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Chore/update deps ensure tempsgs testing #90

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merged 5 commits into from
Jun 17, 2024
Merged

Chore/update deps ensure tempsgs testing #90

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31291a7
Update endpoint logic in test for bogus api key.
justinGilmer Jun 17, 2024
a6650d8
Update np.NaN to use the 2.0 approved np.nan.
justinGilmer Jun 17, 2024
01c952a
Remove debug print.
justinGilmer Jun 17, 2024
b0ef312
Drop 3.7 in test matrix, add in 3.12
justinGilmer Jun 17, 2024
660271f
drop 3.12
justinGilmer Jun 17, 2024
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7 changes: 6 additions & 1 deletion tests/btrdb_integration/test_conn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,7 @@

import btrdb
from btrdb.exceptions import BTrDBError
from btrdb.utils.credentials import credentials_by_profile


@pytest.mark.skipif(
Expand All @@ -20,9 +21,13 @@ def test_connection_info(self, conn):
def test_incorrect_connect(
self,
):
env_name = os.getenv("BTRDB_INTEGRATION_TEST_PROFILE")
creds = credentials_by_profile(env_name)
conn_str = creds["endpoints"]
print(f"{creds = }")
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err_msg = r"""Could not connect to the database, error message: <_InactiveRpcError of RPC that terminated with:\n\tstatus = StatusCode.UNAUTHENTICATED\n\tdetails = "invalid api key"\n"""
with pytest.raises(BTrDBError, match=err_msg):
conn = btrdb.connect(conn_str="127.0.0.1:4410", apikey="BOGUS_KEY")
conn = btrdb.connect(conn_str=conn_str, apikey="BOGUS_KEY")

@pytest.mark.xfail(
reason="Should return BTrDBError, but returns GRPCError instead, FIXME"
Expand Down
36 changes: 18 additions & 18 deletions tests/btrdb_integration/test_streamset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -54,8 +54,8 @@ def test_streamset_arrow_values(conn, tmp_collection):
s2.insert(list(zip(t2, d2)))
ss = btrdb.stream.StreamSet([s1, s2]).filter(start=100, end=121)
expected_times = [100, 101, 105, 106, 110, 114, 115, 119, 120]
expected_col1 = [0.0, np.NaN, 1.0, np.NaN, 2.0, np.NaN, 3.0, np.NaN, 4.0]
expected_col2 = [np.NaN, 5.0, np.NaN, 6.0, 7.0, 8.0, np.NaN, 9.0, np.NaN]
expected_col1 = [0.0, np.nan, 1.0, np.nan, 2.0, np.nan, 3.0, np.nan, 4.0]
expected_col2 = [np.nan, 5.0, np.nan, 6.0, 7.0, 8.0, np.nan, 9.0, np.nan]
expected_schema = pa.schema(
[
pa.field("time", pa.timestamp("ns", tz="UTC"), nullable=False),
Expand All @@ -65,8 +65,8 @@ def test_streamset_arrow_values(conn, tmp_collection):
)
values = ss.arrow_values()
times = [t.value for t in values["time"]]
col1 = [np.NaN if isnan(v.as_py()) else v.as_py() for v in values[str(s1.uuid)]]
col2 = [np.NaN if isnan(v.as_py()) else v.as_py() for v in values[str(s2.uuid)]]
col1 = [np.nan if isnan(v.as_py()) else v.as_py() for v in values[str(s1.uuid)]]
col2 = [np.nan if isnan(v.as_py()) else v.as_py() for v in values[str(s2.uuid)]]
assert times == expected_times
assert col1 == expected_col1
assert col2 == expected_col2
Expand All @@ -91,12 +91,12 @@ def test_streamset_template_schema(conn, tmp_collection):
)
ss = btrdb.stream.StreamSet([s1, s2]).filter(start=100, end=121, schema=schema)
expected_times = [100, 101, 105, 106, 110, 114, 115, 119, 120]
expected_col1 = [0.0, np.NaN, 1.0, np.NaN, 2.0, np.NaN, 3.0, np.NaN, 4.0]
expected_col2 = [np.NaN, 5.0, np.NaN, 6.0, 7.0, 8.0, np.NaN, 9.0, np.NaN]
expected_col1 = [0.0, np.nan, 1.0, np.nan, 2.0, np.nan, 3.0, np.nan, 4.0]
expected_col2 = [np.nan, 5.0, np.nan, 6.0, 7.0, 8.0, np.nan, 9.0, np.nan]
values = ss.arrow_values()
times = [t.value for t in values["t"]]
col1 = [np.NaN if isnan(v.as_py()) else v.as_py() for v in values["a"]]
col2 = [np.NaN if isnan(v.as_py()) else v.as_py() for v in values["b"]]
col1 = [np.nan if isnan(v.as_py()) else v.as_py() for v in values["a"]]
col2 = [np.nan if isnan(v.as_py()) else v.as_py() for v in values["b"]]
assert times == expected_times
assert col1 == expected_col1
assert col2 == expected_col2
Expand Down Expand Up @@ -292,8 +292,8 @@ def test_streamset_to_dataframe(conn, tmp_collection):
ss = btrdb.stream.StreamSet([s1, s2]).filter(start=100, end=121)
values = ss.to_dataframe()
expected_times = [100, 101, 105, 106, 110, 114, 115, 119, 120]
expected_col1 = [0.0, np.NaN, 1.0, np.NaN, 2.0, np.NaN, 3.0, np.NaN, 4.0]
expected_col2 = [np.NaN, 5.0, np.NaN, 6.0, 7.0, 8.0, np.NaN, 9.0, np.NaN]
expected_col1 = [0.0, np.nan, 1.0, np.nan, 2.0, np.nan, 3.0, np.nan, 4.0]
expected_col2 = [np.nan, 5.0, np.nan, 6.0, 7.0, 8.0, np.nan, 9.0, np.nan]
expected_dat = {
tmp_collection + "/s1": expected_col1,
tmp_collection + "/s2": expected_col2,
Expand All @@ -318,10 +318,10 @@ def test_arrow_streamset_to_dataframe(conn, tmp_collection):
pa.scalar(v, type=pa.timestamp("ns", tz="UTC")).as_py() for v in expected_times
]
expected_col1 = pa.array(
[0.0, np.NaN, 1.0, np.NaN, 2.0, np.NaN, 3.0, np.NaN, 4.0], mask=[False] * 9
[0.0, np.nan, 1.0, np.nan, 2.0, np.nan, 3.0, np.nan, 4.0], mask=[False] * 9
)
expected_col2 = pa.array(
[np.NaN, 5.0, np.NaN, 6.0, 7.0, 8.0, np.NaN, 9.0, np.NaN], mask=[False] * 9
[np.nan, 5.0, np.nan, 6.0, 7.0, 8.0, np.nan, 9.0, np.nan], mask=[False] * 9
)
expected_dat = {
"time": expected_times,
Expand Down Expand Up @@ -361,8 +361,8 @@ def test_arrow_streamset_to_polars(conn, tmp_collection):
expected_times = [
pa.scalar(v, type=pa.timestamp("ns", tz="UTC")).as_py() for v in expected_times
]
expected_col1 = [0.0, np.NaN, 1.0, np.NaN, 2.0, np.NaN, 3.0, np.NaN, 4.0]
expected_col2 = [np.NaN, 5.0, np.NaN, 6.0, 7.0, 8.0, np.NaN, 9.0, np.NaN]
expected_col1 = [0.0, np.nan, 1.0, np.nan, 2.0, np.nan, 3.0, np.nan, 4.0]
expected_col2 = [np.nan, 5.0, np.nan, 6.0, 7.0, 8.0, np.nan, 9.0, np.nan]
expected_dat = {
tmp_collection + "/s1": expected_col1,
tmp_collection + "/s2": expected_col2,
Expand Down Expand Up @@ -395,8 +395,8 @@ def test_streamset_arrow_polars_vs_old_to_polars(conn, tmp_collection, name_call
expected_times = [
pa.scalar(v, type=pa.timestamp("ns", tz="UTC")).as_py() for v in expected_times
]
expected_col1 = [0.0, np.NaN, 1.0, np.NaN, 2.0, np.NaN, 3.0, np.NaN, 4.0]
expected_col2 = [np.NaN, 5.0, np.NaN, 6.0, 7.0, 8.0, np.NaN, 9.0, np.NaN]
expected_col1 = [0.0, np.nan, 1.0, np.nan, 2.0, np.nan, 3.0, np.nan, 4.0]
expected_col2 = [np.nan, 5.0, np.nan, 6.0, 7.0, 8.0, np.nan, 9.0, np.nan]
expected_dat = {
tmp_collection + "/s1": expected_col1,
tmp_collection + "/s2": expected_col2,
Expand Down Expand Up @@ -509,8 +509,8 @@ def test_timesnap_backward_extends_range(conn, tmp_collection):
values = ss.arrow_values()
assert [1 * sec, 2 * sec] == [t.value for t in values["time"]]
assert [0.5, 2.0] == [v.as_py() for v in values[str(s1.uuid)]]
assert [np.NaN, 2.0] == [
np.NaN if isnan(v.as_py()) else v.as_py() for v in values[str(s2.uuid)]
assert [np.nan, 2.0] == [
np.nan if isnan(v.as_py()) else v.as_py() for v in values[str(s2.uuid)]
]
assert [1.0, 2.0] == [v.as_py() for v in values[str(s3.uuid)]]

Expand Down
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