@Marvin using prefect-sqlalchemy, I have to do

async def get_session():
    async with await connector.load(DB_BLOCK_NAME) as connector:
        engine = connector.get_engine()
        async_session = async_sessionmaker(engine, expire_on_commit=False)
        async with async_session() as session:

in many tasks i need a session to use in a repository pattern. the above is inefficient since i shouldnt be creating many engines concurrently. is there a better alternative? is there a session manager exposed in prefect-sqlalchemy?

It seems that Prefect's documentation for

prefect-sqlalchemy

doesn't explicitly mention a session manager for reusing database sessions. However, creating multiple engines concurrently is indeed inefficient, and a common practice is to create a single engine and reuse it across tasks. To achieve this, you can structure your code to create the engine once and use it across multiple tasks. Here's a conceptual approach: 1. Create a Singleton Engine: Use a singleton pattern to instantiate the engine once and reuse it. 2. Use Dependency Injection: Pass the session or engine to tasks that need it. Here is a simplified example of how you might implement this:

python
from sqlalchemy.ext.asyncio import create_async_engine, async_sessionmaker
from sqlalchemy.orm import sessionmaker

# Create a singleton engine
engine = create_async_engine("your_database_url", echo=True)

# Create a sessionmaker
SessionLocal = async_sessionmaker(bind=engine, expire_on_commit=False)

async def get_session():
    async with SessionLocal() as session:
        yield session

# Example task using the session
@task
async def some_task():
    async for session in get_session():
        # Use session here
        pass

For more details, you can refer to the Prefect SQLAlchemy integration documentation. If Prefect introduces a session manager in future updates, it would be documented there. For now, managing sessions manually as shown above is a practical approach.

@Marvin then what is the purpose of prefect-sqlalchemy? dont i need it to access the db from flows?

The

prefect-sqlalchemy

integration is designed to help you connect to databases within your Prefect flows. Its primary purpose is to streamline the process of managing database connections and executing SQL commands in a Prefect environment. Here's what it offers: 1. Credential Management: It allows you to save and load database credentials using Prefect's block system. This means you can store your database connection details securely and access them within your flows. 2. Database Operations: It provides methods such as

execute

and

execute_many

to run SQL commands, and

fetch_many

to retrieve data from the database, facilitating interaction with your database directly from Prefect tasks. 3. Integration with Prefect: It ensures that your database operations are well-integrated with Prefect's task and flow management, allowing you to handle database interactions as part of your data workflows. While it simplifies connection management and SQL execution, it doesn't inherently manage session reuse or engine instantiation across multiple tasks. For that, you would still need to implement a pattern to reuse sessions, as discussed previously. For more details, you can explore the Prefect SQLAlchemy integration documentation.

@Marvin say i instantiate my own sqlalchemy engine. can i make it so that all flow runs use that global object?

To ensure all flow runs use a global SQLAlchemy engine, you can create a singleton engine at the module level and ensure that your tasks access this engine. However, Prefect's architecture, which often involves running tasks on different workers or environments, might complicate sharing a global object across flow runs directly. Here's a conceptual approach: 1. Singleton Pattern: Create the SQLAlchemy engine as a singleton in a module that is imported by all tasks needing database access. 2. Environment Consistency: Ensure that all tasks run in the same environment where the singleton engine is instantiated. This might involve running all tasks on the same agent or worker. 3. Configuration Management: Use Prefect's configuration management to pass necessary parameters to ensure the environment is set up consistently. Here is a simple example:

python
from sqlalchemy.ext.asyncio import create_async_engine, async_sessionmaker

# Global engine instance
engine = create_async_engine("your_database_url", echo=True)
SessionLocal = async_sessionmaker(bind=engine, expire_on_commit=False)

def get_global_engine():
    return engine

def get_session():
    return SessionLocal()

# Task example
@task
def my_task():
    session = get_session()
    # Use session here

This setup assumes that the environment where the flow runs is consistent and that the global engine is accessible to all tasks. If your tasks run in distributed environments, you might need to reconsider this approach or use Prefect's infrastructure features to manage shared state or resources. For more details on Prefect's capabilities, you can refer to the Prefect documentation.