skills/codex/azure-eventgrid-py/SKILL.md
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: azure-eventgrid-py description: "Azure Event Grid SDK for Python" --- # Azure Event Grid SDK for Python Event routing service for building event-driven applications with pub/sub semantics. ## Installation ```bash pip install azure-eventgrid azure-identity ``` ## Environment Variables ```bash EVENTGRID_TOPIC_ENDPOINT=https://<topic-name>.<region>.eventgrid.azure.net/api/events EVENTGRID_NAMESPACE_ENDPOINT=https://<namespace
npx skillsauth add frank-luongt/faos-skills-marketplace skills/codex/azure-eventgrid-pyInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Event routing service for building event-driven applications with pub/sub semantics.
pip install azure-eventgrid azure-identity
EVENTGRID_TOPIC_ENDPOINT=https://<topic-name>.<region>.eventgrid.azure.net/api/events
EVENTGRID_NAMESPACE_ENDPOINT=https://<namespace>.<region>.eventgrid.azure.net
from azure.identity import DefaultAzureCredential
from azure.eventgrid import EventGridPublisherClient
credential = DefaultAzureCredential()
endpoint = "https://<topic-name>.<region>.eventgrid.azure.net/api/events"
client = EventGridPublisherClient(endpoint, credential)
| Format | Class | Use Case |
|--------|-------|----------|
| Cloud Events 1.0 | CloudEvent | Standard, interoperable (recommended) |
| Event Grid Schema | EventGridEvent | Azure-native format |
from azure.eventgrid import EventGridPublisherClient, CloudEvent
from azure.identity import DefaultAzureCredential
client = EventGridPublisherClient(endpoint, DefaultAzureCredential())
# Single event
event = CloudEvent(
type="MyApp.Events.OrderCreated",
source="/myapp/orders",
data={"order_id": "12345", "amount": 99.99}
)
client.send(event)
# Multiple events
events = [
CloudEvent(
type="MyApp.Events.OrderCreated",
source="/myapp/orders",
data={"order_id": f"order-{i}"}
)
for i in range(10)
]
client.send(events)
from azure.eventgrid import EventGridEvent
from datetime import datetime, timezone
event = EventGridEvent(
subject="/myapp/orders/12345",
event_type="MyApp.Events.OrderCreated",
data={"order_id": "12345", "amount": 99.99},
data_version="1.0"
)
client.send(event)
event = CloudEvent(
type="MyApp.Events.ItemCreated", # Required: event type
source="/myapp/items", # Required: event source
data={"key": "value"}, # Event payload
subject="items/123", # Optional: subject/path
datacontenttype="application/json", # Optional: content type
dataschema="https://schema.example", # Optional: schema URL
time=datetime.now(timezone.utc), # Optional: timestamp
extensions={"custom": "value"} # Optional: custom attributes
)
event = EventGridEvent(
subject="/myapp/items/123", # Required: subject
event_type="MyApp.ItemCreated", # Required: event type
data={"key": "value"}, # Required: event payload
data_version="1.0", # Required: schema version
topic="/subscriptions/.../topics/...", # Optional: auto-set
event_time=datetime.now(timezone.utc) # Optional: timestamp
)
from azure.eventgrid.aio import EventGridPublisherClient
from azure.identity.aio import DefaultAzureCredential
async def publish_events():
credential = DefaultAzureCredential()
async with EventGridPublisherClient(endpoint, credential) as client:
event = CloudEvent(
type="MyApp.Events.Test",
source="/myapp",
data={"message": "hello"}
)
await client.send(event)
import asyncio
asyncio.run(publish_events())
For Event Grid Namespaces (pull delivery):
from azure.eventgrid.aio import EventGridPublisherClient
# Namespace endpoint (different from custom topic)
namespace_endpoint = "https://<namespace>.<region>.eventgrid.azure.net"
topic_name = "my-topic"
async with EventGridPublisherClient(
endpoint=namespace_endpoint,
credential=DefaultAzureCredential()
) as client:
await client.send(
event,
namespace_topic=topic_name
)
development
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<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-lakebase-provisioned --- # Lakebase Provisioned Patterns and best practices for using Lakebase Provisioned (Databricks managed PostgreSQL) for OLTP workloads. ## When to Use Use this skill when: - Building applications that need a PostgreSQL database for transactional workloads - Adding persistent state to Databricks Apps - Implementing reverse ETL from Delta Lake to an operational database - Storing chat/agent m
tools
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development
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