def test_add_sharded_dataset(self):
reaction = reaction_pb2.Reaction()
ethylamine = reaction.inputs['ethylamine']
component = ethylamine.components.add()
component.identifiers.add(type='SMILES', value='CCN')
component.is_limiting = True
component.amount.moles.value = 2
component.amount.moles.units = reaction_pb2.Moles.MILLIMOLE
reaction.outcomes.add().conversion.value = 25
reaction.provenance.record_created.time.value = '2020-01-02'
reaction.provenance.record_created.person.username = '******'
reaction.provenance.record_created.person.email = '*****@*****.**'
reaction.reaction_id = 'test1'
dataset1 = dataset_pb2.Dataset(reactions=[reaction])
dataset1_filename = os.path.join(self.test_subdirectory, 'test1.pbtxt')
message_helpers.write_message(dataset1, dataset1_filename)
reaction.provenance.record_created.time.value = '2020-01-03'
reaction.provenance.record_created.person.username = '******'
reaction.provenance.record_created.person.email = '*****@*****.**'
reaction.reaction_id = 'test2'
dataset2 = dataset_pb2.Dataset(reactions=[reaction])
dataset2_filename = os.path.join(self.test_subdirectory, 'test2.pbtxt')
message_helpers.write_message(dataset2, dataset2_filename)
added, removed, changed, filenames = self._run()
self.assertEqual(added, {'test1', 'test2'})
self.assertEmpty(removed)
self.assertEmpty(changed)
self.assertLen(filenames, 2)
filenames.pop(filenames.index(self.dataset_filename))
self.assertLen(filenames, 1)
dataset = message_helpers.load_message(filenames[0],
dataset_pb2.Dataset)
self.assertLen(dataset.reactions, 2)
self.assertFalse(os.path.exists(dataset1_filename))
self.assertFalse(os.path.exists(dataset2_filename))
def setUp(self):
super().setUp()
# Suppress RDKit warnings to clean up the test output.
RDLogger.logger().setLevel(RDLogger.CRITICAL)
self.test_subdirectory = tempfile.mkdtemp(dir=flags.FLAGS.test_tmpdir)
reaction1 = reaction_pb2.Reaction()
dummy_input = reaction1.inputs['dummy_input']
dummy_component = dummy_input.components.add()
dummy_component.identifiers.add(type='CUSTOM')
dummy_component.identifiers[0].details = 'custom_identifier'
dummy_component.identifiers[0].value = 'custom_value'
dummy_component.is_limiting = reaction_pb2.Boolean.TRUE
dummy_component.mass.value = 1
dummy_component.mass.units = reaction_pb2.Mass.GRAM
reaction1.outcomes.add().conversion.value = 75
dataset1 = dataset_pb2.Dataset(reactions=[reaction1])
self.dataset1_filename = os.path.join(self.test_subdirectory,
'dataset1.pbtxt')
message_helpers.write_message(dataset1, self.dataset1_filename)
# reaction2 is empty.
reaction2 = reaction_pb2.Reaction()
dataset2 = dataset_pb2.Dataset(reactions=[reaction1, reaction2])
self.dataset2_filename = os.path.join(self.test_subdirectory,
'dataset2.pbtxt')
message_helpers.write_message(dataset2, self.dataset2_filename)
def setUp(self):
super().setUp()
self.test_subdirectory = tempfile.mkdtemp(dir=flags.FLAGS.test_tmpdir)
reaction1 = reaction_pb2.Reaction()
dummy_input = reaction1.inputs['dummy_input']
dummy_component = dummy_input.components.add()
dummy_component.identifiers.add(type='CUSTOM')
dummy_component.identifiers[0].details = 'custom_identifier'
dummy_component.identifiers[0].value = 'custom_value'
dummy_component.is_limiting = True
dummy_component.mass.value = 1
dummy_component.mass.units = reaction_pb2.Mass.GRAM
reaction1.outcomes.add().conversion.value = 75
dataset1 = dataset_pb2.Dataset(reactions=[reaction1])
self.dataset1_filename = os.path.join(self.test_subdirectory,
'dataset1.pb')
with open(self.dataset1_filename, 'wb') as f:
f.write(dataset1.SerializeToString())
# reaction2 is empty.
reaction2 = reaction_pb2.Reaction()
dataset2 = dataset_pb2.Dataset(reactions=[reaction1, reaction2])
self.dataset2_filename = os.path.join(self.test_subdirectory,
'dataset2.pb')
with open(self.dataset2_filename, 'wb') as f:
f.write(dataset2.SerializeToString())
def write_dataset(file_name):
"""Receives a serialized Dataset protobuf and write it to a file."""
dataset = dataset_pb2.Dataset()
dataset.ParseFromString(flask.request.get_data())
resolve_tokens(dataset)
put_dataset(file_name, dataset)
return 'ok'
def test_add_dataset_with_large_data(self):
reaction = reaction_pb2.Reaction()
ethylamine = reaction.inputs['ethylamine']
component = ethylamine.components.add()
component.identifiers.add(type='SMILES', value='CCN')
component.is_limiting = reaction_pb2.Boolean.TRUE
component.moles.value = 2
component.moles.units = reaction_pb2.Moles.MILLIMOLE
reaction.outcomes.add().conversion.value = 25
image = reaction.observations.add().image
image.bytes_value = b'test data value'
image.format = 'png'
dataset = dataset_pb2.Dataset(reactions=[reaction])
dataset_filename = os.path.join(self.test_subdirectory, 'test.pbtxt')
message_helpers.write_message(dataset, dataset_filename)
filenames = self._run_main(min_size=0.0)
self.assertLen(filenames, 2)
filenames.pop(filenames.index(self.dataset_filename))
dataset = message_helpers.load_message(filenames[0],
dataset_pb2.Dataset)
relative_path = (
'data/36/ord_data-'
'36443a1839bf1160087422b7468a93c7b97dac7eea423bfac189208a15823139'
'.png')
expected = ('https://github.com/Open-Reaction-Database/'
'ord-submissions-test/tree/' + relative_path)
self.assertEqual(dataset.reactions[0].observations[0].image.url,
expected)
with open(os.path.join(self.test_subdirectory, relative_path),
'rb') as f:
self.assertEqual(b'test data value', f.read())
def test_add_dataset(self):
reaction = reaction_pb2.Reaction()
ethylamine = reaction.inputs['ethylamine']
component = ethylamine.components.add()
component.identifiers.add(type='SMILES', value='CCN')
component.is_limiting = True
component.amount.moles.value = 2
component.amount.moles.units = reaction_pb2.Moles.MILLIMOLE
reaction.outcomes.add().conversion.value = 25
reaction.provenance.record_created.time.value = '2020-01-01'
reaction.provenance.record_created.person.username = '******'
reaction.provenance.record_created.person.email = '*****@*****.**'
reaction.reaction_id = 'test'
dataset = dataset_pb2.Dataset(reactions=[reaction])
dataset_filename = os.path.join(self.test_subdirectory, 'test.pbtxt')
message_helpers.write_message(dataset, dataset_filename)
added, removed, changed, filenames = self._run()
self.assertEqual(added, {'test'})
self.assertEmpty(removed)
self.assertEmpty(changed)
self.assertLen(filenames, 2)
self.assertFalse(os.path.exists(dataset_filename))
# Check for assignment of dataset and reaction IDs.
filenames.pop(filenames.index(self.dataset_filename))
self.assertLen(filenames, 1)
dataset = message_helpers.load_message(filenames[0],
dataset_pb2.Dataset)
self.assertNotEmpty(dataset.dataset_id)
self.assertLen(dataset.reactions, 1)
self.assertNotEmpty(dataset.reactions[0].reaction_id)
# Check for binary output.
root, ext = os.path.splitext(filenames[0])
self.assertEqual(ext, '.pbtxt')
self.assertTrue(os.path.exists(root + '.pb'))
def test_valid_templating(self):
template_string = self.template_string.replace('value: "CCO"',
'value: "$my_smiles$"')
template_string = template_string.replace('value: 75',
'value: $conversion$')
df = pd.DataFrame.from_dict({
'$my_smiles$': ['CCO', 'CCCO', 'CCCCO'],
'$conversion$': [75, 50, 30],
})
dataset = templating.generate_dataset(template_string, df)
expected_reactions = []
for smiles, conversion in zip(['CCO', 'CCCO', 'CCCCO'], [75, 50, 30]):
reaction = reaction_pb2.Reaction()
reaction.CopyFrom(self.valid_reaction)
reaction.inputs['in'].components[0].identifiers[0].value = smiles
reaction.outcomes[0].conversion.value = conversion
expected_reactions.append(reaction)
expected_dataset = dataset_pb2.Dataset(reactions=expected_reactions)
self.assertEqual(dataset, expected_dataset)
# Test without "$" in column names
df = pd.DataFrame.from_dict({
'my_smiles': ['CCO', 'CCCO', 'CCCCO'],
'conversion': [75, 50, 30],
})
dataset = templating.generate_dataset(template_string, df)
self.assertEqual(dataset, expected_dataset)
def test_crossferences(self):
message = dataset_pb2.Dataset()
reaction1 = message.reactions.add()
reaction2 = message.reactions.add()
reaction3 = message.reactions.add()
# Minimal reaction 1
dummy_input = reaction1.inputs['dummy_input']
reaction1.outcomes.add()
dummy_component = dummy_input.components.add()
dummy_component.identifiers.add(type='CUSTOM')
dummy_component.identifiers[0].details = 'custom_identifier'
dummy_component.identifiers[0].value = 'custom_value'
dummy_component.amount.mass.value = 1
dummy_component.amount.mass.units = reaction_pb2.Mass.GRAM
reaction2.CopyFrom(reaction1)
reaction3.CopyFrom(reaction1)
dummy_component.preparations.add(type='SYNTHESIZED')
dummy_component.preparations[0].reaction_id = 'placeholder_id'
reaction2.reaction_id = 'placeholder_id'
dummy_input.crude_components.add(reaction_id='crude-making step',
has_derived_amount=True)
reaction3.reaction_id = 'crude-making step'
updates.update_dataset(message)
self.assertEqual(dummy_component.preparations[0].reaction_id,
reaction2.reaction_id)
self.assertEqual(dummy_input.crude_components[0].reaction_id,
reaction3.reaction_id)
self.assertNotEqual(dummy_component.preparations[0].reaction_id,
'placeholder_id')
self.assertNotEqual(dummy_input.crude_components[0].reaction_id,
'crude-making step')
def test_resolver(self):
reaction = reaction_pb2.Reaction()
ethylamine = reaction.inputs['ethylamine']
component = ethylamine.components.add()
component.identifiers.add(type='NAME', value='ethylamine')
component.is_limiting = True
component.moles.value = 2
component.moles.units = reaction_pb2.Moles.MILLIMOLE
reaction.outcomes.add().conversion.value = 25
dataset = dataset_pb2.Dataset(reactions=[reaction])
dataset_filename = os.path.join(self.test_subdirectory, 'test.pbtxt')
message_helpers.write_message(dataset, dataset_filename)
filenames = self._run_main()
self.assertLen(filenames, 2)
self.assertFalse(os.path.exists(dataset_filename))
filenames.pop(filenames.index(self.dataset_filename))
self.assertLen(filenames, 1)
dataset = message_helpers.load_message(filenames[0],
dataset_pb2.Dataset)
self.assertLen(dataset.reactions, 1)
identifiers = (dataset.reactions[0].inputs['ethylamine'].components[0].
identifiers)
self.assertLen(identifiers, 3)
self.assertEqual(
identifiers[1],
reaction_pb2.CompoundIdentifier(
type='SMILES', value='CCN',
details='NAME resolved by PubChem'))
self.assertEqual(identifiers[2].type,
reaction_pb2.CompoundIdentifier.RDKIT_BINARY)
def dataset_filename(tmp_path) -> str:
# Create a test database.
connection = connect(ord_interface.client.POSTGRES_DB)
connection.set_session(autocommit=True)
with connection.cursor() as cursor:
cursor.execute("CREATE DATABASE test;")
connection.close()
# Create a test dataset.
reaction = reaction_pb2.Reaction()
reaction.reaction_id = "test"
reaction.identifiers.add(value="reaction", type="REACTION_SMILES")
input1 = reaction.inputs["input1"]
input1.components.add().identifiers.add(value="input1", type="SMILES")
input2 = reaction.inputs["input2"]
input2.components.add().identifiers.add(value="input2a", type="SMILES")
input2.components.add().identifiers.add(value="input2b", type="SMILES")
outcome = reaction.outcomes.add()
product = outcome.products.add()
product.measurements.add(type="YIELD", percentage={"value": 2.5})
product.identifiers.add(value="product", type="SMILES")
reaction.provenance.doi = "10.0000/test.foo"
dataset = dataset_pb2.Dataset(dataset_id="test_dataset", reactions=[reaction])
dataset_filename = (tmp_path / "test.pb").as_posix()
message_helpers.write_message(dataset, dataset_filename)
yield dataset_filename
# Remove the test database.
connection = connect(ord_interface.client.POSTGRES_DB)
connection.set_session(autocommit=True)
with connection.cursor() as cursor:
cursor.execute("DROP DATABASE test;")
connection.close()
def sync_reviews():
"""Import all current pull requests into the datasets table.
These datasets have two extra pieces of metadata: a GitHub PR number and
the PR title text. These are encoded into the dataset name in Postgres
using delimiters."""
if flask.g.user_id != REVIEWER:
return flask.redirect('/')
client = github.Github()
repo = client.get_repo('Open-Reaction-Database/ord-data')
user_id = flask.g.user_id
with flask.g.db.cursor() as cursor:
# First reset all datasets under review.
query = psycopg2.sql.SQL('DELETE FROM datasets WHERE user_id=%s')
cursor.execute(query, [REVIEWER])
# Then import all datasets from open PR's.
for pr in repo.get_pulls():
for remote in pr.get_files():
response = requests.get(remote.raw_url)
if remote.filename.endswith('.pbtxt'):
dataset = dataset_pb2.Dataset()
text_format.Parse(response.text, dataset)
elif remote.filename.endswith('.pb'):
dataset = dataset_pb2.Dataset.FromString(response.content)
else:
continue
name = 'PR_%d ___%s___ %s' % (pr.number, pr.title,
remote.filename[:-6])
query = psycopg2.sql.SQL(
'INSERT INTO datasets VALUES (%s, %s, %s)')
cursor.execute(
query,
[user_id, name, serialize_for_db(dataset)])
flask.g.db.commit()
return flask.redirect('/review')
def write_dataset(name):
"""Inserts a protobuf including upload tokens into the datasets table."""
dataset = dataset_pb2.Dataset()
dataset.ParseFromString(flask.request.get_data())
resolve_tokens(dataset)
put_dataset(name, dataset)
return 'ok'
def test_add_dataset_with_existing_reaction_ids(self):
reaction = reaction_pb2.Reaction()
ethylamine = reaction.inputs['ethylamine']
component = ethylamine.components.add()
component.identifiers.add(type='SMILES', value='CCN')
component.is_limiting = reaction_pb2.Boolean.TRUE
component.moles.value = 2
component.moles.units = reaction_pb2.Moles.MILLIMOLE
reaction.outcomes.add().conversion.value = 25
reaction_id = 'ord-10aed8b5dffe41fab09f5b2cc9c58ad9'
reaction.reaction_id = reaction_id
reaction.provenance.record_created.time.value = '2020-01-01 11 am'
dataset = dataset_pb2.Dataset(reactions=[reaction])
dataset_filename = os.path.join(self.test_subdirectory, 'test.pbtxt')
message_helpers.write_message(dataset, dataset_filename)
filenames = self._run_main()
self.assertLen(filenames, 2)
self.assertFalse(os.path.exists(dataset_filename))
filenames.pop(filenames.index(self.dataset_filename))
self.assertLen(filenames, 1)
dataset = message_helpers.load_message(filenames[0],
dataset_pb2.Dataset)
# Check that existing record IDs for added datasets are not overridden.
self.assertEqual(dataset.reactions[0].reaction_id, reaction_id)
self.assertLen(dataset.reactions[0].provenance.record_modified, 0)
def setUp(self):
super().setUp()
self.test_subdirectory = tempfile.mkdtemp(dir=flags.FLAGS.test_tmpdir)
os.chdir(self.test_subdirectory)
subprocess.run(['git', 'init'], check=True)
subprocess.run(
['git', 'config', '--local', 'user.email', 'test@ord-schema'],
check=True)
subprocess.run(
['git', 'config', '--local', 'user.name', 'Test Runner'],
check=True)
# Add some initial data.
reaction = reaction_pb2.Reaction()
methylamine = reaction.inputs['methylamine']
component = methylamine.components.add()
component.identifiers.add(type='SMILES', value='CN')
component.is_limiting = reaction_pb2.Boolean.TRUE
component.moles.value = 1
component.moles.units = reaction_pb2.Moles.MILLIMOLE
reaction.outcomes.add().conversion.value = 75
reaction.provenance.record_created.time.value = '2020-01-01'
reaction.reaction_id = 'ord-10aed8b5dffe41fab09f5b2cc9c58ad9'
dataset_id = 'ord_dataset-64b14868c5cd46dd8e75560fd3589a6b'
dataset = dataset_pb2.Dataset(reactions=[reaction],
dataset_id=dataset_id)
# Make sure the initial dataset is valid.
validations.validate_message(dataset)
os.makedirs(os.path.join('data', '64'))
self.dataset_filename = os.path.join(self.test_subdirectory, 'data',
'64', f'{dataset_id}.pbtxt')
message_helpers.write_message(dataset, self.dataset_filename)
subprocess.run(['git', 'add', 'data'], check=True)
subprocess.run(['git', 'commit', '-m', 'Initial commit'], check=True)
def init_db():
"""Ensures the db/ directory exists and contains at least one Dataset."""
if not os.path.isdir('db'):
os.mkdir('db')
if os.listdir('db'):
return
dataset = dataset_pb2.Dataset()
put_dataset('dataset', dataset)
def test_main_pass(self):
dataset = dataset_pb2.Dataset()
reaction = dataset.reactions.add()
component = reaction.inputs['test'].components.add()
component.identifiers.add(value='c1ccccc1', type='SMILES')
message_helpers.write_message(dataset, self.pb_filename)
message_helpers.write_message(dataset, self.pbtxt_filename)
self._run()
def _download_dataset(self, name):
"""Downloads an existing dataset."""
response = self.client.get(f'/dataset/{name}/download',
follow_redirects=True)
self.assertEqual(response.status_code, 200)
dataset = dataset_pb2.Dataset()
text_format.Parse(response.data, dataset)
return dataset
def test_delete_reaction_id_blank(self):
name = 'test'
dataset = dataset_pb2.Dataset(reaction_ids=['', 'test', ''])
self._upload_dataset(dataset, name)
response = self.client.get(f'/dataset/{name}/delete/reaction_id',
follow_redirects=True)
self.assertEqual(response.status_code, 200)
downloaded_dataset = self._download_dataset(name)
self.assertLen(downloaded_dataset.reaction_ids, 2)
def _get_dataset() -> dataset_pb2.Dataset:
"""Returns a Dataset for testing."""
dataset = dataset_pb2.Dataset()
with open(os.path.join(TESTDATA, "nielsen_fig1_dataset.pbtxt"), "rt") as f:
text_format.Parse(f.read(), dataset)
# Add some unicode to check for encoding/decoding robustness.
# From https://en.wikipedia.org/wiki/Atlantis.
dataset.reactions[0].provenance.city = "Ἀτλαντὶς νῆσος"
return dataset
def test_read_dataset(client):
name = "test"
dataset = _get_dataset()
_upload_dataset(client, dataset, name)
response = client.get(f"/dataset/proto/read/{name}", follow_redirects=True)
assert response.status_code == 200
downloaded_dataset = dataset_pb2.Dataset()
downloaded_dataset.ParseFromString(response.data)
assert downloaded_dataset == dataset
def test_delete_reaction_id_blank(client):
name = "test"
dataset = dataset_pb2.Dataset(reaction_ids=["", "test", ""])
_upload_dataset(client, dataset, name)
response = client.get(f"/dataset/{name}/delete/reaction_id",
follow_redirects=True)
assert response.status_code == 200
downloaded_dataset = _download_dataset(client, name)
assert len(downloaded_dataset.reaction_ids) == 2
def read_dataset(file_name):
"""Returns a Dataset as a serialized protobuf."""
dataset = dataset_pb2.Dataset()
with open('db/%s.pbtxt' % file_name, 'rb') as pbtxt:
text_format.Parse(pbtxt.read(), dataset)
bites = dataset.SerializeToString(deterministic=True)
response = flask.make_response(bites)
response.headers.set('Content-Type', 'application/protobuf')
return response
def get_dataset(file_name):
"""Reads a .pbtxt file from the db/ directory and parse it."""
with lock(file_name):
if ('%s.pbtxt' % file_name) not in os.listdir('db'):
return None
dataset = dataset_pb2.Dataset()
with open('db/%s.pbtxt' % file_name, 'rb') as pbtxt:
text_format.Parse(pbtxt.read(), dataset)
return dataset
def test_add_sharded_dataset_with_validation_errors(self):
reaction = reaction_pb2.Reaction()
ethylamine = reaction.inputs['ethylamine']
component = ethylamine.components.add()
component.identifiers.add(type='SMILES', value='CCN')
component.is_limiting = True
component.moles.value = 2
component.moles.units = reaction_pb2.Moles.MILLIMOLE
reaction.outcomes.add().conversion.value = 25
dataset1 = dataset_pb2.Dataset(reactions=[reaction])
dataset1_filename = os.path.join(self.test_subdirectory, 'test1.pbtxt')
message_helpers.write_message(dataset1, dataset1_filename)
reaction.inputs['ethylamine'].components[0].identifiers[
0].value = 'C#O'
dataset2 = dataset_pb2.Dataset(reactions=[reaction])
dataset2_filename = os.path.join(self.test_subdirectory, 'test2.pbtxt')
message_helpers.write_message(dataset2, dataset2_filename)
with self.assertRaisesRegex(ValueError, 'could not validate SMILES'):
self._run_main()
def test_multiple_dois(self):
dataset = dataset_pb2.Dataset()
dataset.dataset_id = 'ord_dataset-1'
dataset.reactions.add().provenance.doi = 'foo/bar'
dataset.reactions.add().provenance.doi = 'not/bar'
tempdir = self.create_tempdir()
message_helpers.write_message(
dataset, os.path.join(tempdir, f'{dataset.dataset_id}.pb'))
with flagsaver.flagsaver(input=os.path.join(tempdir, '*.pb')):
list_dois.main(())
def test_read_dataset(self):
name = 'test'
dataset = self._get_dataset()
self._upload_dataset(dataset, name)
response = self.client.get(f'/dataset/proto/read/{name}',
follow_redirects=True)
self.assertEqual(response.status_code, 200)
downloaded_dataset = dataset_pb2.Dataset()
downloaded_dataset.ParseFromString(response.data)
self.assertEqual(downloaded_dataset, dataset)
def test_main_fail(self):
dataset = dataset_pb2.Dataset()
reaction = dataset.reactions.add()
component = reaction.inputs['test'].components.add()
component.identifiers.add(value='c1ccccc1', type='SMILES')
message_helpers.write_message(dataset, self.pb_filename)
component.identifiers.add(value='benzene', type='NAME')
message_helpers.write_message(dataset, self.pbtxt_filename)
with self.assertRaisesRegex(ValueError, 'Datasets differ'):
self._run()
def test_bad_dataset_id(self):
dataset = dataset_pb2.Dataset(reactions=[reaction_pb2.Reaction()],
dataset_id='not-a-real-dataset-id')
filename = os.path.join(self.test_subdirectory, 'test.pbtxt')
message_helpers.write_message(dataset, filename)
with flagsaver.flagsaver(root=self.test_subdirectory,
input_pattern=filename,
validate=False,
update=True):
with self.assertRaisesRegex(ValueError, 'malformed dataset ID'):
process_dataset.main(())
def test_delete_reaction_id(client):
name = "test"
dataset = dataset_pb2.Dataset()
reaction_id = "test_reaction_id"
dataset.reaction_ids.append(reaction_id)
_upload_dataset(client, dataset, name)
response = client.get(f"/dataset/{name}/delete/reaction_id/{reaction_id}",
follow_redirects=True)
assert response.status_code == 200
downloaded_dataset = _download_dataset(client, name)
assert len(downloaded_dataset.reaction_ids) == 0
def test_delete_reaction_id(self):
name = 'test'
dataset = dataset_pb2.Dataset()
reaction_id = 'test_reaction_id'
dataset.reaction_ids.append(reaction_id)
self._upload_dataset(dataset, name)
response = self.client.get(
f'/dataset/{name}/delete/reaction_id/{reaction_id}',
follow_redirects=True)
self.assertEqual(response.status_code, 200)
downloaded_dataset = self._download_dataset(name)
self.assertEmpty(downloaded_dataset.reaction_ids)
