def test_changing_datatype(conn):
with closing(conn.cursor()) as cursor:
datasource = name_to_datasource(cursor, "storagetest")
entitytype = name_to_entitytype(cursor, "UtranCell")
timestamp = pytz.utc.localize(datetime.utcnow())
attribute_names = ['site_nr', 'height']
datapackage_a = DataPackage(
attribute_names=attribute_names,
rows=[
(10023, timestamp, ('10023', '15'))
]
)
datapackage_b = DataPackage(
attribute_names=attribute_names,
rows=[
(10023, timestamp, ('10023', '25.6'))
]
)
attributes = datapackage_a.deduce_attributes()
attributestore = AttributeStore(datasource, entitytype, attributes)
attributestore.create(cursor)
conn.commit()
attributestore.store_txn(datapackage_a).run(conn)
attributestore.store_txn(datapackage_b).run(conn)
conn.commit()
column_names = get_column_names(conn, "attribute_history",
attributestore.table_name())
eq_(len(column_names), 6)
def test_simple(conn):
with closing(conn.cursor()) as cursor:
attribute_names = ['CellID', 'CCR', 'Drops']
datasource = name_to_datasource(cursor, "integration-test")
entitytype = name_to_entitytype(cursor, "UtranCell")
timestamp = pytz.utc.localize(datetime.utcnow())
data_rows = [(10023, timestamp, ('10023', '0.9919', '17'))]
datapackage = DataPackage(attribute_names, data_rows)
attributes = datapackage.deduce_attributes()
attributestore = AttributeStore(datasource, entitytype, attributes)
attributestore.create(cursor)
attributestore.store_txn(datapackage).run(conn)
query = (
"SELECT attribute_directory.materialize_curr_ptr(attributestore) "
"FROM attribute_directory.attributestore "
"WHERE id = %s")
cursor.execute(query, (attributestore.id,))
query = (
"SELECT timestamp "
"FROM {0} "
"LIMIT 1").format(attributestore.table.render())
cursor.execute(query)
timestamp, = cursor.fetchone()
eq_(timestamp.toordinal(), timestamp.toordinal())
def test_extra_column(conn):
with closing(conn.cursor()) as cursor:
datasource = name_to_datasource(cursor, "storagetest")
entitytype = name_to_entitytype(cursor, "UtranCell")
timestamp = pytz.utc.localize(datetime.utcnow())
datapackage_a = DataPackage(
attribute_names=['test0', 'test1'],
rows=[
(10023, timestamp, ('10023', '0.9919'))
]
)
datapackage_b = DataPackage(
attribute_names=['test0', 'test1', "test2"],
rows=[
(10023, timestamp, ('10023', '0.9919', '17'))
]
)
attributes = datapackage_a.deduce_attributes()
attributestore = AttributeStore(datasource, entitytype, attributes)
attributestore.create(cursor)
conn.commit()
attributestore.store_txn(datapackage_a).run(conn)
attributestore.store_txn(datapackage_b).run(conn)
conn.commit()
column_names = get_column_names(conn, 'attribute_history',
attributestore.table_name())
eq_(len(column_names), 7)
def test_store_batch_update(conn):
"""Test batch wise storing with updates using staging table."""
with closing(conn.cursor()) as cursor:
attribute_names = ['CCR', 'Drops']
timestamp = pytz.utc.localize(datetime.utcnow())
datasource = DataSource.from_name(cursor, "integration-test")
entitytype = EntityType.from_name(cursor, "UtranCell")
datapackage = DataPackage(
attribute_names,
[(10023 + i, timestamp, ('0.9919', '17')) for i in range(100)]
)
update_datapackage = DataPackage(
attribute_names,
[(10023 + i, timestamp, ('0.9918', '18')) for i in range(100)]
)
attributes = datapackage.deduce_attributes()
attributestore = AttributeStore(datasource, entitytype, attributes)
attributestore.create(cursor)
attributestore.store_batch(cursor, datapackage)
conn.commit()
modified_query = (
'SELECT modified FROM {0} '
'WHERE entity_id = 10023').format(
attributestore.history_table.render())
cursor.execute(modified_query)
modified_a, = cursor.fetchone()
attributestore.store_batch(cursor, update_datapackage)
conn.commit()
cursor.execute(modified_query)
modified_b, = cursor.fetchone()
assert modified_b > modified_a
cursor.execute(
"SELECT attribute_directory.materialize_curr_ptr(attributestore) "
"FROM attribute_directory.attributestore "
"WHERE id = %s", (attributestore.id,))
query = (
'SELECT timestamp, "Drops" '
'FROM {0}').format(attributestore.table.render())
cursor.execute(query)
# Row count should be the same as the stored batch size
eq_(cursor.rowcount, len(datapackage.rows))
stored_timestamp, drops = cursor.fetchone()
# Timestamp should be the same as the stored batch timestamp
eq_(stored_timestamp, timestamp)
eq_(drops, 18)
def test_deduce_datatypes_empty():
datapackage = DataPackage(
attribute_names=('height', 'power', 'refs'),
rows=[]
)
data_types = datapackage.deduce_data_types()
assert data_types == ['smallint', 'smallint', 'smallint']
def test_compact(conn):
"""Test compacting of redundant data."""
def make_rows(timestamp):
return [
(10023 + i, timestamp, ('0.9919', '17'))
for i in range(100)
]
with closing(conn.cursor()) as cursor:
attribute_names = ['CCR', 'Drops']
datasource = DataSource.from_name(cursor, "integration-test")
entitytype = EntityType.from_name(cursor, "UtranCell")
timestamp = pytz.utc.localize(datetime.utcnow())
datapackage_a = DataPackage(
attribute_names=attribute_names,
rows=make_rows(timestamp)
)
datapackage_b = DataPackage(
attribute_names=attribute_names,
rows=make_rows(timestamp + timedelta(10))
)
attributes = datapackage_a.deduce_attributes()
attributestore = AttributeStore(datasource, entitytype, attributes)
attributestore.create(cursor)
attributestore.store_batch(cursor, datapackage_a)
conn.commit()
attributestore.store_batch(cursor, datapackage_b)
conn.commit()
count_query = (
"SELECT count(*) "
"FROM {0}").format(attributestore.history_table.render())
cursor.execute(count_query)
count, = cursor.fetchone()
# Row count should be the same as the stored batch sizes summed
eq_(count, len(datapackage_b.rows) + len(datapackage_a.rows))
attributestore.compact(cursor)
conn.commit()
cursor.execute(count_query)
count, = cursor.fetchone()
# Row count should be the same as the first stored batch size
eq_(count, len(datapackage_a.rows))
def test_store_empty_rows(conn):
"""Test storing of empty datapackage."""
with closing(conn.cursor()) as cursor:
attribute_names = ['CCR', 'Drops']
data_rows = []
datasource = DataSource.from_name(cursor, "integration-test")
entitytype = EntityType.from_name(cursor, "UtranCell")
datapackage = DataPackage(attribute_names, data_rows)
attributes = datapackage.deduce_attributes()
attributestore = AttributeStore(datasource, entitytype, attributes)
attributestore.create(cursor)
attributestore.store_txn(datapackage).run(conn)
conn.commit()
def test_update_modified_column(conn):
attribute_names = ['CCR', 'Drops']
with closing(conn.cursor()) as cursor:
datasource = name_to_datasource(cursor, "integration-test")
entitytype = name_to_entitytype(cursor, "UtranCell")
timestamp = datasource.tzinfo.localize(datetime.now())
rows = [
(10023, timestamp, ('0.9919', '17')),
(10047, timestamp, ('0.9963', '18'))
]
datapackage_a = DataPackage(
attribute_names=attribute_names,
rows=rows)
datapackage_b = DataPackage(
attribute_names=attribute_names,
rows=rows[:1])
attributes = datapackage_a.deduce_attributes()
attributestore = AttributeStore(datasource, entitytype, attributes)
attributestore.create(cursor)
conn.commit()
query = Query((
"SELECT modified, hash "
"FROM {0} "
"WHERE entity_id = 10023").format(attributestore.history_table.render()))
attributestore.store_txn(datapackage_a).run(conn)
with closing(conn.cursor()) as cursor:
modified_a, hash_a = query.execute(cursor).fetchone()
attributestore.store_txn(datapackage_b).run(conn)
with closing(conn.cursor()) as cursor:
modified_b, hash_b = query.execute(cursor).fetchone()
# modified should be updated when same data is delivered again
ok_(modified_a < modified_b)
# hash should remain the same when then same data is delivered again
eq_(hash_a, hash_b)
def test_store_empty_attributes(conn):
"""Test storing of empty datapackage."""
with closing(conn.cursor()) as cursor:
attribute_names = []
timestamp = pytz.utc.localize(datetime.utcnow())
rows = [(10023 + i, timestamp, tuple()) for i in range(100)]
datasource = DataSource.from_name(cursor, "integration-test")
entitytype = EntityType.from_name(cursor, "UtranCell")
datapackage = DataPackage(attribute_names, rows)
attributes = datapackage.deduce_attributes()
attributestore = AttributeStore(datasource, entitytype, attributes)
attributestore.create(cursor)
attributestore.store_txn(datapackage).run(conn)
conn.commit()
def store(self, column_names, fields, raw_data_rows):
rows = list(raw_data_rows)
raw_datapackage = DataPackage(column_names, rows)
attributes = raw_datapackage.deduce_attributes()
entity_ref = EntityDnRef(rows[0][0])
with closing(self.conn.cursor()) as cursor:
datasource = DataSource.from_name(cursor, self.datasource)
entitytype = entity_ref.get_entitytype(cursor)
attributestore = AttributeStore.from_attributes(
cursor, datasource, entitytype, attributes)
self.conn.commit()
attributestore.store_raw(raw_datapackage).run(self.conn)
def test_to_dict():
datapackage = DataPackage(
attribute_names=('height', 'power'),
rows=[
(10034, TIMESTAMP, ['15.6', '68'])
]
)
json_data = datapackage.to_dict()
expected_json = (
'{"attribute_names": ["height", "power"], '
'"rows": ['
'[10034, "2013-08-30T15:30:00+00:00", ["15.6", "68"]]'
']'
'}')
eq_(json.dumps(json_data), expected_json)
def store(self, column_names, fields, raw_data_rows):
rows = list(raw_data_rows)
raw_datapackage = DataPackage(column_names, rows)
attributes = raw_datapackage.deduce_attributes()
entity_ref = EntityDnRef(rows[0][0])
with closing(self.conn.cursor()) as cursor:
datasource = DataSource.from_name(cursor, self.datasource)
entitytype = entity_ref.get_entitytype(cursor)
attributestore = AttributeStore.from_attributes(
cursor, datasource, entitytype, attributes
)
self.conn.commit()
attributestore.store_raw(raw_datapackage).run(self.conn)
def test_store_txn_with_empty(conn):
"""Test transactional storing with empty value."""
with closing(conn.cursor()) as cursor:
datasource = DataSource.from_name(cursor, "integration-test")
entitytype = EntityType.from_name(cursor, "UtranCell")
timestamp = pytz.utc.localize(datetime.utcnow())
datapackage = DataPackage(
attribute_names=['freeText'],
rows=[
(10023, timestamp, ('',))
]
)
attributes = datapackage.deduce_attributes()
eq_(attributes[0].datatype, 'smallint')
attributestore = AttributeStore.from_attributes(
cursor, datasource, entitytype, attributes)
conn.commit()
attributestore.store_txn(datapackage).run(conn)
def test_store_batch_with_list_c(conn):
"""Test batch wise storing using staging table."""
attribute_names = ['height', 'refs']
timestamp = pytz.utc.localize(datetime.utcnow())
data_rows = [
(10023, timestamp, ('19.5', ['', '', '', ''])),
(10024, timestamp, ('19.3', ['', '', '', '']))
]
datapackage = DataPackage(attribute_names, data_rows)
attributes = datapackage.deduce_attributes()
with closing(conn.cursor()) as cursor:
datasource = DataSource.from_name(cursor, "integration-test")
entitytype = EntityType.from_name(cursor, "UtranCell")
attributestore = AttributeStore(datasource, entitytype, attributes)
attributestore.create(cursor)
attributestore.store_batch(cursor, datapackage)
conn.commit()
def test_array(conn):
with closing(conn.cursor()) as cursor:
datasource = name_to_datasource(cursor, "integration-test")
entitytype = name_to_entitytype(cursor, "UtranCell")
timestamp = pytz.utc.localize(datetime.utcnow())
datapackage = DataPackage(
attribute_names=['channel', 'pwr'],
rows=[
(10023, timestamp, ('7', '0,0,0,2,5,12,87,34,5,0,0')),
(10024, timestamp, ('9', '0,0,0,1,11,15,95,41,9,0,0'))
]
)
attributes = datapackage.deduce_attributes()
attributestore = AttributeStore(datasource, entitytype, attributes)
attributestore.create(cursor)
conn.commit()
attributestore.store_txn(datapackage).run(conn)
def test_update(conn):
with closing(conn.cursor()) as cursor:
attribute_names = ['CellID', 'CCR', 'Drops']
datasource = name_to_datasource(cursor, "integration-test")
entitytype = name_to_entitytype(cursor, "UtranCell")
time1 = datasource.tzinfo.localize(datetime.now())
data_rows = [
(10023, time1, ('10023', '0.9919', '17')),
(10047, time1, ('10047', '0.9963', '18'))
]
update_data_rows = [
(10023, time1, ('10023', '0.5555', '17'))
]
datapackage = DataPackage(attribute_names, data_rows)
attributes = datapackage.deduce_attributes()
attributestore = AttributeStore(datasource, entitytype, attributes)
attributestore.create(cursor)
attributestore.store_txn(datapackage).run(conn)
time.sleep(1)
datapackage = DataPackage(attribute_names, update_data_rows)
attributestore.store_txn(datapackage).run(conn)
conn.commit()
query = (
'SELECT modified, "CCR" '
'FROM {0}').format(attributestore.history_table.render())
cursor.execute(query)
test_list = [(modified, ccr) for modified, ccr in cursor.fetchall()]
assert_not_equal(test_list[0][0], test_list[1][0])
assert_not_equal(test_list[0][1], test_list[1][1])
def test_store_batch_with_list_a(conn):
"""Test batch wise storing using staging table."""
attribute_names = ['height', 'refs']
timestamp = pytz.utc.localize(datetime.utcnow())
data_rows = [
(10023 + i, timestamp, ('19.5', ['r34', 'r23', 'r33']))
for i in range(100)]
datapackage = DataPackage(attribute_names, data_rows)
attributes = datapackage.deduce_attributes()
with closing(conn.cursor()) as cursor:
datasource = DataSource.from_name(cursor, "integration-test")
entitytype = EntityType.from_name(cursor, "UtranCell")
attributestore = AttributeStore(datasource, entitytype, attributes)
attributestore.create(cursor)
attributestore.store_batch(cursor, datapackage)
conn.commit()
cursor.execute(
"SELECT attribute_directory.materialize_curr_ptr(attributestore) "
"FROM attribute_directory.attributestore "
"WHERE id = %s", (attributestore.id,))
query = (
"SELECT timestamp, height "
"FROM {0}").format(attributestore.table.render())
cursor.execute(query)
# Row count should be the same as the stored batch size
eq_(cursor.rowcount, len(datapackage.rows))
stored_timestamp, height = cursor.fetchone()
# Timestamp should be the same as the stored batch timestamp
eq_(stored_timestamp, timestamp)
eq_(height, 19.5)
def test_from_dict():
json_data = {
"timestamp": "2013-09-16T16:55:00+00:00",
"attribute_names": ["tilt", "azimuth"],
"rows": [
[13403, ["4", "180"]]
]
}
datapackage = DataPackage.from_dict(json_data)
eq_(datapackage.attribute_names[1], "azimuth")
eq_(datapackage.rows[0][0], 13403)
eq_(datapackage.rows[0][1][1], "180")
def load_datapackage(stream):
return DataPackage.from_dict(json.load(stream))
