kopia lustrzana https://dev.funkwhale.audio/funkwhale/funkwhale
147 wiersze
4.4 KiB
Python
147 wiersze
4.4 KiB
Python
import logging
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import time
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import troi
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import troi.core
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from django.core.cache import cache
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from django.core.exceptions import ValidationError
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from django.db.models import Q
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from requests.exceptions import ConnectTimeout
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from funkwhale_api.music import models as music_models
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from funkwhale_api.typesense import utils
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logger = logging.getLogger(__name__)
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patches = troi.utils.discover_patches()
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SUPPORTED_PATCHES = patches.keys()
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def run(config, **kwargs):
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"""Validate the received config and run the queryset generation"""
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candidates = kwargs.pop("candidates", music_models.Track.objects.all())
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validate(config)
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return TroiPatch().get_queryset(config, candidates)
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def validate(config):
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patch = config.get("patch")
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if patch not in SUPPORTED_PATCHES:
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raise ValidationError(
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'Invalid patch "{}". Supported patches: {}'.format(
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config["patch"], SUPPORTED_PATCHES
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)
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)
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return True
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def build_radio_queryset(patch, radio_qs):
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"""Take a troi patch, match the missing mbid and then build a radio queryset"""
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start_time = time.time()
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try:
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recommendations = patch.generate_playlist()
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except ConnectTimeout:
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raise ValueError(
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"Timed out while connecting to ListenBrainz. No candidates could be retrieved for the radio."
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)
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end_time_rec = time.time()
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logger.info("Troi fetch took :" + str(end_time_rec - start_time))
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if not recommendations:
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raise ValueError("No candidates found by troi")
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recommended_mbids = [
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recommended_recording.mbid
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for recommended_recording in recommendations.playlists[0].recordings
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]
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logger.info("Searching for MusicBrainz ID in Funkwhale database")
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qs_recommended = (
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music_models.Track.objects.all()
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.filter(mbid__in=recommended_mbids)
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.order_by("mbid", "pk")
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.distinct("mbid")
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)
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qs_recommended_mbid = [str(i.mbid) for i in qs_recommended]
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recommended_mbids_not_qs = [
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mbid for mbid in recommended_mbids if mbid not in qs_recommended_mbid
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]
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cached_match = cache.get_many(recommended_mbids_not_qs)
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cached_match_mbid = [str(i) for i in cached_match.keys()]
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if qs_recommended and cached_match_mbid:
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logger.info("MusicBrainz IDs found in Funkwhale database and redis")
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qs_recommended_mbid.extend(cached_match_mbid)
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mbids_found = qs_recommended_mbid
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elif qs_recommended and not cached_match_mbid:
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logger.info("MusicBrainz IDs found in Funkwhale database")
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mbids_found = qs_recommended_mbid
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elif not qs_recommended and cached_match_mbid:
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logger.info("MusicBrainz IDs found in redis cache")
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mbids_found = cached_match_mbid
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else:
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logger.info(
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"Couldn't find any matches in Funkwhale database. Trying to match all"
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)
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mbids_found = []
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recommended_recordings_not_found = [
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i for i in recommendations.playlists[0].recordings if i.mbid not in mbids_found
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]
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logger.info("Matching missing MusicBrainz ID to Funkwhale track")
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start_time_resolv = time.time()
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utils.resolve_recordings_to_fw_track(recommended_recordings_not_found)
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end_time_resolv = time.time()
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logger.info(
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"Resolving "
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+ str(len(recommended_recordings_not_found))
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+ " tracks in "
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+ str(end_time_resolv - start_time_resolv)
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)
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cached_match = cache.get_many(recommended_mbids)
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if not mbids_found and not cached_match:
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raise ValueError("No candidates found for troi radio")
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mbids_found_pks = list(
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music_models.Track.objects.all()
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.filter(mbid__in=mbids_found)
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.order_by("mbid", "pk")
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.distinct("mbid")
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.values_list("pk", flat=True)
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)
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mbids_found_pks_unique = [
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i for i in mbids_found_pks if i not in cached_match.keys()
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]
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if mbids_found and cached_match:
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return radio_qs.filter(
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Q(pk__in=mbids_found_pks_unique) | Q(pk__in=cached_match.values())
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)
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if mbids_found and not cached_match:
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return radio_qs.filter(pk__in=mbids_found_pks_unique)
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if not mbids_found and cached_match:
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return radio_qs.filter(pk__in=cached_match.values())
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class TroiPatch:
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code = "troi-patch"
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label = "Troi Patch"
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def get_queryset(self, config, qs):
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patch_string = config.pop("patch")
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patch = patches[patch_string]
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return build_radio_queryset(patch(config), qs)
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