def test_add_dims():
""" test adding dimensions """
conn = pc.AACTConnection(source=USED_DB)
ss = AACTStudySet.AACTStudySet(conn=conn)
tested_dims = random.sample(list(DIM_HANDLE_MAP.keys()), NUM_RANDOM_DIMS)
ss.add_dimensions(tested_dims)
assert len(ss.dimensions.keys()) > 0
def test_source_setting():
ac = pconn.AACTConnection()
ac.set_source(ac.REMOTE)
assert ac.source == ac.REMOTE
ac.set_source(ac.LOCAL)
assert ac.source == ac.LOCAL
def test_constraints():
""" adding and removing constraints """
conn = pc.AACTConnection(source=USED_DB)
ss = AACTStudySet.AACTStudySet(conn=conn)
ss.add_constraint("start_date >= '2018-06-30'")
ss.add_constraint("start_date <= '2018-12-31'")
ss.load_studies()
assert 0 < ss.studies.shape[0] < 50000
def test_drop_data():
""" dropping data from studies """
conn = pc.AACTConnection(source=USED_DB)
ss = AACTStudySet.AACTStudySet(conn=conn)
ss.add_constraint("start_date >= '2017-06-30'")
ss.add_constraint("start_date <= '2017-12-31'")
ss.load_studies()
ss.drop_studies(ss.studies.index)
assert ss.studies.shape[0] == 0
def test_drop_dims():
""" dropping data from dimensions """
conn = pc.AACTConnection(source=USED_DB)
ss = AACTStudySet.AACTStudySet(conn=conn)
ss.add_constraint("start_date >= '2017-12-31'")
ss.add_constraint("start_date <= '2018-12-31'")
ss.load_studies()
tested_dims = random.sample(list(DIM_HANDLE_MAP.keys()), NUM_RANDOM_DIMS)
ss.add_dimensions(tested_dims)
ss.drop_dimensions(tested_dims)
assert len(ss.dimensions) == 0
def test_all_dimensions():
""" test loading data from all dimensions """
conn = pc.AACTConnection(source=USED_DB)
ss = AACTStudySet.AACTStudySet(conn=conn)
ss.add_constraint("start_date >= '2017-06-30'")
ss.add_constraint("start_date <= '2017-12-31'")
ss.load_studies()
tested_dims = DIM_HANDLE_MAP.keys()
ss.add_dimensions(tested_dims)
ss.refresh_dim_data()
for _, cur_dim in ss.dimensions.items():
assert cur_dim.data.shape[0] > 0
def test_refresh_dims():
""" test adding dimensions """
conn = pc.AACTConnection(source=USED_DB)
ss = AACTStudySet.AACTStudySet(conn=conn)
ss.add_constraint("start_date >= '2016-06-30'")
ss.add_constraint("start_date <= '2016-12-31'")
ss.load_studies()
tested_dims = random.sample(list(DIM_HANDLE_MAP.keys()), NUM_RANDOM_DIMS)
ss.add_dimensions(tested_dims)
ss.refresh_dim_data()
for _, cur_dim in ss.dimensions.items():
assert cur_dim.data.shape[0] > 0
def test_memory_freeing():
""" test dropping data frees up memory """
conn = pc.AACTConnection(source=USED_DB)
ss = AACTStudySet.AACTStudySet(conn=conn)
ss.load_studies()
tested_dims = random.sample(list(DIM_HANDLE_MAP.keys()), NUM_RANDOM_DIMS)
ss.add_dimensions(tested_dims)
ss.refresh_dim_data()
process = psutil.Process(os.getpid())
pre_clear_mem = process.memory_info().rss
ss.drop_studies(ss.studies.index)
post_clear_mem = process.memory_info().rss
assert post_clear_mem < pre_clear_mem * MEM_THRESH
def __init__(self, conn=None, tqdm_handler=None):
""" conn specifies the database connection, if None, attempts to establish a default local connection """
super().__init__()
self._constraints = [] # constraints in a syntax that is understood by the _load_studies method
self.tqdm = tqdm_handler
self.dimensions = {} # keyed by dim name, to the dim object with the data
self.avail_dims = DimAutoCompleter()
# other attrs avail on the super:
# self.studies = None # stores the object that represents the flat studies data
# self.required_dims = None # stores the list of dim_name that represents required dimensions
if conn:
self.conn = conn
else:
self.conn = pc.AACTConnection(source=pc.AACTConnection.LOCAL)
def test_load_studies():
""" loading a set of studies """
conn = pc.AACTConnection(source=USED_DB)
ss = AACTStudySet.AACTStudySet(conn=conn)
ss.load_studies()
assert ss.studies.shape[0] > 0
def test_remote_conn():
ac = pconn.AACTConnection()
ac.connect_to_remote()
assert ac.active_conn.closed == 0
ac.close()
def test_bad_set_source():
ac = pconn.AACTConnection()
ac.set_source('foo')
assert True
ac.close()
def test_poor_source():
ac = pconn.AACTConnection()
ac.source = 'foo' # bad source
df = ac.query("SELECT * FROM studies LIMIT 1")
assert not df
ac.close()
def test_local_query():
ac = pconn.AACTConnection()
ac.set_source(ac.LOCAL)
df = ac.query("SELECT * FROM studies LIMIT 1")
assert df.shape[0] == 1
ac.close()
def test_remote_query():
ac = pconn.AACTConnection()
df = ac.query("SELECT * FROM studies LIMIT 1")
assert df.shape[0] == 1
ac.close()
def test_local_conn():
ac = pconn.AACTConnection()
ac.connect_to_local()
assert ac.active_conn.closed == 0
ac.close()
