* Drop support for checkpoints
* Deprecate .flush()
* Remove .begin/.commit
* Remove rollback() and deprecate save/autosave/reset()
There's no need to commit anymore, as the Rust code is handling
transactions for us.
* Add safer transact() method
This will ensure add-on authors can't accidentally leave a transaction
open, leading to data loss.
---------
Co-authored-by: Damien Elmes <gpg@ankiweb.net>
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>
* 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>
* Replace Card.data with .original_position
* Use and update original position in v3
* Show original position in card info
* Revert restoring original position for now
* Fix pb card to/from pylib card
* Try original_position as the last pb field
* minor wording tweaks (dae)
* Use submodule imports in aqt
* Use submodule imports in pylib
* More submodule imports in pylib
These required removing some direct imports to get rid of import cycles.
The packaged builds of 2.1.50 use python -OO, which means our assertion
statements won't be run. This is not an issue for unit tests (as we
don't run them from a packaged build), or for type assertions (which are
added for mypy's benefit), but we do need to ensure that invariant checks
are still run.
This adds Python 3.9 and 3.10 typing syntax to files that import
attributions from __future___. Python 3.9 should be able to cope with
the 3.10 syntax, but Python 3.8 will no longer work.
On Windows/Mac, install the latest Python 3.9 version from python.org.
There are currently no orjson wheels for Python 3.10 on Windows/Mac,
which will break the build unless you have Rust installed separately.
On Linux, modern distros should have Python 3.9 available already. If
you're on an older distro, you'll need to build Python from source first.
In order to split backend.proto into a more manageable size, the protobuf
handling needed to be updated. This took more time than I would have
liked, as each language handles protobuf differently:
- The Python Protobuf code ignores "package" directives, and relies
solely on how the files are laid out on disk. While it would have been
nice to keep the generated files in a private subpackage, Protobuf gets
confused if the files are located in a location that does not match
their original .proto layout, so the old approach of storing them in
_backend/ will not work. They now clutter up pylib/anki instead. I'm
rather annoyed by that, but alternatives seem to be having to add an extra
level to the Protobuf path, making the other languages suffer, or trying
to hack around the issue by munging sys.modules.
- Protobufjs fails to expose packages if they don't start with a capital
letter, despite the fact that lowercase packages are the norm in most
languages :-( This required a patch to fix.
- Rust was the easiest, as Prost is relatively straightforward compared
to Google's tools.
The Protobuf files are now stored in /proto/anki, with a separate package
for each file. I've split backend.proto into a few files as a test, but
the majority of that work is still to come.
The Python Protobuf building is a bit of a hack at the moment, hard-coding
"proto" as the top level folder, but it seems to get the job done for now.
Also changed the workspace name, as there seems to be a number of Bazel
repos moving away from the more awkward reverse DNS naming style.
Avoids duplicate work, and is a step towards allowing the next
states to be modified by third-party code.
Also:
- fixed incorrect underlined count, due to reviews being labeled as
learning cards
- fixed reviewer not refreshing when undoing a test review, by splitting
up backend queue rebuilding from frontend reviewer refresh
- moved answering into a CollectionOp
'card modified' covers the common case where we need to rebuild the
study queue, but is also set when changing the card flags. We want to
avoid a queue rebuild in that case, as it causes UI flicker, and may
result in a different card being shown. Note marking doesn't trigger
a queue build, but still causes flicker, and may return the user back
to the front side when they were looking at the answer.
I still think entity-based change tracking is the simplest in the
common case, but to solve the above, I've introduced an enum describing
the last operation that was taken. This currently is not trying to list
out all possible operations, and just describes the ones we want to
special-case.
Other changes:
- Fire the old 'state_did_reset' hook after an operation is performed,
so legacy code can refresh itself after an operation is performed.
- Fire the new `operation_did_execute` hook when mw.reset() is called,
so that as the UI is updated to the use the new hook, it will still
be able to refresh after legacy code calls mw.reset()
- Update the deck browser, overview and review screens to listen to
the new hook, instead of relying on the main window to call moveToState()
- Add a 'set flag' backend action, so we can distinguish it from a
normal card update.
- Drop the separate added/modified entries in the change list in
favour of a single entry per entity.
- Add typing to mw.state
- Tweak perform_op()
- Convert a few more actions to use perform_op()
This splits update_card() into separate undoable/non-undoable ops
like the change to notes in b4396b94abdeba3347d30025c5c0240d991006c9
It means that actions get a blanket 'Update Card' description - in the
future we'll probably want to either add specific actions to the backend,
or allow an enum or string to be passed in to describe the op.
Other changes:
- card.flush() can no longer be used to add new cards. Card creation
is only supposed to be done in response to changes in a note's fields,
and this functionality was only exposed because the card generation
hadn't been migrated to the backend at that point. As far as I'm aware,
only Arthur's "copy notes" add-on used this functionality, and that should
be an easy fix - when the new note is added, the associated cards will
be generated, and they can then be retrieved with note.cards()
- tidy ups/PEP8
- note.flush() behaves like before, as otherwise actions or add-ons
that perform bulk flushing would end up creating an undo entry for
each note
- added col.update_note() to opt in to the new behaviour
- tidy up the names of some related routines
- anki._backend stores the protobuf files and rsbackend.py code
- pylib modules import protobuf messages directly from the
_pb2 files, and explicitly export any will be returned or consumed
by public pylib functions, so that calling code can import from pylib
- the "rsbackend" no longer imports and re-exports protobuf messages
- pylib can just consume them directly.
- move errors to errors.py
Still todo:
- rsbridge
- finishing the work on rsbackend, and check what we need to add
back to the original file location to avoid breaking add-ons
- changes are now committed in bulk when closing the dialog,
and can be canceled
- it's not necessary to save the note to the database to preview it
- duplicate fields are now shown as duplicates in the top list
- redraw preview more quickly
- use + instead of _ when deduplicating names, as the latter is a
glob character
Saves having to serialize the note fields and q/a templates, which
is particularly a win when rendering question/answer in the browse
screen.
Also some work towards being able to preview notes without having to
commit them to the database.
