def load_recordings_from_msids(msids):
""" Returns data for a recording with specified MessyBrainz ID.
Args:
msid (uuid): the MessyBrainz ID of the recording
Returns:
A dict containing the recording data for the recording with specified MessyBrainz ID
"""
with db.engine.begin() as connection:
return data.load_recordings_from_msids(connection, msids)
def insert_single(connection, recording):
""" Inserts a single recording into MessyBrainz.
Args:
connection: the sqlalchemy db connection to be used to execute queries
recording: the recording to be inserted
Returns:
A dict containing the recording data for inserted recording
"""
gid = data.get_id_from_recording(connection, recording)
if not gid:
gid = data.submit_recording(connection, recording)
loaded = data.load_recordings_from_msids(connection, [gid])[0]
return loaded
def insert_test_data_with_metadata(self, user_id, neg_score=False):
""" Insert test data with metadata into the database """
with msb_db.engine.connect() as connection:
msid = submit_recording(connection, self.sample_recording)
artists = load_recordings_from_msids(connection, [msid])
self.saved_artist_msid = artists[0]["ids"]["artist_msid"]
self.sample_feedback_with_metadata[0]["recording_msid"] = msid
query = """INSERT INTO listen_mbid_mapping
(id, recording_mbid, release_mbid, artist_credit_id, artist_mbids,
artist_credit_name, recording_name, match_type)
VALUES (1,
'076255b4-1575-11ec-ac84-135bf6a670e3',
'1fd178b4-1575-11ec-b98a-d72392cd8c97',
65,
'{6a221fda-2200-11ec-ac7d-dfa16a57158f}'::UUID[],
'artist name', 'recording name', 'exact_match')"""
with ts.engine.connect() as connection:
connection.execute(sqlalchemy.text(query))
query = """INSERT INTO listen_join_listen_mbid_mapping
(recording_msid, listen_mbid_mapping)
VALUES ('%s', 1)""" % msid
with ts.engine.connect() as connection:
connection.execute(sqlalchemy.text(query))
for fb in self.sample_feedback_with_metadata:
db_feedback.insert(
Feedback(user_id=user_id,
recording_msid=fb["recording_msid"],
score=fb["score"]))
return len(self.sample_feedback_with_metadata)
def test_load_recordings_from_msids(self):
with db.engine.connect() as connection:
recording_msid = data.submit_recording(connection, recording)
result = data.load_recordings_from_msids(connection, [recording_msid])[0]
self.assertDictEqual(result['payload'], recording)
def test_get_release(self):
with db.engine.connect() as connection:
recording_msid = data.submit_recording(connection, recording)
release_msid = data.get_release(connection, recording['release'])
recording_data = data.load_recordings_from_msids(connection, [recording_msid])[0]
self.assertEqual(release_msid, recording_data['ids']['release_msid'])
def test_get_artist_credit(self):
with db.engine.connect() as connection:
recording_msid = data.submit_recording(connection, recording)
artist_msid = data.get_artist_credit(connection, recording['artist'])
recording_data = data.load_recordings_from_msids(connection, [recording_msid])[0]
self.assertEqual(artist_msid, recording_data['ids']['artist_msid'])
def get_feedback_for_user(user_id: int, limit: int, offset: int, score: int = None, metadata: bool = False) -> List[Feedback]:
""" Get a list of recording feedback given by the user in descending order of their creation
Args:
user_id: the row ID of the user in the DB
score: the score value by which the results are to be filtered. If 1 then returns the loved recordings,
if -1 returns hated recordings.
limit: number of rows to be returned
offset: number of feedback to skip from the beginning
metadata: fetch metadata for the returned feedback recordings
Returns:
A list of Feedback objects
"""
args = {"user_id": user_id, "limit": limit, "offset": offset}
query = """ SELECT user_id,
"user".musicbrainz_id AS user_name,
recording_msid::text, score,
recording_feedback.created
FROM recording_feedback
JOIN "user"
ON "user".id = recording_feedback.user_id
WHERE user_id = :user_id """
if score:
query += " AND score = :score"
args["score"] = score
query += """ ORDER BY recording_feedback.created DESC
LIMIT :limit OFFSET :offset """
with db.engine.connect() as connection:
result = connection.execute(sqlalchemy.text(query), args)
feedback = [Feedback(**dict(row)) for row in result.fetchall()]
if metadata and len(feedback) > 0:
msids = [f.recording_msid for f in feedback]
index = {f.recording_msid: f for f in feedback}
# Fetch the artist and track names from MSB
with msb_db.engine.connect() as connection:
try:
msb_recordings = load_recordings_from_msids(connection, msids)
except NoDataFoundException:
msb_recordings = []
artist_msids = {}
if msb_recordings:
for rec in msb_recordings:
index[rec["ids"]["recording_msid"]].track_metadata = {
"artist_name": rec["payload"]["artist"],
"release_name": rec["payload"].get("release_name", ""),
"track_name": rec["payload"]["title"]}
artist_msids[rec["ids"]["recording_msid"]
] = rec["ids"]["artist_msid"]
# Fetch the mapped MBIDs from the mapping
query = """SELECT recording_msid::TEXT, recording_mbid::TEXT, release_mbid::TEXT, artist_mbids::TEXT[]
FROM listen_join_listen_mbid_mapping lj
JOIN listen_mbid_mapping mbid
ON lj.listen_mbid_mapping = mbid.id
WHERE recording_msid in :msids
ORDER BY recording_msid"""
with timescale.engine.connect() as connection:
result = connection.execute(
sqlalchemy.text(query), msids=tuple(msids))
for row in result.fetchall():
if row["recording_mbid"] is not None:
index[row["recording_msid"]].track_metadata['additional_info'] = {
"recording_mbid": row["recording_mbid"],
"release_mbid": row["release_mbid"],
"artist_mbids": row["artist_mbids"],
"artist_msid": artist_msids[rec["ids"]["recording_msid"]]}
return feedback