Prefect sqlalchemy

prefect-sqlalchemy

The prefect-sqlalchemy helps you connect to a database in your Prefect flows.

Getting Started

Prerequisites

• Prefect installed.

Install prefect-sqlalchemy

Install or update to the latest version of the prefect-sqlalchemy library and dependencies.

Prefect 2

pip install -U prefect-sqlalchemy

Register newly installed block types

Register the block types in the prefect-sqlalchemy module to make them available for use.

prefect block register -m prefect_sqlalchemy

Examples

Save credentials to a block

To use the load method on Blocks, you must have a block saved through code or saved through the UI.

from prefect_sqlalchemy import SqlAlchemyConnector, ConnectionComponents, SyncDriver

connector = SqlAlchemyConnector(
    connection_info=ConnectionComponents(
        driver=SyncDriver.POSTGRESQL_PSYCOPG2,
        username="USERNAME-PLACEHOLDER",
        password="PASSWORD-PLACEHOLDER",
        host="localhost",
        port=5432,
        database="DATABASE-PLACEHOLDER",
    )
)

connector.save("BLOCK_NAME-PLACEHOLDER")

Load the saved block that holds your credentials:

from prefect_sqlalchemy import SqlAlchemyConnector

SqlAlchemyConnector.load("BLOCK_NAME-PLACEHOLDER")

The required arguments depend upon the desired driver. For example, SQLite requires only the driver and database arguments:

from prefect_sqlalchemy import SqlAlchemyConnector, ConnectionComponents, SyncDriver

connector = SqlAlchemyConnector(
    connection_info=ConnectionComponents(
        driver=SyncDriver.SQLITE_PYSQLITE,
        database="DATABASE-PLACEHOLDER.db"
    )
)

connector.save("BLOCK_NAME-PLACEHOLDER")

Work with databases in a flow

To set up a table, use the execute and execute_many methods.

Use the fetch_many method to retrieve data in a stream until there’s no more data.

Use the SqlAlchemyConnector as a context manager, to ensure that the SQLAlchemy engine and any connected resources are closed properly after you’re done with them.

Async support

SqlAlchemyConnector supports async workflows. Just be sure to save, load, and use an async driver, as in the example below.

from prefect_sqlalchemy import SqlAlchemyConnector, ConnectionComponents, AsyncDriver

connector = SqlAlchemyConnector(
    connection_info=ConnectionComponents(
        driver=AsyncDriver.SQLITE_AIOSQLITE,
        database="DATABASE-PLACEHOLDER.db"
    )
)

if __name__ == "__main__":
    connector.save("BLOCK_NAME-PLACEHOLDER")

Sync

from prefect import flow, task
from prefect_sqlalchemy import SqlAlchemyConnector


@task
def setup_table(block_name: str) -> None:
    with SqlAlchemyConnector.load(block_name) as connector:
        connector.execute(
            "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
        )
        connector.execute(
            "INSERT INTO customers (name, address) VALUES (:name, :address);",
            parameters={"name": "Marvin", "address": "Highway 42"},
        )
        connector.execute_many(
            "INSERT INTO customers (name, address) VALUES (:name, :address);",
            seq_of_parameters=[
                {"name": "Ford", "address": "Highway 42"},
                {"name": "Unknown", "address": "Highway 42"},
            ],
        )

@task
def fetch_data(block_name: str) -> list:
    all_rows = []
    with SqlAlchemyConnector.load(block_name) as connector:
        while True:
            # Repeated fetch* calls using the same operation will
            # skip re-executing and instead return the next set of results
            new_rows = connector.fetch_many("SELECT * FROM customers", size=2)
            if len(new_rows) == 0:
                break
            all_rows.append(new_rows)
    return all_rows

@flow
def sqlalchemy_flow(block_name: str) -> list:
    setup_table(block_name)
    all_rows = fetch_data(block_name)
    return all_rows

if __name__ == "__main__":
    sqlalchemy_flow("BLOCK-NAME-PLACEHOLDER")

Resources

Refer to the prefect-sqlalchemy SDK documentation linked in the sidebar to explore all the capabilities of the prefect-sqlalchemy library.

For assistance using SQLAlchemy, consult the SQLAlchemy documentation.