* 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
* Feat/FSRS-6
* update comment
* add decay to Card
* ./ninja fix:minilints
* pass check
* fix NaN in evaluation
* remove console
* decay should fallback to 0.5 when it's None.
* Update SimulatorModal.svelte
* Update a few comments
* Update FSRS decay defaults to use constants for better maintainability and clarity
* Update rslib/src/storage/card/data.rs
* Empty cards is undoable
If there was a reason for this operation not to be undoable, I can't easily guess it. My main hyposhesis was that the number of deleted card may be too big. But I realized that deleting a deck is undoable and may delete as many note.
As you may know, I realized that only the undoable operations triggered notification in AnkiDroid that we may have to update the UI. And while I just wanted to trigger more notifications, some reviewers thought it would be nicer if the operation were returning a OpChanges. So here it's done. If you would please consider merging it.
I decided to introduce a new string because the closest strings I could find currently are "Empty cards..." and the trailing commas don't seem nice in "undo". And the title, which we may not be able to reuse in all language
* Don't count cards that have already been removed (dae)
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.
* 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>
* Automatically elide empty inputs and outputs to backend methods
* Refactor service generation
Despite the fact that the majority of our Protobuf service methods require
an open collection, they were not accessible with just a Collection
object. To access the methods (e.g. because we haven't gotten around to
exposing the correct API in Collection yet), you had to wrap the collection
in a Backend object, and pay a mutex-acquisition cost for each call, even
if you have exclusive access to the object.
This commit migrates the majority of service methods to the Collection, so
they can now be used directly, and improves the ergonomics a bit at the
same time.
The approach taken:
- The service generation now happens in rslib instead of anki_proto, which
avoids the need for trait constraints and associated types.
- Service methods are assumed to be collection-based by default. Instead of
implementing the service on Backend, we now implement it on Collection, which
means our methods no longer need to use self.with_col(...).
- We automatically generate methods in Backend which use self.with_col() to
delegate to the Collection method.
- For methods that are only appropriate for the backend, we add a flag in
the .proto file. The codegen uses this flag to write the method into a
BackendFooService instead of FooService, which the backend implements.
- The flag can also allows us to define separate implementations for collection
and backend, so we can e.g. skip the collection mutex in the i18n service
while also providing the service on a collection.
