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Unit tests: clean up warnings #386

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merged 2 commits into from
Nov 14, 2023
Merged

Unit tests: clean up warnings #386

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a70f586
test_sess: clear client from mock store for conflicting sessions tests
sbesson Oct 30, 2023
efdd174
test_hdfstorage: catch and test NonNaturalNameWarning thrown by PyTables
sbesson Oct 30, 2023
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2 changes: 2 additions & 0 deletions test/unit/clitest/test_sess.py
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Original file line number Diff line number Diff line change
Expand Up @@ -658,6 +658,7 @@ def testSessionReattachConflictingPort(self, connection, port, group):
connection, name=None, port=port[1], group=group)
with pytest.raises(NonZeroReturnCode):
cli.invoke(["s", "login", "-k", "%s" % MOCKKEY] + key_conn_args)
cli.STORE.clear(testhost, testuser)

@pytest.mark.parametrize('connection', CONNECTION_TYPES)
@pytest.mark.parametrize('port', ALL_PORTS)
Expand Down Expand Up @@ -706,6 +707,7 @@ def testSessionReattachFailsPortGroup(self, connection, port, group):
connection, name=None, port=port[1], group=group[1])
with pytest.raises(NonZeroReturnCode):
cli.invoke(["s", "login", "-k", "%s" % MOCKKEY] + key_conn_args)
cli.STORE.clear(testhost, testuser)

@pytest.mark.parametrize('port', ALL_PORTS)
@pytest.mark.parametrize('connection', CONNECTION_TYPES)
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7 changes: 6 additions & 1 deletion test/unit/tablestest/test_hdfstorage.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,6 +30,7 @@

import omero.hdfstorageV2 as storage_module
import sys
import warnings

if sys.platform.startswith("win"):
pytest.skip("skipping tests on windows", allow_module_level=True)
Expand Down Expand Up @@ -344,7 +345,11 @@ def testNonNaturalNameWarning(self, name):
hdf = HdfStorage(self.hdfpath(), self.lock)
cols = [omero.columns.StringColumnI(
name, "A column with non natural name", bytesize, None)]
hdf.initialize(cols)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
hdf.initialize(cols)
assert len(w) == 1
assert issubclass(w[-1].category, tables.NaturalNameWarning)
cols[0].settable(hdf._HdfStorage__mea) # Needed for size
cols[0].values = ["foo", "bar"]
hdf.append(cols)
Expand Down