https://github.com/databendcloud/databend-sqlalchemy

Databend SQLAlchemy
https://github.com/databendcloud/databend-sqlalchemy

Last synced: 3 months ago
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Databend SQLAlchemy

• Host: GitHub
• URL: https://github.com/databendcloud/databend-sqlalchemy
• Owner: datafuselabs
• License: apache-2.0
• Created: 2022-11-07T13:30:24.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2024-07-29T10:40:54.000Z (4 months ago)
• Last Synced: 2024-08-17T23:01:43.858Z (3 months ago)
• Language: Python
• Size: 107 KB
• Stars: 13
• Watchers: 6
• Forks: 3
• Open Issues: 3
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE

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README

        
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 row in cursor:

            print(row)

Merge Command Support

---------------------

Databend SQLAlchemy supports upserts via its `Merge` custom expression.

See [Merge](https://docs.databend.com/sql/sql-commands/dml/dml-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](https://github.com/datafuselabs/databend-py) as internal driver when version < v0.4.0, but when version >= v0.4.0 it use [databend driver python binding](https://github.com/datafuselabs/bendsql/blob/main/bindings/python/README.md) 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.