azure-eventhub-py — скилл Python-стриминга
Скилл для работы с Azure Event Hubs из Python: отправка событий, чтение партиций, чекпоинты в blob-хранилище. Пригодится, когда агент пишет продюсеров и консьюмеров.
npx skills add microsoft/skills --skill azure-eventhub-py -a claude-codeЧто делает azure-eventhub-py
Скилл описывает Python SDK azure-eventhub: как создать EventHubProducerClient и EventHubConsumerClient, собрать батч событий с учётом лимита размера, отправить его в конкретную партицию по partition_id или по ключу, а на приёме — обновлять чекпоинт после обработки. Есть разделы про синхронный и асинхронный клиенты.
Для чекпоинтов нужен отдельный пакет azure-eventhub-checkpointstoreblob-aio и blob-хранилище: BlobCheckpointStore принимает URL аккаунта и имя контейнера. Аутентификация идёт через DefaultAzureCredential — локально он подхватывает Azure CLI или VS Code, в Azure работает через managed identity. Скилл советует не тащить в код строки подключения и ключи: они обходят аудит и ротацию в Entra. В продакшене credential chain ограничивают переменной AZURE_TOKEN_CREDENTIALS=prod.
Перед запуском понадобятся переменные окружения: EVENT_HUB_FULLY_QUALIFIED_NAMESPACE и EVENT_HUB_NAME для любой схемы аутентификации, а для чекпоинтов ещё STORAGE_ACCOUNT_URL и CHECKPOINT_CONTAINER. Клиенты скилл требует оборачивать в контекстный менеджер, иначе сокеты и кэш токенов освобождаются не сразу.
Какие задачи решает
- отправить поток событий в Event Hub батчами
- прочитать события из партиции и не потерять позицию
- настроить чекпоинты в blob-хранилище
- переписать продюсера на асинхронный клиент
- заменить строку подключения на DefaultAzureCredential
Примеры запросов агенту
- напиши продюсера на azure-eventhub, который шлёт батч событий в my-eventhub
- сделай консьюмера с чекпоинтами в BlobCheckpointStore
- переведи отправку событий на асинхронный EventHubProducerClient
Как установить azure-eventhub-py
1Через Skills CLI (Vercel)
npx skills add microsoft/skills --skill azure-eventhub-py -a claude-code2Вручную: положить файлы
~/.claude/skills/azure-eventhub-py/SKILL.mdПапка скилла целиком; для одного проекта — .claude/skills/azure-eventhub-py/
Вручную: положить файлы
.agents/skills/azure-eventhub-py/SKILL.mdДля всех проектов — ~/.agents/skills/
Вручную: положить файлы
.cursor/skills/azure-eventhub-py/SKILL.mdCursor читает и .agents/skills/, и .claude/skills/
1GitHub CLI
gh skill install microsoft/skills azure-eventhub-py2Вручную: положить файлы
.github/skills/azure-eventhub-py/SKILL.mdКомандой платформы
gemini skills install https://github.com/microsoft/skills --path .github/plugins/azure-sdk-python/skills/azure-eventhub-pyВручную: положить файлы
.devin/skills/azure-eventhub-py/SKILL.mdСтарый путь .windsurf/skills/ тоже читается
Claude.ai
Упакуйте папку в zip и загрузите в Settings → Capabilities → Skills
По шагам, с командами для каждой платформы: Как установить скилл в Claude Code: пять способов
Вопросы о azure-eventhub-py
Как установить azure-eventhub-py в Claude?
Выполните npx skills add microsoft/skills --skill azure-eventhub-py -a claude-code. Скилл окажется в ~/.claude/skills/azure-eventhub-py/SKILL.md.
Что делает azure-eventhub-py?
Даёт агенту рабочие примеры Python SDK для Azure Event Hubs: продюсеры, консьюмеры, партиции и чекпоинты.
Какие пакеты нужны для работы скилла?
azure-eventhub и azure-identity, а для чекпоинтов в blob-хранилище — azure-eventhub-checkpointstoreblob-aio.
Исходный текст
SKILL.md · MIT
---
name: azure-eventhub-py
description: |
Azure Event Hubs SDK for Python streaming. Use for high-throughput event ingestion, producers, consumers, and checkpointing.
Triggers: "event hubs", "EventHubProducerClient", "EventHubConsumerClient", "streaming", "partitions".
license: MIT
metadata:
author: Microsoft
version: "1.0.0"
package: azure-eventhub
---
# 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 # Required for all auth methods
EVENT_HUB_NAME=my-eventhub # Required for all auth methods
STORAGE_ACCOUNT_URL=https://<account>.blob.core.windows.net # Required for checkpoint storage
CHECKPOINT_CONTAINER=checkpoints # Required for checkpoint storage
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production
```
## Authentication & Lifecycle
> **🔑 Two rules apply to every code sample below:**
>
> 1. **Prefer `DefaultAzureCredential`.** It works locally (Azure CLI / VS Code / Developer CLI) and in Azure (managed identity, workload identity) with no code change. Avoid connection strings, account/API keys — they bypass Entra audit and rotation.
> - Local dev: `DefaultAzureCredential` works as-is.
> - Production: set `AZURE_TOKEN_CREDENTIALS=prod` (or `AZURE_TOKEN_CREDENTIALS=<specific_credential>`) to constrain the credential chain to production-safe credentials.
> 2. **Wrap every client in a context manager** so HTTP transports, sockets, and token caches are released deterministically:
> - Sync: `with <Client>(...) as client:`
> - Async: `async with <Client>(...) as client:` **and** `async with DefaultAzureCredential() as credential:` (from `azure.identity.aio`)
>
> Snippets may abbreviate this setup, but production code should always follow both rules.
```python
from azure.identity import DefaultAzureCredential, ManagedIdentityCredential
from azure.eventhub import EventHubProducerClient, EventHubConsumerClient
# Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
credential = DefaultAzureCredential(require_envvar=True)
# Or use a specific credential directly in production:
# See https://learn.microsoft.com/python/api/overview/azure/identity-readme?view=azure-python#credential-classes
# credential = ManagedIdentityCredential()
namespace = "<namespace>.servicebus.windows.net"
eventhub_name = "my-eventhub"
# Producer
with EventHubProducerClient(
fully_qualified_namespace=namespace,
eventhub_name=eventhub_name,
credential=credential
) as producer:
# Use producer here (see following sections for operations)
...
# Consumer
with EventHubConsumerClient(
fully_qualified_namespace=namespace,
eventhub_name=eventhub_name,
consumer_group="$Default",
credential=credential
) as consumer:
# Use consumer here (see following sections for operations)
...
```
## Client Types
| Client | Purpose |
|--------|---------|
| `EventHubProducerClient` | Send events to Event Hub |
| `EventHubConsumerClient` | Receive events from Event Hub |
| `BlobCheckpointStore` | Track consumer progress |
## Send Events
```python
from azure.eventhub import EventHubProducerClient, EventData
from azure.identity import DefaultAzureCredential
with EventHubProducerClient(
fully_qualified_namespace="<namespace>.servicebus.windows.net",
eventhub_name="my-eventhub",
credential=DefaultAzureCredential()
) as producer:
# Create batch (handles size limits)
event_data_batch = producer.create_batch()
for i in range(10):
try:
event_data_batch.add(EventData(f"Event {i}"))
except ValueError:
# Batch is full, send and create new one
producer.send_batch(event_data_batch)
event_data_batch = producer.create_batch()
event_data_batch.add(EventData(f"Event {i}"))
# Send remaining
producer.send_batch(event_data_batch)
```
### Send to Specific Partition
```python
# By partition ID
event_data_batch = producer.create_batch(partition_id="0")
# By partition key (consistent hashing)
event_data_batch = producer.create_batch(partition_key="user-123")
```
## Receive Events
### Simple Receive
```python
from azure.eventhub import EventHubConsumerClient
def on_event(partition_context, event):
print(f"Partition: {partition_context.partition_id}")
print(f"Data: {event.body_as_str()}")
partition_context.update_checkpoint(event)
with EventHubConsumerClient(
fully_qualified_namespace="<namespace>.servicebus.windows.net",
eventhub_name="my-eventhub",
consumer_group="$Default",
credential=DefaultAzureCredential()
) as 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()
)
with EventHubConsumerClient(
fully_qualified_namespace="<namespace>.servicebus.windows.net",
eventhub_name="my-eventhub",
consumer_group="$Default",
credential=DefaultAzureCredential(),
checkpoint_store=checkpoint_store
) as consumer:
def on_event(partition_context, event):
print(f"Received: {event.body_as_str()}")
# Checkpoint after processing
partition_context.update_checkpoint(event)
consumer.receive(on_event=on_event)
```
## Async Client
```python
from azure.eventhub.aio import EventHubProducerClient, EventHubConsumerClient
from azure.identity.aio import DefaultAzureCredential
import asyncio
async def send_events():
credential = DefaultAzureCredential()
async with EventHubProducerClient(
fully_qualified_namespace="<namespace>.servicebus.windows.net",
eventhub_name="my-eventhub",
credential=credential
) as producer:
batch = await producer.create_batch()
batch.add(EventData("Async event"))
await producer.send_batch(batch)
async def receive_events():
async def on_event(partition_context, event):
print(event.body_as_str())
await partition_context.update_checkpoint(event)
async with EventHubConsumerClient(
fully_qualified_namespace="<namespace>.servicebus.windows.net",
eventhub_name="my-eventhub",
consumer_group="$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. **Pick sync OR async and stay consistent.** Do not mix `azure.xxx` sync clients with `azure.xxx.aio` async clients in the same call path. Choose one mode per module.
2. **Always use context managers for clients and async credentials.** Wrap every client in `with Client(...) as client:` (sync) or `async with Client(...) as client:` (async) for proper cleanup. For async `DefaultAzureCredential` from `azure.identity.aio`, also use `async with credential:` so tokens and transports are cleaned up.
3. **Use `DefaultAzureCredential`** for portable auth across local dev and Azure (avoid connection strings / API keys when possible).
4. **Use batches** for sending multiple events
5. **Use checkpoint store** in production for reliable processing
6. **Use async client** for high-throughput scenarios
7. **Use partition keys** for ordered delivery within a partition
8. **Handle batch size limits** — catch ValueError when batch is full
9. **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 |
© Microsoft · MIT · microsoft/skills