def test_tsdb_dictdb():
# synthetic data
t = np.array([1, 1.5, 2, 2.5, 10, 11, 12])
v1 = np.array([10, 12, -11, 1.5, 10, 13, 17])
v2 = np.array([8, 12, -11, 1.5, 10, 13, 17])
a1 = TimeSeries(t, v1)
a2 = TimeSeries(t, v2)
identity = lambda x: x
schema = {
'pk': {'convert': identity, 'index': None},
'ts': {'convert': identity, 'index': None},
'order': {'convert': int, 'index': 1},
'blarg': {'convert': int, 'index': 1},
'useless': {'convert': identity, 'index': None},
'mean': {'convert': float, 'index': 1},
'std': {'convert': float, 'index': 1},
'vp': {'convert': bool, 'index': 1},
'deleted': {'convert': bool, 'index': 1}
}
# create dictionary
ddb = DictDB(schema, 'pk')
# CHECK INSERTION/UPSERTION/DELETION -->
# insert two new time series and metadata
ddb.insert_ts('pk1', a1)
ddb.upsert_meta('pk1', {'order': 1, 'blarg': 2})
ddb.insert_ts('pk2', a2)
ddb.upsert_meta('pk2', {'order': 2, 'blarg': 2})
# try to insert a duplicate primary key
with pytest.raises(ValueError):
ddb.insert_ts('pk2', a2)
# delete a valid time series
ddb.delete_ts('pk1')
print(ddb.indexes)
# check that it isn't present any more
pk, selected = ddb.select({'pk': 'pk1'}, [], None)
assert pk == []
assert len(selected) == 0
# add the time series back in
ddb.insert_ts('pk1', a1)
# Test consecutives meta upsert
ddb.upsert_meta('pk1', {'order': 2, 'blarg': 3})
for k, v in ddb.indexes['order'].items():
if k == 2:
assert ('pk1' in v)
else:
assert ('pk1' not in v)
ddb.upsert_meta('pk1', {'order': 1, 'blarg': 2})
for k, v in ddb.indexes['blarg'].items():
if k == 2:
assert ('pk1' in v)
else:
assert ('pk1' not in v)
# check that it's present now
pk, selected = ddb.select({'pk': 'pk1'}, [], None)
assert pk == ['pk1']
assert len(selected) == 1
# delete an invalid time series
with pytest.raises(ValueError):
ddb.delete_ts('not_here')
# try to insert metadata for a time series that isn't present
with pytest.raises(ValueError):
ddb.upsert_meta('pk3', {'order': 2, 'blarg': 2})
# extract database entries for testing
db_rows = ddb.rows
idx = sorted(db_rows.keys()) # sorted primary keys
# check primary keys
assert idx == ['0DELETED_pk1', 'pk1', 'pk2']
# check metadata
assert db_rows['pk1']['order'] == 1
assert db_rows['pk2']['order'] == 2
assert db_rows['pk1']['blarg'] == 2
assert db_rows['pk2']['blarg'] == 2
# CHECK SELECT OPERATIONS -->
pk, selected = ddb.select({}, None, None)
assert sorted(pk) == ['pk1', 'pk2']
assert selected == [{}, {}]
pk, selected = ddb.select({}, None, {'sort_by': '-order', 'limit': 5})
assert sorted(pk) == ['pk1', 'pk2']
assert selected == [{}, {}]
pk, selected = ddb.select({}, None, {'sort_by': '+pk'})
assert pk == ['pk1', 'pk2']
assert selected == [{}, {}]
pk, selected = ddb.select({'order': 1, 'blarg': 2}, [], None)
assert pk == ['pk1']
assert len(selected) == 1
assert selected[0]['pk'] == 'pk1'
assert selected[0]['order'] == 1
assert selected[0]['blarg'] == 2
pk, selected = ddb.select({'order': [1, 2], 'blarg': 2}, [], None)
assert sorted(pk) == ['pk1', 'pk2']
assert len(selected) == 2
idx = pk.index('pk1')
assert selected[idx]['pk'] == 'pk1'
assert selected[idx]['order'] == 1
assert selected[idx]['blarg'] == 2
pk, selected = ddb.select({'order': {'>=': 4}}, ['order'], None)
assert len(pk) == 0
assert len(selected) == 0
# field not in schema
with pytest.raises(ValueError):
ddb.select({}, None, {'sort_by': '-unknown', 'limit': 5})
# bulk update of indices
ddb.index_bulk()
check_indexes = ['blarg', 'deleted', 'mean', 'order', 'std', 'vp']
assert sorted(ddb.indexes.keys()) == check_indexes
for v in ddb.indexes.values():
assert isinstance(v, defaultdict)
