danube-client 0.5.0

Python async client for the Danube messaging platform

Danube-py client

The Python async client library for interacting with Danube Messaging Broker platform.

Danube is an open-source distributed Messaging platform written in Rust. Consult the documentation for supported concepts and the platform architecture.

Features

📤 Producer Capabilities

• Basic Messaging - Send messages with byte payloads
• Partitioned Topics - Distribute messages across multiple partitions for horizontal scaling
• Reliable Dispatch - Guaranteed message delivery with persistence (WAL + cloud storage)
• Schema Integration - Type-safe messaging with automatic validation (Bytes, String, Number, Avro, JSON Schema, Protobuf)

📥 Consumer Capabilities

• Flexible Subscriptions - Four subscription types for different use cases:
  • Exclusive - Single active consumer, guaranteed ordering
  • Shared - Load balancing across multiple consumers, parallel processing
  • Failover - High availability with automatic standby promotion
  • Key-Shared - Per-key ordering with multi-consumer parallelism; messages with the same routing key always go to the same consumer
• Key Filtering - In Key-Shared mode, subscribe to a subset of routing keys with glob patterns
• Message Acknowledgment - Reliable message processing with at-least-once delivery
• Partitioned Consumption - Automatic handling of messages from all partitions

🔐 Schema Registry

• Schema Management - Register, version, and retrieve schemas (JSON Schema, Avro, Protobuf)
• Compatibility Checking - Validate schema evolution (Backward, Forward, Full, None modes)
• Type Safety - Automatic validation against registered schemas
• Schema Evolution - Safe schema updates with compatibility enforcement

🏗️ Client Features

• Async/Await - Built on asyncio and grpc.aio for efficient async I/O
• Connection Pooling - Shared connection management across producers/consumers
• Automatic Reconnection - Resilient connection handling with retry logic
• Topic Namespaces - Organize topics with namespace structure (/namespace/topic-name)

Installation

pip install danube-client

Or install from source:

git clone https://github.com/danube-messaging/danube-py.git
cd danube-py
pip install -e .

Example Usage

Check out the example files.

Start the Danube server

Use the instructions from the documentation to run the Danube broker/cluster.

Create Producer

import asyncio
from danube import DanubeClientBuilder

async def main():
    client = await (
        DanubeClientBuilder()
        .service_url("http://127.0.0.1:6650")
        .build()
    )

    topic = "/default/test_topic"
    producer_name = "test_producer"

    producer = (
        client.new_producer()
        .with_topic(topic)
        .with_name(producer_name)
        .build()
    )

    await producer.create()
    print(f"The Producer {producer_name} was created")

    payload = b"Hello Danube"
    message_id = await producer.send(payload)
    print(f"The Message with id {message_id} was sent")

    await producer.close()

asyncio.run(main())

Reliable Dispatch (optional)

Reliable dispatch can be enabled when creating the producer, the broker will stream the messages to the consumer from WAL and cloud storage.

from danube import DispatchStrategy

producer = (
    client.new_producer()
    .with_topic(topic)
    .with_name(producer_name)
    .with_dispatch_strategy(DispatchStrategy.RELIABLE)
    .build()
)

Key-Shared Routing

Tag messages with a routing key so all messages with the same key go to the same consumer:

await producer.send_with_key(payload, None, "order-123")

Create Consumer

import asyncio
from danube import DanubeClientBuilder, SubType

async def main():
    client = await (
        DanubeClientBuilder()
        .service_url("http://127.0.0.1:6650")
        .build()
    )

    topic = "/default/test_topic"
    consumer_name = "test_consumer"
    subscription_name = "test_subscription"

    consumer = (
        client.new_consumer()
        .with_topic(topic)
        .with_consumer_name(consumer_name)
        .with_subscription(subscription_name)
        .with_subscription_type(SubType.EXCLUSIVE)
        .build()
    )

    # Subscribe to the topic
    await consumer.subscribe()
    print(f"The Consumer {consumer_name} was created")

    # Start receiving messages
    queue = await consumer.receive()

    while True:
        message = await queue.get()
        payload = message.payload.decode()
        print(f"Received message: {payload!r}")

        # Acknowledge the message
        await consumer.ack(message)

asyncio.run(main())

Key-Shared with Filtering

Subscribe to only specific routing keys in a Key-Shared subscription:

consumer = (
    client.new_consumer()
    .with_topic(topic)
    .with_consumer_name("payments-worker")
    .with_subscription("orders-sub")
    .with_subscription_type(SubType.KEY_SHARED)
    .with_key_filter("payment")
    .with_key_filter("invoice")
    .build()
)

Schema Registry

import json
from danube import SchemaType

schema_client = client.schema()

# Register a JSON schema
json_schema = json.dumps({
    "type": "object",
    "properties": {
        "field1": {"type": "string"},
        "field2": {"type": "integer"},
    },
})

schema_id = await (
    schema_client.register_schema("my-app-events")
    .with_type(SchemaType.JSON_SCHEMA)
    .with_schema_data(json_schema.encode())
    .execute()
)

# Create producer with schema reference
producer = (
    client.new_producer()
    .with_topic("/default/test_topic")
    .with_name("schema_producer")
    .with_schema_subject("my-app-events")
    .build()
)

Browse the examples directory for complete working code:

• simple_producer_consumer — basic send/receive
• reliable_dispatch — at-least-once delivery with acks
• partitions — partitioned topic
• key_shared — Key-Shared routing, filtering, and producer with routing keys
• json_producer / avro_producer — schema registry integration
• schema_evolution — schema versioning and compatibility

Contribution

Working on improving and adding new features. Please feel free to contribute or report any issues you encounter.

Running Integration Tests

Before submitting a PR, install the dev dependencies, start the test cluster and run the integration tests:

# 1. Install dev dependencies
pip install -e ".[dev]"

# 2. Start the cluster
cd docker/
docker compose up -d

# 3. Wait for the broker to be healthy
docker compose ps

# 4. Run the integration tests from the repository root
cd ..
pytest integration_tests/ -v --timeout=120

# 5. Stop the cluster when done
cd docker/
docker compose down -v

Regenerating gRPC stubs

Make sure the proto files are the latest from the Danube project.

Install the required tools:

pip install grpcio-tools

Generate the Python gRPC code from the proto files:

python -m grpc_tools.protoc \
    --proto_path=danube/proto \
    --python_out=danube/proto \
    --grpc_python_out=danube/proto \
    danube/proto/DanubeApi.proto

python -m grpc_tools.protoc \
    --proto_path=danube/proto \
    --python_out=danube/proto \
    --grpc_python_out=danube/proto \
    danube/proto/SchemaRegistry.proto

Then fix the imports in the generated *_grpc.py files to use package-relative imports:

sed -i 's/^import DanubeApi_pb2/from danube.proto import DanubeApi_pb2/' danube/proto/DanubeApi_pb2_grpc.py
sed -i 's/^import SchemaRegistry_pb2/from danube.proto import SchemaRegistry_pb2/' danube/proto/SchemaRegistry_pb2_grpc.py