MetaBrainz

hey lucifer i'm having trouble in verifying OAuth2 implementation as well as i cant validate api becoz funkwhale setup when i tried to login with superuser funkwhale i'm getting access denied

how can fix this?
should i push this commit ?

lucifer: I have a code snippet below, so these are the queries being used right now in the listening_activity stats

    def get_aggregate_query(self, table):
        return f"""
            SELECT user_id
                 , date_format(listened_at, '{self.spark_date_format}') AS time_range
                 , count(listened_at) AS listen_count
              FROM {table}
          GROUP BY user_id
                 , time_range
        """

def get_table_prefix(self) -> str:
    return f"{self.entity}_listeners_{self.stats_range}"

table = f"{self.provider.get_table_prefix()}_full_listens"
full_query = self.provider.get_aggregate_query(table)
full_df = run_query(full_query)

On local I would access the listens in TimeScaleDB by the table namelistens with a filter of the time frame for the stats_range but the above code is a does that differently, is that just for prod or am I going wrong somewhere?

lucifer: I have a code snippet below, so these are the queries being used right now in the listening_activity stats

    def get_aggregate_query(self, table):
        return f"""
            SELECT user_id
                 , date_format(listened_at, '{self.spark_date_format}') AS time_range
                 , count(listened_at) AS listen_count
              FROM {table}
          GROUP BY user_id
                 , time_range
        """
def get_table_prefix(self) -> str:
    return f"{self.entity}_listeners_{self.stats_range}"

        table = f"{self.provider.get_table_prefix()}_full_listens"
        full_query = self.provider.get_aggregate_query(table)
        full_df = run_query(full_query)

On local I would access the listens in TimeScaleDB by the table namelistens with a filter of the time frame for the stats_range but the above code is a does that differently, is that just for prod or am I going wrong somewhere?

lucifer: I have a code snippet below, so these are the queries being used right now in the listening_activity stats

    def get_aggregate_query(self, table):
        return f"""
            SELECT user_id
                 , date_format(listened_at, '{self.spark_date_format}') AS time_range
                 , count(listened_at) AS listen_count
              FROM {table}
          GROUP BY user_id
                 , time_range
        """

def get_table_prefix(self) -> str:
    return f"{self.entity}_listeners_{self.stats_range}"

        table = f"{self.provider.get_table_prefix()}_full_listens"
        full_query = self.provider.get_aggregate_query(table)
        full_df = run_query(full_query)

On local I would access the listens in TimeScaleDB by the table namelistens with a filter of the time frame for the stats_range but the above code is a does that differently, is that just for prod or am I going wrong somewhere?

lucifer: I have a code snippet below, so these are the queries being used right now in the listening_activity stats

    def get_aggregate_query(self, table):
        return f"""
            SELECT user_id
                 , date_format(listened_at, '{self.spark_date_format}') AS time_range
                 , count(listened_at) AS listen_count
              FROM {table}
          GROUP BY user_id
                 , time_range
        """

def get_table_prefix(self) -> str:
    return f"{self.entity}_listeners_{self.stats_range}"

table = f"{self.provider.get_table_prefix()}_full_listens"
full_query = self.provider.get_aggregate_query(table)
full_df = run_query(full_query)

On local I would access the listens in TimeScaleDB by the table namelistens with a filter of the time frame for the stats_range but the above code is a does that differently, is that just for prod or am I going wrong somewhere?