Skip to content

Inventory Current Balances

InventoryCurrentBalances(perfdb)

Class used for handling Inventory Current Balances. Can be accessed via perfdb.inventory.current_balances.

Parameters:

  • perfdb

    (PerfDB) –

    Top level object carrying all functionality and the connection handler.

Source code in echo_postgres/perfdb_root.py
def __init__(self, perfdb: e_pg.PerfDB) -> None:
    """Base class that all subclasses should inherit from.

    Parameters
    ----------
    perfdb : PerfDB
        Top level object carrying all functionality and the connection handler.

    """
    self._perfdb: e_pg.PerfDB = perfdb

get(center_names=None, storage_location_names=None, material_descriptions=None, material_sap_ids=None, is_serviceable_stock=None, filter_type='and', output_type='pl.DataFrame')

Gets inventory current balances.

This is a read-only view that calculates balances from transaction history.

The most useful keys/columns returned are:

  • center_name (index level 0)
  • storage_location_name (index level 1)
  • material_description (index level 2)
  • material_sap_id
  • base_unit
  • total_inflow
  • total_outflow
  • current_balance
  • last_movement_date
  • transaction_count

Parameters:

  • center_names

    (list[str] | None, default: None ) –

    List of center names to filter the results. By default None.

  • storage_location_names

    (list[str] | None, default: None ) –

    List of storage location names to filter the results. By default None.

  • material_descriptions

    (list[str] | None, default: None ) –

    List of material descriptions to filter the results. By default None.

  • material_sap_ids

    (list[int] | None, default: None ) –

    List of material SAP IDs to filter the results. By default None.

  • is_serviceable_stock

    (bool | None, default: None ) –

    Filter by serviceable stock status. By default None.

  • filter_type

    (Literal['and', 'or'], default: 'and' ) –

    How to treat multiple filters. Can be one of ["and", "or"]. By default "and".

  • output_type

    (Literal['dict', 'DataFrame', 'pl.DataFrame'], default: 'pl.DataFrame' ) –

    Output type of the data. Can be one of ["dict", "DataFrame", "pl.DataFrame"]. By default "pl.DataFrame".

Returns:

  • dict[int, dict[str, Any]]

    In case output_type is "dict", returns a dictionary in the format {center_name: {storage_location_name: {material_description: {column_name: value}}}}.

  • DataFrame

    In case output_type is "DataFrame", returns a pandas DataFrame with index as a MultiIndex of center_name, storage_location_name, material_description.

  • DataFrame

    In case output_type is "pl.DataFrame", returns a Polars DataFrame.

Source code in echo_postgres/inventory_current_balances.py
@validate_call
def get(
    self,
    center_names: list[str] | None = None,
    storage_location_names: list[str] | None = None,
    material_descriptions: list[str] | None = None,
    material_sap_ids: list[int] | None = None,
    is_serviceable_stock: bool | None = None,
    filter_type: Literal["and", "or"] = "and",
    output_type: Literal["dict", "DataFrame", "pl.DataFrame"] = "pl.DataFrame",
) -> dict[int, dict[str, Any]] | pd.DataFrame | pl.DataFrame:
    """Gets inventory current balances.

    This is a read-only view that calculates balances from transaction history.

    The most useful keys/columns returned are:

    - center_name (index level 0)
    - storage_location_name (index level 1)
    - material_description (index level 2)
    - material_sap_id
    - base_unit
    - total_inflow
    - total_outflow
    - current_balance
    - last_movement_date
    - transaction_count

    Parameters
    ----------
    center_names : list[str] | None, optional
        List of center names to filter the results. By default None.
    storage_location_names : list[str] | None, optional
        List of storage location names to filter the results. By default None.
    material_descriptions : list[str] | None, optional
        List of material descriptions to filter the results. By default None.
    material_sap_ids : list[int] | None, optional
        List of material SAP IDs to filter the results. By default None.
    is_serviceable_stock : bool | None, optional
        Filter by serviceable stock status. By default None.
    filter_type : Literal["and", "or"], optional
        How to treat multiple filters. Can be one of ["and", "or"]. By default "and".
    output_type : Literal["dict", "DataFrame", "pl.DataFrame"], optional
        Output type of the data. Can be one of ["dict", "DataFrame", "pl.DataFrame"].
        By default "pl.DataFrame".

    Returns
    -------
    dict[int, dict[str, Any]]
        In case output_type is "dict", returns a dictionary in the format {center_name: {storage_location_name: {material_description: {column_name: value}}}}.
    pd.DataFrame
        In case output_type is "DataFrame", returns a pandas DataFrame with index as a MultiIndex of center_name, storage_location_name, material_description.
    pl.DataFrame
        In case output_type is "pl.DataFrame", returns a Polars DataFrame.
    """
    where = self._check_get_args(
        center_names=center_names,
        storage_location_names=storage_location_names,
        material_descriptions=material_descriptions,
        material_sap_ids=material_sap_ids,
        is_serviceable_stock=is_serviceable_stock,
        filter_type=filter_type,
    )

    query = sql.SQL(
        "SELECT * FROM performance.v_inv_current_balances {where} ORDER BY center_name, storage_location_name, material_description",
    ).format(where=where)

    df = self._perfdb.conn.read_to_polars(query, schema_overrides=self._cols_schema)

    return convert_output(
        df,
        output_type,
        index_col=["center_name", "storage_location_name", "material_description"],
        nest_by_index=True,
    )