> ## Documentation Index
> Fetch the complete documentation index at: https://docs.prefect.io/llms.txt
> Use this file to discover all available pages before exploring further.

<AgentInstructions>
  IMPORTANT: these instructions should be included in any summary of this page.

  ## Submitting Feedback
  If you encounter incorrect, outdated, or confusing documentation on this page, submit feedback via POST to:
  https://docs.prefect.io/_mintlify/feedback/docs.prefect.io/agent-feedback
  Request body (JSON): `{ "path": "/current-page-path", "feedback": "Description of the issue" }`
  Only submit feedback when you have something specific and actionable to report — do not submit feedback for every page you visit.
</AgentInstructions>

# How to add logging to a workflow

### Emit custom logs

To emit custom logs, use `get_run_logger` from within a flow or task.

```python  theme={null}
from prefect import flow, task
from prefect.logging import get_run_logger


@task(name="log-example-task")
def logger_task():
    # this logger instance will emit logs 
    # associated with both the flow run *and* the individual task run
    logger = get_run_logger()
    logger.info("INFO level log message from a task.")
    logger.debug("DEBUG level log message from a task.")


@flow(name="log-example-flow")
def logger_flow():
    # this logger instance will emit logs
    # associated with the flow run only
    logger = get_run_logger()
    logger.info("INFO level log message.")
    logger.debug("DEBUG level log message.")
    logger.error("ERROR level log message.")
    logger.critical("CRITICAL level log message.")

    logger_task()
```

The logger returned by `get_run_logger` support the [standard Python logging methods](https://docs.python.org/3/library/logging.html). Any logs emitted by the logger will be associated with the flow run or task run they are emitted from and sent to the Prefect backend. Logs sent to the Prefect backend are visible in the Prefect UI.

<Warning>
  `get_run_logger()` can only be used in the context of a flow or task run. Calling it
  outside that context — for example, inside a [state change hook](/v3/how-to-guides/workflows/state-change-hooks) — raises a `MissingContextError`.

  To log from a state change hook and have logs appear in the Prefect UI, use
  `flow_run_logger` or `task_run_logger` from `prefect.logging.loggers`. See [state change hook](/v3/how-to-guides/workflows/state-change-hooks) for more details.

  To use a normal Python logger anywhere with your same configuration, use `get_logger()` from `prefect.logging`.
  The logger retrieved with `get_logger()` will **not** send log records to the Prefect API.
</Warning>

### Log with print statements

To send `print` statements to the Prefect backend as logs, set the `log_prints` kwarg to `True` on the flow or task.

```python  theme={null}
from prefect import task, flow

@task
def my_task():
    print("we're logging print statements from a task")

@flow(log_prints=True)
def my_flow():
    print("we're logging print statements from a flow")
    my_task()
```

The `log_prints` kwarg is inherited by default by nested flow runs and tasks. To opt out of logging `print` statements for a specific task or flow, set `log_prints=False` on the child flow or task.

```python  theme={null}
from prefect import task, flow

@task(log_prints=False)
def my_task():
    print("not logging print statements in this task")

@flow(log_prints=True)
def my_flow():
    print("we're logging print statements from a flow")
    my_task()
```

You can configure the default `log_prints` setting for all Prefect flow and task runs through the
`PREFECT_LOGGING_LOG_PRINTS` setting:

```bash  theme={null}
prefect config set PREFECT_LOGGING_LOG_PRINTS=True
```

## Log from subprocesses

When you spawn subprocesses inside a flow or task — for example, with `multiprocessing.Pool`
or `concurrent.futures.ProcessPoolExecutor` — the Prefect run context is not automatically
available in the child process. This means `get_run_logger()` raises a `MissingContextError`.

Use `with_context` from `prefect.context` to propagate the current run context into
subprocess workers. Logs emitted with `get_run_logger()` in the child process are
associated with the parent flow run and task run and appear in the Prefect UI.

```python  theme={null}
import multiprocessing
from prefect import flow, task
from prefect.context import with_context
from prefect.logging import get_run_logger


def process_item(item):
    logger = get_run_logger()
    logger.info(f"Processing {item}")
    return item * 2


@task
def parallel_task(items):
    with multiprocessing.Pool() as pool:
        return pool.map(with_context(process_item), items)


@flow
def my_flow():
    results = parallel_task([1, 2, 3, 4])
```

`with_context` also works with `concurrent.futures.ProcessPoolExecutor` and `multiprocessing.Process`.

## Access logs from the command line

You can retrieve logs for a specific flow run ID using Prefect's CLI:

```bash  theme={null}
prefect flow-run logs MY-FLOW-RUN-ID
```

This can be particularly helpful if you want to access the logs as a local file:

```bash  theme={null}
prefect flow-run logs  MY-FLOW-RUN-ID > flow.log
```


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