def snapshot_raw(self) -> Optional[str]:
"""Snapshot of the run as a JSON-formatted string (or None)"""
if is_column_in_table(self.conn, "runs", "snapshot"):
return select_one_where(self.conn, "runs", "snapshot", "run_id",
self.run_id)
else:
return None
def test_perform_actual_upgrade_4_to_5(db_file):
v4fixpath = os.path.join(fixturepath, 'db_files', 'version4')
db_file += '.db'
dbname_old = os.path.join(v4fixpath, db_file)
if not os.path.exists(dbname_old):
pytest.skip("No db-file fixtures found. You can generate test db-files"
" using the scripts in the "
"https://github.com/QCoDeS/qcodes_generate_test_db/ repo")
with temporarily_copied_DB(dbname_old, debug=False, version=4) as conn:
# firstly, assert the situation with 'snapshot' column of 'runs' table
if 'with_runs_and_snapshots' in db_file:
assert is_column_in_table(conn, 'runs', 'snapshot')
else:
assert not is_column_in_table(conn, 'runs', 'snapshot')
# secondly, perform the upgrade
perform_db_upgrade_4_to_5(conn)
# finally, assert the 'snapshot' column exists in 'runs' table
assert is_column_in_table(conn, 'runs', 'snapshot')
def test_column_in_table(dataset):
assert mut.is_column_in_table(dataset.conn, "runs", "run_id")
assert not mut.is_column_in_table(dataset.conn, "runs",
"non-existing-column")
def generate_DB_file_with_runs_and_snapshots():
"""
Generate a .db-file with a handful of runs some of which have snapshots.
Generated runs:
#1: run with a snapshot that has some content
#2: run with a snapshot of an empty station
#3: run without a snapshot
"""
v4fixturepath = os.path.join(utils.fixturepath, 'version4')
os.makedirs(v4fixturepath, exist_ok=True)
path = os.path.join(v4fixturepath, 'with_runs_and_snapshots.db')
if os.path.exists(path):
os.remove(path)
from qcodes.dataset.sqlite_base import is_column_in_table
from qcodes.dataset.measurements import Measurement
from qcodes.dataset.experiment_container import Experiment
from qcodes import Parameter, Station
from qcodes.dataset.descriptions import RunDescriber
from qcodes.dataset.dependencies import InterDependencies
exp = Experiment(path_to_db=path,
name='experiment_1',
sample_name='no_sample_1')
conn = exp.conn
# Now make some parameters to use in measurements
params = []
for n in range(4):
params.append(Parameter(f'p{n}', label=f'Parameter {n}',
unit=f'unit {n}', set_cmd=None, get_cmd=None))
# We are going to make 3 runs
run_ids = []
# Make a run with a snapshot with some content
full_station = Station(*params[0:1], default=False)
assert Station.default is None
meas = Measurement(exp, full_station)
meas.register_parameter(params[0])
meas.register_parameter(params[1])
meas.register_parameter(params[2], basis=(params[1],))
meas.register_parameter(params[3], setpoints=(params[1], params[2]))
with meas.run() as datasaver:
for x in np.random.rand(4):
for y in np.random.rand(4):
z = np.random.rand()
datasaver.add_result((params[1], x),
(params[2], y),
(params[3], z))
run_ids.append(datasaver.run_id)
# Make a run with a snapshot of empty station
empty_station = Station(default=False)
assert Station.default is None
meas = Measurement(exp, empty_station)
meas.register_parameter(params[0])
meas.register_parameter(params[1])
meas.register_parameter(params[2])
meas.register_parameter(params[3], setpoints=(params[1], params[2]))
with meas.run() as datasaver:
for x in np.random.rand(4):
for y in np.random.rand(4):
z = np.random.rand()
datasaver.add_result((params[1], x),
(params[2], y),
(params[3], z))
run_ids.append(datasaver.run_id)
# Make a run without a snapshot (i.e. station is None)
assert Station.default is None
meas = Measurement(exp)
meas.register_parameter(params[0])
meas.register_parameter(params[1])
meas.register_parameter(params[2], basis=(params[1],))
meas.register_parameter(params[3], setpoints=(params[1], params[2]))
with meas.run() as datasaver:
for x in np.random.rand(4):
for y in np.random.rand(4):
z = np.random.rand()
datasaver.add_result((params[1], x),
(params[2], y),
(params[3], z))
run_ids.append(datasaver.run_id)
# Check correctness of run_id's
assert [1, 2, 3] == run_ids, 'Run ids of generated runs are not as ' \
'expected after generating runs #1-3'
# Ensure snapshot column
assert is_column_in_table(conn, 'runs', 'snapshot')
def generate_DB_file_with_runs_but_no_snapshots():
"""
Generate a .db-file with a handful of runs without snapshots
"""
# This function will run often on CI and re-generate the .db-files
# That should ideally be a deterministic action
# (although this hopefully plays no role)
np.random.seed(0)
v4fixturepath = os.path.join(utils.fixturepath, 'version4')
os.makedirs(v4fixturepath, exist_ok=True)
path = os.path.join(v4fixturepath, 'with_runs_but_no_snapshots.db')
if os.path.exists(path):
os.remove(path)
from qcodes.dataset.sqlite_base import connect, is_column_in_table
from qcodes.dataset.measurements import Measurement
from qcodes.dataset.experiment_container import Experiment
from qcodes import Parameter, Station
connect(path)
exp = Experiment(path_to_db=path,
name='experiment_1',
sample_name='no_sample_1')
conn = exp.conn
assert not is_column_in_table(conn, 'runs', 'snapshot')
# Now make some parameters to use in measurements
params = []
for n in range(4):
params.append(Parameter(f'p{n}', label=f'Parameter {n}',
unit=f'unit {n}', set_cmd=None, get_cmd=None))
assert Station.default is None
# Set up an experiment
meas = Measurement(exp)
meas.register_parameter(params[0])
meas.register_parameter(params[1])
meas.register_parameter(params[2], basis=(params[1],))
meas.register_parameter(params[3], setpoints=(params[1], params[2]))
# Make a number of identical runs
for _ in range(4):
with meas.run() as datasaver:
for x in np.random.rand(4):
for y in np.random.rand(4):
z = np.random.rand()
datasaver.add_result((params[1], x),
(params[2], y),
(params[3], z))
assert not is_column_in_table(conn, 'runs', 'snapshot')