leaf_engine.adapt.load
======================

.. py:module:: leaf_engine.adapt.load

.. autoapi-nested-parse::

   This module contains function to load standard Adapt outputs into their
   corresponding data stores.



Attributes
----------

.. autoapisummary::

   leaf_engine.adapt.load.LaneAdaptDetaiLoadException
   leaf_engine.adapt.load.LanePlansLoadException
   leaf_engine.adapt.load.NetworkMoveLoadException
   leaf_engine.adapt.load.caller
   leaf_engine.adapt.load.logger
   leaf_engine.adapt.load.planning_caller


Functions
---------

.. autoapisummary::

   leaf_engine.adapt.load.filter_network_moves
   leaf_engine.adapt.load.insert_carrier_churn
   leaf_engine.adapt.load.insert_consolidated_flex
   leaf_engine.adapt.load.insert_lane_adapt_detail
   leaf_engine.adapt.load.insert_lane_plans
   leaf_engine.adapt.load.insert_lane_quick_ref
   leaf_engine.adapt.load.insert_network_moves
   leaf_engine.adapt.load.insert_observations_patterns
   leaf_engine.adapt.load.insert_should_be_flex
   leaf_engine.adapt.load.is_allowed_column
   leaf_engine.adapt.load.read_carrier_churn
   leaf_engine.adapt.load.read_consolidated_flex
   leaf_engine.adapt.load.read_lane_adapt_detail
   leaf_engine.adapt.load.read_lane_plans
   leaf_engine.adapt.load.read_lane_quick_ref
   leaf_engine.adapt.load.read_network_moves
   leaf_engine.adapt.load.read_observations_patterns
   leaf_engine.adapt.load.read_should_be_flex
   leaf_engine.adapt.load.remove_unwanted_columns
   leaf_engine.adapt.load.transform_network_moves


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

.. py:function:: filter_network_moves(moves_df: pandas.DataFrame, company_id: int, batch_date: str, incl_record_types: list[str]) -> pandas.DataFrame

   Filters moves with lanes that are not in the `analytics.lane` table or that
   have been previously inserted.


.. py:function:: insert_carrier_churn(company_id: int, company_name: str, batch_date: str, equipment_class: str, dry_run: bool = False) -> None

.. py:function:: insert_consolidated_flex(company_id: int, company_name: str, batch_date: str, equipment_class: str, dry_run: bool = False) -> None

.. py:function:: insert_lane_adapt_detail(company_id: int, company_name: str, batch_date: str, equipment_class: str, dry_run: bool = False)

.. py:function:: insert_lane_plans(company_id: int, company_name: str, batch_date: str, equipment_class: str, dry_run: bool = False) -> pandas.DataFrame

   Inserts lane plans into DB.

   Read the lane plans file(s) from the company's data directory.


.. py:function:: insert_lane_quick_ref(company_id: int, company_name: str, batch_date: str, equipment_class: str, dry_run: bool = False) -> None

   Inserts lane quick ref into DB.

   Read the lane quick ref file(s) from the company's data directory.


.. py:function:: insert_network_moves(company_id: int, company_name: str, batch_date: str, equipment_class: str, record_type: str, incl_record_types: list[str], dry_run: bool = False) -> None

   Reads, transforms, filters, validates network moves and makes insertion
   calls.

   Before inserting records, filters existing moves from the same
   `batch_date` from moves DataFrame, then deletes existing moves for
   `company_id` from batches other than `batch_date`.


.. py:function:: insert_observations_patterns(company_id: int, company_name: str, batch_date: str, equipment_class: str, dry_run: bool = False) -> None

   Inserts observation patterns into DB.

   Read the observation patterns file(s) from the company's data
   directory.


.. py:function:: insert_should_be_flex(company_id: int, company_name: str, batch_date: str, equipment_class: str, dry_run: bool = False) -> None

   Inserts should be flex into DB.

   Read the should be flex file(s) from the company's data directory.


.. py:function:: is_allowed_column(col_name)

.. py:function:: read_carrier_churn(company_id: int, company_name: str, batch_date: str, equipment_class: str) -> pandas.DataFrame

   Reads carrier churn file into pd.DataFrame.


.. py:function:: read_consolidated_flex(company_id: int, company_name: str, batch_date: str, equipment_class: str) -> pandas.DataFrame

   Reads consolidated flex file into pd.DataFrame.


.. py:function:: read_lane_adapt_detail(company_id: int, company_name: str, batch_date: str, equipment_class: str)

.. py:function:: read_lane_plans(company_id: int, company_name: str, batch_date: str, equipment_class: str) -> pandas.DataFrame

   Reads lane_plan file into pd.DataFrame.


.. py:function:: read_lane_quick_ref(company_id: int, company_name: str, batch_date: str, equipment_class: str) -> pandas.DataFrame

   Reads lane quick ref file into pd.DataFrame.


.. py:function:: read_network_moves(company_id: int, company_name: str, batch_date: str, equipment_class: str) -> pandas.DataFrame

   Reads network moves file into pd.DataFrame.


.. py:function:: read_observations_patterns(company_id: int, company_name: str, batch_date: str, equipment_class: str) -> pandas.DataFrame

   Reads observation patterns file into pd.DataFrame.

   Combines weekly and daily since the data is stored in separate files
   but the schema is the same. Only the format of the pattern is
   different.


.. py:function:: read_should_be_flex(company_id: int, company_name: str, batch_date: str, equipment_class: str) -> pandas.DataFrame

   Reads should be flex file into pd.DataFrame.


.. py:function:: remove_unwanted_columns(df)

.. py:function:: transform_network_moves(moves_df: pandas.DataFrame, company_id: str, batch_date: str, equipment_class: str, record_type: str, inplace: bool = True) -> pandas.DataFrame

   Transforms network moves to match DB constraints.

   NOTE that by default these transformations are in-place: the
   DataFrame passed as the first argument will be mutated (this is
   because creating a copy will have a high memory cost). Use the
   `inplace` parameter to change this behavior.


.. py:data:: LaneAdaptDetaiLoadException

.. py:data:: LanePlansLoadException

.. py:data:: NetworkMoveLoadException

.. py:data:: caller

.. py:data:: logger

.. py:data:: planning_caller