---
title: How to customize Prefect's logging configuration
sidebarTitle: Customize logging
---

Prefect relies on [the standard Python implementation of logging configuration](https://docs.python.org/3/library/logging.config.html).
The full specification of the default logging configuration for any version of Prefect can always be inspected [here](https://github.com/PrefectHQ/prefect/blob/main/src/prefect/logging/logging.yml).
The default logging level is `INFO`.

### Customize logging configuration

Prefect provides several settings to configure the logging level and individual loggers.

Any value in [Prefect's logging configuration file](https://github.com/PrefectHQ/prefect/blob/main/src/prefect/logging/logging.yml) can be overridden through 
a Prefect setting of the form `PREFECT_LOGGING_[PATH]_[TO]_[KEY]=value` corresponding to the nested address of the field you are configuring.

For example, to change the default logging level for flow runs but not task runs, update your profile with:
```bash
prefect config set PREFECT_LOGGING_LOGGERS_PREFECT_FLOW_RUNS_LEVEL="ERROR"
```
or set the corresponding environment variable:
```bash
export PREFECT_LOGGING_LOGGERS_PREFECT_FLOW_RUNS_LEVEL="ERROR"
```

You can also configure the "root" Python logger. The root logger receives logs from all loggers unless they 
explicitly opt out by disabling propagation. By default, the root logger is configured to output `WARNING` level logs 
to the console. As with other logging settings, you can override this from the environment or in the logging configuration 
file. For example, you can change the level with the `PREFECT_LOGGING_ROOT_LEVEL` environment variable.

In some situations you may want to completely overhaul the Prefect logging configuration by providing your own `logging.yml` file.
You can create your own version of `logging.yml` in one of two ways:

1. Create a `logging.yml` file in your `PREFECT_HOME` directory (default is `~/.prefect`).
2. Specify a custom path to your `logging.yml` file using the `PREFECT_LOGGING_SETTINGS_PATH` setting.

If Prefect cannot find the `logging.yml` file at the specified location, it will fall back to using the default logging configuration.

See the Python [Logging configuration](https://docs.python.org/3/library/logging.config.html#logging.config.dictConfig) 
documentation for more information about the configuration options and syntax used by `logging.yml`.

<Note>
As with all Prefect settings, logging settings are loaded at runtime.
This means that to customize Prefect logging in a remote environment requires setting the appropriate environment variables and/or profile in that environment.
</ Note>

### Formatters

Prefect log formatters specify the format of log messages. 
The default formatting for task and flow run records is 
`"%(asctime)s.%(msecs)03d | %(levelname)-7s | Task run %(task_run_name)r - %(message)s"` for tasks and
similarly `"%(asctime)s.%(msecs)03d | %(levelname)-7s | Flow run %(flow_run_name)r - %(message)s"` for flows.

The variables available to interpolate in log messages vary by logger. 
In addition to the run context, message string, 
and any keyword arguments, flow and task run loggers have access to additional variables.

The flow run logger has the following variables available for formatting:

- `flow_run_name`
- `flow_run_id`
- `flow_name`

The task run logger has the following variables available for formatting:

- `task_run_id`
- `flow_run_id`
- `task_run_name`
- `task_name`
- `flow_run_name`
- `flow_name`

You can specify custom formatting by setting the relevant environment variable or by modifying the formatter in a custom `logging.yml` file as
described earlier. 
For example, the following changes the formatting for the flow runs formatter:


```bash
PREFECT_LOGGING_FORMATTERS_STANDARD_FLOW_RUN_FMT="%(asctime)s.%(msecs)03d | %(levelname)-7s | %(flow_run_id)s - %(message)s"
```

The resulting messages, using the flow run ID instead of name, look like this:


```bash
10:40:01.211 | INFO    | e43a5a80-417a-41c4-a39e-2ef7421ee1fc - Created task run
'othertask-1c085beb-3' for task 'othertask'
```

### Styles

By default, Prefect highlights specific keywords in the console logs with a variety of colors.
You can toggle highlighting on/off with the `PREFECT_LOGGING_COLORS` setting:


```bash
PREFECT_LOGGING_COLORS=False
```

You can also change what gets highlighted and even adjust the colors by updating the styles - see the `styles`
section of [the Prefect logging configuration file](https://github.com/PrefectHQ/prefect/blob/main/src/prefect/logging/logging.yml) for available keys.

<Note>
Note that these style settings only impact the display within a terminal, not the Prefect UI.
</ Note>

You can even build your own handler with a [custom highlighter](https://rich.readthedocs.io/en/stable/highlighting.html#custom-highlighters). 
For example, to additionally highlight emails:

1. Copy and paste the following code into  `my_package_or_module.py` (rename as needed) in the same directory as the flow run 
script; or ideally as part of a Python package so it's available in `site-packages` and accessible anywhere within your environment.

```python
import logging
from typing import Dict, Union

from rich.highlighter import Highlighter

from prefect.logging.handlers import PrefectConsoleHandler
from prefect.logging.highlighters import PrefectConsoleHighlighter

class CustomConsoleHighlighter(PrefectConsoleHighlighter):
    base_style = "log."
    highlights = PrefectConsoleHighlighter.highlights + [
        # ?P<email> is naming this expression as `email`
        r"(?P<email>[\w-]+@([\w-]+\.)+[\w-]+)",
    ]

class CustomConsoleHandler(PrefectConsoleHandler):
    def __init__(
        self,
        highlighter: Highlighter = CustomConsoleHighlighter,
        styles: Dict[str, str] = None,
        level: Union[int, str] = logging.NOTSET,
   ):
        super().__init__(highlighter=highlighter, styles=styles, level=level)
```

2. Update `~/.prefect/logging.yml` to use `my_package_or_module.CustomConsoleHandler` and additionally reference the 
base_style and named expression: `log.email`.

```yaml
    console_flow_runs:
        level: 0
        class: my_package_or_module.CustomConsoleHandler
        formatter: flow_runs
        styles:
            log.email: magenta
            # other styles can be appended here, e.g.
            # log.completed_state: green
```

3. On your next flow run, text that looks like an email is highlighted. For example, `my@email.com` is colored in 
magenta below:

```python
from prefect import flow
from prefect.logging import get_run_logger

@flow
def log_email_flow():
    logger = get_run_logger()
    logger.info("my@email.com")

log_email_flow()
```

### Apply markup in logs

To use [Rich's markup](https://rich.readthedocs.io/en/stable/markup.html#console-markup) in Prefect logs, first 
configure `PREFECT_LOGGING_MARKUP`:


```bash
PREFECT_LOGGING_MARKUP=True
```

The following will highlight "fancy" in red:

```python
from prefect import flow
from prefect.logging import get_run_logger

@flow
def my_flow():
    logger = get_run_logger()
    logger.info("This is [bold red]fancy[/]")

my_flow()
```
<Warning>
**Inaccurate logs could result**

If enabled, strings that contain square brackets may be 
inaccurately interpreted and lead to incomplete output. For example, `DROP TABLE [dbo].[SomeTable];"` outputs 
`DROP TABLE .[SomeTable];`.
</Warning>

## Include logs from other libraries

By default, Prefect won't capture log statements from libraries that your flows
and tasks use. You can tell Prefect to include logs from these libraries with
the `PREFECT_LOGGING_EXTRA_LOGGERS` setting.

To use this setting, specify one or more Python library names to include,
separated by commas. For example, if you want Prefect to capture Dask
and SciPy logging statements with your flow and task run logs, use:

`PREFECT_LOGGING_EXTRA_LOGGERS=dask,scipy`

Configure this setting as an environment variable or in a profile. See
[Settings](/v3/develop/settings-and-profiles/) for more details about how to use settings.