def test_extract_db_type_from_uri():
uri = "{}://username:password@host:port/database"
for legit_db in DATABASE_ENGINES:
assert legit_db == extract_db_type_from_uri(uri.format(legit_db))
assert legit_db == get_uri_scheme(uri.format(legit_db))
with_driver = legit_db + "+driver-string"
assert legit_db == extract_db_type_from_uri(uri.format(with_driver))
assert legit_db == get_uri_scheme(uri.format(with_driver))
for unsupported_db in ["a", "aa", "sql"]:
with pytest.raises(MlflowException):
extract_db_type_from_uri(unsupported_db)
def __init__(self, db_uri, default_artifact_root):
"""
Create a database backed store.
:param db_uri: The SQLAlchemy database URI string to connect to the database. See
the `SQLAlchemy docs
<https://docs.sqlalchemy.org/en/latest/core/engines.html#database-urls>`_
for format specifications. Mlflow supports the dialects ``mysql``,
``mssql``, ``sqlite``, and ``postgresql``.
:param default_artifact_root: Path/URI to location suitable for large data (such as a blob
store object, DBFS path, or shared NFS file system).
"""
super(SqlAlchemyStore, self).__init__()
self.db_uri = db_uri
self.db_type = extract_db_type_from_uri(db_uri)
self.artifact_root_uri = default_artifact_root
self.engine = sqlalchemy.create_engine(db_uri, pool_pre_ping=True)
insp = sqlalchemy.inspect(self.engine)
# On a completely fresh MLflow installation against an empty database (verify database
# emptiness by checking that 'experiments' etc aren't in the list of table names), run all
# DB migrations
expected_tables = set([
SqlExperiment.__tablename__,
SqlRun.__tablename__,
SqlMetric.__tablename__,
SqlParam.__tablename__,
SqlTag.__tablename__,
SqlExperimentTag.__tablename__,
SqlLatestMetric.__tablename__,
])
if len(expected_tables & set(insp.get_table_names())) == 0:
SqlAlchemyStore._initialize_tables(self.engine)
Base.metadata.bind = self.engine
SessionMaker = sqlalchemy.orm.sessionmaker(bind=self.engine)
self.ManagedSessionMaker = self._get_managed_session_maker(
SessionMaker)
SqlAlchemyStore._verify_schema(self.engine)
if _is_local_uri(default_artifact_root):
mkdir(local_file_uri_to_path(default_artifact_root))
if len(self.list_experiments()) == 0:
with self.ManagedSessionMaker() as session:
self._create_default_experiment(session)
def __init__(self, artifact_uri):
self.db_uri, self.root = extract_db_uri_and_root_path(artifact_uri)
self.db_type = extract_db_type_from_uri(self.db_uri)
self.engine = sqlalchemy.create_engine(self.db_uri)
super(DBArtifactRepository, self).__init__(self.db_uri)
insp = sqlalchemy.inspect(self.engine)
self.expected_tables = set([
SqlArtifact.__tablename__,
])
if len(self.expected_tables & set(insp.get_table_names())) == 0:
DBArtifactRepository._initialize_tables(self.engine)
InitialBase.metadata.bind = self.engine
SessionMaker = sqlalchemy.orm.sessionmaker(bind=self.engine)
self.ManagedSessionMaker = self._get_managed_session_maker(
SessionMaker)
# Indicate to MLflow that this is an artifact repository plugin
self.is_plugin = True
