The previous code had a number of problems, including:
- Calls to the filters API were scattered through UI and viewmodel code.
- Repeated places where the differences between the v1 and v2 Mastodon
filters API had to be handled.
- UI and viewmodel code using the network filter classes, which tied
them to the API implementation.
- Error handling was inconsistent.
Fix this.
## FiltersRepository
- All filter management now goes through `FiltersRepository`.
- `FiltersRepository` exposes the current set of filters as a
`StateFlow`, and automatically updates it when the current server
changes or any changes to filters are made. This makes
`FilterChangeEvent` obsolete.
- Other operations on filters are exposed through `FiltersRepository` as
functions for viewmodels to call.
- Within the bulk of the app a new `Filter` class is used to represent a
filter; handling the differences between the v1 and v2 APIs is
encapsulated in `FiltersRepository`.
- Represent errors when handling filters as subclasses of `PachliError`,
and use `Result<V, E>` throughout, including using `ApiResult` for all
filter API results.
- Provide different types to distinguish between new-and-unsaved
filters, new-and-unsaved keywords, and in-progress edits to filters.
## Editing filters
- Accept an optional complete filter, or filter ID, as parameters in the
intent that launches `EditFilterActivity`. Pass those to the viewmodel
using assisted injection so the viewmodel has the info immediately.
- In the viewmodel use a new `FilterViewData` type to model the data
used to display and edit the filter.
- Start using the UiSuccess/UiError model. Refrain from cutting over to
full the action implementation as that would be a much larger change.
- Use `FiltersRepository` instead of making any API calls directly.
## Listing filters
- Use `FiltersRepository` instead of making any API calls directly.
## EventHub
- Remove `FilterChangedEvent`. Update everywhere that used it to use the
flow from `FiltersRepository`.
Implement suggestions as a new `feature:suggestions` module, with
associated activity, fragment, etc.
Suggested accounts are shown with their normal information, as well as
information about the number of follows / followers, and a guide to
posting frequency, so the user can make a more informed decision about
whether to follow or not.