For non-developers who want to try beta versions, the easiest way is to use a packaged version - please see:
Pre-built Python packages are available on PyPI. They are useful if you wish to:
- Run Anki from a local Python installation without building it yourself
- Get code completion when developing add-ons
- Make command line scripts that modify .anki2 files via Anki's Python libraries
You will need the 64 bit version of Python 3.9 or later installed. 3.9 is recommended, as Anki has only received minimal testing on 3.10+ so far, and some dependencies have not been fully updated yet. You can install Python from python.org or from your distro.
For further instructions, please see https://betas.ankiweb.net/#via-pypipip. Note that
in the provided commands, --pre tells pip to fetch alpha/beta versions. If you remove
--pre, it will download the latest stable version instead.
Clone the git repo into a folder of your choosing. The folder path must not contain spaces, and should not be too long if you are on Windows.
On all platforms, you will need to install:
- Rustup (https://rustup.rs/). The Rust version pinned in rust-toolchain.toml will be automatically downloaded if not yet installed. If removing that file to use a distro-provided Rust, newer Rust versions will typically work for building but may fail tests; older Rust versions may not work at all.
- N2 or Ninja. N2 gives better status output. You can install it with
tools/install-n2, orbash tools\install-n2on Windows. If you want to use Ninja, it can be downloaded from https://github.com/ninja-build/ninja/releases/tag/v1.11.1 and placed on your path, or from your distro/homebrew if it's 1.10+.
Platform-specific requirements:
From the top level of Anki's source folder:
./run
(.\run on Windows)
This will build Anki and run it in place.
The first build will take a while, as it downloads and builds a bunch of dependencies. When the build is complete, Anki will automatically start.
To run all tests at once, from the top-level folder:
./ninja check
(tools\ninja check on Windows).
You can also run specific checks. For example, if you see during the checks
that check:svelte:editor is failing, you can use ./ninja check:svelte:editor
to re-run that check, or ./ninja check:svelte to re-run all Svelte checks.
When formatting issues are reported, they can be fixed with
./ninja format
./ninja fix
cargo clippy --fix
If you want to add files or folders to the project tree that should be excluded from version tracking and not be matched by formatters and checks, place them in an extra folder and they will automatically be ignored.
The ./run command will create a non-optimized build by default. This is faster
to compile, but will mean Anki will run slower.
To run Anki in optimized mode, use:
./tools/runopt
Or set RELEASE=1 or RELEASE=2. The latter will further optimize the output, but make the build much slower.
The ./run method described in the platform-specific instructions is a shortcut
for starting Anki directly from the build folder. For regular study, it's recommended
you build Python wheels and then install them into your own python venv. This is also
a good idea if you wish to install extra tools from PyPi that Anki's build process
does not use.
To build wheels on Mac/Linux:
./tools/build
(on Windows, \tools\build.bat)
The generated wheels are in out/wheels. You can then install them by copying the paths into a pip install command.
Follow the steps on the beta site, but replace the
pip install --upgrade --pre aqt[qt6] line with something like:
/my/pyenv/bin/pip install --upgrade out/wheels/*.whl
(On Windows you'll need to list out the filenames manually instead of using a wildcard).
You'll also need to install PyQt:
$ /my/pyenv/bin/pip install pyqt6 pyqt6-webengine
or
$ my/pyenv/bin/pip install pyqt5 pyqtwebengine
Apart from submodule checkouts, most build files go into the out/ folder (and
node_modules on Windows). You can delete that folder for a clean build, or
to free space.
Cargo, yarn and pip all cache downloads of dependencies in a shared cache that
other builds on your system may use as well. If you wish to clear up those caches,
they can be found in ~/.rustup, ~/.cargo and ~/.cache/{yarn,pip}.
If you invoke Rust outside of the build scripts (eg by running cargo, or
with Rust Analyzer), output files will go into target/ unless you have
overriden the default output location.
Please see this separate page for setting up an editor/IDE.
See this page
For Rust:
cargo doc --open
For Python:
./ninja python:sphinx && open out/python/sphinx/html/py-modindex.html
If ANKIDEV is set before starting Anki, some extra log messages will be printed on stdout, and automatic backups will be disabled - so please don't use this except on a test profile. It is automatically enabled when using ./run.
If TRACESQL is set, all SQL statements will be printed as they are executed.
If LOGTERM is set before starting Anki, warnings and error messages that are normally placed in the collection2.log file will also be printed on stdout.
If ANKI_PROFILE_CODE is set, Python profiling data will be written on exit.
Anki's official binary packages are created with ./ninja bundle. The bundling
process was created specifically for the official builds, and is provided as-is;
we are unfortunately not able to provide assistance with any issues you may run
into when using it.
You may wish to create a separate profile with File>Switch Profile for use during development. You can pass the arguments "-p [profile name]" when starting Anki to load a specific profile.
If you're using PyCharm:
- right click on the "run" file in the root of the PyCharm Anki folder
- click "Edit 'run'..." - in Script options and enter: "-p [dev profile name]" without the quotes
- click "Ok"