django-activity-audit 1.3.0.dev19

A Django package for easy CRUD operation logging and container logs

Django Activity Audit

A Django package that extends the default logging mechanism to track CRUD operations and container logs.

Features

• Automatic logging of CRUD operations (Create, Read, Update, Delete)
• Tracks both HTTP requests and model changes
• Custom log levels Audit(21) and API(22) for CRUD and Request-Response auditing.
• Structured JSON logs for audit trails
• Human-readable container logs
• Separate log files for audit and container logs
• Console and file output options

Installation

1. Install the package:

pip install django-activity-audit

2. Add 'activity_audit' to your INSTALLED_APPS in settings.py:

INSTALLED_APPS = [
    ...
    'activity_audit',
]

3. Add the middleware to your MIDDLEWARE in settings.py:

MIDDLEWARE = [
    ...
    'activity_audit.middleware.AuditLoggingMiddleware',
]

4. Configure logging in settings.py:

from activity_audit import *

LOGGING = {
    "version": 1,
    "disable_existing_loggers": False,
    "formatters": {
        "json": get_json_formatter(),
        "verbose": get_console_formatter(),
    },
    "handlers": {
        "console": {
            "level": "DEBUG",
            "class": "logging.StreamHandler",
            "formatter": "verbose",
        },
        "file": get_json_handler(level="DEBUG", formatter="json"),
        "api_file": get_api_file_handler(),
        "audit_file": get_audit_handler(),
    },
    "root": {"level": "DEBUG", "handlers": ["console", "file"]},
    "loggers": {
        "audit.request": {
            "handlers": ["api_file"],
            "level": "API",
            "propagate": False,
        },
        "audit.model": {
            "handlers": ["audit_file"],
            "level": "AUDIT",
            "propagate": False,
        },
        "django": {
            "handlers": ["console", "file"],
            "level": "INFO",
            "propagate": False,
        },
    }
}

5. Configure the service name in settings.py (optional, defaults to "default"):

AUDIT_SERVICE_NAME = "my_service"

6. For external services logging, extend HTTPClient or SFTPClient

class ExternalService(HTTPClient):
    def __init__(self):
        super().__init__("service_name")

    def connect(self):
        url = "https://www.sample.com"
        response = self.get(url) # sample log structure below

8. Create audit_logs folder in project directory

Log Types

Container Logs

Console Log Format

'%(levelname)s %(asctime)s %(pathname)s %(module)s %(funcName)s %(message)s'
-----------------------------------------------------------------------------
INFO 2025-04-30 08:51:10,403 /app/patients/api/utils.py utils create_patient_with_contacts_and_diseases Patient 'd6c9a056-0b57-453a-8c0f-44319004b761 - Patient3' created.

File Log Format

APP Log

{
    "timestamp": "2025-05-15 13:38:02.141",
    "level": "DEBUG",
    "name": "botocore.auth",
    "path": "/opt/venv/lib/python3.11/site-packages/botocore/auth.py",
    "module": "auth",
    "function": "add_auth",
    "message": "Calculating signature using v4 auth.",
    "exception": ""
}

CRUD Log

{
    "timestamp": "2025-08-16 17:06:32.403",
    "level": "AUDIT",
    "name": "audit.model",
    "message": "CREATE event by User (id: 6f77b814-f9c1-4cab-a737-6677734bc303)",
    "model": "User",
    "event_type": "CREATE",
    "instance_id": "6f77b814-f9c1-4cab-a737-6677734bc303",
    "instance_repr" : {
        "name": "Test Model",
        "is_active": true,
        "created_at": "2025-08-29T08:18:54Z",
        "updated_at": "2025-08-29T08:18:54Z"
    },
    "user_id": "cae8ffb4-ba52-409c-9a6f-e10362bfaf97",
    "user_info": {
        "title": "mr",
        "email": "[e-mail]",
        "first_name": "mohamlal",
        "middle_name": "v",
        "last_name": "nair",
        "sex": "m",
    },
    "extra": {}
}

Request-Response Log

Incoming Log Format

{
    "timestamp": "2025-05-19 15:25:27.836",
    "level": "API",
    "name": "audit.request",
    "message": "Audit Internal Request",
    "service_name": "my_service",
    "request_type": "internal",
    "protocol": "http",
    "user_id": "14ab1197-ebdd-4300-a618-5910e0219936",
    "user_info": {
        "title": "mr",
        "email": "[e-mail]",
        "first_name": "mohanlal",
        "middle_name": "",
        "last_name": "nair",
        "sex": "male",
        "date_of_birth": "21/30/1939"
    },
    "request_repr": {
        "method": "GET",
        "path": "/api/v1/health/",
        "query_params": {},
        "headers": {
            "Content-Type": "application/json",
        },
        "user": null,
        "body": {
            "title": "hello"
        }
    },
    "response_repr": {
        "status_code": 200,
        "headers": {
            "Content-Type": "application/json",
        },
        "body": {
            "status": "ok"
        }
    },
    "error_message": null,
    "execution_time": 5.376734018325806
}

External Log format

{
    "timestamp": "2025-05-19 15:25:27.717",
    "level": "API",
    "name": "audit.request",
    "message": "Audit External Service",
    "service_name": "apollo",
    "request_type": "external",
    "protocol": "http",
    "user_id": "14ab1197-ebdd-4300-a618-5910e0219936",
    "user_info": {
        "title": "mr",
        "email": "[e-mail]",
        "first_name": "mohanlal",
        "middle_name": "",
        "last_name": "nair",
        "sex": "male",
        "date_of_birth": "21/30/1939"
    },
    "request_repr": {
        "endpoint": "example.com",
        "method": "GET",
        "headers": {},
        "body": {}
    },
    "response_repr": {
        "status_code": 200,
        "body": {
            "title": "title",
            "expiresIn": 3600,
            "error": "",
            "errorDescription": ""
        }
    },
    "error_message": "",
    "execution_time": 5.16809344291687
}

Notes

• Compatible with Django 3.2+ and Python 3.7+.
• Designed for easy integration with observability stacks using Vector, ClickHouse, and Grafana.
• Capture Django CRUD operations automatically
• Write structured JSON logs
• Ready for production-grade logging pipelines
• Simple pip install, reusable across projects
• Zero additional database overhead!

Related Tools

• Vector.dev
• ClickHouse
• Grafana

License

This project is licensed under the MIT License - see the LICENSE file for details.