* Feat/per-deck desired retention
* Refactor desired retention logic in Collection implementation
Updated the logic for retrieving deck-specific desired retention in both `memory_state.rs` and `mod.rs` to handle cases where the deck's normal state may not be available. This change ensures that the default configuration is used when necessary, improving the robustness of the retention handling.
* Refactor desired retention handling in FsrsOptions.svelte
Updated the logic for effective desired retention to use the configuration default instead of the deck-specific value. This change improves consistency in the retention value used throughout the component, ensuring that the correct value is bound to the UI elements.
* refactor the logic for obtaining deck-specific desired retention by using method chaining
* support deck-specific desired retention when rescheduling
* Refactor desired retention logic to use a dedicated method for improved clarity and maintainability.
* Only get_deck_config when load balancer is enabled
* Refactor load balancer card addition logic to use pre-fetched deckconfig_id
* Refactor get_scheduling_states to use context for deck configuration
* Add `last_review_time` to card data
* cargo clippy
* Calculate days elapsed since last review time in add_extract_fsrs_relative_retrievability
* expose last_review_time to Card in Python
* Fix last_review_time assignment in Card class to use last_review_time_secs
* format
* Update last_review_time assignment to exclude filtered preview state in Card class
* Migrate build system to uv
Closes#3787, and is a step towards #3081 and #4022
This change breaks our PyOxidizer bundling process. While we probably
could update it to work with the new venvs & lockfile, my intention
is to use this as a base to try out a uv-based packager/installer.
Some notes about the changes:
- Use uv for python download + venv installation
- Drop python/requirements* in favour of pyproject files / uv.lock
- Bumped to latest Python 3.9 version. The move to 3.13 should be
a fairly trivial change when we're ready.
- Dropped the old write_wheel.py in favour of uv/hatchling. This has
the unfortunate side-effect of dropping leading zeros in our wheels,
which we could try hack around in the future.
- Switch to Qt 6.7 for the dev repo, as it's the first PyQt version
with a Linux/ARM WebEngine wheel.
- Unified our macOS deployment target with minimum required for ARM.
- Dropped unused fluent python files
- Dropped unused python license generation
- Dropped helpers to run under Qt 5, as our wheels were already
requiring Qt 6 to install.
* Build action to create universal uv binary
* Drop some PyOxidizer-related files
* Use Windows ARM64 cargo/node binaries during build
We can't provide ARM64 wheels to users yet due to #4079, but we can
at least speed up the build.
The rustls -> native-tls change on Windows is because ring requires
clang to compile for ARM64, and I figured it's best to keep our Windows
deps consistent. We already built the wheels with native-tls.
* Make libankihelper a universal library
We were shipping a single arch library in a purelib, leading to
breakages when running on a different platform.
* Use Python wheel for mpv/lame on Windows/Mac
This is convenient, but suboptimal on a Mac at the moment. The first
run of mpv will take a number of seconds for security checks to run,
and our mpv code ends up timing out, repeating the process each time.
Our installer stub will need to invoke mpv once first to get it validated.
We could address this by distributing the audio with the installer/stub,
or perhaps by putting the binaries in a .pkg file that's notarized+stapled
and then included in the wheel.
* Add some helper scripts to build a fully-locked wheel
* Initial macOS launcher prototype
* Add a hidden env var to preload our libs and audio helpers on macOS
* qt/bundle -> qt/launcher
- remove more of the old bundling code
- handle app icon
* Fat binary, notarization & dmg
* Publish wheels on testpypi for testing
* Use our Python pin for the launcher too
* Python cleanups
* Extend launcher to other platforms + more
- Switch to Qt 6.8 for repo default, as 6.7 depends on an older
libwebp/tiff which is unavailable on newer installs
- Drop tools/mac-x86, as we no longer need to test against Qt 5
- Add flags to cross compile wheels on Mac and Linux
- Bump glibc target to 2_36, building on Debian Stable
- Increase mpv timeout on macOS to allow for initial gatekeeper checks
- Ship both arm64 and amd64 uv on Linux, with a bash stub to pick
the appropriate arch.
* Fix pylint on Linux
* Fix failure to run from /usr/local/bin
* Remove remaining pyoxidizer refs, and clean up duplicate release folder
* Rust dep updates
- Rust 1.87 for now (1.88 due out in around a week)
- Nom looks involved, so I left it for now
- prost-reflect depends on a new prost version that got yanked
* Python 3.13 + dep updates
Updated protoc binaries + add helper in order to try fix build breakage.
Ended up being due to an AI-generated update to pip-system-certs that
was not reviewed carefully enough:
https://gitlab.com/alelec/pip-system-certs/-/issues/36
The updated mypy/black needed some tweaks to our files.
* Windows compilation fixes
* Automatically run Anki after installing on Windows
* Touch pyproject.toml upon install, so we check for updates
* Update Python deps
- urllib3 for CVE
- pip-system-certs got fixed
- markdown/pytest also updated
* Feat/grade now
* pass ci
* fix from_queue
* Refactor card answering to support from_queue flag
- Add `from_queue` field to `CardAnswer` struct and proto message
- Modify `answer_card_inner` to handle queue updates based on `from_queue`
- Remove `grade_card` method and consolidate card answering logic
- Update related test cases to set `from_queue` flag
* fix current_changes() called when no op set
* Optimize queue updates for batch card processing
- Refactor `grade_now` to collect processed card IDs first
- Add new `update_queues_for_processed_cards` method for efficient batch queue updates
- Improve queue management by removing entries and updating counts in a single pass
- Remove individual queue update method in favor of batch processing
* pass ci
* keep the same style
* remove ineffective code
* remove unused imports
* Fix/fallback to non-manual entry when first_of_last_learn_entries non found
* refactor single_card_revlog_to_item(s)
* update unit test of bypassed_learning_is_handled
* move comment line
* remove first_relearn_entries
* skip cram entry
* only pick non_manual_entries after ignore date
* fallback to non_manual_entries if the first learning step is before the ignore date
* pass ci
* update ignore_before_date_between_learning_steps_when_reviewing
* shorten the comment
* Minor refactoring
- fsrs_items_for_memory_state - fsrs_items_for_memory_states
- single_card_revlog_to_item -> fsrs_item_for_memory_state
(to match fsrs_items_for_training)
- single_card_revlog_to_items -> reviews_for_fsrs
- Use struct instead of tuple for reviews_for_fsrs output
- Don't return count, since we're already returning the filtered list
* More renaming/comment tweaks
- non_manual_entries -> first_user_grade_idx
- change comments to reflect the fact that we're working backwards
- Use "user-graded" rather than "non-manual"
* Add extra unit test
* Some wording tweaks
* Update to FSRS-rs v1.3.2
* add fsrs_short_term_with_steps_enabled to config
* ./ninja fix:minilints
* fix defaults_for_testing
* if current parameters are invalid, skip comparison
fix#3498
* fix redundant_field_names
* cargo clippy --fix
* Update to FSRS-rs v1.3.3
* Update to FSRS-rs v1.3.4
* Avoid an extra config lookup on each card answer (dae)
* start of load balancer
* add configuration options; option to load balance per deck
* formatting
* clippy
* add myself to contributors
* cleanup
* cargo fmt
* copyright header on load_balancer.rs
* remove extra space
* more formatting
* python formatting
* ignore this being None
only doing this cause python has awful lambdas and can't
loop in a meaningful way without doing this
* only calculate notes on each day if we are trying to avoid siblings
* don't fuzz intervals if the load balancer is enabled
* force generator to eval so this actually happens
* load balance instead of fuzzing, rather than in addition to
* use builtin fuzz_bounds rather than reinvent something new
* print some debug info on how its load balancing
* clippy
* more accurately load balance only when we want to fuzz
* incorrectly doublechecking the presence of the load balancer
* more printfs for debugging
* avoid siblings -> disperse siblings
* load balance learning graduating intervals
* load balancer: respect min/max intervals; graduating easy should be at least +1 good
* filter out after-days under minimum interval
* this is an inclusive check
* switch load balancer to caching instead of on the fly calculation
* handle case where load balancer would balance outside of its bounds
* disable lb when unselecting it in preferences
* call load_balancer in StateContext::with_review_fuzz instead of next to
* rebuild load balancer when card queue is rebuilt
* remove now-unused configuration options
* add note option to notetype to enable/disable sibling dispersion
* add options to exclude decks from load balancing
* theres a lint checking that the link actually exists so I guess I'll add the anchor back in later?
* how did I even update this
* move load balancer to cardqueue
* remove per-deck balancing options
* improve determining whether to disperse siblings when load balancing
* don't recalculate notes on days every time
* remove debug code
* remove all configuration; load balancer enabled by default; disperse siblings if bury_reviews is set
* didn't fully remove caring about decks from load balancer sql query
* load balancer should only count cards in the same preset
* fuzz interval if its outside of load balancer's range
* also check minimum when bailing out of load balancer
* cleanup; make tests happy
* experimental weight-based load balance fuzzing
* take into account interval when weighting as it seems to help
* if theres no cards the interval weight is just 1.0
* make load balancer disableable through debug console
* remove debug prints
* typo
* remove debugging print
* explain a bit how load balancer works
* properly balance per preset
* use inclusive range rather than +1
* -1 type cast
* move type hint somewhere less ugly; fix comment typo
* Reuse existing deck list from parent function (dae)
Minor optimisation
Currently prop searches and the retrievability column will continue to
derive the days from the card only, as it's difficulty to integrate revlog
upgrade lookups into those code paths, especially in a performant way.
One possible way we could solve this in the future is to store last_review_day
in the card data, so we can know it even if the due date has been shifted.
Check DB could fill it in for existing cards.
If we want to be able to factor the desired retention into a sort based
on relative overdueness, having the values accessible on the card makes
things easier.
Allowing some decks to be FSRS and some SM-2 will lead to confusing
behavior when sorting on SM-2 or FSRS-specific fields, or when moving
cards between decks.
* Pack FSRS data into card.data
* Update FSRS card data when preset or weights change
+ Show FSRS stats in card stats
* Show a warning when there's a limited review history
* Add some translations; tweak UI
* Fix default requested retention
* Add browser columns, fix calculation of R
* Property searches
eg prop:d>0.1
* Integrate FSRS into reviewer
* Warn about long learning steps
* Hide minimum interval when FSRS is on
* Don't apply interval multiplier to FSRS intervals
* Expose memory state to Python
* Don't set memory state on new cards
* Port Jarret's new tests; add some helpers to make tests more compact
https://github.com/open-spaced-repetition/fsrs-rs/pull/64
* Fix learning cards not being given memory state
* Require update to v3 scheduler
* Don't exclude single learning step when calculating memory state
* Use relearning step when learning steps unavailable
* Update docstring
* fix single_card_revlog_to_items (#2656)
* not need check the review_kind for unique_dates
* add email address to CONTRIBUTORS
* fix last first learn & keep early review
* cargo fmt
* cargo clippy --fix
* Add Jarrett to about screen
* Fix fsrs_memory_state being initialized to default in get_card()
* Set initial memory state on graduate
* Update to latest FSRS
* Fix experiment.log being empty
* Fix broken colpkg imports
Introduced by "Update FSRS card data when preset or weights change"
* Update memory state during (re)learning; use FSRS for graduating intervals
* Reset memory state when cards are manually rescheduled as new
* Add difficulty graph; hide eases when FSRS enabled
* Add retrievability graph
* Derive memory_state from revlog when it's missing and shouldn't be
---------
Co-authored-by: Jarrett Ye <jarrett.ye@outlook.com>
Due to the orphan rule, this meant removing our usages of impl ProtoStruct,
or converting them to a trait when they were used commonly.
rslib now directly references anki_proto and anki_i18n, instead of
'pub use'-ing them, and we can put the generated files back in OUT_DIR.
* Move open_test_collection into Collection test impl
* Fix invalid ids when checking database
* Report fixed invalid ids
* Improve message when trying to export invalid ids
Also move ImportError due to namespace conflicts with snafu macro.
* Take a human name in DeckAdder::new
* Mention timestamps in the db check message (dae)
Will help to correlate the fix with the message shown when importing/
exporting.
* Remove outdated comment.
* Revert removal of independent bury rules
* Revert 'hierarchical bury modes'
It's now again allowed to bury new, but not review cards e.g., but
siblings of previously gathered card queues will not be buried.
* Tweak docs (dae)
* Add missing Learn and PreviewRepeat queues
* Enforce hierarchical bury modes
Interday learning burying is only allowed if review burying is enabled
and review burying is only allowed if new burying is enabled.
Closes#2352.
* Switch front end to new bury modes
* Wording tweaks (dae)
* Hide interday option if using v2 scheduler (dae)
* Run cargo +nightly fmt
* Latest prost-build includes clippy workaround
* Tweak Rust protobuf imports
- Avoid use of stringify!(), as JetBrains editors get confused by it
- Stop merging all protobuf symbols into a single namespace
* Remove some unnecessary qualifications
Found via IntelliJ lint
* Migrate some asserts to assert_eq/ne
* Remove mention of node_modules exclusion
This no longer seems to be necessary after migrating away from Bazel,
and excluding it means TS/Svelte files can't be edited properly.
* Add crate snafu
* Replace all inline structs in AnkiError
* Derive Snafu on AnkiError
* Use snafu for card type errors
* Use snafu whatever error for InvalidInput
* Use snafu for NotFoundError and improve message
* Use snafu for FileIoError to attach context
Remove IoError.
Add some context-attaching helpers to replace code returning bare
io::Errors.
* Add more context-attaching io helpers
* Add message, context and backtrace to new snafus
* Utilize error context and backtrace on frontend
* Rename LocalizedError -> BackendError.
* Remove DocumentedError.
* Have all backend exceptions inherit BackendError.
* Rename localized(_description) -> message
* Remove accidentally committed experimental trait
* invalid_input_context -> ok_or_invalid
* ensure_valid_input! -> require!
* Always return `Err` from `invalid_input!`
Instead of a Result to unwrap, the macro accepts a source error now.
* new_tempfile_in_parent -> new_tempfile_in_parent_of
* ok_or_not_found -> or_not_found
* ok_or_invalid -> or_invalid
* Add crate convert_case
* Use unqualified lowercase type name
* Remove uses of snafu::ensure
* Allow public construction of InvalidInputErrors (dae)
Needed to port the AnkiDroid changes.
* Make into_protobuf() public (dae)
Also required for AnkiDroid. Not sure why it worked previously - possible
bug in older Rust version?
* Enable state-dependent custom scheduling data
* Next(Card)States -> SchedulingStates
The fact that `current` was included in `next` always bothered me,
and custom data is part of the card state, so that was a bit confusing
too.
* Store custom_data in SchedulingState
* Make custom_data optional when answering
Avoids having to send it 4 extra times to the frontend, and avoids the
legacy answerCard() API clobbering the stored data.
Co-authored-by: Damien Elmes <gpg@ankiweb.net>
* Add card meta for persisting custom scheduling state
* Rename meta -> custom_data
* Enforce limits on size of custom data
Large values will slow down table scans of the cards table, and it's
easier to be strict now and possibly relax things in the future than
the opposite.
* Pack card states and customData into a single message
+ default customData to empty if it can't be parsed
Co-authored-by: Damien Elmes <gpg@ankiweb.net>