def test_atomicity(two_empty_temp_db_connections, some_interdeps):
"""
Test the atomicity of the transaction by extracting and inserting two
runs where the second one is not completed. The not completed error must
roll back any changes to the target
"""
source_conn, target_conn = two_empty_temp_db_connections
source_path = path_to_dbfile(source_conn)
target_path = path_to_dbfile(target_conn)
# The target file must exist for us to be able to see whether it has
# changed
Path(target_path).touch()
source_exp = Experiment(conn=source_conn)
source_ds_1 = DataSet(conn=source_conn, exp_id=source_exp.exp_id)
source_ds_2 = DataSet(conn=source_conn, exp_id=source_exp.exp_id)
for ds in (source_ds_1, source_ds_2):
ds.set_interdependencies(some_interdeps[1])
ds.mark_started()
ds.add_result({name: 2.1 for name in some_interdeps[1].names})
# importantly, source_ds_2 is NOT marked as completed
source_ds_1.mark_completed()
# now check that the target file is untouched
with raise_if_file_changed(target_path):
# although the not completed error is a ValueError, we get the
# RuntimeError from SQLite
with pytest.raises(RuntimeError):
extract_runs_into_db(source_path, target_path, 1, 2)
def test_load_by_X_functions(two_empty_temp_db_connections, some_interdeps):
"""
Test some different loading functions
"""
source_conn, target_conn = two_empty_temp_db_connections
source_path = path_to_dbfile(source_conn)
target_path = path_to_dbfile(target_conn)
source_exp1 = Experiment(conn=source_conn)
source_ds_1_1 = DataSet(conn=source_conn, exp_id=source_exp1.exp_id)
source_exp2 = Experiment(conn=source_conn)
source_ds_2_1 = DataSet(conn=source_conn, exp_id=source_exp2.exp_id)
source_ds_2_2 = DataSet(conn=source_conn,
exp_id=source_exp2.exp_id,
name="customname")
for ds in (source_ds_1_1, source_ds_2_1, source_ds_2_2):
ds.set_interdependencies(some_interdeps[1])
ds.mark_started()
ds.add_result({name: 0.0 for name in some_interdeps[1].names})
ds.mark_completed()
extract_runs_into_db(source_path, target_path, source_ds_2_2.run_id)
test_ds = load_by_guid(source_ds_2_2.guid, target_conn)
assert source_ds_2_2.the_same_dataset_as(test_ds)
test_ds = load_by_id(1, target_conn)
assert source_ds_2_2.the_same_dataset_as(test_ds)
test_ds = load_by_counter(1, 1, target_conn)
assert source_ds_2_2.the_same_dataset_as(test_ds)
def test_integration_station_and_measurement(two_empty_temp_db_connections,
inst):
"""
An integration test where the runs in the source DB file are produced
with the Measurement object and there is a Station as well
"""
source_conn, target_conn = two_empty_temp_db_connections
source_path = path_to_dbfile(source_conn)
target_path = path_to_dbfile(target_conn)
source_exp = Experiment(conn=source_conn)
# Set up measurement scenario
station = Station(inst)
meas = Measurement(exp=source_exp, station=station)
meas.register_parameter(inst.back)
meas.register_parameter(inst.plunger)
meas.register_parameter(inst.cutter, setpoints=(inst.back, inst.plunger))
with meas.run() as datasaver:
for back_v in [1, 2, 3]:
for plung_v in [-3, -2.5, 0]:
datasaver.add_result((inst.back, back_v),
(inst.plunger, plung_v),
(inst.cutter, back_v+plung_v))
extract_runs_into_db(source_path, target_path, 1)
target_ds = DataSet(conn=target_conn, run_id=1)
assert datasaver.dataset.the_same_dataset_as(target_ds)
def test_runs_from_different_experiments_raises(two_empty_temp_db_connections,
some_paramspecs):
"""
Test that inserting runs from multiple experiments raises
"""
source_conn, target_conn = two_empty_temp_db_connections
source_path = path_to_dbfile(source_conn)
target_path = path_to_dbfile(target_conn)
source_exp_1 = Experiment(conn=source_conn)
source_exp_2 = Experiment(conn=source_conn)
# make 5 runs in first experiment
exp_1_run_ids = []
for _ in range(5):
source_dataset = DataSet(conn=source_conn, exp_id=source_exp_1.exp_id)
exp_1_run_ids.append(source_dataset.run_id)
for ps in some_paramspecs[2].values():
source_dataset.add_parameter(ps)
source_dataset.mark_started()
for val in range(10):
source_dataset.add_result(
{ps.name: val
for ps in some_paramspecs[2].values()})
source_dataset.mark_completed()
# make 5 runs in second experiment
exp_2_run_ids = []
for _ in range(5):
source_dataset = DataSet(conn=source_conn, exp_id=source_exp_2.exp_id)
exp_2_run_ids.append(source_dataset.run_id)
for ps in some_paramspecs[2].values():
source_dataset.add_parameter(ps)
source_dataset.mark_started()
for val in range(10):
source_dataset.add_result(
{ps.name: val
for ps in some_paramspecs[2].values()})
source_dataset.mark_completed()
run_ids = exp_1_run_ids + exp_2_run_ids
source_exp_ids = np.unique([1, 2])
matchstring = ('Did not receive runs from a single experiment\\. '
f'Got runs from experiments {source_exp_ids}')
# make the matchstring safe to use as a regexp
matchstring = matchstring.replace('[', '\\[').replace(']', '\\]')
with pytest.raises(ValueError, match=matchstring):
extract_runs_into_db(source_path, target_path, *run_ids)
def test_old_versions_not_touched(two_empty_temp_db_connections,
some_interdeps):
source_conn, target_conn = two_empty_temp_db_connections
target_path = path_to_dbfile(target_conn)
source_path = path_to_dbfile(source_conn)
_, new_v = get_db_version_and_newest_available_version(source_path)
fixturepath = os.sep.join(qcodes.tests.dataset.__file__.split(os.sep)[:-1])
fixturepath = os.path.join(fixturepath,
'fixtures', 'db_files', 'version2',
'some_runs.db')
if not os.path.exists(fixturepath):
pytest.skip("No db-file fixtures found. You can generate test db-files"
" using the scripts in the legacy_DB_generation folder")
# First test that we cannot use an old version as source
with raise_if_file_changed(fixturepath):
with pytest.warns(UserWarning) as warning:
extract_runs_into_db(fixturepath, target_path, 1)
expected_mssg = ('Source DB version is 2, but this '
f'function needs it to be in version {new_v}. '
'Run this function again with '
'upgrade_source_db=True to auto-upgrade '
'the source DB file.')
assert warning[0].message.args[0] == expected_mssg
# Then test that we cannot use an old version as target
# first create a run in the new version source
source_exp = Experiment(conn=source_conn)
source_ds = DataSet(conn=source_conn, exp_id=source_exp.exp_id)
source_ds.set_interdependencies(some_interdeps[1])
source_ds.mark_started()
source_ds.add_results([{name: 0.0
for name in some_interdeps[1].names}])
source_ds.mark_completed()
with raise_if_file_changed(fixturepath):
with pytest.warns(UserWarning) as warning:
extract_runs_into_db(source_path, fixturepath, 1)
expected_mssg = ('Target DB version is 2, but this '
f'function needs it to be in version {new_v}. '
'Run this function again with '
'upgrade_target_db=True to auto-upgrade '
'the target DB file.')
assert warning[0].message.args[0] == expected_mssg
def test_experiments_with_NULL_sample_name(two_empty_temp_db_connections,
some_paramspecs):
"""
In older API versions (corresponding to DB version 3),
users could get away with setting the sample name to None
This test checks that such an experiment gets correctly recognised and
is thus not ever re-inserted into the target DB
"""
source_conn, target_conn = two_empty_temp_db_connections
source_exp_1 = Experiment(conn=source_conn, name='null_sample_name')
source_path = path_to_dbfile(source_conn)
target_path = path_to_dbfile(target_conn)
# make 5 runs in experiment
exp_1_run_ids = []
for _ in range(5):
source_dataset = DataSet(conn=source_conn, exp_id=source_exp_1.exp_id)
exp_1_run_ids.append(source_dataset.run_id)
for ps in some_paramspecs[2].values():
source_dataset.add_parameter(ps)
source_dataset.mark_started()
for val in range(10):
source_dataset.add_result(
{ps.name: val
for ps in some_paramspecs[2].values()})
source_dataset.mark_completed()
sql = """
UPDATE experiments
SET sample_name = NULL
WHERE exp_id = 1
"""
source_conn.execute(sql)
source_conn.commit()
assert source_exp_1.sample_name is None
extract_runs_into_db(source_path, target_path, 1, 2, 3, 4, 5)
assert len(get_experiments(target_conn)) == 1
extract_runs_into_db(source_path, target_path, 1, 2, 3, 4, 5)
assert len(get_experiments(target_conn)) == 1
assert len(Experiment(exp_id=1, conn=target_conn)) == 5
def test_result_table_naming_and_run_id(two_empty_temp_db_connections,
some_paramspecs):
"""
Check that a correct result table name is given and that a correct run_id
is assigned
"""
source_conn, target_conn = two_empty_temp_db_connections
source_path = path_to_dbfile(source_conn)
target_path = path_to_dbfile(target_conn)
source_exp1 = Experiment(conn=source_conn)
source_ds_1_1 = DataSet(conn=source_conn, exp_id=source_exp1.exp_id)
for ps in some_paramspecs[2].values():
source_ds_1_1.add_parameter(ps)
source_ds_1_1.mark_started()
source_ds_1_1.add_result(
{ps.name: 0.0
for ps in some_paramspecs[2].values()})
source_ds_1_1.mark_completed()
source_exp2 = Experiment(conn=source_conn)
source_ds_2_1 = DataSet(conn=source_conn, exp_id=source_exp2.exp_id)
for ps in some_paramspecs[2].values():
source_ds_2_1.add_parameter(ps)
source_ds_2_1.mark_started()
source_ds_2_1.add_result(
{ps.name: 0.0
for ps in some_paramspecs[2].values()})
source_ds_2_1.mark_completed()
source_ds_2_2 = DataSet(conn=source_conn,
exp_id=source_exp2.exp_id,
name="customname")
for ps in some_paramspecs[2].values():
source_ds_2_2.add_parameter(ps)
source_ds_2_2.mark_started()
source_ds_2_2.add_result(
{ps.name: 0.0
for ps in some_paramspecs[2].values()})
source_ds_2_2.mark_completed()
extract_runs_into_db(source_path, target_path, source_ds_2_2.run_id)
# The target ds ought to have a runs table "customname-1-1"
# and ought to be the same dataset as its "ancestor"
target_ds = DataSet(conn=target_conn, run_id=1)
assert target_ds.table_name == "customname-1-1"
assert target_ds.the_same_dataset_as(source_ds_2_2)
def test_load_by_X_functions(two_empty_temp_db_connections, some_paramspecs):
"""
Test some different loading functions
"""
source_conn, target_conn = two_empty_temp_db_connections
source_path = path_to_dbfile(source_conn)
target_path = path_to_dbfile(target_conn)
source_exp1 = Experiment(conn=source_conn)
source_ds_1_1 = DataSet(conn=source_conn, exp_id=source_exp1.exp_id)
for ps in some_paramspecs[2].values():
source_ds_1_1.add_parameter(ps)
source_ds_1_1.mark_started()
source_ds_1_1.add_result(
{ps.name: 0.0
for ps in some_paramspecs[2].values()})
source_ds_1_1.mark_completed()
source_exp2 = Experiment(conn=source_conn)
source_ds_2_1 = DataSet(conn=source_conn, exp_id=source_exp2.exp_id)
for ps in some_paramspecs[2].values():
source_ds_2_1.add_parameter(ps)
source_ds_2_1.mark_started()
source_ds_2_1.add_result(
{ps.name: 0.0
for ps in some_paramspecs[2].values()})
source_ds_2_1.mark_completed()
source_ds_2_2 = DataSet(conn=source_conn,
exp_id=source_exp2.exp_id,
name="customname")
for ps in some_paramspecs[2].values():
source_ds_2_2.add_parameter(ps)
source_ds_2_2.mark_started()
source_ds_2_2.add_result(
{ps.name: 0.0
for ps in some_paramspecs[2].values()})
source_ds_2_2.mark_completed()
extract_runs_into_db(source_path, target_path, source_ds_2_2.run_id)
test_ds = load_by_guid(source_ds_2_2.guid, target_conn)
assert source_ds_2_2.the_same_dataset_as(test_ds)
test_ds = load_by_id(1, target_conn)
assert source_ds_2_2.the_same_dataset_as(test_ds)
test_ds = load_by_counter(1, 1, target_conn)
assert source_ds_2_2.the_same_dataset_as(test_ds)
def test_column_mismatch(two_empty_temp_db_connections, some_interdeps, inst):
"""
Test insertion of runs with no metadata and no snapshot into a DB already
containing a run that has both
"""
source_conn, target_conn = two_empty_temp_db_connections
source_path = path_to_dbfile(source_conn)
target_path = path_to_dbfile(target_conn)
target_exp = Experiment(conn=target_conn)
# Set up measurement scenario
station = Station(inst)
meas = Measurement(exp=target_exp, station=station)
meas.register_parameter(inst.back)
meas.register_parameter(inst.plunger)
meas.register_parameter(inst.cutter, setpoints=(inst.back, inst.plunger))
with meas.run() as datasaver:
for back_v in [1, 2, 3]:
for plung_v in [-3, -2.5, 0]:
datasaver.add_result((inst.back, back_v),
(inst.plunger, plung_v),
(inst.cutter, back_v+plung_v))
datasaver.dataset.add_metadata('meta_tag', 'meta_value')
Experiment(conn=source_conn)
source_ds = DataSet(conn=source_conn)
source_ds.set_interdependencies(some_interdeps[1])
source_ds.mark_started()
source_ds.add_results([{name: 2.1
for name in some_interdeps[1].names}])
source_ds.mark_completed()
extract_runs_into_db(source_path, target_path, 1)
# compare
target_copied_ds = DataSet(conn=target_conn, run_id=2)
assert target_copied_ds.the_same_dataset_as(source_ds)
def test_extracting_dataless_run(two_empty_temp_db_connections):
"""
Although contrived, it could happen that a run with no data is extracted
"""
source_conn, target_conn = two_empty_temp_db_connections
source_path = path_to_dbfile(source_conn)
target_path = path_to_dbfile(target_conn)
Experiment(conn=source_conn)
source_ds = DataSet(conn=source_conn)
source_ds.mark_started()
source_ds.mark_completed()
extract_runs_into_db(source_path, target_path, source_ds.run_id)
loaded_ds = DataSet(conn=target_conn, run_id=1)
assert loaded_ds.the_same_dataset_as(source_ds)
def test_real_dataset_2d(two_empty_temp_db_connections, inst):
source_conn, target_conn = two_empty_temp_db_connections
source_path = path_to_dbfile(source_conn)
target_path = path_to_dbfile(target_conn)
source_exp = load_or_create_experiment(experiment_name="myexp",
conn=source_conn)
source_dataset, _, _ = do2d(inst.back,
0,
1,
10,
0,
inst.plunger,
0,
0.1,
15,
0,
inst.cutter,
exp=source_exp)
extract_runs_into_db(source_path, target_path, source_dataset.run_id)
target_dataset = load_by_guid(source_dataset.guid, conn=target_conn)
assert source_dataset.the_same_dataset_as(target_dataset)
# explicit regression test for https://github.com/QCoDeS/Qcodes/issues/3953
assert source_dataset.description.shapes == {
"extract_run_inst_cutter": (10, 15)
}
assert source_dataset.description.shapes == target_dataset.description.shapes
source_data = source_dataset.get_parameter_data(
)["extract_run_inst_cutter"]
target_data = target_dataset.get_parameter_data(
)["extract_run_inst_cutter"]
for source_data, target_data in zip(source_data.values(),
target_data.values()):
assert_array_equal(source_data, target_data)
def test_missing_runs_raises(two_empty_temp_db_connections, some_paramspecs):
"""
Test that an error is raised if we attempt to extract a run not present in
the source DB
"""
source_conn, target_conn = two_empty_temp_db_connections
source_exp_1 = Experiment(conn=source_conn)
# make 5 runs in first experiment
exp_1_run_ids = []
for _ in range(5):
source_dataset = DataSet(conn=source_conn, exp_id=source_exp_1.exp_id)
exp_1_run_ids.append(source_dataset.run_id)
for ps in some_paramspecs[2].values():
source_dataset.add_parameter(ps)
source_dataset.mark_started()
for val in range(10):
source_dataset.add_result(
{ps.name: val
for ps in some_paramspecs[2].values()})
source_dataset.mark_completed()
source_path = path_to_dbfile(source_conn)
target_path = path_to_dbfile(target_conn)
run_ids = [1, 8, 5, 3, 2, 4, 4, 4, 7, 8]
wrong_ids = [8, 7, 8]
expected_err = ("Error: not all run_ids exist in the source database. "
"The following run(s) is/are not present: "
f"{wrong_ids}")
with pytest.raises(ValueError, match=re.escape(expected_err)):
extract_runs_into_db(source_path, target_path, *run_ids)
def test_atomicity(two_empty_temp_db_connections, some_paramspecs):
"""
Test the atomicity of the transaction by extracting and inserting two
runs where the second one is not completed. The not completed error must
roll back any changes to the target
"""
source_conn, target_conn = two_empty_temp_db_connections
source_path = path_to_dbfile(source_conn)
target_path = path_to_dbfile(target_conn)
# The target file must exist for us to be able to see whether it has
# changed
Path(target_path).touch()
source_exp = Experiment(conn=source_conn)
source_ds_1 = DataSet(conn=source_conn, exp_id=source_exp.exp_id)
for ps in some_paramspecs[2].values():
source_ds_1.add_parameter(ps)
source_ds_1.mark_started()
source_ds_1.add_result(
{ps.name: 2.1
for ps in some_paramspecs[2].values()})
source_ds_1.mark_completed()
source_ds_2 = DataSet(conn=source_conn, exp_id=source_exp.exp_id)
for ps in some_paramspecs[2].values():
source_ds_2.add_parameter(ps)
source_ds_2.mark_started()
source_ds_2.add_result(
{ps.name: 2.1
for ps in some_paramspecs[2].values()})
# This dataset is NOT marked as completed
# now check that the target file is untouched
with raise_if_file_changed(target_path):
# although the not completed error is a ValueError, we get the
# RuntimeError from SQLite
with pytest.raises(RuntimeError):
extract_runs_into_db(source_path, target_path, 1, 2)
def test_load_by_X_functions(two_empty_temp_db_connections,
some_interdeps):
"""
Test some different loading functions
"""
source_conn, target_conn = two_empty_temp_db_connections
source_path = path_to_dbfile(source_conn)
target_path = path_to_dbfile(target_conn)
source_exp1 = Experiment(conn=source_conn)
source_ds_1_1 = DataSet(conn=source_conn, exp_id=source_exp1.exp_id)
source_exp2 = Experiment(conn=source_conn)
source_ds_2_1 = DataSet(conn=source_conn, exp_id=source_exp2.exp_id)
source_ds_2_2 = DataSet(conn=source_conn,
exp_id=source_exp2.exp_id,
name="customname")
for ds in (source_ds_1_1, source_ds_2_1, source_ds_2_2):
ds.set_interdependencies(some_interdeps[1])
ds.mark_started()
ds.add_results([{name: 0.0 for name in some_interdeps[1].names}])
ds.mark_completed()
extract_runs_into_db(source_path, target_path, source_ds_2_2.run_id)
extract_runs_into_db(source_path, target_path, source_ds_2_1.run_id)
extract_runs_into_db(source_path, target_path, source_ds_1_1.run_id)
test_ds = load_by_guid(source_ds_2_2.guid, target_conn)
assert source_ds_2_2.the_same_dataset_as(test_ds)
test_ds = load_by_id(1, target_conn)
assert source_ds_2_2.the_same_dataset_as(test_ds)
test_ds = load_by_run_spec(captured_run_id=source_ds_2_2.captured_run_id,
conn=target_conn)
assert source_ds_2_2.the_same_dataset_as(test_ds)
assert source_exp2.exp_id == 2
# this is now the first run in the db so run_id is 1
target_run_id = 1
# and the experiment ids will be interchanged.
target_exp_id = 1
test_ds = load_by_counter(target_run_id, target_exp_id, target_conn)
assert source_ds_2_2.the_same_dataset_as(test_ds)
def test_basic_extraction(two_empty_temp_db_connections, some_paramspecs):
source_conn, target_conn = two_empty_temp_db_connections
source_path = path_to_dbfile(source_conn)
target_path = path_to_dbfile(target_conn)
type_casters = {'numeric': float,
'array': (lambda x: np.array(x) if hasattr(x, '__iter__')
else np.array([x])),
'text': str}
source_exp = Experiment(conn=source_conn)
source_dataset = DataSet(conn=source_conn, name="basic_copy_paste_name")
with pytest.raises(RuntimeError) as excinfo:
extract_runs_into_db(source_path, target_path, source_dataset.run_id)
assert error_caused_by(excinfo, ('Dataset not completed. An incomplete '
'dataset can not be copied. The '
'incomplete dataset has GUID: '
f'{source_dataset.guid} and run_id: '
f'{source_dataset.run_id}'))
for ps in some_paramspecs[1].values():
source_dataset.add_parameter(ps)
for value in range(10):
result = {ps.name: type_casters[ps.type](value)
for ps in some_paramspecs[1].values()}
source_dataset.add_result(result)
source_dataset.add_metadata('goodness', 'fair')
source_dataset.add_metadata('test', True)
source_dataset.mark_complete()
extract_runs_into_db(source_path, target_path, source_dataset.run_id)
target_exp = Experiment(conn=target_conn, exp_id=1)
length1 = len(target_exp)
assert length1 == 1
# trying to insert the same run again should be a NOOP
with raise_if_file_changed(target_path):
extract_runs_into_db(source_path, target_path, source_dataset.run_id)
assert len(target_exp) == length1
target_dataset = DataSet(conn=target_conn, run_id=1)
# Now make the interesting comparisons: are the target objects the same as
# the source objects?
assert source_dataset.the_same_dataset_as(target_dataset)
source_data = source_dataset.get_data(*source_dataset.parameters.split(','))
target_data = target_dataset.get_data(*target_dataset.parameters.split(','))
assert source_data == target_data
exp_attrs = ['name', 'sample_name', 'format_string', 'started_at',
'finished_at']
for exp_attr in exp_attrs:
assert getattr(source_exp, exp_attr) == getattr(target_exp, exp_attr)
# trying to insert the same run again should be a NOOP
with raise_if_file_changed(target_path):
extract_runs_into_db(source_path, target_path, source_dataset.run_id)
def test_correct_experiment_routing(two_empty_temp_db_connections,
some_paramspecs):
"""
Test that existing experiments are correctly identified AND that multiple
insertions of the same runs don't matter (run insertion is idempotent)
"""
source_conn, target_conn = two_empty_temp_db_connections
source_exp_1 = Experiment(conn=source_conn)
# make 5 runs in first experiment
exp_1_run_ids = []
for _ in range(5):
source_dataset = DataSet(conn=source_conn, exp_id=source_exp_1.exp_id)
exp_1_run_ids.append(source_dataset.run_id)
for ps in some_paramspecs[2].values():
source_dataset.add_parameter(ps)
for val in range(10):
source_dataset.add_result({ps.name: val
for ps in some_paramspecs[2].values()})
source_dataset.mark_complete()
# make a new experiment with 1 run
source_exp_2 = Experiment(conn=source_conn)
ds = DataSet(conn=source_conn, exp_id=source_exp_2.exp_id, name="lala")
exp_2_run_ids = [ds.run_id]
for ps in some_paramspecs[2].values():
ds.add_parameter(ps)
for val in range(10):
ds.add_result({ps.name: val for ps in some_paramspecs[2].values()})
ds.mark_complete()
source_path = path_to_dbfile(source_conn)
target_path = path_to_dbfile(target_conn)
# now copy 2 runs
extract_runs_into_db(source_path, target_path, *exp_1_run_ids[:2])
target_exp1 = Experiment(conn=target_conn, exp_id=1)
assert len(target_exp1) == 2
# copy two other runs, one of them already in
extract_runs_into_db(source_path, target_path, *exp_1_run_ids[1:3])
assert len(target_exp1) == 3
# insert run from different experiment
extract_runs_into_db(source_path, target_path, ds.run_id)
assert len(target_exp1) == 3
target_exp2 = Experiment(conn=target_conn, exp_id=2)
assert len(target_exp2) == 1
# finally insert every single run from experiment 1
extract_runs_into_db(source_path, target_path, *exp_1_run_ids)
# check for idempotency once more by inserting all the runs but in another
# order
with raise_if_file_changed(target_path):
extract_runs_into_db(source_path, target_path, *exp_1_run_ids[::-1])
target_exps = get_experiments(target_conn)
assert len(target_exps) == 2
assert len(target_exp1) == 5
assert len(target_exp2) == 1
# check that all the datasets match up
for run_id in exp_1_run_ids + exp_2_run_ids:
source_ds = DataSet(conn=source_conn, run_id=run_id)
target_ds = load_by_guid(guid=source_ds.guid, conn=target_conn)
assert source_ds.the_same_dataset_as(target_ds)
source_data = source_ds.get_data(*source_ds.parameters.split(','))
target_data = target_ds.get_data(*target_ds.parameters.split(','))
assert source_data == target_data
def test_combine_runs(two_empty_temp_db_connections, empty_temp_db_connection,
some_interdeps):
"""
Test that datasets that are exported in random order from 2 datasets
can be reloaded by the original captured_run_id and the experiment
name.
"""
source_conn_1, source_conn_2 = two_empty_temp_db_connections
target_conn = empty_temp_db_connection
source_1_exp = Experiment(conn=source_conn_1,
name='exp1',
sample_name='no_sample')
source_1_datasets = [
DataSet(conn=source_conn_1, exp_id=source_1_exp.exp_id)
for i in range(10)
]
source_2_exp = Experiment(conn=source_conn_2,
name='exp2',
sample_name='no_sample')
source_2_datasets = [
DataSet(conn=source_conn_2, exp_id=source_2_exp.exp_id)
for i in range(10)
]
source_all_datasets = source_1_datasets + source_2_datasets
shuffled_datasets = source_all_datasets.copy()
random.shuffle(shuffled_datasets)
for ds in source_all_datasets:
ds.set_interdependencies(some_interdeps[1])
ds.mark_started()
ds.add_results([{name: 0.0 for name in some_interdeps[1].names}])
ds.mark_completed()
# now let's insert all datasets in random order
for ds in shuffled_datasets:
extract_runs_into_db(ds.conn.path_to_dbfile,
target_conn.path_to_dbfile, ds.run_id)
for ds in source_all_datasets:
loaded_ds = load_by_run_spec(captured_run_id=ds.captured_run_id,
experiment_name=ds.exp_name,
conn=target_conn)
assert ds.the_same_dataset_as(loaded_ds)
for ds in source_all_datasets:
loaded_ds = load_by_run_spec(captured_run_id=ds.captured_counter,
experiment_name=ds.exp_name,
conn=target_conn)
assert ds.the_same_dataset_as(loaded_ds)
# Now test that we generate the correct table for the guids above
# this could be split out into its own test
# but the test above has the useful side effect of
# setting up datasets for this test.
guids = [ds.guid for ds in source_all_datasets]
table = generate_dataset_table(guids, conn=target_conn)
lines = table.split('\n')
headers = re.split(r'\s+', lines[0].strip())
cfg = qc.config
guid_comp = cfg['GUID_components']
# borrowed fallback logic from generate_guid
sampleint = guid_comp['sample']
if sampleint == 0:
sampleint = int('a' * 8, base=16)
for i in range(2, len(lines)):
split_line = re.split(r'\s+', lines[i].strip())
mydict = {headers[j]: split_line[j] for j in range(len(split_line))}
ds = load_by_guid(guids[i - 2], conn=target_conn)
assert ds.captured_run_id == int(mydict['captured_run_id'])
assert ds.captured_counter == int(mydict['captured_counter'])
assert ds.exp_name == mydict['experiment_name']
assert ds.sample_name == mydict['sample_name']
assert int(mydict['sample_id']) == sampleint
assert guid_comp['location'] == int(mydict['location'])
assert guid_comp['work_station'] == int(mydict['work_station'])
def test_copy_datasets_and_add_new(two_empty_temp_db_connections,
some_interdeps):
"""
Test that new runs get the correct captured_run_id and captured_counter
when adding on top of a dataset with partial exports
"""
source_conn, target_conn = two_empty_temp_db_connections
source_exp_1 = Experiment(conn=source_conn,
name='exp1',
sample_name='no_sample')
source_exp_2 = Experiment(conn=source_conn,
name='exp2',
sample_name='no_sample')
source_datasets_1 = [
DataSet(conn=source_conn, exp_id=source_exp_1.exp_id) for i in range(5)
]
source_datasets_2 = [
DataSet(conn=source_conn, exp_id=source_exp_2.exp_id) for i in range(5)
]
source_datasets = source_datasets_1 + source_datasets_2
for ds in source_datasets:
ds.set_interdependencies(some_interdeps[1])
ds.mark_started()
ds.add_results([{name: 0.0 for name in some_interdeps[1].names}])
ds.mark_completed()
# now let's insert only some of the datasets
# and verify that the ids and counters are set correctly
for ds in source_datasets[-3:]:
extract_runs_into_db(ds.conn.path_to_dbfile,
target_conn.path_to_dbfile, ds.run_id)
loaded_datasets = [
load_by_run_spec(captured_run_id=i, conn=target_conn)
for i in range(8, 11)
]
expected_run_ids = [1, 2, 3]
expected_captured_run_ids = [8, 9, 10]
expected_counter = [1, 2, 3]
expected_captured_counter = [3, 4, 5]
for ds, eri, ecri, ec, ecc in zip(loaded_datasets, expected_run_ids,
expected_captured_run_ids,
expected_counter,
expected_captured_counter):
assert ds.run_id == eri
assert ds.captured_run_id == ecri
assert ds.counter == ec
assert ds.captured_counter == ecc
exp = load_experiment_by_name('exp2', conn=target_conn)
# add additional runs and verify that the ids and counters increase as
# expected
new_datasets = [
DataSet(conn=target_conn, exp_id=exp.exp_id) for i in range(3)
]
for ds in new_datasets:
ds.set_interdependencies(some_interdeps[1])
ds.mark_started()
ds.add_results([{name: 0.0 for name in some_interdeps[1].names}])
ds.mark_completed()
expected_run_ids = [4, 5, 6]
expected_captured_run_ids = [11, 12, 13]
expected_counter = [4, 5, 6]
expected_captured_counter = [6, 7, 8]
for ds, eri, ecri, ec, ecc in zip(new_datasets, expected_run_ids,
expected_captured_run_ids,
expected_counter,
expected_captured_counter):
assert ds.run_id == eri
assert ds.captured_run_id == ecri
assert ds.counter == ec
assert ds.captured_counter == ecc