feat: Add Official Microsoft & Gemini Skills (845+ Total)
🚀 Impact Significantly expands the capabilities of **Antigravity Awesome Skills** by integrating official skill collections from **Microsoft** and **Google Gemini**. This update increases the total skill count to **845+**, making the library even more comprehensive for AI coding assistants. ✨ Key Changes 1. New Official Skills - **Microsoft Skills**: Added a massive collection of official skills from [microsoft/skills](https://github.com/microsoft/skills). - Includes Azure, .NET, Python, TypeScript, and Semantic Kernel skills. - Preserves the original directory structure under `skills/official/microsoft/`. - Includes plugin skills from the `.github/plugins` directory. - **Gemini Skills**: Added official Gemini API development skills under `skills/gemini-api-dev/`. 2. New Scripts & Tooling - **`scripts/sync_microsoft_skills.py`**: A robust synchronization script that: - Clones the official Microsoft repository. - Preserves the original directory heirarchy. - Handles symlinks and plugin locations. - Generates attribution metadata. - **`scripts/tests/inspect_microsoft_repo.py`**: Debug tool to inspect the remote repository structure. - **`scripts/tests/test_comprehensive_coverage.py`**: Verification script to ensure 100% of skills are captured during sync. 3. Core Improvements - **`scripts/generate_index.py`**: Enhanced frontmatter parsing to safely handle unquoted values containing `@` symbols and commas (fixing issues with some Microsoft skill descriptions). - **`package.json`**: Added `sync:microsoft` and `sync:all-official` scripts for easy maintenance. 4. Documentation - Updated `README.md` to reflect the new skill counts (845+) and added Microsoft/Gemini to the provider list. - Updated `CATALOG.md` and `skills_index.json` with the new skills. 🧪 Verification - Ran `scripts/tests/test_comprehensive_coverage.py` to verify all Microsoft skills are detected. - Validated `generate_index.py` fixes by successfully indexing the new skills.
This commit is contained in:
Ahmed Rehan
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skills/official/microsoft/python/messaging/eventhub/SKILL.md
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skills/official/microsoft/python/messaging/eventhub/SKILL.md
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---
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name: azure-eventhub-py
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description: |
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Azure Event Hubs SDK for Python streaming. Use for high-throughput event ingestion, producers, consumers, and checkpointing.
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Triggers: "event hubs", "EventHubProducerClient", "EventHubConsumerClient", "streaming", "partitions".
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package: azure-eventhub
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---
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# Azure Event Hubs SDK for Python
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Big data streaming platform for high-throughput event ingestion.
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## Installation
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```bash
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pip install azure-eventhub azure-identity
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# For checkpointing with blob storage
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pip install azure-eventhub-checkpointstoreblob-aio
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```
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## Environment Variables
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```bash
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EVENT_HUB_FULLY_QUALIFIED_NAMESPACE=<namespace>.servicebus.windows.net
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EVENT_HUB_NAME=my-eventhub
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STORAGE_ACCOUNT_URL=https://<account>.blob.core.windows.net
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CHECKPOINT_CONTAINER=checkpoints
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```
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## Authentication
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```python
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from azure.identity import DefaultAzureCredential
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from azure.eventhub import EventHubProducerClient, EventHubConsumerClient
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credential = DefaultAzureCredential()
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namespace = "<namespace>.servicebus.windows.net"
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eventhub_name = "my-eventhub"
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# Producer
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producer = EventHubProducerClient(
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fully_qualified_namespace=namespace,
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eventhub_name=eventhub_name,
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credential=credential
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)
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# Consumer
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consumer = EventHubConsumerClient(
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fully_qualified_namespace=namespace,
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eventhub_name=eventhub_name,
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consumer_group="$Default",
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credential=credential
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)
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```
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## Client Types
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| Client | Purpose |
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|--------|---------|
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| `EventHubProducerClient` | Send events to Event Hub |
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| `EventHubConsumerClient` | Receive events from Event Hub |
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| `BlobCheckpointStore` | Track consumer progress |
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## Send Events
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```python
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from azure.eventhub import EventHubProducerClient, EventData
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from azure.identity import DefaultAzureCredential
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producer = EventHubProducerClient(
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fully_qualified_namespace="<namespace>.servicebus.windows.net",
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eventhub_name="my-eventhub",
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credential=DefaultAzureCredential()
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)
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with producer:
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# Create batch (handles size limits)
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event_data_batch = producer.create_batch()
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for i in range(10):
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try:
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event_data_batch.add(EventData(f"Event {i}"))
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except ValueError:
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# Batch is full, send and create new one
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producer.send_batch(event_data_batch)
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event_data_batch = producer.create_batch()
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event_data_batch.add(EventData(f"Event {i}"))
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# Send remaining
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producer.send_batch(event_data_batch)
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```
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### Send to Specific Partition
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```python
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# By partition ID
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event_data_batch = producer.create_batch(partition_id="0")
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# By partition key (consistent hashing)
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event_data_batch = producer.create_batch(partition_key="user-123")
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```
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## Receive Events
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### Simple Receive
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```python
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from azure.eventhub import EventHubConsumerClient
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def on_event(partition_context, event):
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print(f"Partition: {partition_context.partition_id}")
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print(f"Data: {event.body_as_str()}")
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partition_context.update_checkpoint(event)
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consumer = EventHubConsumerClient(
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fully_qualified_namespace="<namespace>.servicebus.windows.net",
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eventhub_name="my-eventhub",
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consumer_group="$Default",
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credential=DefaultAzureCredential()
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)
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with consumer:
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consumer.receive(
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on_event=on_event,
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starting_position="-1", # Beginning of stream
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)
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```
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### With Blob Checkpoint Store (Production)
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```python
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from azure.eventhub import EventHubConsumerClient
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from azure.eventhub.extensions.checkpointstoreblob import BlobCheckpointStore
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from azure.identity import DefaultAzureCredential
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checkpoint_store = BlobCheckpointStore(
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blob_account_url="https://<account>.blob.core.windows.net",
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container_name="checkpoints",
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credential=DefaultAzureCredential()
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)
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consumer = EventHubConsumerClient(
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fully_qualified_namespace="<namespace>.servicebus.windows.net",
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eventhub_name="my-eventhub",
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consumer_group="$Default",
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credential=DefaultAzureCredential(),
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checkpoint_store=checkpoint_store
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)
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def on_event(partition_context, event):
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print(f"Received: {event.body_as_str()}")
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# Checkpoint after processing
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partition_context.update_checkpoint(event)
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with consumer:
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consumer.receive(on_event=on_event)
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```
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## Async Client
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```python
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from azure.eventhub.aio import EventHubProducerClient, EventHubConsumerClient
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from azure.identity.aio import DefaultAzureCredential
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import asyncio
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async def send_events():
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credential = DefaultAzureCredential()
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async with EventHubProducerClient(
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fully_qualified_namespace="<namespace>.servicebus.windows.net",
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eventhub_name="my-eventhub",
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credential=credential
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) as producer:
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batch = await producer.create_batch()
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batch.add(EventData("Async event"))
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await producer.send_batch(batch)
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async def receive_events():
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async def on_event(partition_context, event):
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print(event.body_as_str())
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await partition_context.update_checkpoint(event)
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async with EventHubConsumerClient(
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fully_qualified_namespace="<namespace>.servicebus.windows.net",
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eventhub_name="my-eventhub",
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consumer_group="$Default",
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credential=DefaultAzureCredential()
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) as consumer:
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await consumer.receive(on_event=on_event)
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asyncio.run(send_events())
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```
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## Event Properties
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```python
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event = EventData("My event body")
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# Set properties
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event.properties = {"custom_property": "value"}
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event.content_type = "application/json"
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# Read properties (on receive)
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print(event.body_as_str())
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print(event.sequence_number)
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print(event.offset)
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print(event.enqueued_time)
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print(event.partition_key)
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```
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## Get Event Hub Info
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```python
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with producer:
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info = producer.get_eventhub_properties()
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print(f"Name: {info['name']}")
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print(f"Partitions: {info['partition_ids']}")
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for partition_id in info['partition_ids']:
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partition_info = producer.get_partition_properties(partition_id)
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print(f"Partition {partition_id}: {partition_info['last_enqueued_sequence_number']}")
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```
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## Best Practices
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1. **Use batches** for sending multiple events
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2. **Use checkpoint store** in production for reliable processing
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3. **Use async client** for high-throughput scenarios
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4. **Use partition keys** for ordered delivery within a partition
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5. **Handle batch size limits** — catch ValueError when batch is full
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6. **Use context managers** (`with`/`async with`) for proper cleanup
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7. **Set appropriate consumer groups** for different applications
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## Reference Files
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| File | Contents |
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|------|----------|
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| [references/checkpointing.md](references/checkpointing.md) | Checkpoint store patterns, blob checkpointing, checkpoint strategies |
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| [references/partitions.md](references/partitions.md) | Partition management, load balancing, starting positions |
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| [scripts/setup_consumer.py](scripts/setup_consumer.py) | CLI for Event Hub info, consumer setup, and event sending/receiving |
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