Skip to main content

SQLAlchemy extension that provides an easy way to track changes to your database models.

Project description

SQLAudit

SQLAudit is a SQLAlchemy extension that provides an easy way to track changes to your database models. It automatically creates an audit trail of changes made to your models, including the user who made the change, the timestamp of the change.

It is designed to work with SQLAlchemy's ORM and provides a simple way to track changes to your models without having to write custom code for each model. SQLAudit only requires you to decorate your models with the @track_table decorator, and it will automatically track changes to the specified fields.

@track_table(tracked_fields=["name", "email", "user_id"])
class Customer(Base):
    __tablename__ = "customers"

    customer_id: Mapped[int] = mapped_column(
        Integer, primary_key=True, autoincrement=True
    )
    name: Mapped[str] = mapped_column(String)
    email: Mapped[str] = mapped_column(String)
    created_by: Mapped[str] = mapped_column(ForeignKey("users.user_id"))

Notice

This project is in its early stages and is not yet ready for production use.

Quick start

To get started with SQLAudit, you need to install it using pip:

pip install sqlaudit

Follow the steps below to set up and use SQLAudit in your SQLAlchemy application.

This short guide demonstrates how to setup and use SQLAudit.

Step 1: Define your Base and User model

SQLAudit requires access to a SQAlchemy Base class. We will also define a User class which will be used to identify who made which change, and a session factory to create sessions.

from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker, DeclarativeBase

# Create an in-memory SQLite database
DATABASE_URL = "sqlite:///:memory:"
engine = create_engine(DATABASE_URL, connect_args={"check_same_thread": False})

SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)


def get_db():
    """Yield a database session for an in-memory SQLite DB."""
    db = SessionLocal()
    try:
        yield db
    finally:
        db.close()


class Base(DeclarativeBase):
    pass


class User(Base):
    __tablename__ = "users"
    user_id: Mapped[int] = mapped_column(primary_key=True, autoincrement=True)
    name: Mapped[string] = mapped_column()

Step 2: Configure SQLAudit

Set the global configuration using set_audit_config().

from sqlaudit import set_audit_config
from utils.db import engine, get_db  # your db utils

set_audit_config(
    engine=engine, #  SQLAlchemy engine
    Base=Base, # SQLAlchemy Base class defined in Step 1
    session_factory=get_db, # function to get a SQLAlchemy session
    default_user_id_field="user_id", # field in User model to identify user
    user_model=User, # User model defined in Step 1
    user_id_field="user_id", # field in User model to identify user
)

Step 3: Add SQLAudit to your models

To enable auditing for your models use the @track_table decorator. This decorator will automatically track changes to the model and store them in the audit table. There are various options you can pass to the decorator to customize the behavior. The most basic usage only requires a list of strings representing the columns you want to track.

from sqlaudit import track_table
from sqlalchemy import Integer, String

@track_table(tracked_fields=["name", "email", "user_id"])
class Customer(Base):
    __tablename__ = "customers"

    customer_id: Mapped[int] = mapped_column(
        Integer, primary_key=True, autoincrement=True
    )
    name: Mapped[str] = mapped_column(String)
    email: Mapped[str] = mapped_column(String)
    user_id: Mapped[str] = mapped_column(String, nullable=False)

Step 4: Register the SQLAudit hooks

SQLAudit uses two SQLAlchemy events to track changes: before_flush and after_flush. You need to register these hooks to enable auditing.

We will be doing this in a startup function that will be called when the application starts.

if __name__ == "__main__":
    Base.metadata.create_all(engine)

    register_audit_hooks()

Step 5: Use the session to make changes

Now you can use the session to make changes to your models. SQLAudit will automatically track these changes and store them in the audit table.

with next(get_db()) as session:
    user = User()
    session.add(user)
    session.commit()

    new_customer = Customer(
        name="John Doe", email="jdoe@example.com", user_id=user.user_id
    )

    session.add(new_customer)

    session.commit()
    print(
        f"Customer {new_customer.customer_id} added with name {new_customer.name} and email {new_customer.email}."
    )

    # We check if the customer is in the database
    customer = (
        session.query(Customer)
        .filter_by(customer_id=new_customer.customer_id)
        .first()
    )

    new_customer2 = Customer(
        name="Jane Doe", email="jane@example.com", user_id=user.user_id
    )

    session.add(new_customer2)

    session.commit()
    print(
        f"Customer {new_customer2.customer_id} added with name {new_customer2.name} and email {new_customer2.email}."
    )

    session.refresh(new_customer2)

    new_customer2.name = "Jane Smith"

    session.commit()

    changes = get_resource_changes(
        model_class=Customer,
        session=session,
        filter_resource_ids=["1,", "2"],
        filter_user_ids=str(user.user_id),
    )

    for change in changes:
        print(change)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sqlaudit-0.1.3.tar.gz (12.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

sqlaudit-0.1.3-py3-none-any.whl (15.5 kB view details)

Uploaded Python 3

File details

Details for the file sqlaudit-0.1.3.tar.gz.

File metadata

  • Download URL: sqlaudit-0.1.3.tar.gz
  • Upload date:
  • Size: 12.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for sqlaudit-0.1.3.tar.gz
Algorithm Hash digest
SHA256 4b10f360983dcb1192b9544e7dd538768cdb69a5a5144932ec7d50f949be24ee
MD5 ef99a4d59fce91e452a9917a0f0c75c7
BLAKE2b-256 428df278b71fc4c08475b431e221766bb0ae2b977e7651b10c7cdaf6b7728f27

See more details on using hashes here.

Provenance

The following attestation bundles were made for sqlaudit-0.1.3.tar.gz:

Publisher: publish.yml on SanderJBouwman/sqlaudit

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file sqlaudit-0.1.3-py3-none-any.whl.

File metadata

  • Download URL: sqlaudit-0.1.3-py3-none-any.whl
  • Upload date:
  • Size: 15.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for sqlaudit-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 f8e97bf96de68b2d8c1947dfa9d69ec77845bb9935feb469015c8f46d2221b98
MD5 7a6bf93abd48a3d7b29fd68e5a66b81d
BLAKE2b-256 aeb7447210af7e5a4ace7067412e904f77dc77c40360330e2d220aee69652166

See more details on using hashes here.

Provenance

The following attestation bundles were made for sqlaudit-0.1.3-py3-none-any.whl:

Publisher: publish.yml on SanderJBouwman/sqlaudit

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page