The undo code was using triggers and a temporary table to write out all changed rows before making a change. This made for powerful undo/redo support, but had some problems:
- creating the tables and triggers wasn't cheap, especially on mobile devices
- likewise, every data modification required writing into two separate databases, almost doubling the amount of writes required
- it was possible to leave the DB in an inconsistent state if an undoable operation is followed by a non-undoable operation that references the undoable operation, and the user then rolls back the undoable operation.
To address these issues, we simplify undo by integrating it with the autosave changes:
- .save() can be passed a name to mark a rollback point. If the user undoes the change, any changes since the last save are lost
- autosaves happen every 5 minutes, and are pushed back on a .save(), so the maximum work a user can lose is 5 minutes.
- reviews are handled separately, so we can let the user undo multiple reviews at once
- if necessary, special cases could be added for other operations like marking
This means that if a user does two damaging operations in a row they won't be able to restore the first one, but such an event is both unlikely, and is also covered by the backups made each time a deck is opened.
Previously cloze deletions were handled by copying the contents of one field
into another and applying transforms to it. This had a number of problems:
- after you add a card, you can't undo the cloze deletion
- if you spot a mistake, you have to edit it twice (or more if you have more
than one cloze for a sentence)
- making multiple clozes requires copying & pasting the sentence multiple
times
- this also lead to much bigger decks if the sentences being cloze-deleted are
large
- related clozes can't be spaced apart as siblings
To address these issues, we introduce the idea of cloze tags in the card
template and fields. If the template has the text:
{{cloze:1:field}}
And a field has the following contents:
{{c1::hello}}
Then the template will automatically replace that part of the text with either
occluded text, or a highlighted answer. All other clozes in the field are
displayed normally.
At the same time, we add support for text: into the template library, instead
of manually creating text: fields in the dict for every field.
Finally, add a forecast routine to get the due counts for the next week, which
is used in the GUI.
The media table was originally introduced when Anki hashed media filenames,
and needed a way to remember the original filename. It also helped with:
1) getting a quick list of all media used in the deck, or the media added
since the last sync, for mobile clients
2) merging identical files with different names
But had some drawbacks:
- every operation that modifies templates, models or facts meant generating
the q/a and checking if any new media had appeared
- each entry is about 70 bytes, and some decks have 100k+ media files
So we remove the media table. We address 1) by being more intelligent about
media downloads on the mobile platform. We ask the user after a full sync if
they want to look for missing media, and they can choose not to if they know
they haven't added any. And on a partial sync, we can scan the contents of the
incoming facts for media references, and download any references we find. This
also avoids all the issues people had with media not downloading because it
was in their media folder but not in the media database.
For 2), when copying media to the media folder, if we have a duplicate
filename, we check if that file has the same md5, and avoid copying if so.
This won't merge identical content that has separate names, but instances
where users need that are rare.
The 'entry due' is the due time of a failed card before it enters the learning
queue. When the card graduates or is removed, it has its old due time
restored. We could pull this from the revlog, but it's cheaper to do it this
way.
We originally were triggering on 100 opcodes, because at the time we were
doing write-heavy alterations to the DB for inactive tags, and a higher level
of opcodes would pause the interface for a long time. The query structure is
different now, so we can afford to save the overhead of more frequent calls.
With the change, a .reset() triggers the handler 3 times; fixIntegrity()
triggers it 30 times over a period of 4.5 seconds.
A lot of the old checks in fixIntegrity() are no longer relevant, and some of
the others may no longer be required. They can be added back in as the need
arises.
We want to ensure that we never recycle ids from deleted cards. We could do
this with an autoincrement column in sqlite, but it's cheaper for us to handle
the ids ourselves, as the deck object is always in memory.
- remove revlog.py and move code into scheduler
- add a routine to log a learn repetition
- rename flags to type and set type=0 for learn mode
- add to unit test
Because the cards table is small now, loading it in and doing a table scan
isn't necessary. The facts table is bigger now, so we still need that index.
When adding facts, you can now pass in a group id which the GUI should support
editing. Templates will have an optional group id which overrides the provided
id, so users can automatically put certain card types in a different group (or
all of them, if desired). Greying out the group box in the GUI in that case
would be a good idea.
This means that the default learn queue sort order doesn't need another column
in the index, but it also means that generated cards will have a higher id,
and would appear later even if they have a lower ordinal. This is probably an
infrequent issue, and a plugin which rewrites ids would probably be an
adequate solution.
Our goal is to allow decks created on one platform to use similar fonts (even
if named differently) when moving to another platform. The old solution wasn't
useful for the web version or mobile versions. Instead, we store a mapping in
the deck, and when generating the CSS, we list all possible fonts. An option
in the interface for the user to add extra fonts might be nice.
The model now has a css column, and when it's flushed, it generates the css
for the fields and templates. This means we don't have to generate the CSS on
deck load anymore.
The hex cache has also been removed. Javascript couldn't handle big ints, but
since ints are small numbers now, we no longer need a cache to efficiently
convert an id to hex.
- convert checksums to int
- add bulk update & update on upgrade
- add indices pending performance testing. The fsum table & indices add about
2MB to a deck with 50k unique fields
the field cache (fsums table) also needs to store the model id to preserve the
old behaviour of limiting duplicate checks to a given model, and to ensure
we're actually comparing against the same fields
removed the dingsbums and wcu importers; will accept them back if the authors
port them to the new codebase.
Since Anki first moved to an SQL backend, it has stored fields in a fields
table, with one field per line. This is a natural layout in a relational
database, and it had some nice properties. It meant we could retrieve an
individual field of a fact, which we used for limiting searches to a
particular field, for sorting, and for determining if a field was unique, by
adding an index on the field value.
The index was very expensive, so as part of the early work towards 2.0 I added
a checksum field instead, and added an index to that. This was a lot cheaper
than storing the entire value twice for the purpose of fast searches, but it
only partly solved the problem. We still needed an index on factId so that we
could retrieve a given fact's fields quickly. For simple models this was
fairly cheap, but as the number of fields grows the table grows very big. 25k
facts with 30 fields each and the fields table has grown to 750k entries. This
makes the factId index and checksum index really expensive - with the q/a
cache removed, about 30% of the deck in such a situation.
Equally problematic was sorting on those fields. Short of adding another
expensive index, a sort involves a table scan of the entire table.
We solve these problems by moving all fields into the facts table. For this to
work, we need to address some issues:
Sorting: we'll add an option to the model to specify the sort field. When
facts are modified, that field is written to a separate sort column. It can be
HTML stripped, and possibly truncated to a maximum number of letters. This
means that switching sort to a different field involves an expensive rewrite
of the sort column, but people tend to leave their sort field set to the same
value, and we don't need to clear the field if the user switches temporarily
to a non-field sort like due order. And it has the nice properties of allowing
different models to be sorted on different columns at the same time, and
makes it impossible for models to be hidden because the user has sorted on a
field which doesn't appear in some models.
Searching for words with embedded HTML: 1.2 introduced a HTML-stripped cache
of the fields content, which both sped up searches (since we didn't have to
search the possibly large fields table), and meant we could find "bob" in
"b<b>ob</b>" quickly. The ability to quickly search for words peppered with
HTML was nice, but it meant doubling the cost of storing text in many cases,
and meant after any edit more data has to be written to the DB. Instead, we'll
do it on the fly. On this i7 computer, stripping HTML from all fields takes
1-2.6 seconds on 25-50k decks. We could possibly skip the stripping for people
who don't require it - the number of people who bold parts of words is
actually pretty small.
Duplicate detection: one option would be to fetch all fields when the add
cards dialog or editor are opened. But this will be expensive on mobile
devices. Instead, we'll create a separate table of (fid, csum), with an index
on both columns. When we edit a fact, we delete all the existing checksums for
that fact, and add checksums for any fields that must be checked as unique. We
could optionally skip the index on csum - some benchmarking is required.
As for the new table layout, creating separate columns for each field won't
scale. Instead, we store the fields in a single column, separated by an ascii
record separator. We split on that character when extracting from
the database, and join on it when writing to the DB.
Searching on a particular field in the browser will be accomplished by finding
all facts that match, and then unpacking to see if the relevant field matched.
Tags have been moved back to a separate column. Now that fields are on the
facts table, there is no need to pack them in as a field simply to avoid
another table hit.
Anki used random 64bit IDs for cards, facts and fields. This had some nice
properties:
- merging data in syncs and imports was simply a matter of copying each way,
as conflicts were astronomically unlikely
- it made it easy to identify identical cards and prevent them from being
reimported
But there were some negatives too:
- they're more expensive to store
- javascript can't handle numbers > 2**53, which means AnkiMobile, iAnki and
so on have to treat the ids as strings, which is slow
- simply copying data in a sync or import can lead to corruption, as while a
duplicate id indicates the data was originally the same, it may have
diverged. A more intelligent approach is necessary.
- sqlite was sorting the fields table based on the id, which meant the fields
were spread across the table, and costly to fetch
So instead, we'll move to incremental ids. In the case of model changes we'll
declare that a schema change and force a full sync to avoid having to deal
with conflicts, and in the case of cards and facts, we'll need to update the
ids on one end to merge. Identical cards can be detected by checking to see if
their id is the same and their creation time is the same.
Creation time has been added back to cards and facts because it's necessary
for sync conflict merging. That means facts.pos is not required.
The graves table has been removed. It's not necessary for schema related
changes, and dead cards/facts can be represented as a card with queue=-4 and
created=0. Because we will record schema modification time and can ensure a
full sync propagates to all endpoints, it means we can remove the dead
cards/facts on schema change.
Tags have been removed from the facts table and are represented as a field
with ord=-1 and fmid=0. Combined with the locality improvement for fields, it
means that fetching fields is not much more expensive than using the q/a
cache.
Because of the above, removing the q/a cache is a possibility now. The q and a
columns on cards has been dropped. It will still be necessary to render the
q/a on fact add/edit, since we need to record media references. It would be
nice to avoid this in the future. Perhaps one way would be the ability to
assign a type to fields, like "image", "audio", or "latex". LaTeX needs
special consider anyway, as it was being rendered into the q/a cache.
- make sure we're actually stripping text in the field cache
- make sure a default group is added on upgrade
- make sure old style field references are upgrade
SQLAlchemy is a great tool, but it wasn't a great fit for Anki:
- We often had to drop down to raw SQL for performance reasons.
- The DB cursors and results were wrapped, which incurred a
sizable performance hit due to introspection. Operations like fetching 50k
records from a hot cache were taking more than twice as long to complete.
- We take advantage of sqlite-specific features, so SQL language abstraction
is useless to us.
- The anki schema is quite small, so manually saving and loading objects is
not a big burden.
In the process of porting to DBAPI, I've refactored the database schema:
- App configuration data that we don't need in joins or bulk updates has been
moved into JSON objects. This simplifies serializing, and means we won't
need DB schema changes to store extra options in the future. This change
obsoletes the deckVars table.
- Renamed tables:
-- fieldModels -> fields
-- cardModels -> templates
-- fields -> fdata
- a number of attribute names have been shortened
Classes like Card, Fact & Model remain. They maintain a reference to the deck.
To write their state to the DB, call .flush().
Objects no longer have their modification time manually updated. Instead, the
modification time is updated when they are flushed. This also applies to the
deck.
Decks will now save on close, because various operations that were done at
deck load will be moved into deck close instead. Operations like undoing
buried card are cheap on a hot cache, but expensive on startup.
Programmatically you can call .close(save=False) to avoid a save and a
modification bump. This will be useful for generating due counts.
Because of the new saving behaviour, the save and save as options will be
removed from the GUI in the future.
The q/a cache and field cache generating has been centralized. Facts will
automatically rebuild the cache on flush; models can do so with
model.updateCache().
Media handling has also been reworked. It has moved into a MediaRegistry
object, which the deck holds. Refcounting has been dropped - it meant we had
to compare old and new value every time facts or models were changed, and
existed for the sole purpose of not showing errors on a missing media
download. Instead we just media.registerText(q+a) when it's updated. The
download function will be expanded to ask the user if they want to continue
after a certain number of files have failed to download, which should be an
adequate alternative. And we now add the file into the media DB when it's
copied to th emedia directory, not when the card is commited. This fixes
duplicates a user would get if they added the same media to a card twice
without adding the card.
The old DeckStorage object had its upgrade code split in a previous commit;
the opening and upgrading code has been merged back together, and put in a
separate storage.py file. The correct way to open a deck now is import anki; d
= anki.Deck(path).
deck.getCard() -> deck.sched.getCard()
same with answerCard
deck.getCard(id) returns a Card object now.
And the DB wrapper has had a few changes:
- sql statements are a more standard DBAPI:
- statement() -> execute()
- statements() -> executemany()
- called like execute(sql, 1, 2, 3) or execute(sql, a=1, b=2, c=3)
- column0 -> list
The tags tables were initially added to speed up the loading of the browser by
speeding up two operations: gathering a list of all tags to show in the
dropdown box, and finding cards with a given tag. The former functionality is
provided by the tags table, and the latter functionality by the cardTags
table.
Selective study is handled by groups now, which perform better since they
don't require a join or subselect, and can be embedded in the index. So the
only remaining benefit of cardTags is for the browser.
Performance testing indicates that cardTags is not saving us a large amount.
It only takes us 30ms to search a 50k card table for matches with a hot cache.
On a cold cache it means the facts table has to be loaded into memory, which
roughly doubles the load time with the default settings (we need to load the
cards table too, as we're sorting the cards), but that startup time was
necessary with certain settings in the past too (sorting by fact created for
example). With groups implemented, the cost of maintaining a cache just for
initial browser load time is hard to justify.
Other changes:
- the tags table has any missing tags added to it when facts are added/edited.
This means old tags will stick around even when no cards reference them, but
is much cheaper than reference counting or a separate table, and simplifies
updates and syncing.
- the tags table has a modified field now so we can can sync it instead of
having to scan all facts coming across in a sync
- priority field removed
- we no longer put model names or card templates into the tags table. There
were two reasons we did this in the past: so we could cram/selective study
them, and for plugins. Selective study uses groups now, and plugins can
check the model's name instead (and most already do). This also does away
with the somewhat confusing behaviour of names also being tags.
- facts have their tags as _tags now. You can get a list with tags(), but
editing operations should use add/deleteTags() instead of manually editing
the string.
- removed 'created' column from various tables. We don't care when things like
models are created, and card creation time didn't reflect the actual time a
card was created
- facts were previously ordered by their creation date. The code would
manually set the creation time for subsequent facts on import by 0.0001
seconds, and then card due times were set by adding the fact time to the
ordinal number*0.000001. This was prone to error, and the number of zeros used
was actually different in different parts of the code. Instead of this, we
replace it with a 'pos' column on facts, which increments for each new fact.
- importing should add new facts with a higher pos, but concurrent updates in
a synced deck can have multiple facts with the same pos
- due times are completely different now, and depend on the card type
- new cards have due=fact.pos or random(0, 10000)
- reviews have due set to an integer representing days since deck
creation/download
- cards in the learn queue use an integer timestamp in seconds
- many columns like modified, lastSync, factor, interval, etc have been converted to
integer columns. They are cheaper to store (large decks can save 10s of
megabytes) and faster to search for.
- cards have their group assigned on fact creation. In the future we'll add a
per-template option for a default group.
- switch to due/random order for the review queue on upgrade. Users can still
switch to the old behaviour if they want, but many people don't care what
it's set to, and due is considerably faster, which may result in a better
user experience
- instead of the old 4 settings, we move to just two, as there's no point
having separate include and exclude options for a non-overlapping set of
cards
- revGroups and newGroups are a list of groupIds to include in the queue. If
all groups are enabled, the UI should set it to an empty list rather than a
list of every available group, and groupLimit() will leave off the
constraint completely
- skip updating buried cards on startup; it's expensive and we'll do that on
deck close in the future
- add an index for groupId. Initial profiling indicates that groupId-based
selective study is considerably faster in certain scenarios
The 50k element deck I'm testing with now opens and builds the queue in 40ms
on a cold cache, of which 34ms is the initial deck startup and 6ms the queue
build. Adding back the undo log and backups will of course increase this, but
this is a big improvement for checking due times in the deck browser.
Users who want to study small subsections at one time (eg, "lesson 14") are
currently best served by creating lots of little decks. This is because:
- selective study is a bit cumbersome to switch between
- the graphs and statitics are for the entire deck
- selective study can be slow on mobile devices - when the list of cards to
hide/show is big, or when there are many due cards, performance can suffer
- scheduling can only be configured per deck
Groups are intended to address the above problems. All cards start off in the
same group, but they can have their group changed. Unlike tags, cards can only
be a member of a single group at once time. This allows us to divide the deck
up into a non-overlapping set of cards, which will make things like showing
due counts for a single category considerably cheaper. The user interface
might want to show something like a deck browser for decks that have more than
one group, showing due counts and allowing people to study each group
individually, or to study all at once.
Instead of storing the scheduling config in the deck or the model, we move the
scheduling into a separate config table, and link that to the groups table.
That way a user can have multiple groups that all share the same scheduling
information if they want.
And deletion tracking is now in a single table.
- limits are stored separately so we can access them quickly when checking
deck counts
- data is used to store cssCache and hexCache; these may be refactored or go
away in the future
- model config is now stored as a json-serialized dict, which allows us to
quickly gather the info and allows for adding extra options more easily in
the future
- denormalize modelId into the cards table, so we can get the model scheduling
information without having to hit the facts table
- remove position - since we will handle spacing differently we don't need a
separate variable to due to define sort order
- remove lastInterval from cards; the new cram mode and review early shouldn't
need it
- successive->streak
- add new columns for learn mode
- move cram mode into new file; learn more and review early need more thought
- initial work on learn mode
- initial unit tests
- move most scheduling parameters from deck to models
- remove obsolete fields in deck and models
- decks->deck
- remove deck id reference in models
- move some deckVars into the deck table
- simplify deckstorage
- lock sessionhelper by default
- add models/currentModel as properties instead of ORM mappings
- remove models.tags
- remove remaining support for memory-backed databases
- use a blank string for syncName instead of null
- remove backup code; will handle in gui
- bump version to 100
- update unit tests
- tags.tag -> tags.name
- priority reset to 0 for now; will be used differently in the future
- cardTags.id removed; (tagId, cardId) is the primary key now
- cardTags.src -> cardTags.type
Cards had developed quite a lot of cruft from incremental changes, and a
number of important attributes were stored in names that had no bearing to
their actual use.
Added:
- position, which new cards will be sorted on in the future
- flags, which is reserved for future use
Renamed:
- type to queue
- relativeDelay to type
- noCount to lapses
Removed:
- all new/young/matureEase counts; the information is in the revlog
- firstAnswered, lastDue, lastFactor, averageTime and totalTime for the same
reason
- isDue, spaceUntil and combinedDue, because they are no longer used. Spaced
cards will be implemented differently in a coming commit.
- priority
- yesCount, because it can be inferred from reps & lapses
- tags; they've been stored in facts for a long time now
Also compatibility with deck versions less than 65 has been dropped, so decks
will need to be upgraded to 1.2 before they can be upgraded by the dev code.
All shared decks are on 1.2, so this should hopefully not be a problem.
- rename to revlog
- change the pk to time, as we want an index on time, and the old multi-column
index was expensive and not useful
- remove yes/no count; they can be inferred from the ease
- remove lastFactor, as it's in the previous entry
- remove delay, it can be inferred from last entry
- remove 'next' from nextInterval and nextFactor
- rename 'thinkingTime' to 'userTime'
- rename reps to rep
- migrate old data to new table, and fix some problems in the process: ease0
-> ease1, and limit thinking time to 60 seconds as it should have been
previously
The stats table was how the early non-SQL versions of Anki kept track of
statistics, before there was a revision log. It is being removed because:
- it's not possible to show the statistics for a subset of the deck
- it can't meaningfully be copied on import/export
- it makes it harder to implement sync merging
Implications:
- graphs and deck stats roughly 1.5-3x longer than before, but we'll have the
ability to generate stats for subsections of the deck, and it's not time
critical code
- people who've been using anki since the very early days may notice a drop in
statistics, as early repetitions were recorded in the stats table but the
revlog didn't exist at that point.
- due bugs in old syncs and imports/exports, the stats and revlog may not
match numbers exactly
To remove it, the following changes have been made:
- the graphs and deck stats now generate their data entirely from the revlog
- there are no stats to keep track of how many cards we've answered, so we
pull that information from the revlog in reset()
- we remove _globalStats and _dailyStats from the deck
- we check if a day rollover has occurred using failedCutoff instead
- we remove the getStats() routine
- the ETA code is currently disabled
- timeboxing routines use repsToday instead of stats
- remove stats delete from export
- remove stats table and index in upgrade
- remove stats syncing and globalStats refresh pre-sync
- remove stats count check in fullSync check, which was redundant anyway
- update unit tests
Also:
- newCountToday -> newCount, to bring it in line with revCount&failedCount
which also reflect the currently due count
- newCount -> newAvail
- timeboxing routines renamed since the old names were confusingly similar to
refreshSession() which does something different
Todo:
- update newSeenToday & repsToday when answering a card
- reimplement eta
Calculating the average on startup is expensive on mobile devices. It might be
nice to provide it as a deck option or per-model setting in the future so that
people can specify how hard their material is and have it treated accordingly.
Previously we had an index on the value field, which was very expensive for
long fields. Instead we use a separate column and take the first 8 characters
of the field value's md5sum, and index that. In decks with lots of text in
fields, it can cut the deck size by 30% or more, and many decks improve by
10-20%. Decks with only a few characters in fields may increase in size
slightly, but this is offset by the fact that we only generate a checksum for
fields that have uniqueness checking on.
Also, fixed import->update reporting the total # of available facts instead of
the number of facts that were imported.
Anki 1.0 had a similar feature but we do things a bit differently now. The
relative spacing applies only to reviews, and spaces cards according to their
interval, instead of spacing all cards the same. Any delay < 1 full day is
treated as no delay, so with the default 10% setting, reviews with an interval
< 10 days are not spaced at all. This should hopefully cut down on support
queries for people wondering why many of their cards were delayed, allows the
two settings to be documented separately, and does away with the somewhat
confusing usage of non-integer new sibling values to disable review spacing.
- this fixes a state where cards failed on that future day could end up
with an earlier due date that the rest of the failed mature cards, leading
to the newly failed cards being repeated prematurely
- this leads to non-deterministic scheduling of the mature bonus fails, so
they are effectively randomized which is probably what most users want
if a client with a clock greater than server time synced a deck, the modified
time ended up higher than lastSync when the deck was modified on the server.
instead we force the modified time to be <= the server time, which is known
correct.
this addresses a bug where mplayer was sometimes not being restarted when
opening a new deck, and should remove the need for atexit or hacks in the GUI
code to make sure mplayer is closed
This works fine if the user is showing all cards, but if they have limited
reviews to certain categories, it can result in the counts going negative
because we decremented for cards which weren't actually due. Determining if a
card was actually due or not is an expensive operation, so instead we leave
the counts alone and make sure reviews will finish early if the new/rev counts
are non-zero but the queue is empty.
because field formatting is always on now, users with custom font
sizes/families set only on the card will still have to alter their templates
and either configure the fields or replace the references with triple
curly braces
- move latex preamble into a deck var and include amsmath by default
- include the pre/postamble in the hash, so changes to the preamble result in
newly generated images
- latex now slots in to the formatQA hook to render images in the q/a
- moved call() to utils
- cache/uncache latex have been obsoleted. User can delete manually, and
images will be regenerated with a DB check
- media is no longer hashed, and instead stored in the db using its original
name
- when adding media, its checksum is calculated and used to look for
duplicates
- duplicate filenames will result in a number tacked on the file
- the size column is used to count card references to media. If media is
referenced in a fact but not the question or answer, the count will be zero.
- there is no guarantee media will be listed in the media db if it is unused
on the question & answer
- if rebuildMediaDir(delete=True), then entries with zero references are
deleted, along with any unused files in the media dir.
- rebuildMediaDir() will update the internal checksums, and set the checksum
to "" if a file can't be found
- rebuildMediaDir() is a lot less destructive now, and will leave alone
directories it finds in the media folder (but not look in them either)
- rebuildMediaDir() returns more information about the state of media now
- the online and mobile clients will need to to make sure that when
downloading media, entries with no checksum are non-fatal and should not
abort the download process.
- the ref count is updated every time the q/a is updated - so the db should be
up to date after every add/edit/import
- since we look for media on the q/a now, card templates like '<img
src="{{{field}}}">' will work now
- export original files as gone as it is not needed anymore
- move from per-model media URL to deckVar. downloadMissingMedia() uses this
now. Deck subscriptions will have to be updated to share media another way.
- pass deck in formatQA, as latex support is going to change
this bypasses rebuilding the queue and other startup initialization and thus
loads the deck considerably faster. This is useful when you want to perform
operations on the deck like syncing, but don't need the ability to review
cards
- obsolete spaceUntil - it serves no useful purpose
- the old per-model spacing variables are obsolete, as the new approach
requires uniform spacing across all models for new cards
- introduce a new per-deck variable: newSpacing
- don't fill new queue if we've done today's cards
- still need to check cramming / review early
newSpacing is a time in seconds to delay introduction of sibling new cards.
It can be applied as many times as necessary as there is no harm in new cards
being delayed repeatedly. Because the default queue length is 200 and it can
take quite some time for the spaced cards to be placed in the queue again, we
use a separate array to track spaced new cards provided the configured delay
is less than 20 minutes. At times under 20 minutes this number is not a
guaranteed minimum spacing - if the new card queue is empty the spaced cards
will be flushed before checking the new queue again, as otherwise we end up
trying to fill on every repetition. The due counts no longer decrease by more
than one if the spacing is less than the due cutoff, since that confused some
users.
Review cards are now placed at the end of the current review queue, and will
never be rescheduled to a different day. The old approach had a number of
problems:
- the more card models you had, the more likely a card would be spaced
multiple times, resulting in you forgetting the card before you get a chance
to review it
- spacing was applied even if the due card was already late
- repeatedly failing one card over a period of days or weeks would also stave
the other cards of attention
- use bar graphs instead of line graphs for 3 months or less
- easier to read shades of blue for reps graph
- simplify day cutoff calculation
- fix off by one bug in work done data
- add missing entries when calculating cumulative due
- the local deck name must now match the online deck
- syncName is a hash of the current deck's path or None
- the hash is checked on deck load, and if it is different (because the deck
was copied or moved), syncing is disabled. This should prevent people from
accidentally clobbering their online decks
When you call operations like deleteCards(), suspendCards() and so on, it is
now necessary to call deck.reset() afterwards. This allows the calling code to
delay a reset if necessary. If the calling code calls a function that says the
caller must reset, the caller should be sure to call .reset() and fetch the
current card again. Failure to do the latter will result in answerCard()
attempting to remove the card from the queue, when the queue has been cleared.
- make sure cardLimit() matches on sql statements that are broken over lines
- fix logic in getCardId()
- don't increment failed count if delay1>0 and card was mature
The old delay1 behaviour isn't easy to achieve with the queue code, as we only
refresh the queue when it's emptied, and if the user has delay1 set to say 9
hours, failed mature cards sitting in the queue could prevent subsequent young
failures from being displayed. Instead we convert delay1 to a count in days in
which to offset failed mature cards. 0 means the same time as delay0, 1 means
show the card a day later, and so on. This means users will lose the ability
to delay mature cards for x number of minutes more than young cards, but a
scan of AnkiOnline decks indicates that's not often done.
We also need to use a separate cutoff for failed cards, since we need to be
able to display them as they expire if the user has disabled per-day
scheduling.
And instead of marking cards as due in the future, we set their due time to
the current time, and move the delay0 calculation to getCardId(). This means
that if the user changes their failed card settings from say 1 hour to 10
minutes, the changes apply to the currently failed cards and not just cards
failed in the future.
In various parts of the code we need to get all cards of a given category
(new, failed, etc) regardless of whether they're suspended, buried, etc. So we
store the true type in the obsolete relativeDelay column and add in index for
it, because it's cheaper than putting indices on reps & successive.
- because the cutoff adds a few hours past midnight, it's possible for a card
that's scheduled for 1.0 days ahead to fall within the current cutoff, so we
need to make sure that doesn't happen
- set spaceUntil=0 when answering card again
- fix randomizeNewCards() query. the whole codebase needs auditing for type
references which need updating
* Adjust type to remove cards from the queues, so we don't have to rebuild
priorities to restore them:
Type -= 3 when suspending
Type += 3 when burying
Type += 6 when cramming / reviewing early
We still need to adjust priorities for backwards compatibility, but this can
be removed in the future.
* Factor out scheduler-specific code in answerCard(), so the different
schedulers are now fully modular
* Differentiate between a card's current queue and its type
* Make sure dueCutoff cuts off at the chosen offset instead of midnight
- new type, combinedDue for failed cards & count checks
- only reset() on deck load if not already done
- remove isDue from dynamic indices but leave old ones around for now
- cramming is now a separate scheduler type
- correctly answering a card while cramming causes its scheduling to be
changed in the standard review too
- options to sort cards by earliest modified, ordered, random
- render priority 0 obsolete, as it's all done at queue generation time now
- reimplement reviewEarly and newEarly by replacing parts of the scheduler,
instead of adding special conditions
- remove references to isDue and priority (1,2,3,4) which is not necessary
anymore
- add option to switch between per-day scheduling and due now scheduling
- newCardsToday() -> newCardsDoneToday()
- don't decrement counts for suspended cards
- make sure to update type when suspending/unsuspending
- fix findCards()
- set hardInterval = 1-1.1 on upgrade, or the default per day scheduling doesn't
make sense
Previously we used getCard() to fetch a card at the time. This required a
number of indices to perform efficiently, and the indices were expensive in
terms of disk space and time required to keep them up to date. Instead we now
gather a bunch of cards at once.
- Drop checkDue()/isDue so writes are not necessary to the DB when checking
for due cards
- Due counts checked on deck load, and only updated once a day or at the end
of a session. This prevents cards from expiring during reviews, leading to
confusing undo behaviour and due counts that go up instead of down as you
review. The default will be to only expire cards once a day, which represents
a change from the way things were done previously.
- Set deck var defaults on deck load/create instead of upgrade, which should
fix upgrade issues
- The scheduling code can now have bits and pieces switched out, which should
make review early / cram etc easier to integrate
- Cards with priority <= 0 now have their type incremented by three, so we can
get access to schedulable cards with a single column.
- rebuildQueue() -> reset()
- refresh() -> refreshSession()
- Views and many of the indices on the cards table are now obsolete and will
be removed in the future. I won't remove them straight away, so as to not
break backward compatibility.
- Use bigger intervals between successive card templates, as the previous
intervals were too small to represent in doubles in some circumstances
Still to do:
- review early
- learn more
- failing mature cards where delay1 > delay0
this has the negative effect of causing multiple full syncs if syncing
multiple times within a 5 minute period of the previous full sync, but it
makes it much less likely that people's due counts will fall out of sync
- never bump deck mod while syncing
- set lastSync to current time, not deck modified time
- don't update lastSync until the final part of the sync
- lower clock skew allowance to ~5 minutes
- bump full sync threshold to 1000 modified items
If the user is not careful to only sync when one side has been modified, they
can end up with cards on one side and not the other. If they then delete a
card, deleting the dangling facts also deletes the fact associated with the
not-yet-synced card. In order to avoid this, we avoid deleting dangling facts
until a DB check.
Attaching new to old causes old to be implicitly commited.
We also can't access old from new if a write lock has been
taken out, so the only option left is to move all the data
through Python and take the speed hit.
Since SM2's grading has a bias towards starting high and going down (fail/hard
decrease the interval more than easy increases it), more conservative users
find their average interval reaches the minimum allowable interval and the
times given by hard/good start to converge. In the future, the whole concept
of using the average interval for new cards should be revisited to see if the
data supports it
suspicious of the previous change, I had a look at the example pascal and
found the EF _was_ actually updated on a failure. The spec is misleading there.
- don't touch factor on fail, as per SM2 specs
- hard code no-punish-on-hard 'learning period' to 7 days so users who tweak
the initial intervals aren't punished too early
