASE_BANNER = "my-package-repository build"
By default, Julia optimizes its system image to the native architecture of the build machine. This is usually not what you want when building packages, as it will make Julia fail at startup on any machine with incompatible CPUs (in particular older ones with more restricted instruction sets).
We therefore recommend that you pass the
MARCH variable when calling
make, setting it to the baseline target you intend to support. This will determine the target CPU for both the Julia executable and libraries, and the system image (the latter can also be set using
JULIA_CPU_TARGET). Typically useful values for x86 CPUs are
core2 (for 64-bit builds) and
pentium4 (for 32-bit builds). Unfortunately, CPUs older than Pentium 4 are currently not supported (see this issue).
The full list of CPU targets supported by LLVM can be obtained by running
make binary-dist creates a tarball that contains a fully functional Julia installation. If you wish to create a distribution package such as a
.rpm, some extra effort is needed. See the julia-debian repository for an example of what metadata is needed for creating
.deb packages for Debian and Ubuntu-based systems. See the Fedora package for RPM-based distributions. Although we have not yet experimented with it, Alien could be used to generate Julia packages for various Linux distributions.
Julia supports overriding standard installation directories via
prefix and other environment variables you can pass when calling
make install. See Make.inc for their list.
DESTDIR can also be used to force the installation into a temporary directory.
By default, Julia loads
$prefix/etc/julia/startup.jl as an installation-wide initialization file. This file can be used by distribution managers to set up custom paths or initialization code. For Linux distribution packages, if
$prefix is set to
/usr, there is no
/usr/etc to look into. This requires the path to Julia's private
etc directory to be changed. This can be done via the
sysconfdir make variable when building. Simply pass
make when building and Julia will first check
/etc/julia/startup.jl before trying
To create a binary distribution on OSX, build Julia first, then cd to
contrib/mac/app, and run
make with the same makevars that were used with
make when building Julia proper. This will then create a
.dmg file in the
contrib/mac/app directory holding a completely self-contained Julia.app.
Alternatively, Julia may be built as a framework by invoking
make with the
darwinframework target and
DARWIN_FRAMEWORK=1 set. For example,
make DARWIN_FRAMEWORK=1 darwinframework.
Instructions for reating a Julia distribution on Windows are described in the build devdocs for Windows.
Julia builds OpenBLAS by default, which includes the BLAS and LAPACK libraries. On 32-bit architectures, Julia builds OpenBLAS to use 32-bit integers, while on 64-bit architectures, Julia builds OpenBLAS to use 64-bit integers (ILP64). It is essential that all Julia functions that call BLAS and LAPACK API routines use integers of the correct width.
Most BLAS and LAPACK distributions provided on linux distributions, and even commercial implementations ship libraries that use 32-bit APIs. In many cases, a 64-bit API is provided as a separate library.
When using vendor provided or OS provided libraries, a
make option called
USE_BLAS64 is available as part of the Julia build. When doing
make USE_BLAS64=0, Julia will call BLAS and LAPACK assuming a 32-bit API, where all integers are 32-bit wide, even on a 64-bit architecture.
Other libraries that Julia uses, such as SuiteSparse also use BLAS and LAPACK internally. The APIs need to be consistent across all libraries that depend on BLAS and LAPACK. The Julia build process will build all these libraries correctly, but when overriding defaults and using system provided libraries, this consistency must be ensured.
Also note that Linux distributions sometimes ship several versions of OpenBLAS, some of which enable multithreading, and others only working in a serial fashion. For example, in Fedora,
libopenblasp.so is threaded, but
libopenblas.so is not. We recommend using the former for optimal performance. To choose an OpenBLAS library whose name is different from the default
$(YOURBLAS) with the name of your library. You can also add
.so.0 to the name of the library if you want your package to work without requiring the unversioned
Finally, OpenBLAS includes its own optimized version of LAPACK. If you set
USE_SYSTEM_LAPACK=1, you should also set
LIBLAPACKNAME=lib$(YOURBLAS). Else, the reference LAPACK will be used and performance will typically be much lower.
Starting with Julia 1.7, Julia uses libblastrampoline to pick a different BLAS at runtime.
Creating a point/patch release consists of several distinct steps.
Some pull requests are labeled "backport pending x.y", e.g. "backport pending 0.6". This designates that the next subsequent release tagged from the release-x.y branch should include the commit(s) in that pull request. Once the pull request is merged into master, each of the commits should be cherry picked to a dedicated branch that will ultimately be merged into release-x.y.
First, create a new branch based on release-x.y. The typical convention for Julia branches is to prefix the branch name with your initials if it's intended to be a personal branch. For the sake of example, we'll say that the author of the branch is Jane Smith.
git fetch origin git checkout release-x.y git rebase origin/release-x.y git checkout -b js/backport-x.y
This ensures that your local copy of release-x.y is up to date with origin before you create a new branch from it.
Now we do the actual backporting. Find all merged pull requests labeled "backport pending x.y" in the GitHub web UI. For each of these, scroll to the bottom where it says "someperson merged commit
master XX minutes ago". Note that the commit name is a link; if you click it, you'll be shown the contents of the commit. If this page shows that
123abc is a merge commit, go back to the PR page–-we don't want merge commits, we want the actual commits. However, if this does not show a merge commit, it means that the PR was squash-merged. In that case, use the git SHA of the commit, listed next to commit on this page.
Once you have the SHA of the commit, cherry-pick it onto the backporting branch:
git cherry-pick -x -e <sha>
There may be conflicts which need to be resolved manually. Once conflicts are resolved (if applicable), add a reference to the GitHub pull request that introduced the commit in the body of the commit message.
After all of the relevant commits are on the backports branch, push the branch to GitHub.
Point releases should never introduce performance regressions. Luckily the Julia benchmarking bot, Nanosoldier, can run benchmarks against any branch, not just master. In this case we want to check the benchmark results of js/backport-x.y against release-x.y. To do this, awaken the Nanosoldier from his robotic slumber using a comment on your backporting pull request:
@nanosoldier `runbenchmarks(ALL, vs=":release-x.y")`
This will run all registered benchmarks on release-x.y and js/backport-x.y and produce a summary of results, marking all improvements and regressions.
If Nanosoldier finds any regressions, try verifying locally and rerun Nanosoldier if necessary. If the regressions are deemed to be real rather than just noise, you'll have to find a commit on master to backport that fixes it if one exists, otherwise you should determine what caused the regression and submit a patch (or get someone who knows the code to submit a patch) to master, then backport the commit once that's merged. (Or submit a patch directly to the backport branch if appropriate.)
After the backport PR has been merged into the
release-x.y branch, update your local clone of Julia, then get the SHA of the branch using
git rev-parse origin/release-x.y
Keep that handy, as it's what you'll enter in the "Revision" field in the buildbot UI.
For now, all you need are binaries for Linux x86-64, since this is what's used for running PackageEvaluator. Go to https://buildog.julialang.org, submit a job for
nuke_linux64, then queue up a job for
package_linux64, providing the SHA as the revision. When the packaging job completes, it will upload the binary to the
julialang2 bucket on AWS. Retrieve the URL, as it will be used for PackageEvaluator.
Point releases should never break packages, with the possible exception of packages that are doing some seriously questionable hacks using Base internals that are not intended to be user-facing. (In those cases, maybe have a word with the package author.)
Checking whether changes made in the forthcoming new version will break packages can be accomplished using PackageEvaluator, often called "PkgEval" for short. PkgEval is what populates the status badges on GitHub repos and on pkg.julialang.org. It typically runs on one of the non-benchmarking nodes of Nanosoldier and uses Vagrant to perform its duties in separate, parallel VirtualBox virtual machines.
Clone PackageEvaluator and create a branch called
backport-x.y.z, and check it out. Note that the required changes are a little hacky and confusing, and hopefully that will be addressed in a future version of PackageEvaluator. The changes to make will be modeled off of this commit.
The setup script takes its first argument as the version of Julia to run and the second as the range of package names (AK for packages named A-K, LZ for L-Z). The basic idea is that we're going to tweak that a bit to run only two versions of Julia, the current x.y release and our backport version, each with three ranges of packages.
In the linked diff, we're saying that if the second argument is LZ, use the binaries built from our backport branch, otherwise (AK) use the release binaries. Then we're using the first argument to run a section of the package list: A-F for input 0.4, G-N for 0.5, and O-Z for 0.6.
To run PkgEval, find a hefty enough machine (such as Nanosoldier node 1), then run
git clone https://github.com/JuliaCI/PackageEvaluator.jl.git cd PackageEvaluator.jl/scripts git checkout backport-x.y.z ./runvagrant.sh
This produces some folders in the scripts/ directory. The folder names and their contents are decoded below:
|Folder name||Julia version||Package range|
Once that's done, you can use
./summary.sh from that same directory to produce a summary report of the findings. We'll do so for each of the folders to aggregate overall results by version.
./summary.sh 0.4AK/*.json > summary_release.txt ./summary.sh 0.5AK/*.json >> summary_release.txt ./summary.sh 0.6AK/*.json >> summary_release.txt ./summary.sh 0.4LZ/*.json > summary_backport.txt ./summary.sh 0.5LZ/*.json >> summary_backport.txt ./summary.sh 0.6LZ/*.json >> summary_backport.txt
Now we have two files,
summary_backport.txt, containing the PackageEvaluator test results (pass/fail) for each package for the two versions.
To make these easier to ingest into a Julia, we'll convert them into CSV files then use the DataFrames package to process the results. To convert to CSV, copy each .txt file to a corresponding .csv file, then enter Vim and execute
:%s/\.json /",/g. (You don't have to use Vim; this just is one way to do it.) Now process the results with Julia code similar to the following.
using DataFrames release = readtable("summary_release.csv", header=false, names=[:package, :release]) backport = readtable("summary_backport.csv", header=false, names=[:package, :backport]) results = join(release, backport, on=:package, kind=:outer) for result in eachrow(results) a = result[:release] b = result[:backport] if (isna(a) && !isna(b)) || (isna(b) && !isna(a)) color = :yellow elseif a != b && occursin("pass", b) color = :green elseif a != b color = :red else continue end printstyled(result[:package], ": Release ", a, " -> Backport ", b, "\n", color=color) end
This will write color-coded lines to
stdout. All lines in red must be investigated as they signify potential breakages caused by the backport version. Lines in yellow should be looked into since it means a package ran on one version but not on the other for some reason. If you find that your backported branch is causing breakages, use
git bisect to identify the problematic commits,
git revert those commits, and repeat the process.
After you have ensured that
- the backported commits pass all of Julia's unit tests,
- there are no performance regressions introduced by the backported commits as compared to the release branch, and
- the backported commits do not break any registered packages,
then the backport branch is ready to be merged into release-x.y. Once it's merged, go through and remove the "backport pending x.y" label from all pull requests containing the commits that have been backported. Do not remove the label from PRs that have not been backported.
The release-x.y branch should now contain all of the new commits. The last thing we want to do to the branch is to adjust the version number. To do this, submit a PR against release-x.y that edits the VERSION file to remove
-pre from the version number. Once that's merged, we're ready to tag.
It's time! Check out the release-x.y branch and make sure that your local copy of the branch is up to date with the remote branch. At the command line, run
git tag v$(cat VERSION) git push --tags
This creates the tag locally and pushes it to GitHub.
After tagging the release, submit another PR to release-x.y to bump the patch number and add
-pre back to the end. This denotes that the branch state reflects a prerelease version of the next point release in the x.y series.
Follow the remaining directions in the Makefile.
Some of these steps will require secure passwords. To obtain the appropriate passwords, contact Elliot Saba (staticfloat) or Alex Arslan (ararslan). Note that code signing for each platform must be performed on that platform (e.g. Windows signing must be done on Windows, etc.).
Code signing must be done manually on Linux, but it's quite simple. First obtain the file
julia.key from the CodeSigning folder in the
juliasecure AWS bucket. Add this to your GnuPG keyring using
gpg --import julia.key
This will require entering a password that you must obtain from Elliot or Alex. Next, set the trust level for the key to maximum. Start by entering a
gpg --edit-key julia
At the prompt, type
trust, then when asked for a trust level, provide the maximum available (likely 5). Exit GnuPG.
Now, for each of the Linux tarballs that were built on the buildbots, enter
gpg -u julia --armor --detach-sig julia-x.y.z-linux-<arch>.tar.gz
This will produce a corresponding .asc file for each tarball. And that's it!
Code signing should happen automatically on the macOS buildbots. However, it's important to verify that it was successful. On a system or virtual machine running macOS, download the .dmg file that was built on the buildbots. For the sake of example, say that the .dmg file is called
mkdir ./jlmnt hdiutil mount -readonly -mountpoint ./jlmnt julia-x.y.z-osx.dmg codesign -v jlmnt/Julia-x.y.app
Be sure to note the name of the mounted disk listed when mounting! For the sake of example, we'll assume this is
disk3. If the code signing verification exited successfully, there will be no output from the
codesign step. If it was indeed successful, you can detach the .dmg now:
hdiutil eject /dev/disk3 rm -rf ./jlmnt
If you get a message like
Julia-x.y.app: code object is not signed at all
then you'll need to sign manually.
To sign manually, first retrieve the OS X certificates from the CodeSigning folder in the
juliasecure bucket on AWS. Add the .p12 file to your keychain using Keychain.app. Ask Elliot Saba (staticfloat) or Alex Arslan (ararslan) for the password for the key. Now run
hdiutil convert julia-x.y.z-osx.dmg -format UDRW -o julia-x.y.z-osx_writable.dmg mkdir ./jlmnt hdiutil mount -mountpoint julia-x.y.z-osx_writable.dmg codesign -s "AFB379C0B4CBD9DB9A762797FC2AB5460A2B0DBE" --deep jlmnt/Julia-x.y.app
This may fail with a message like
Julia-x.y.app: resource fork, Finder information, or similar detritus not allowed
If that's the case, you'll need to remove extraneous attributes:
xattr -cr jlmnt/Julia-x.y.app
Then retry code signing. If that produces no errors, retry verification. If all is now well, unmount the writable .dmg and convert it back to read-only:
hdiutil eject /dev/disk3 rm -rf ./jlmnt hdiutil convert julia-x.y.z-osx_writable.dmg -format UDZO -o julia-x.y.z-osx_fixed.dmg
Verify that the resulting .dmg is in fact fixed by double clicking it. If everything looks good, eject it then drop the
_fixed suffix from the name. And that's it!
Signing must be performed manually on Windows. First obtain the Windows 10 SDK, which contains the necessary signing utilities, from the Microsoft website. We need the
SignTool utility which should have been installed somewhere like
C:\Program Files (x86)\Windows Kits\10\App Certification Kit. Grab the Windows certificate files from CodeSigning on
juliasecure and put them in the same directory as the executables. Open a Windows CMD window,
cd to where all the files are, and run
set PATH=%PATH%;C:\Program Files (x86)\Windows Kits\10\App Certification Kit; signtool sign /f julia-windows-code-sign_2017.p12 /p "PASSWORD" ^ /t http://timestamp.verisign.com/scripts/timstamp.dll ^ /v julia-x.y.z-win32.exe
^ is a line continuation character in Windows CMD and
PASSWORD is a placeholder for the password for this certificate. As usual, contact Elliot or Alex for passwords. If there are no errors, we're all good!
Now that everything is signed, we need to upload the binaries to AWS. You can use a program like Cyberduck or the
aws command line utility. The binaries should go in the
julialang2 bucket in the appropriate folders. For example, Linux x86-64 goes in
julialang2/bin/linux/x.y. Be sure to delete the current
julia-x.y-latest-linux-<arch>.tar.gz file and replace it with a duplicate of
We also need to upload the checksums for everything we've built, including the source tarballs and all release binaries. This is simple:
shasum -a 256 julia-x.y.z* | grep -v -e sha256 -e md5 -e asc > julia-x.y.z.sha256 md5sum julia-x.y.z* | grep -v -e sha256 -e md5 -e asc > julia-x.y.z.md5
Note that if you're running those commands on macOS, you'll get very slightly different output, which can be reformatted by looking at an existing file. Mac users will also need to use
md5 -r instead of
md5sum. Upload the .md5 and .sha256 files to
julialang2/bin/checksums on AWS.
Ensure that the permissions on AWS for all uploaded files are set to "Everyone: READ."
For each file we've uploaded, we need to purge the Fastly cache so that the links on the website point to the updated files. As an example:
curl -X PURGE https://julialang-s3.julialang.org/bin/checksums/julia-x.y.z.sha256
Sometimes this isn't necessary but it's good to do anyway.