(for upgrading users, please see the notes at the bottom)

Bazel brought a lot of nice things to the table, such as rebuilds based on
content changes instead of modification times, caching of build products,
detection of incorrect build rules via a sandbox, and so on. Rewriting the build
in Bazel was also an opportunity to improve on the Makefile-based build we had
prior, which was pretty poor: most dependencies were external or not pinned, and
the build graph was poorly defined and mostly serialized. It was not uncommon
for fresh checkouts to fail due to floating dependencies, or for things to break
when trying to switch to an older commit.

For day-to-day development, I think Bazel served us reasonably well - we could
generally switch between branches while being confident that builds would be
correct and reasonably fast, and not require full rebuilds (except on Windows,
where the lack of a sandbox and the TS rules would cause build breakages when TS
files were renamed/removed).

Bazel achieves that reliability by defining rules for each programming language
that define how source files should be turned into outputs. For the rules to
work with Bazel's sandboxing approach, they often have to reimplement or
partially bypass the standard tools that each programming language provides. The
Rust rules call Rust's compiler directly for example, instead of using Cargo,
and the Python rules extract each PyPi package into a separate folder that gets
added to sys.path.

These separate language rules allow proper declaration of inputs and outputs,
and offer some advantages such as caching of build products and fine-grained
dependency installation. But they also bring some downsides:

- The rules don't always support use-cases/platforms that the standard language
tools do, meaning they need to be patched to be used. I've had to contribute a
number of patches to the Rust, Python and JS rules to unblock various issues.
- The dependencies we use with each language sometimes make assumptions that do
not hold in Bazel, meaning they either need to be pinned or patched, or the
language rules need to be adjusted to accommodate them.

I was hopeful that after the initial setup work, things would be relatively
smooth-sailing. Unfortunately, that has not proved to be the case. Things
frequently broke when dependencies or the language rules were updated, and I
began to get frustrated at the amount of Anki development time I was instead
spending on build system upkeep. It's now about 2 years since switching to
Bazel, and I think it's time to cut losses, and switch to something else that's
a better fit.

The new build system is based on a small build tool called Ninja, and some
custom Rust code in build/. This means that to build Anki, Bazel is no longer
required, but Ninja and Rust need to be installed on your system. Python and
Node toolchains are automatically downloaded like in Bazel.

This new build system should result in faster builds in some cases:

- Because we're using cargo to build now, Rust builds are able to take advantage
of pipelining and incremental debug builds, which we didn't have with Bazel.
It's also easier to override the default linker on Linux/macOS, which can
further improve speeds.
- External Rust crates are now built with opt=1, which improves performance
of debug builds.
- Esbuild is now used to transpile TypeScript, instead of invoking the TypeScript
compiler. This results in faster builds, by deferring typechecking to test/check
time, and by allowing more work to happen in parallel.

As an example of the differences, when testing with the mold linker on Linux,
adding a new message to tags.proto (which triggers a recompile of the bulk of
the Rust and TypeScript code) results in a compile that goes from about 22s on
Bazel to about 7s in the new system. With the standard linker, it's about 9s.

Some other changes of note:

- Our Rust workspace now uses cargo-hakari to ensure all packages agree on
available features, preventing unnecessary rebuilds.
- pylib/anki is now a PEP420 implicit namespace, avoiding the need to merge
source files and generated files into a single folder for running. By telling
VSCode about the extra search path, code completion now works with generated
files without needing to symlink them into the source folder.
- qt/aqt can't use PEP420 as it's difficult to get rid of aqt/__init__.py.
Instead, the generated files are now placed in a separate _aqt package that's
added to the path.
- ts/lib is now exposed as @tslib, so the source code and generated code can be
provided under the same namespace without a merging step.
- MyPy and PyLint are now invoked once for the entire codebase.
- dprint will be used to format TypeScript/json files in the future instead of
the slower prettier (currently turned off to avoid causing conflicts). It can
automatically defer to prettier when formatting Svelte files.
- svelte-check is now used for typechecking our Svelte code, which revealed a
few typing issues that went undetected with the old system.
- The Jest unit tests now work on Windows as well.

If you're upgrading from Bazel, updated usage instructions are in docs/development.md and docs/build.md. A summary of the changes:

- please remove node_modules and .bazel
- install rustup (https://rustup.rs/)
- install rsync if not already installed (on windows, use pacman - see docs/windows.md)
- install Ninja (unzip from https://github.com/ninja-build/ninja/releases/tag/v1.11.1 and
place on your path, or from your distro/homebrew if it's 1.10+)
- update .vscode/settings.json from .vscode.dist

2022-11-27 15:24:20 +10:00

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Local sync server

A local sync server is bundled with Anki. If you cannot or do not wish to use AnkiWeb, you can run the server on a machine on your local network.

Things to be aware of:

Media syncing is not currently supported. You will either need to disable syncing of sounds and images in the preferences screen, sync your media via AnkiWeb, or use some other solution.
AnkiMobile does not yet provide an option for using a local sync server, so for now this will only be usable with the computer version of Anki, and AnkiDroid.
This code is partly new, and while it has had some testing, it's possible something has been missed. Please make backups, and report any bugs you run into.
The server runs over an unencrypted HTTP connection and does not require authentication, so it is only suitable for use on a private network.
This is an advanced feature, targeted at users who are comfortable with networking and the command line. If you use this, the expectation is you can resolve any setup/network/firewall issues you run into yourself, and use of this is entirely at your own risk.

From source

If you run Anki from git, you can run a sync server with:

./tools/runopt --syncserver

From a packaged build

From 2.1.39beta1+, the sync server is included in the packaged binaries.

On Windows in a cmd.exe session:

"\program files\anki\anki-console.exe" --syncserver

Or MacOS, in Terminal.app:

/Applications/Anki.app/Contents/MacOS/AnkiMac --syncserver

Or Linux:

anki --syncserver

Without Qt dependencies

You can run the server without installing the GUI portion of Anki. Once Anki 2.1.39 is released, the following will work:

pip install anki[syncserver]
python -m anki.syncserver

Server setup

The server needs to store a copy of your collection in a folder. By default it is ~/.syncserver; you can change this by defining a FOLDER environmental variable. This should not be the same location as your normal Anki data folder.

You can also define HOST and PORT.

Client setup

When the server starts, it will print the address it is listening on. You need to set an environmental variable before starting your Anki clients to tell them where to connect to. Eg:

set SYNC_ENDPOINT="http://10.0.0.5:8080/sync/"
anki

Currently any username and password will be accepted. If you wish to keep using AnkiWeb for media, sync once with AnkiWeb first, then switch to your local endpoint - collection syncs will be local, and media syncs will continue to go to AnkiWeb.

Contributing

Authentication shouldn't be too hard to add - login() and request() in http_client.rs can be used as a reference. A PR that accepts a password in an env var, and generates a stable hkey based on it would be welcome.

Once that is done, basic multi-profile support could be implemented by moving the col object into an array or dict, and fetching the relevant collection based on the user's authentication.

Because this server is bundled with Anki, simplicity is a design goal - it is targeted at individual/family use, only makes use of Python libraries the GUI is already using, and does not require a configuration file. PRs that deviate from this are less likely to be merged, so please consider reaching out first if you are thinking of starting work on a larger change.

3.3 KiB Raw Blame History