With for Update in SQLAlchemy - SQL

When working with database transactions, it is often necessary to ensure that certain rows or tables are not modified by other concurrent transactions. This is achieved through the concept of locking, where a transaction acquires a lock on a row or table and prevents other transactions from modifying it until the lock is released.

In SQLAlchemy, the with_for_update clause can be used to acquire a lock on one or more rows in a table for the duration of a transaction. This ensures that no other transaction can modify those rows until the lock is released.

Basic Syntax

The with_for_update clause is used in conjunction with a SQLAlchemy query to acquire a lock on the selected rows. Here is the basic syntax:

from sqlalchemy import create_engine, MetaData, Table, Column, Integer, String
from sqlalchemy.sql import select

engine = create_engine('postgresql://username:password@host:port/database_name')

metadata = MetaData()
users = Table('users', metadata,
    Column('id', Integer, primary_key=True),
    Column('name', String),
    Column('age', Integer)
)

with engine.begin() as conn:
    stmt = select([users]).where(users.c.name == 'Alice').with_for_update()
    result = conn.execute(stmt)
    # Perform transaction

In this example, we acquire a lock on all rows in the users table that satisfy the condition name = 'Alice'. The with_for_update() method is used to indicate that a lock should be acquired on these rows for the duration of the transaction.

Locking Strategies

There are several locking strategies that can be used with the with_for_update clause to control how the lock is acquired:

FOR UPDATE

The FOR UPDATE locking strategy acquires a row-level lock on the selected rows. This prevents other transactions from modifying those rows until the lock is released.

stmt = select([users]).where(users.c.name == 'Alice').with_for_update()

FOR SHARE

The FOR SHARE locking strategy acquires a row-level lock on the selected rows, but allows other transactions to also acquire a FOR SHARE lock on the same rows. This is useful in situations where multiple transactions need to read the same data without interfering with each other.

stmt = select([users]).where(users.c.name == 'Alice').with_for_update(read=True)

NOWAIT

The NOWAIT locking strategy attempts to acquire the lock immediately, but raises an exception if it cannot be acquired. This can be useful in situations where you want to lock a row for modification, but do not want to wait for other transactions to finish modifying it.

stmt = select([users]).where(users.c.name == 'Alice').with_for_update(nowait=True)

SKIP LOCKED

The SKIP LOCKED locking strategy skips over rows that are already locked by another transaction. This can be useful in situations where you want to select some rows that are not currently locked by any transaction.

stmt = select([users]).where(users.c.name == 'Alice').with_for_update(skip_locked=True)

Conclusion

The with_for_update clause in SQLAlchemy can be a powerful tool for managing locking in database transactions. By specifying the appropriate locking strategy, you can control how rows are locked and ensure that concurrent transactions do not interfere with each other.