databend-sqlalchemy 0.4.6

Sqlalchemy adapter for Databend

databend-sqlalchemy

Databend dialect for SQLAlchemy.

Installation

The package is installable through PIP::

pip install databend-sqlalchemy

Usage

The DSN format is similar to that of regular Postgres::

    from sqlalchemy import create_engine, text
    from sqlalchemy.engine.base import Connection, Engine
    engine = create_engine(
        f"databend://{username}:{password}@{host_port_name}/{database_name}?sslmode=disable"
    )
    connection = engine.connect()
    result = connection.execute(text("SELECT 1"))
    assert len(result.fetchall()) == 1

    import connector
    cursor = connector.connect('databend://root:@localhost:8000?sslmode=disable').cursor()
    cursor.execute('SELECT * FROM test')
    # print(cursor.fetchone())
    # print(cursor.fetchall())
    for i in cursor.next():
        print(i)

Merge Command Support

Databend SQLAlchemy supports upserts via its Merge custom expression. See Merge for full documentation.

The Merge command can be used as below::

    from sqlalchemy.orm import sessionmaker
    from sqlalchemy import MetaData, create_engine
    from databend_sqlalchemy.databend_dialect import Merge

    engine = create_engine(db.url, echo=False)
    session = sessionmaker(bind=engine)()
    connection = engine.connect()

    meta = MetaData()
    meta.reflect(bind=session.bind)
    t1 = meta.tables['t1']
    t2 = meta.tables['t2']

    merge = Merge(target=t1, source=t2, on=t1.c.t1key == t2.c.t2key)
    merge.when_matched_then_delete().where(t2.c.marked == 1)
    merge.when_matched_then_update().where(t2.c.isnewstatus == 1).values(val = t2.c.newval, status=t2.c.newstatus)
    merge.when_matched_then_update().values(val=t2.c.newval)
    merge.when_not_matched_then_insert().values(val=t2.c.newval, status=t2.c.newstatus)
    connection.execute(merge)

Table Options

Databend SQLAlchemy supports databend specific table options for Engine, Cluster Keys and Transient tables

The table options can be used as below::

    from sqlalchemy import Table, Column
    from sqlalchemy import MetaData, create_engine

    engine = create_engine(db.url, echo=False)

    meta = MetaData()
    # Example of Transient Table
    t_transient = Table(
        "t_transient",
        meta,
        Column("c1", Integer),
        databend_transient=True,
    )

    # Example of Engine
    t_engine = Table(
        "t_engine",
        meta,
        Column("c1", Integer),
        databend_engine='Memory',
    )

    # Examples of Table with Cluster Keys
    t_cluster_1 = Table(
        "t_cluster_1",
        meta,
        Column("c1", Integer),
        databend_cluster_by=[c1],
    )
    #
    c = Column("id", Integer)
    c2 = Column("Name", String)
    t_cluster_2 = Table(
        't_cluster_2',
        meta,
        c,
        c2,
        databend_cluster_by=[cast(c, String), c2],
    )

    meta.create_all(engine)

Compatibility

• If databend version >= v0.9.0 or later, you need to use databend-sqlalchemy version >= v0.1.0.
• The databend-sqlalchemy use databend-py as internal driver when version < v0.4.0, but when version >= v0.4.0 it use databend driver python binding as internal driver. The only difference between the two is that the connection parameters provided in the DSN are different. When using the corresponding version, you should refer to the connection parameters provided by the corresponding Driver.