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Add this skill
npx mdskills install sickn33/azure-eventhub-pyComprehensive Azure Event Hubs reference with clear examples for producers, consumers, and checkpointing
Big data streaming platform for high-throughput event ingestion.
pip install azure-eventhub azure-identity
# For checkpointing with blob storage
pip install azure-eventhub-checkpointstoreblob-aio
EVENT_HUB_FULLY_QUALIFIED_NAMESPACE=.servicebus.windows.net
EVENT_HUB_NAME=my-eventhub
STORAGE_ACCOUNT_URL=https://.blob.core.windows.net
CHECKPOINT_CONTAINER=checkpoints
from azure.identity import DefaultAzureCredential
from azure.eventhub import EventHubProducerClient, EventHubConsumerClient
credential = DefaultAzureCredential()
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="$Default",
credential=credential
)
| Client | Purpose |
|---|---|
EventHubProducerClient | Send events to Event Hub |
EventHubConsumerClient | Receive events from Event Hub |
BlobCheckpointStore | Track consumer progress |
from azure.eventhub import EventHubProducerClient, EventData
from azure.identity import DefaultAzureCredential
producer = EventHubProducerClient(
fully_qualified_namespace=".servicebus.windows.net",
eventhub_name="my-eventhub",
credential=DefaultAzureCredential()
)
with producer:
# Create batch (handles size limits)
event_data_batch = producer.create_batch()
for i in range(10):
try:
event_data_batch.add(EventData(f"Event {i}"))
except ValueError:
# Batch is full, send and create new one
producer.send_batch(event_data_batch)
event_data_batch = producer.create_batch()
event_data_batch.add(EventData(f"Event {i}"))
# Send remaining
producer.send_batch(event_data_batch)
# By partition ID
event_data_batch = producer.create_batch(partition_id="0")
# By partition key (consistent hashing)
event_data_batch = producer.create_batch(partition_key="user-123")
from azure.eventhub import EventHubConsumerClient
def on_event(partition_context, event):
print(f"Partition: {partition_context.partition_id}")
print(f"Data: {event.body_as_str()}")
partition_context.update_checkpoint(event)
consumer = EventHubConsumerClient(
fully_qualified_namespace=".servicebus.windows.net",
eventhub_name="my-eventhub",
consumer_group="$Default",
credential=DefaultAzureCredential()
)
with consumer:
consumer.receive(
on_event=on_event,
starting_position="-1", # Beginning of stream
)
from azure.eventhub import EventHubConsumerClient
from azure.eventhub.extensions.checkpointstoreblob import BlobCheckpointStore
from azure.identity import DefaultAzureCredential
checkpoint_store = BlobCheckpointStore(
blob_account_url="https://.blob.core.windows.net",
container_name="checkpoints",
credential=DefaultAzureCredential()
)
consumer = EventHubConsumerClient(
fully_qualified_namespace=".servicebus.windows.net",
eventhub_name="my-eventhub",
consumer_group="$Default",
credential=DefaultAzureCredential(),
checkpoint_store=checkpoint_store
)
def on_event(partition_context, event):
print(f"Received: {event.body_as_str()}")
# Checkpoint after processing
partition_context.update_checkpoint(event)
with consumer:
consumer.receive(on_event=on_event)
from azure.eventhub.aio import EventHubProducerClient, EventHubConsumerClient
from azure.identity.aio import DefaultAzureCredential
import asyncio
async def send_events():
credential = DefaultAzureCredential()
async with EventHubProducerClient(
fully_qualified_namespace=".servicebus.windows.net",
eventhub_name="my-eventhub",
credential=credential
) as producer:
batch = await producer.create_batch()
batch.add(EventData("Async event"))
await producer.send_batch(batch)
async def receive_events():
async def on_event(partition_context, event):
print(event.body_as_str())
await partition_context.update_checkpoint(event)
async with EventHubConsumerClient(
fully_qualified_namespace=".servicebus.windows.net",
eventhub_name="my-eventhub",
consumer_group="$Default",
credential=DefaultAzureCredential()
) as consumer:
await consumer.receive(on_event=on_event)
asyncio.run(send_events())
event = 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)
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']}")
with/async with) for proper cleanup| 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 |
Install via CLI
npx mdskills install sickn33/azure-eventhub-pyAzure Eventhub Py is a free, open-source AI agent skill. |
Install Azure Eventhub Py with a single command:
npx mdskills install sickn33/azure-eventhub-pyThis downloads the skill files into your project and your AI agent picks them up automatically.
Azure Eventhub Py works with Claude Code, Claude Desktop, Cursor, Vscode Copilot, Windsurf, Continue Dev, Codex, Gemini Cli, Amp, Roo Code, Goose, Opencode, Trae, Qodo, Command Code. Skills use the open SKILL.md format which is compatible with any AI coding agent that reads markdown instructions.