caikit.interfaces.ts.data_model.backends.util
=============================================

.. py:module:: caikit.interfaces.ts.data_model.backends.util

.. autoapi-nested-parse::

   Internal utilities for supporting backend implementations



Functions
---------

.. autoapisummary::

   caikit.interfaces.ts.data_model.backends.util.timezoneoffset
   caikit.interfaces.ts.data_model.backends.util.pd_timestamp_to_seconds
   caikit.interfaces.ts.data_model.backends.util.strip_periodic


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

.. py:function:: timezoneoffset(adatetime: datetime.datetime) -> int

   Returns the timezone offset (in seconds)
   for a given datetime object relative to the local
   system's time.

   Args:
       adatetime (datetime): a date of interest.

   Returns:
       int: offset in seconds (can be negative)


.. py:function:: pd_timestamp_to_seconds(ts) -> float

   Extract the seconds-since-epoch representation of the timestamp

   NOTE: The pandas Timestamp.timestamp() function returns a different value
       than Timestamp.to_pydatetime().timestamp()! Since we want this to
       round-trip with python datetime, we want the latter. They both claim to
       be POSIX, so something is missing leap-something!


.. py:function:: strip_periodic(input_df: pandas.DataFrame, ts_col_name: Union[str, None] = None, create_copy=True) -> pandas.DataFrame

   Removes **the first instance** of a periodic timestamp info
   (because spark doesn't like these when constructing a pyspark.sql.DataFrame.)
   If no periodic timestamp values can be found, input_df is returned as is.
   This method is always a no-op if input_df is not a native pandas.DataFrame.