How to customize Prefect's logging configuration
Prefect relies on the standard Python implementation of logging configuration.
The full specification of the default logging configuration for any version of Prefect can always be inspected here.
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 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:
or set the corresponding environment variable:
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:
- Create a
logging.yml
file in yourPREFECT_HOME
directory (default is~/.prefect
). - Specify a custom path to your
logging.yml
file using thePREFECT_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
documentation for more information about the configuration options and syntax used by logging.yml
.
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.
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:
The resulting messages, using the flow run ID instead of name, look like this:
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:
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 for available keys.
Note that these style settings only impact the display within a terminal, not the Prefect UI.
You can even build your own handler with a custom highlighter. For example, to additionally highlight emails:
- 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 insite-packages
and accessible anywhere within your environment.
- Update
~/.prefect/logging.yml
to usemy_package_or_module.CustomConsoleHandler
and additionally reference the base_style and named expression:log.email
.
- On your next flow run, text that looks like an email is highlighted. For example,
my@email.com
is colored in magenta below:
Apply markup in logs
To use Rich’s markup in Prefect logs, first
configure PREFECT_LOGGING_MARKUP
:
The following will highlight “fancy” in red:
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];
.
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 for more details about how to use settings.