Skip to main content

Per-model audit logs to TABLENAME_log with entry-point capture (HTTP/management/shell/celery)

Project description

Awesome Audit Log for Django

PyPI version codecov Python versions License

This is an awesome package to have your models logs in corresponding _log tables.

Having a single model/table as audit storage can cause heavy db operation and useless for large applications.

With this package you will have each model log in a separate table which can be beneficial if you want to truncate a specific model logs or run a query on them.

You can choose between having logs table in your default database or adding a new backend db as logs db.

Supported DBs to store logs:

  1. PostgreSQL
  2. MySQL
  3. SQLite

This package is in its early stage development and the following features will be added ASAP:

  1. Log rotation
  2. Mongo DB support
  3. Add management, shell, celery as entry point of logs
  4. Document page!

Compatible With

This package works on the below listed Django, Python versions and Databases.

  • Django versions: 4.2, 5.0, 5.1
  • Python versions: 3.10, 3.11, 3.12
  • Databases: SQLite, PostgreSQL, MySQL
  • Celery: Optional for Async logging

Installation

  1. Add App
INSTALLED_APPS = [
    # ...
    'awesome_audit_log.apps.AwesomeAuditLogConfig',
]
  1. Add Middleware
MIDDLEWARE = [
    # ...
    "awesome_audit_log.middleware.RequestEntryPointMiddleware",
]
  1. Settings
AWESOME_AUDIT_LOG = {
    "ENABLED": True,
    "DATABASE_ALIAS": "default",
    # PostgreSQL schema for audit tables (defaults to 'public')
    "PG_SCHEMA": None,
    # Enable async logging with Celery (requires Celery to be installed and configured)
    "ASYNC": False,
    # "all" or list like ["app_label.ModelA", "app.ModelB"]
    "AUDIT_MODELS": "all",
    # like AUDIT_MODELS but for opt-out, useful when AUDIT_MODELS set to all
    "NOT_AUDIT_MODELS": None,
    "CAPTURE_HTTP": True,
    # set to False means if audit db is unavailable, silently skip logging (with a warning) instead of raising
    "RAISE_ERROR_IF_DB_UNAVAILABLE": False,
    # if audit alias missing/unavailable, use 'default' intentionally, this requires RAISE_ERROR_IF_DB_UNAVAILABLE is set to False
    "FALLBACK_TO_DEFAULT": False,
}

Async Logging with Celery

This package supports async audit logging using Celery. When ASYNC is set to True, audit logs will be inserted asynchronously using Celery tasks, which can improve performance for high-traffic applications.

Setup

  1. Install Celery (if not already installed):
pip install celery
  1. Configure Celery in your Django project (this package doesn't configure Celery for you):
# settings.py
CELERY_BROKER_URL = 'redis://localhost:6379/0'  # or your preferred broker
CELERY_RESULT_BACKEND = 'redis://localhost:6379/0'
  1. Enable async logging:
AWESOME_AUDIT_LOG = {
    "ASYNC": True,  # Enable async logging
    # ... other settings
}

Notes

  • The package automatically detects if Celery is available and falls back to synchronous logging if not
  • Works with any Celery broker (Redis, RabbitMQ, database, etc.)
  • No additional configuration is required in this package - it uses your existing Celery setup
  • Async logging is disabled by default for backward compatibility
  • Important: Timestamps are captured at event time, not at database insert time, ensuring accurate audit logs even with async processing

Timestamp Accuracy

This package ensures that audit log timestamps (created_at) accurately reflect when events occur, not when they're saved to the database. This is especially important for async logging where there may be a delay between the event and database insertion.

See MIGRATION_GUIDE.md if you're upgrading from a version prior to 1.0.0.

Development

Preparation

# Install dependencies
poetry install

Running Tests and Linter Locally

# Run tests
poetry run pytest

# Run linting
poetry run ruff check awesome_audit_log tests
poetry run ruff format --check awesome_audit_log tests

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

awesome_audit_log_django-1.0.0.tar.gz (12.2 kB view details)

Uploaded Source

Built Distribution

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

awesome_audit_log_django-1.0.0-py3-none-any.whl (14.8 kB view details)

Uploaded Python 3

File details

Details for the file awesome_audit_log_django-1.0.0.tar.gz.

File metadata

  • Download URL: awesome_audit_log_django-1.0.0.tar.gz
  • Upload date:
  • Size: 12.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.2.1 CPython/3.12.11 Linux/6.11.0-1018-azure

File hashes

Hashes for awesome_audit_log_django-1.0.0.tar.gz
Algorithm Hash digest
SHA256 f14b9071c8eb5a08f70ae35fa4479a839dcb6bef442412d3050f726039fcbbc6
MD5 99de63005ddcbc1460bbfe0519fda49f
BLAKE2b-256 c99146892ab44fa7e03d5b5f845f4da04862480fcc8f0d02d0a2fa26f9725cd2

See more details on using hashes here.

File details

Details for the file awesome_audit_log_django-1.0.0-py3-none-any.whl.

File metadata

File hashes

Hashes for awesome_audit_log_django-1.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 d79c7c03be824c07744093a5dab68f5ac357540afc06e751633f8cb16af5d3aa
MD5 fc42238596684eeeb66b9565bf5ccbc8
BLAKE2b-256 c5e26d258e5af7063099792b2607c3c7f7668b22a489715dfd623c34c54fc047

See more details on using hashes here.

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