bazis-async-background 2.2.3

Async Background core framework for Bazis.

Bazis Async Background

Core background task framework for Bazis. It provides Kafka broker helpers, task schemas, status storage in Redis, and a base API to retrieve task results.

Quick Start

# Install the package
uv add bazis-async-background

# Configure environment variables / settings (.env uses BS_ prefix)
BS_INSTALLED_APPS='["bazis.contrib.async_background", ...]'
BS_BAZIS_CONFIG_APPS='["bazis.contrib.async_background", ...]'

# Kafka settings
BS_KAFKA_BOOTSTRAP_SERVERS=localhost:9093
BS_KAFKA_TOPIC_ASYNC_BG=my_app_background_tasks
BS_KAFKA_GROUP_ID=my_app_background
BS_KAFKA_TASKS='["my_app.background.tasks"]'

# Run consumer in Kubernetes
python manage.py kafka_consumer_single

# Run multiple consumers locally
python manage.py kafka_consumer_multiple --consumers-count=5

Table of Contents

• Description
• Requirements
• Installation
• Architecture
• Configuration
  • Environment Variables / Settings
  • Route Registration
• Usage
  • Running Consumers
• Examples
• License
• Links

Description

Bazis Async Background is a core package for running background tasks in the Bazis framework. It includes:

• Kafka Producer — sending tasks to Kafka queue
• Kafka Consumer — processing tasks from the queue
• Redis storage — storing task execution results
• API endpoint — retrieving results by task_id

Requirements

• Python: 3.12+
• bazis: latest version
• PostgreSQL: 12+
• Redis: For storing results and caching
• Kafka: For task queue

Installation

Using uv (recommended)

uv add bazis-async-background

Using pip

pip install bazis-async-background

Running Tests

Run from the project root:

docker compose -f sample/docker-compose.test.yml up --build --exit-code-from bazis-async-background-pytest --attach bazis-async-background-pytest --attach bazis-async-background-consumer-test

This waits for the pytest container to finish and streams logs only from the Python containers, so test completion and output are easy to follow.

Architecture

┌─────────────┐
│   Client    │
└──────┬──────┘
       │ Background task request
       ▼
┌─────────────────────┐
│   API Endpoint      │
│ (Async Background)  │
└──────┬──────────────┘
       │ 1. Return task_id (202)
       │ 2. Send to Kafka
       ▼
┌─────────────────────┐
│   Kafka Topic       │
│ (async_background)  │
└──────┬──────────────┘
       │
       │ Consumer polls
       ▼
┌─────────────────────┐
│  Kafka Consumer     │
│  (Background Worker)│
└──────┬──────────────┘
       │ 3. Process task
       │ 4. Save result to Redis
       ▼
┌─────────────────────┐
│      Redis          │
│   (Results Store)   │
└──────┬──────────────┘
       │
       │ 5. GET /async_background_response/{task_id}/
       ▼
┌─────────────────────┐
│   API Endpoint      │
│   (Get Result)      │
└─────────────────────┘

Configuration

Environment Variables / Settings

Add to your .env (use BS_ prefix for Bazis settings) or settings.py:

# Required settings
INSTALLED_APPS='["bazis.contrib.async_background", ...]'
BAZIS_CONFIG_APPS='["bazis.contrib.async_background", ...]'
KAFKA_TASKS='["my_app.background.tasks"]'

# Kafka settings
KAFKA_BOOTSTRAP_SERVERS=localhost:9093
KAFKA_TOPIC_ASYNC_BG=my_app_background_tasks
KAFKA_GROUP_ID=my_app_background

# Optional settings
KAFKA_CONSUMER_LIFETIME_SEC=900           # Consumer lifetime (15 minutes)
KAFKA_CONSUMER_LIFETIME_JITTER_SEC=180    # Random deviation (3 minutes)
KAFKA_AUTO_OFFSET_RESET=latest
KAFKA_ENABLE_AUTO_COMMIT=true
KAFKA_AUTO_COMMIT_INTERVAL_MS=5000
KAFKA_LOG_LEVEL=INFO

When placing these in a .env file, prefix them with BS_, for example:

BS_INSTALLED_APPS='["bazis.contrib.async_background", ...]'
BS_BAZIS_CONFIG_APPS='["bazis.contrib.async_background", ...]'
BS_KAFKA_TASKS='["my_app.background.tasks"]'

Parameters:

• KAFKA_TASKS — dotted module paths imported by the consumer to register tasks
• KAFKA_BOOTSTRAP_SERVERS — Kafka broker address
• KAFKA_TOPIC_ASYNC_BG — topic for async tasks
• KAFKA_GROUP_ID — consumer group
• KAFKA_CONSUMER_LIFETIME_SEC — consumer working time before restart
• KAFKA_CONSUMER_LIFETIME_JITTER_SEC — random deviation to avoid simultaneous restart
• KAFKA_AUTO_OFFSET_RESET — Kafka auto offset reset policy
• KAFKA_ENABLE_AUTO_COMMIT — Kafka auto-commit toggle
• KAFKA_AUTO_COMMIT_INTERVAL_MS — auto-commit interval in ms
• KAFKA_LOG_LEVEL — log level for consumers

Route Registration

Add the route for getting results to your router.py:

from bazis.core.routing import BazisRouter

router = BazisRouter(prefix='/api/v1')

# Register background task results route
router.register('bazis.contrib.async_background.router')

This adds the endpoint: GET /api/v1/async_background_response/{task_id}/

Usage

Running Consumers

For Kubernetes (one consumer per pod)

python manage.py kafka_consumer_single

Runs one consumer that processes tasks from Kafka. Suitable for horizontal scaling in Kubernetes.

For Local Development (multiple consumers)

python manage.py kafka_consumer_multiple --consumers-count=5

Runs 5 consumers in separate processes. Suitable for local development or deployment without orchestration.

Parameters:

• --consumers-count — number of consumers to run (default: 1)

Examples

Minimal Task Registration

from bazis.contrib.async_background.broker import get_broker_for_consumer
from bazis.contrib.async_background.schemas import KafkaTask, TaskStatus
from bazis.contrib.async_background.utils import set_and_publish_status_async
from pydantic import BaseModel


class DemoPayload(BaseModel):
    message: str


@get_broker_for_consumer().subscriber("my_app_background_tasks")
async def consumer_demo(task: KafkaTask[DemoPayload]):
    await set_and_publish_status_async(
        task_id=task.task_id,
        channel_name=task.channel_name,
        status=TaskStatus.COMPLETED,
        response={"echo": task.payload.model_dump()},
    )

License

Apache License 2.0

See LICENSE file for details.

Links

• Bazis Documentation — main repository
• Bazis Async Background Repository — package repository
• Issue Tracker — report bugs or request features
• Apache Kafka — Kafka documentation