def get_listening_activity_year() -> Iterator[Optional[UserListeningActivityStatMessage]]:
""" Calculate the number of listens for an user in each month of the past and current year. """
logger.debug("Calculating listening_activity_year")
to_date = get_latest_listen_ts()
from_date = datetime(to_date.year-1, 1, 1)
month = datetime(to_date.year-1, 1, 1)
time_range = []
# Genarate a dataframe containing months of last and current year along with start and end time
while month < to_date:
time_range.append([month.strftime('%B %Y'), month, get_month_end(month)])
month = offset_months(month, 1, shift_backwards=False)
time_range_df = listenbrainz_spark.session.createDataFrame(time_range, time_range_schema)
time_range_df.createOrReplaceTempView('time_range')
_get_listens(from_date, to_date)
data = get_listening_activity()
messages = create_messages(data=data, stats_range='year', from_ts=from_date.timestamp(), to_ts=to_date.timestamp())
logger.debug("Done!")
return messages
def test_get_listening_activity_year(self, mock_create_messages,
mock_get_listening_activity,
mock_get_listens,
mock_get_latest_listen_ts):
mock_df = MagicMock()
mock_get_listens.return_value = mock_df
listening_activity_stats.get_listening_activity_year()
to_date = datetime(2020, 6, 19)
from_date = month = datetime(2019, 1, 1)
time_range = []
while month < to_date:
time_range.append(
[month.strftime('%B %Y'), month,
get_month_end(month)])
month = offset_months(month, 1, shift_backwards=False)
time_range_df = run_query("SELECT * FROM time_range")
time_range_result = time_range_df.rdd.map(list).collect()
self.assertListEqual(time_range_result, time_range)
mock_get_latest_listen_ts.assert_called_once()
mock_get_listens.assert_called_with(from_date, to_date,
LISTENBRAINZ_DATA_DIRECTORY)
mock_df.createOrReplaceTempView.assert_called_with('listens')
mock_create_messages.assert_called_with(
data='listening_activity_table',
stats_range='year',
from_ts=from_date.timestamp(),
to_ts=to_date.timestamp())
def test_get_listening_activity_year(self, mock_create_messages, _,
mock_get_listens):
listening_activity_stats.get_listening_activity('year')
from_date = month = datetime(2019, 1, 1)
to_date = datetime(2021, 1, 1)
time_range = []
while month < to_date:
time_range.append(
[month.strftime('%B %Y'), month,
get_month_end(month)])
month = offset_months(month, 1, shift_backwards=False)
time_range_df = run_query("SELECT * FROM time_range")
time_range_result = time_range_df.rdd.map(list).collect()
self.assertListEqual(time_range_result, time_range)
mock_get_listens.assert_called_with(from_date, to_date)
mock_create_messages.assert_called_with(data='activity_table',
stats_range='year',
from_date=from_date,
to_date=to_date)
def get_entity_year(
entity: str,
use_mapping: bool = False
) -> Optional[List[SitewideEntityStatMessage]]:
""" Get the yearly sitewide top entity """
current_app.logger.debug("Calculating sitewide_{}_year...".format(entity))
to_date = get_latest_listen_ts()
from_date = datetime(to_date.year - 1, 1, 1)
month = from_date
time_range = []
# Genarate a dataframe containing months of last and current year along with start and end time
while month < to_date:
time_range.append([
month.strftime('%B %Y'),
int(month.timestamp()),
int(get_month_end(month).timestamp())
])
month = offset_months(month, 1, shift_backwards=False)
time_range_df = listenbrainz_spark.session.createDataFrame(
time_range, schema=time_range_schema)
time_range_df.createOrReplaceTempView('time_range')
listens_df = get_listens(from_date, to_date, LISTENBRAINZ_DATA_DIRECTORY)
table_name = 'sitewide_{}_year'.format(entity)
listens_df.createOrReplaceTempView(table_name)
handler = entity_handler_map[entity]
data = handler(table_name, "MMMM yyyy", use_mapping)
message = create_message(data=data,
entity=entity,
stats_range='year',
from_ts=from_date.timestamp(),
to_ts=to_date.timestamp())
current_app.logger.debug("Done!")
return message
def test_get_month_end(self):
month = datetime.datetime(2020, 6, 1)
self.assertEqual(datetime.datetime(2020, 6, 30, 23, 59, 59, 999999), stats.get_month_end(month))