PennyLane has support for Python’s logging framework. PennyLane defines all logging configuration in a static TOML file, log_config.toml, which can be customized to support rules for a given user or system environment.

To see the default logging options you can explore the contexts of log_config.toml at the path given from pennylane.logging.config_path().

Enabling logging

To enable logging support with the default options defined in log_config.toml simply call pennylane.logging.enable_logging() after importing PennyLane:

import pennylane as qml

This will ensure all levels of the execution pipeline logs function entries, and outputs to the default configured handler, which is directed to the standard output stream. To also direct logging output to a file named qml_debug.log in the directory of execution, the qml_debug_file handler can be added to the defined loggers in log_config.toml as follows:

# Control logging across pennylane
handlers = ["qml_debug_stream", "qml_debug_file"]
level = "DEBUG" # Set to TRACE for highest verbosity
propagate = false

For more info on the customization of the logging options, please see the logging development guide at Logging development guidelines, and the Python logging documentation.