Provisioning and third-party dependencies
Zulip is a large project, with well over 100 third-party dependencies, and managing them well is essential to the quality of the project. In this document, we discuss the various classes of dependencies that Zulip has, and how we manage them. Zulip’s dependency management has some really nice properties:
Fast provisioning. When switching to a different commit in the Zulip project with the same dependencies, it takes under 5 seconds to re-provision a working Zulip development environment after switching. If there are new dependencies, one only needs to wait to download the new ones, not all the pre-existing dependencies.
Consistent provisioning. Every time a Zulip development or production environment is provisioned/installed, it should end up using the exactly correct versions of all major dependencies.
Low maintenance burden. To the extent possible, we want to avoid manual work and keeping track of things that could be automated. This makes it easy to keep running the latest versions of our various dependencies.
The purpose of this document is to detail all of Zulip’s third-party dependencies and how we manage their versions.
Provisioning
We refer to “provisioning” as the process of installing and
configuring the dependencies of a Zulip development environment. It’s
done using tools/provision
, and the output is conveniently logged by
var/log/provision.log
to help with debugging. Provisioning makes
use of a lot of caching. Some of those caches are not immune to being
corrupted if you mess around with files in your repository a lot. We
have tools/provision --force
to (still fairly quickly) rerun most
steps that would otherwise have been skipped due to caching.
In the Vagrant development environment, vagrant provision
will run
the provision script; vagrant up
will boot the machine, and will
also run an initial provision the first time only.
PROVISION_VERSION
In version.py
, we have a special parameter, PROVISION_VERSION
,
which is used to help ensure developers don’t spend time debugging
test/linter/etc. failures that actually were caused by the developer
rebasing and forgetting to provision”. PROVISION_VERSION
has a
format of (x, y)
; when x
doesn’t match the value from the last time
the user provisioned, or y
is higher than the value from last
time, most Zulip tools will crash early and ask the user to provision.
This has empirically made a huge impact on how often developers spend
time debugging a “weird failure” after rebasing that had an easy
solution. (Of course, the other key part of achieving this is all the
work that goes into making sure that provision
reliably leaves the
development environment in a good state.)
PROVISION_VERSION
must be manually updated when making changes that
require re-running provision, so don’t forget about it!
Philosophy on adding third-party dependencies
In the Zulip project, we take a pragmatic approach to third-party
dependencies. Overall, if a third-party project does something well
that Zulip needs to do (and has an appropriate license), we’d love to
use it rather than reinventing the wheel. If the third-party project
needs some small changes to work, we prefer to make those changes and
contribute them upstream. When the upstream maintainer is slow to
respond, we may use a fork of the dependency until the code is merged
upstream; as a result, we usually have a few packages in
requirements.txt
that are installed from a GitHub URL.
What we look for in choosing dependencies is whether the project is well-maintained. Usually one can tell fairly quickly from looking at a project’s issue tracker how well-managed it is: a quick look at how the issue tracker is managed (or not) and the test suite is usually enough to decide if a project is going to be a high-maintenance dependency or not. That said, we do still take on some smaller dependencies that don’t have a well-managed project, if we feel that using the project will still be a better investment than writing our own implementation of that project’s functionality. We’ve adopted a few projects in the past that had a good codebase but whose maintainer no longer had time for them.
One case where we apply added scrutiny to third-party dependencies is JS libraries. They are a particularly important concern because we want to keep the Zulip web app’s JS bundle small, so that Zulip continues to load quickly on systems with low network bandwidth. We’ll look at large JS libraries with much greater scrutiny for whether their functionality justifies their size than Python dependencies, since an extra 50KB of code usually doesn’t matter in the backend, but does in JavaScript.
System packages
For the third-party services like PostgreSQL, Redis, nginx, and RabbitMQ
that are documented in the
architecture overview, we rely on the
versions of those packages provided alongside the Linux distribution
on which Zulip is deployed. Because Zulip
only supports Ubuntu in production, this
usually means apt
, though we do support
other platforms in development. Since
we don’t control the versions of these dependencies, we avoid relying
on specific versions of these packages wherever possible.
The exact lists of apt
packages needed by Zulip are maintained in a
few places:
For production, in our Puppet configuration,
puppet/zulip/
, using thePackage
andSafePackage
directives.For development, in
SYSTEM_DEPENDENCIES
intools/lib/provision.py
.The packages needed to build a Zulip virtualenv, in
VENV_DEPENDENCIES
inscripts/lib/setup_venv.py
. These are separate from the rest because (1) we may need to install a virtualenv before running the more complex scripts that, in turn, install other dependencies, and (2) because that list is shared between development and production.
We also rely on the PGroonga PPA for the PGroonga PostgreSQL extension, used by our full-text search.
Python packages
Zulip uses the version of Python itself provided by the host OS for
the Zulip server. We currently support Python 3.8 and newer, with
Ubuntu 20.04 being the platform requiring 3.8 support. The comments
in .github/workflows/zulip-ci.yml
document the Python versions used
by each supported platform.
We manage Python packages via the Python-standard requirements.txt
system and virtualenvs, but there’s a number of interesting details
about how Zulip makes this system work well for us that are worth
highlighting. The system is largely managed by the code in
scripts/lib/setup_venv.py
Using
pip
to manage dependencies. This is standard in the Python ecosystem, and means we only need to record a list of versions in arequirements.txt
file to declare what we’re using. Since we have a few different installation targets, we maintain severalrequirements.txt
format files in therequirements/
directory (e.g.dev.in
for development,prod.in
for production,docs.in
for ReadTheDocs,common.in
for the vast majority of packages common to prod and development, etc.). We usepip install --no-deps
to ensure we only install the packages we explicitly declare as dependencies.virtualenv with pinned versions. For a large application like Zulip, it is important to ensure that we’re always using consistent, predictable versions of all of our Python dependencies. To ensure this, we install our dependencies in a virtualenv that contains only the packages and versions that Zulip needs, and we always pin exact versions of our dependencies in our
requirements.txt
files. We pin exact versions, not minimum versions, so that installing Zulip won’t break if a dependency makes a buggy release. A side effect is that it’s easy to debug problems caused by dependency upgrades, since we’re always doing those upgrades with an explicit commit updating therequirements/
directory.Pinning versions of indirect dependencies. We “pin” or “lock” the versions of our indirect dependencies files with
tools/update-locked-requirements
(powered bypip-compile
). What this means is that we have some “source” requirements files, likerequirements/common.in
, that declare the packages that Zulip depends on directly. Those packages have their own recursive dependencies. When adding or removing a dependency from Zulip, one simply edits the appropriate “source” requirements files, and then runstools/update-locked-requirements
. That tool will usepip-compile
to generate the locked requirements files likeprod.txt
,dev.txt
etc files that explicitly declare versions of all of Zulip’s recursive dependencies. For indirect dependencies (i.e. dependencies not explicitly declared in the source requirements files), it provides helpful comments explaining which direct dependency (or dependencies) needed that indirect dependency. The process for using this system is documented in more detail inrequirements/README.md
.Caching of virtualenvs and packages. To make updating the dependencies of a Zulip installation efficient, we maintain a cache of virtualenvs named by the hash of the relevant
requirements.txt
file (scripts/lib/hash_reqs.py
). These caches live under/srv/zulip-venv-cache/<hash>
. That way, when re-provisioning a development environment or deploying a new production version with the same Python dependencies, no downloading or installation is required: we just use the same virtualenv. When the only changes are upgraded versions, we’ll use virtualenv-clone to clone the most similar existing virtualenv and then just upgrade the packages needed, making small version upgrades extremely efficient. And finally, we usepip
’s built-in caching to ensure that a specific version of a specific package is only downloaded once.Garbage-collecting caches. We have a tool,
scripts/lib/clean_venv_cache.py
, which will clean old cached virtualenvs that are no longer in use. In production, the algorithm preserves recent virtualenvs as well as those in use by any current production deployment directory under/home/zulip/deployments/
. This helps ensure that a Zulip installation doesn’t leak large amounts of disk over time.Scripts. Often, we want a script running in production to use the Zulip virtualenv. To make that work without a lot of duplicated code, we have a helpful function,
scripts.lib.setup_path.setup_path
, which on import will put the currently running Python script into the Zulip virtualenv. This is called by./manage.py
to ensure that our Django code always uses the correct virtualenv as well.Mypy type checker. Because we’re using mypy in a strict mode, when you add use of a new Python dependency, you usually need to either adds stubs to the
stubs/
directory for the library, or editpyproject.toml
in the root of the Zulip project to configureignore_missing_imports
for the new library. See our mypy docs for more details.
Upgrading packages
See the README file in requirements/
directory
to learn how to upgrade a single Python package.
JavaScript and other frontend packages
We use the same set of strategies described for Python dependencies for most of our JavaScript dependencies, so we won’t repeat the reasoning here.
In a fashion very analogous to the Python codebase,
scripts/lib/node_cache.py
manages cachednode_modules
directories in/srv/zulip-npm-cache
. Each is named by its hash, computed by thegenerate_sha1sum_node_modules
function.scripts/lib/clean_node_cache.py
handles garbage-collection.We use yarn, a
pip
-like tool for JavaScript, to download most JavaScript dependencies. Yarn talks to standard the npm repository. We use the standardpackage.json
file to declare our direct dependencies, with sections for development and production. Yarn takes care of pinning the versions of indirect dependencies in theyarn.lock
file;yarn install
updates theyarn.lock
files.tools/update-prod-static
. This process is discussed in detail in the static asset pipeline article, but we don’t use thenode_modules
directories directly in production. Instead, static assets are compiled using our static asset pipeline and it is the compiled assets that are served directly to users. As a result, we don’t ship thenode_modules
directory in a Zulip production release tarball, which is a good thing, because doing so would more than double the size of a Zulip release tarball.Checked-in packages. In contrast with Python, we have a few JavaScript dependencies that we have copied into the main Zulip repository under
static/third
, often with patches. These date from an era beforenpm
existed. It is a project goal to eliminate these checked-in versions of dependencies and instead use versions managed by the npm repositories.
Node.js and Yarn
Node.js is installed by scripts/lib/install-node
to
/srv/zulip-node
and symlinked to /usr/local/bin/node
. Yarn is
installed by scripts/lib/install-yarn
to /srv/zulip-yarn
and
symlinked to /usr/bin/yarn
.
We don’t do anything special to try to manage multiple versions of
Node.js or Yarn. (Previous versions of Zulip installed multiple
versions of Node.js using the third-party nvm
installer, but the
current version no longer uses nvm
; if it’s present in
/usr/local/nvm
where previous versions installed it, it will now be
removed.)
ShellCheck and shfmt
In the development environment, the tools/setup/install-shellcheck
and tools/setup/install-shfmt
scripts download binaries for
ShellCheck and shfmt from GitHub, check them against a known hash, and
install them to /usr/local/bin
. These tools are run as part of the
linting system.
Puppet packages
Third-party puppet modules are downloaded from the Puppet Forge into
subdirectories under /srv/zulip-puppet-cache
, hashed based on their
versions; the latest is always symlinked as
/srv/zulip-puppet-cache/current
. zulip-puppet-apply
installs
these dependencies immediately before they are needed.
Other third-party and generated files
In this section, we discuss the other third-party dependencies, generated code, and other files whose original primary source is not the Zulip server repository, and how we provision and otherwise maintain them.
Emoji
Zulip uses the iamcal emoji data package for its emoji data
and sprite sheets. We download this dependency using npm
, and then
have a tool, tools/setup/build_emoji
, which reformats the emoji data
into the files under static/generated/emoji
. Those files are in
turn used by our Markdown processor and
tools/update-prod-static
to make Zulip’s emoji work in the various
environments where they need to be displayed.
Since processing emoji is a relatively expensive operation, as part of
optimizing provisioning, we use the same caching strategy for the
compiled emoji data as we use for virtualenvs and node_modules
directories, with scripts/lib/clean_emoji_cache.py
responsible for
garbage-collection. This caching and garbage-collection is required
because a correct emoji implementation involves over 1000 small image
files and a few large ones. There is a more extended article on our
emoji infrastructure.
Translations data
Zulip’s translations infrastructure generates
several files from the source data, which we manage similar to our
emoji, but without the caching (and thus without the
garbage-collection). New translations data is downloaded from
Transifex and then compiled to generate both the production locale
files and also language data in locale/language*.json
using
manage.py compilemessages
, which extends the default Django
implementation of that tool.
Pygments data
The list of languages supported by our Markdown syntax highlighting
comes from the pygments package. tools/setup/build_pygments_data
is
responsible for generating static/generated/pygments_data.json
so that
our JavaScript Markdown processor has access to the supported list.
Modifying provisioning
When making changes to Zulip’s provisioning process or dependencies, usually one needs to think about making changes in 3 places:
tools/lib/provision.py
. This is the main provisioning script, used by most developers to maintain their development environment.docs/development/dev-setup-non-vagrant.md
. This is our “manual installation” documentation. Strategically, we’d like to move the support for more versions of Linux from here intotools/lib/provision.py
.Production. Our tools for compiling/generating static assets need to be called from
tools/update-prod-static
, which is called bytools/build-release-tarball
(for doing Zulip releases) as well astools/upgrade-zulip-from-git
(for deploying a Zulip server off ofmain
).