azure-eventhub-py
|
Works with
---
name: azure-eventhub-py
description: |
license: MIT
---
# Azure Event Hubs SDK for Python
Big data streaming platform for high-throughput event ingestion.
## Installation
```bash
pip install azure-eventhub azure-identity
# For checkpointing with blob storage
pip install azure-eventhub-checkpointstoreblob-aio
```
## Environment Variables
```bash
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
```python
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="$Default",
credential=credential
)
```
## Client Types
| Client | Purpose |
|--------|---------|
| `EventHubProducerClient` | Send events to Event Hub |
| `EventHubConsumerClient` | Receive events from Event Hub |
| `BlobCheckpointStore` | Track consumer progress |
## Send Events
```python
from azure.eventhub import EventHubProducerClient, EventData
from azure.identity import DefaultAzureCredential
producer = EventHubProducerClient(
fully_qualified_namespace="<namespace>.servicebus.windows.net",
eventhub_name="my-eventhub",
credential=DefaultAzureCredential()
)
with producer:
# Create batch (handles size limits)
event_data_batch = producer.create_batch()
for i in range(10):
try:
event_data_batch.add(EventData(f"Event {i}"))
except ValueError:
# Batch is full, send and create new one
producer.send_batch(event_data_batch)
event_data_batch = producer.create_batch()
event_data_batch.add(EventData(f"Event {i}"))
# Send remaining
producer.send_batch(event_data_batch)
```
### Send to Specific Partition
```python
# By partition ID
event_data_batch = producer.create_batch(partition_id="0")
# By partition key (consistent hashing)
event_data_batch = producer.create_batch(partition_key="user-123")
```
## Receive Events
### Simple Receive
```python
from azure.eventhub import EventHubConsumerClient
def on_event(partition_context, event):
print(f"Partition: {partition_context.partition_id}")
print(f"Data: {event.body_as_str()}")
partition_context.update_checkpoint(event)
consumer = EventHubConsumerClient(
fully_qualified_namespace="<namespace>.servicebus.windows.net",
eventhub_name="my-eventhub",
consumer_group="$Default",
credential=DefaultAzureCredential()
)
with consumer:
consumer.receive(
on_event=on_event,
starting_position="-1", # Beginning of stream
)
```
### With Blob Checkpoint Store (Production)
```python
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="$Default",
credential=DefaultAzureCredential(),
checkpoint_store=checkpoint_store
)
def on_event(partition_context, event):
print(f"Received: {event.body_as_str()}")
# Checkpoint after processing
partition_context.update_checkpoint(event)
with consumer:
consumer.receive(on_event=on_event)
```
## Async Client
```python
from azure.eventhub.aio import EventHubProducerClient, EventHubConsumerClient
from azure.identity.aio import DefaultAzureCredential
import asyncio
async def send_events():
credential = DefaultAzureCredential()
async with EventHubProducerClient(
fully_qualified_namespace="<namespace>.servicebus.windows.net",
eventhub_name="my-eventhub",
credential=credential
) as producer:
batch = await producer.create_batch()
batch.add(EventData("Async event"))
await producer.send_batch(batch)
async def receive_events():
async def on_event(partition_context, event):
print(event.body_as_str())
await partition_context.update_checkpoint(event)
async with EventHubConsumerClient(
fully_qualified_namespace="<namespace>.servicebus.windows.net",
eventhub_name="my-eventhub",
consumer_group="$Default",
credential=DefaultAzureCredential()
) as consumer:
await consumer.receive(on_event=on_event)
asyncio.run(send_events())
```
## Event Properties
```python
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
```python
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
1. **Use batches** for sending multiple events
2. **Use checkpoint store** in production for reliable processing
3. **Use async client** for high-throughput scenarios
4. **Use partition keys** for ordered delivery within a partition
5. **Handle batch size limits** — catch ValueError when batch is full
6. **Use context managers** (`with`/`async with`) for proper cleanup
7. **Set appropriate consumer groups** for different applications
## Reference Files
| File | Contents |
|------|----------|
| [references/checkpointing.md](references/checkpointing.md) | Checkpoint store patterns, blob checkpointing, checkpoint strategies |
| [references/partitions.md](references/partitions.md) | Partition management, load balancing, starting positions |
| [scripts/setup_consumer.py](scripts/setup_consumer.py) | CLI for Event Hub info, consumer setup, and event sending/receiving |More DevOps & Infrastructure skills
azure-ai
microsoft/azure-skills
Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.
appinsights-instrumentation
microsoft/azure-skills
Guidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. WHEN: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM best practices.
azure-storage
microsoft/azure-skills
Azure Storage Services including Blob Storage, File Shares, Queue Storage, Table Storage, and Data Lake. Answers questions about storage access tiers (hot, cool, cold, archive), when to use each tier, and tier comparison. Provides object storage, SMB file shares, async messaging, NoSQL key-value, and big data analytics. Includes lifecycle management. USE FOR: blob storage, file shares, queue storage, table storage, data lake, upload files, download blobs, storage accounts, access tiers, storage tiers, hot cool cold archive, storage tier comparison, when to use storage tiers, lifecycle management, Azure Storage concepts. DO NOT USE FOR: SQL databases, Cosmos DB (use azure-prepare), messaging with Event Hubs or Service Bus (use azure-messaging).

