* Bump golang from 1.23-bookworm to 1.24-bookworm
Bumps golang from 1.23-bookworm to 1.24-bookworm.
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updated-dependencies:
- dependency-name: golang
dependency-type: direct:production
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Signed-off-by: dependabot[bot] <support@github.com>
* Update to use `go tool`, see https://go.dev/doc/go1.24#go-command.
* Update go.mod to go 1.24
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Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
* Bump several API dependencies to the latest versions
Bump github.com/stretchr/testify from 1.9.0 to 1.10.0 in /api
Bump github.com/vektah/gqlparser/v2 from 2.5.19 to 2.5.20 in /api
Bump gorm.io/driver/postgres from 1.5.10 to 1.5.11 in /api
Bump golang.org/x/image from 0.22.0 to 0.23.0 in /api
Bump golang.org/x/crypto from 0.29.0 to 0.30.0 in /api
Bump github.com/99designs/gqlgen from 0.17.56 to 0.17.57 in /api
* Regenerate GraphQL code
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Co-authored-by: Konstantin Koval
* Refactor `auth.go` and `media.go` to remove deprecated dependencies
* Move the `text` dependency to direct ones in the `go.mod`
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Co-authored-by: Konstantin Koval
* names, constants of reusable strings, removed unneeded `if`, replaced deprecated imports
* more deprecated imports replaced
* What is this?))
* Fix a path and quote a var in Dockerfile
* Addressing review comments
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Co-authored-by: Konstantin Koval <kkb@ukr.net>
Once you have more than a few paths assigned to a user, it becomes
quite hard to oversee the list.
Personally, I would add my albums to Photoview one by one, so I can
manage the processing better. For example, I can review and fix the face
recognition for one new album at a time, and I don't need to deal with
too much data.
Since I started to add the albums in a random order, it's relatively
hard to find which album is added and which is not.
An easy fix is to order the photo paths by their name.
- Extended the query of the rootAlbums to order them by path
The subquery returns all potential media id's. Typically, we have a couple of faces and thousands of media files.
A join is much faster.
With about 50k images and a face that was present in 2'000 images the query was unusable slow, it took about 60s.
This is a very important performance fix, as I think many users will run into it.
Maybe there are other areas where the same improvement is possible, I didn't check.
- Album resolvers has been refactored to make it easier to test, this is
done by converting some of the resolvers to actions.
- The album tests has been rewritten (and simplified) to accommodate the changes.
