Preparing Archive
azure-eventhub-py
Azure Event Hubs SDK for Python streaming. Use for high-throughput event ingestion, producers, consumers, and checkpointing.
Architectural Overview
"This module is grounded in ai engineering patterns and exposes 1 core capabilities across 1 execution phases."
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.
Primary Stack
Python
Tooling Surface
Guide only
Workspace Path
.agents/skills/azure-eventhub-py
Operational Ecosystem
The complete hardware and software toolchain required.
Module Topology
Antigravity Core
Principal Engineering Agent
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