* Refactor media sync handling
- The media USN is now returned in sync/meta, which avoids an extra
round-trip.
- Media syncing is now automatically started by the syncing code at
the end of a normal or full sync, which avoids it competing for bandwidth
and resources, and avoids duplicate invalid login messages when the auth
token is invalid.
- Added a new media_sync_progress() method to both check if media is
syncing, and get access to the latest progress.
- Updated the sync log screen to only show the latest line, like AnkiMobile.
- Show media sync errors in a pop-up, so they don't get missed. Use a non-modal
pop-up to avoid potential conflicts with other modals.
* Remove print statement
* Accept iterables as inputs to backend methods
* Shift add-on check to backend; use new endpoint
The new endpoint will return info on a suitable branch if found,
instead of returning all branches. This simplifies the frontend code,
and means that you can now drop support for certain versions without
it also remotely disabling the add-on for people who are running one of
the excluded versions, like in
https://forums.ankiweb.net/t/prevent-add-ons-from-being-disabled-remote-stealthily-surreptitiously/33427
* Bump version to 23.09
This changes Anki's version numbering system to year.month.patch, as
previously mentioned on https://forums.ankiweb.net/t/use-a-different-versioning-system-semver-perhaps/20046/5
This is shaping up to be a big release, with the introduction of FSRS and
image occlusion, and it seems like a good time to be finally updating the
version scheme as well. AnkiWeb has been updated to understand the new
format, and add-on authors will now specify version compatibility using
the full version number, as can be seen here:
https://ankiweb.net/shared/info/3918629684
* Shift update check to backend, and tidy up update.py
* Use the shared client for sync connections too
* 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.
