leaf_engine.logging
===================

.. py:module:: leaf_engine.logging


Attributes
----------

.. autoapisummary::

   leaf_engine.logging.DATE_FORMAT
   leaf_engine.logging.LOG_FORMAT
   leaf_engine.logging.LOG_NAME
   leaf_engine.logging.logger


Functions
---------

.. autoapisummary::

   leaf_engine.logging._get_file_handler
   leaf_engine.logging._get_log_path
   leaf_engine.logging._get_stream_handler
   leaf_engine.logging.get_logger
   leaf_engine.logging.log
   leaf_engine.logging.log_git
   leaf_engine.logging.log_params
   leaf_engine.logging.log_shape
   leaf_engine.logging.log_spend
   leaf_engine.logging.setup_logger


Module Contents
---------------

.. py:function:: _get_file_handler(file_name: str, level=logging.INFO, mode='a')

.. py:function:: _get_log_path()

.. py:function:: _get_stream_handler(level=logging.INFO)

.. py:function:: get_logger()

.. py:function:: log(*factory_args, **factory_kwargs)

   Decorator factory that allows adding arguments to the _log explicit
   decorator below.

   You can use this decorator to add arbitrary logging to any function
   that takes a pd.DataFrame as its first argument and returns a pd.DataFrame.

   For example, to log the shape before and after an arbitrary function:

   >>> @log(log_fn=lambda df: df.shape, level=logging.INFO)
   >>> def function(df):
   >>>    return df

   Or to specify custom input/output logging functions:
   >>> @log(
   >>>    input_log_fn=lambda df: f"This is the input shape: {df.shape}",
   >>>    output_log_fn=lambda df: df['id'].value_counts(),
   >>>    level=logging.INFO
   >>> )
   >>> def function(df):
   >>>    return df


.. py:function:: log_git() -> None

.. py:function:: log_params(input_params: dict) -> None

.. py:function:: log_shape(*factory_args, **factory_kwargs)

   Decorator factory that allows adding arguments to the log_shape explicit
   decorator below.


.. py:function:: log_spend(*factory_args, **factory_kwargs)

   Decorator factory that allows adding arguments to the log_shape explicit
   decorator below.


.. py:function:: setup_logger(file_name: str, cloudwatch: bool = True)

   Sets up local file and AWS CloudWatch log handlers.

   :param cloudwatch: Enables writing logs to AWS CloudWatch in the
   :type cloudwatch: bool, optional
   :param leaf_engine log group. Defaults to True.:


.. py:data:: DATE_FORMAT
   :value: '%Y-%m-%d %H:%M:%S%z'


.. py:data:: LOG_FORMAT
   :value: '[%(asctime)s] %(levelname)s | %(message)s'


.. py:data:: LOG_NAME
   :value: 'leaf_engine'


.. py:data:: logger