azure-eventhub-py
Azure Event Hubs SDK for Python streaming. Use for high-throughput event ingestion, producers, consumers, and checkpointing.
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- date added
- 2026-02-27
Azure Event Hubs SDK for Python
Big data streaming platform for high-throughput event ingestion.
Installation
pip install azure-eventhub azure-identity # For checkpointing with blob storage pip install azure-eventhub-checkpointstoreblob-aio
Environment Variables
EVENT_HUB_FULLY_QUALIFIED_NAMESPACE=<namespace>.servicebus.windows.net EVENT_HUB_NAME=my-eventhub STORAGE_ACCOUNT_URL=https://<account>.blob.core.windows.net CHECKPOINT_CONTAINER=checkpoints
Authentication
from azure.identity import DefaultAzureCredential from azure.eventhub import EventHubProducerClient, EventHubConsumerClient credential = DefaultAzureCredential() namespace = "<namespace>.servicebus.windows.net" eventhub_name = "my-eventhub" # Producer producer = EventHubProducerClient( fully_qualified_namespace=namespace, eventhub_name=eventhub_name, credential=credential ) # Consumer consumer = EventHubConsumerClient( fully_qualified_namespace=namespace, eventhub_name=eventhub_name, consumer_group="$Default", credential=credential )
Client Types
| Client | Purpose |
|---|---|
EventHubProducerClient | Send events to Event Hub |
EventHubConsumerClient | Receive events from Event Hub |
BlobCheckpointStore | Track consumer progress |
Send Events
from azure.eventhub import EventHubProducerClient, EventData from azure.identity import DefaultAzureCredential producer = EventHubProducerClient( fully_qualified_namespace="<namespace>.servicebus.windows.net", eventhub_name="my-eventhub", credential=DefaultAzureCredential() ) with producer: # Create batch (handles size limits) event_data_batch = producer.create_batch() for i in range(10): try: event_data_batch.add(EventData(f"Event {i}")) except ValueError: # Batch is full, send and create new one producer.send_batch(event_data_batch) event_data_batch = producer.create_batch() event_data_batch.add(EventData(f"Event {i}")) # Send remaining producer.send_batch(event_data_batch)
Send to Specific Partition
# By partition ID event_data_batch = producer.create_batch(partition_id="0") # By partition key (consistent hashing) event_data_batch = producer.create_batch(partition_key="user-123")
Receive Events
Simple Receive
from azure.eventhub import EventHubConsumerClient def on_event(partition_context, event): print(f"Partition: {partition_context.partition_id}") print(f"Data: {event.body_as_str()}") partition_context.update_checkpoint(event) consumer = EventHubConsumerClient( fully_qualified_namespace="<namespace>.servicebus.windows.net", eventhub_name="my-eventhub", consumer_group="$Default", credential=DefaultAzureCredential() ) with consumer: consumer.receive( on_event=on_event, starting_position="-1", # Beginning of stream )
With Blob Checkpoint Store (Production)
from azure.eventhub import EventHubConsumerClient from azure.eventhub.extensions.checkpointstoreblob import BlobCheckpointStore from azure.identity import DefaultAzureCredential checkpoint_store = BlobCheckpointStore( blob_account_url="https://<account>.blob.core.windows.net", container_name="checkpoints", credential=DefaultAzureCredential() ) consumer = EventHubConsumerClient( fully_qualified_namespace="<namespace>.servicebus.windows.net", eventhub_name="my-eventhub", consumer_group="$Default", credential=DefaultAzureCredential(), checkpoint_store=checkpoint_store ) def on_event(partition_context, event): print(f"Received: {event.body_as_str()}") # Checkpoint after processing partition_context.update_checkpoint(event) with consumer: consumer.receive(on_event=on_event)
Async Client
from azure.eventhub.aio import EventHubProducerClient, EventHubConsumerClient from azure.identity.aio import DefaultAzureCredential import asyncio async def send_events(): credential = DefaultAzureCredential() async with EventHubProducerClient( fully_qualified_namespace="<namespace>.servicebus.windows.net", eventhub_name="my-eventhub", credential=credential ) as producer: batch = await producer.create_batch() batch.add(EventData("Async event")) await producer.send_batch(batch) async def receive_events(): async def on_event(partition_context, event): print(event.body_as_str()) await partition_context.update_checkpoint(event) async with EventHubConsumerClient( fully_qualified_namespace="<namespace>.servicebus.windows.net", eventhub_name="my-eventhub", consumer_group="$Default", credential=DefaultAzureCredential() ) as consumer: await consumer.receive(on_event=on_event) asyncio.run(send_events())
Event Properties
event = EventData("My event body") # Set properties event.properties = {"custom_property": "value"} event.content_type = "application/json" # Read properties (on receive) print(event.body_as_str()) print(event.sequence_number) print(event.offset) print(event.enqueued_time) print(event.partition_key)
Get Event Hub Info
with producer: info = producer.get_eventhub_properties() print(f"Name: {info['name']}") print(f"Partitions: {info['partition_ids']}") for partition_id in info['partition_ids']: partition_info = producer.get_partition_properties(partition_id) print(f"Partition {partition_id}: {partition_info['last_enqueued_sequence_number']}")
Best Practices
- Use batches for sending multiple events
- Use checkpoint store in production for reliable processing
- Use async client for high-throughput scenarios
- Use partition keys for ordered delivery within a partition
- Handle batch size limits — catch ValueError when batch is full
- Use context managers (
with/async with) for proper cleanup - Set appropriate consumer groups for different applications
Reference Files
| File | Contents |
|---|---|
| references/checkpointing.md | Checkpoint store patterns, blob checkpointing, checkpoint strategies |
| references/partitions.md | Partition management, load balancing, starting positions |
| scripts/setup_consumer.py | CLI for Event Hub info, consumer setup, and event sending/receiving |
When to Use
This skill is applicable to execute the workflow or actions described in the overview.