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temporalio__skill-temporal-…/references/python/observability.md
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# Python SDK Observability
## Overview
The Python SDK provides comprehensive observability through logging, metrics, tracing, and visibility (Search Attributes).
## Logging
### Workflow Logging (Replay-Safe)
Use `workflow.logger` for replay-safe logging that avoids duplicate messages:
```python
@workflow.defn
class MyWorkflow:
@workflow.run
async def run(self, name: str) -> str:
workflow.logger.info("Workflow started", extra={"name": name})
result = await workflow.execute_activity(
my_activity,
start_to_close_timeout=timedelta(minutes=5),
)
workflow.logger.info("Activity completed", extra={"result": result})
return result
```
The workflow logger automatically:
- Suppresses duplicate logs during replay
- Includes workflow context (workflow ID, run ID, etc.)
### Activity Logging
Use `activity.logger` for context-aware activity logging:
```python
@activity.defn
async def process_order(order_id: str) -> str:
activity.logger.info(f"Processing order {order_id}")
# Perform work...
activity.logger.info("Order processed successfully")
return "completed"
```
Activity logger includes:
- Activity ID, type, and task queue
- Workflow ID and run ID
- Attempt number (for retries)
### Customizing Logger Configuration
```python
import logging
# Applies to temporalio.workflow.logger and temporalio.activity.logger, as Temporal inherits the default logger
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
)
```
## Metrics
### Enabling SDK Metrics
```python
from temporalio.client import Client
from temporalio.runtime import Runtime, TelemetryConfig, PrometheusConfig
# Create a custom runtime
runtime = Runtime(
telemetry=TelemetryConfig(
metrics=PrometheusConfig(bind_address="0.0.0.0:9000")
)
)
# Set it as the global default BEFORE any Client/Worker is created
# Do this only ONCE.
Runtime.set_default(runtime, error_if_already_set=True)
# error_if_already_set can be False if you want to overwrite an existing default without raising.
# ...elsewhere, client = ... as usual
```
### Key SDK Metrics
- `temporal_request` - Client requests to server
- `temporal_workflow_task_execution_latency` - Workflow task processing time
- `temporal_activity_execution_latency` - Activity execution time
- `temporal_workflow_task_replay_latency` - Replay duration
## Search Attributes (Visibility)
See the Search Attributes section of `references/python/data-handling.md`
## Best Practices
1. Use `workflow.logger` in workflows, `activity.logger` in activities
2. Don't use print() in workflows - it will produce duplicate output on replay
3. Configure metrics for production monitoring
4. Use Search Attributes for business-level visibility