def test_deps_cache_chain():
"""
Test that a Query -> cached1 -> cached2 chain will
return only a dependency on cached1.
"""
dl1 = daily_location("2016-01-01")
hl1 = ModalLocation(daily_location("2016-01-01"),
daily_location("2016-01-02"))
hl1.store().result()
hl2 = ModalLocation(daily_location("2016-01-03"),
daily_location("2016-01-04"))
flow = Flows(hl1, hl2)
bad_dep = dl1.md5
good_dep = hl1.md5
assert 6 == len(flow._get_stored_dependencies())
assert good_dep in [x.md5 for x in flow._get_stored_dependencies()]
assert bad_dep not in [x.md5 for x in flow._get_stored_dependencies()]
def test_retrieve_all():
"""
Test that Query.get_stored returns everything.
"""
dl1 = daily_location("2016-01-01")
dl1.store().result()
hl1 = ModalLocation(daily_location("2016-01-01"),
daily_location("2016-01-02"))
hl1.store().result()
hl2 = ModalLocation(daily_location("2016-01-03"),
daily_location("2016-01-04"))
flow = Flows(hl1, hl2)
flow.store().result()
from_cache = [obj.query_id for obj in Query.get_stored()]
assert dl1.query_id in from_cache
assert hl1.query_id in from_cache
assert flow.query_id in from_cache
def test_invalidate_cache_multi(flowmachine_connect):
"""
Test that invalidating a simple query that is part of
a bigger one drops both tables, cleans up dependencies
and removes both from cache.
"""
dl1 = daily_location("2016-01-01")
dl1.store().result()
hl1 = ModalLocation(daily_location("2016-01-01"),
daily_location("2016-01-02"))
hl1.store().result()
assert dl1.is_stored
assert hl1.is_stored
dl1.invalidate_db_cache()
assert not dl1.is_stored
assert not hl1.is_stored
assert not cache_table_exists(get_db(), dl1.query_id)
assert not cache_table_exists(get_db(), hl1.query_id)
has_deps = bool(get_db().fetch("SELECT * FROM cache.dependencies"))
assert has_deps # the remaining dependencies are due to underlying Table objects
def test_contact_reference_location_stats_custom_geometry(get_dataframe):
""" Test ContactReferenceLocationStats with custom geometry column. """
cb = ContactBalance("2016-01-01", "2016-01-03")
ml = ModalLocation(*[
daily_location(
d,
spatial_unit=make_spatial_unit("versioned-cell"),
subscriber_subset=cb.counterparts_subset(include_subscribers=True),
) for d in list_of_dates("2016-01-01", "2016-01-03")
])
cb.store()
ml.store()
ml = CustomQuery(
f"SELECT subscriber, ST_POINT(lon, lat) AS loc FROM ({ml.get_query()}) _",
["subscriber", "loc"],
)
query = ContactReferenceLocationStats(cb,
ml,
statistic="avg",
geom_column="loc")
df = get_dataframe(query).set_index("subscriber")
assert df.value["gwAynWXp4eWvxGP7"] == pytest.approx(298.7215)
