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Transaction management in Python ORM: ensuring data integrity

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Python ORM 中的事务管理:确保数据完整性

Characteristics of transactions:

  • Atomicity: All operations in the transaction are either fully committed or fully rolled back, and there is no partial submission.
  • Consistency: After the transaction is completed, the database must be in a consistent state and comply with all constraints and integrity rules.
  • Isolation: Different transactions are independent of each other and will not affect each other.
  • Durability (Durability): Once a transaction is committed, the changes made to the database will be permanently saved, even if a system failure occurs.

Explicit transactions in Python ORM:

To ensure data integrity, transactions can be started and committed explicitly. For example, when using sqlAlchemy ORM, you can use a context manager to manage transactions:

from sqlalchemy.orm import sessionmaker

Session = sessionmaker()
session = Session()

try:
#Perform database operations
session.commit()
exceptException:
session.rollback()

Implicit transactions in Python ORM:

Some ORM frameworks provide implicit transaction management, automatically starting and committing transactions. For example, when using the Peewee ORM, database operations are automatically wrapped in transactions unless explicitly disabled:

from peewee import *

database = SqliteDatabase("database.db")
database.connect()

#Perform database operations

database.close()

When to use transactions:

It is important to use transactions in the following situations:

  • In operations involving multiple database tables, to ensure atomicity of data.
  • When it is necessary to ensure the consistency of the database and prevent inconsistent states.
  • When multiple users concurrently access the database, to isolate different transactions and prevent conflicts.

Frequently Asked Questions about Transactions:

  • Deadlock: A conflict that occurs when multiple transactions try to access the same resource.
  • Dirty read: A transaction reads the unfinished changes of another transaction that have not yet been committed to the database.
  • Non-repeatable read: A transaction reads the same data repeatedly, but obtains different results due to changes by another transaction.

Best practices to avoid transaction problems:

  • Avoid performing long-running operations within a transaction.
  • Use locks to prevent conflicts and deadlocks.
  • Perform regular database maintenance, including index optimization and cleaning.
  • Write robust transaction processing code to correctly handle exceptions and rollbacks.

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