Coverage for airflow.macros.hive : 13%

import datetime 

def max_partition( 

        table, schema="default", field=None, filter=None, 

        metastore_conn_id='metastore_default'): 

    ''' 

    Gets the max partition for a table. 

    :param schema: The hive schema the table lives in 

    :type schema: string 

    :param table: The hive table you are interested in, supports the dot 

        notation as in "my_database.my_table", if a dot is found, 

        the schema param is disregarded 

    :type table: string 

    :param hive_conn_id: The hive connection you are interested in. 

        If your default is set you don't need to use this parameter. 

    :type hive_conn_id: string 

    :param filter: filter on a subset of partition as in 

        `sub_part='specific_value'` 

    :type filter: string 

    :param field: the field to get the max value from. If there's only 

        one partition field, this will be inferred 

    >>> max_partition('airflow.static_babynames_partitioned') 

    '2015-01-01' 

    ''' 

    from airflow.hooks import HiveMetastoreHook 

    if '.' in table: 

        schema, table = table.split('.') 

    hh = HiveMetastoreHook(metastore_conn_id=metastore_conn_id) 

    return hh.max_partition( 

        schema=schema, table_name=table, field=field, filter=filter) 

def _closest_date(target_dt, date_list, before_target=None): 

    ''' 

    This function finds the date in a list closest to the target date. 

    An optional parameter can be given to get the closest before or after. 

    :param target_dt: The target date 

    :type target_dt: datetime.date 

    :param date_list: The list of dates to search 

    :type date_list: datetime.date list 

    :param before_target: closest before or after the target 

    :type before_target: bool or None 

    :returns: The closest date 

    :rtype: datetime.date or None 

    ''' 

    fb = lambda d: d - target_dt if d >= target_dt else datetime.timedelta.max 

    fa = lambda d: d - target_dt if d <= target_dt else datetime.timedelta.min 

    fnone = lambda d: target_dt - d if d < target_dt else d - target_dt 

    if before_target is None: 

        return min(date_list, key=fnone).date() 

    if before_target: 

        return min(date_list, key=fb).date() 

    else: 

        return min(date_list, key=fa).date() 

def closest_ds_partition( 

        table, ds, before=True, schema="default", 

        metastore_conn_id='metastore_default'): 

    ''' 

    This function finds the date in a list closest to the target date. 

    An optional parameter can be given to get the closest before or after. 

    :param table: A hive table name 

    :type table: str 

    :param ds: A datestamp ``%Y-%m-%d`` e.g. ``yyyy-mm-dd`` 

    :type ds: datetime.date list 

    :param before: closest before (True), after (False) or either side of ds 

    :type before: bool or None 

    :returns: The closest date 

    :rtype: str or None 

    >>> tbl = 'airflow.static_babynames_partitioned' 

    >>> closest_ds_partition(tbl, '2015-01-02') 

    '2015-01-01' 

    ''' 

    from airflow.hooks import HiveMetastoreHook 

    if '.' in table: 

        schema, table = table.split('.') 

    hh = HiveMetastoreHook(metastore_conn_id=metastore_conn_id) 

    partitions = hh.get_partitions(schema=schema, table_name=table) 

    if not partitions: 

        return None 

    part_vals = [list(p.values())[0] for p in partitions] 

    if ds in part_vals: 

        return ds 

    else: 

        parts = [datetime.datetime.strptime(pv, '%Y-%m-%d') 

                 for pv in part_vals] 

        target_dt = datetime.datetime.strptime(ds, '%Y-%m-%d') 

        closest_ds = _closest_date(target_dt, parts, before_target=before) 

        return closest_ds.isoformat()