Subcomponent Models

SubcomponentModels(perfdb)

Class used for handling subcomponent models. Can be accessed via perfdb.components.subcomponents.models.

Parameters:

• perfdb

  (PerfDB) –

  Top level object carrying all functionality and the connection handler.

Source code in echo_postgres/subcomponent_models.py

def __init__(self, perfdb: e_pg.PerfDB) -> None:
    """Class used for handling subcomponent models. Can be accessed via `perfdb.components.subcomponents.models`.

    Parameters
    ----------
    perfdb : PerfDB
        Top level object carrying all functionality and the connection handler.
    """
    super().__init__(perfdb)

    from .subcomponent_model_attributes import SubcomponentModelAttributes

    # * subclasses

    self.attributes = SubcomponentModelAttributes(perfdb)

get(component_types=None, subcomponent_models=None, subcomponent_types=None, manufacturers=None, filter_type='and', get_attributes=False, output_type='dict')

Gets all subcomponent models definitions with detailed information.

The most useful keys/columns returned are:

• id
• description
• component_type_id
• subcomponent_type_id
• manufacturer_id
• manufacturer_name

Parameters:

• component_types

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

  Name of the component types to filter the results.

• subcomponent_types

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

  Name of the subcomponent types to filter the results, by default None

• subcomponent_models

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

  Name of the subcomponent models to filter the results, by default None

• manufacturers

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

  Name of the manufacturers to filter the results, by default None

• filter_type

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

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

• get_attributes

  (bool, default: False ) –

  If True, will also get the attributes of the subcomponent models.

• output_type

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

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

Returns:

• dict[str, dict[str, Any]] –

  In case output_type is "dict", returns a dictionary in the format {component_type: {subcomponents_type: {subcomponent_model: {attribute: value, ...}, ...}, ...}, ...}

• DataFrame –

  In case output_type is "DataFrame", returns a DataFrame with the following format: index = MultiIndex[component_type_name, subcomponents_type_name, name], columns = [attribute, ...]

Source code in echo_postgres/subcomponent_models.py

@validate_call
def get(
    self,
    component_types: list[str] | None = None,
    subcomponent_models: list[str] | None = None,
    subcomponent_types: list[str] | None = None,
    manufacturers: list[str] | None = None,
    filter_type: Literal["and", "or"] = "and",
    get_attributes: bool = False,
    output_type: Literal["dict", "DataFrame"] = "dict",
) -> dict[str, int]:
    """Gets all subcomponent models definitions with detailed information.

    The most useful keys/columns returned are:

    - id
    - description
    - component_type_id
    - subcomponent_type_id
    - manufacturer_id
    - manufacturer_name

    Parameters
    ----------
    component_types : list[str] | None
        Name of the component types to filter the results.
    subcomponent_types : list[str] | None, optional
        Name of the subcomponent types to filter the results, by default None
    subcomponent_models : list[str] | None, optional
        Name of the subcomponent models to filter the results, by default None
    manufacturers : list[str] | None, optional
        Name of the manufacturers to filter the results, by default None
    filter_type : Literal["and", "or"], optional
        How to treat multiple filters. Can be one of ["and", "or"]. By default "and"
    get_attributes : bool, optional
        If True, will also get the attributes of the subcomponent models.
    output_type : Literal["dict", "DataFrame"], optional
        Output type of the data. Can be one of ["dict", "DataFrame"]
        By default "dict"

    Returns
    -------
    dict[str, dict[str, Any]]
        In case output_type is "dict", returns a dictionary in the format {component_type: {subcomponents_type: {subcomponent_model: {attribute: value, ...}, ...}, ...}, ...}
    DataFrame
        In case output_type is "DataFrame", returns a DataFrame with the following format: index = MultiIndex[component_type_name, subcomponents_type_name, name], columns = [attribute, ...]
    """
    where = self._check_get_args(
        component_types=component_types,
        subcomponent_models=subcomponent_models,
        subcomponent_types=subcomponent_types,
        filter_type=filter_type,
        manufacturers=manufacturers,
    )

    query = [
        sql.SQL("SELECT * FROM performance.v_subcomponent_models "),
        where,
        sql.SQL(" ORDER BY component_type_name, subcomponent_type_name, name"),
    ]
    query = sql.Composed(query)

    with self._perfdb.conn.reconnect() as conn:
        df = conn.read_to_pandas(query)

    # getting attributes
    if get_attributes:
        # names of the subcomponent models
        got_subcomponent_models = df["name"].tolist()
        attrs: DataFrame = self._perfdb.components.subcomponents.models.attributes.get(
            subcomponent_models=got_subcomponent_models,
            output_type="DataFrame",
            values_only=False,
        )
        if attrs.empty:
            logger.debug("No attributes found for the subcomponent models")
        else:
            # pivot the attributes
            attrs = attrs.reset_index(drop=False).pivot(
                index="subcomponent_model_id",
                columns="attribute_name",
                values="attribute_value",
            )
            # merging the attributes with the subcomponent models
            df = df.set_index("id")
            df = df.merge(attrs, left_index=True, right_index=True, how="left")
            df = df.reset_index(drop=False)

    df = df.set_index(["component_type_name", "subcomponent_type_name", "name"])

    if output_type == "DataFrame":
        return df

    result = df.to_dict(orient="index")
    final_result = {}
    for (component_type_name, subcomponent_type_name, name), values in result.items():
        if component_type_name not in final_result:
            final_result[component_type_name] = {}
        if subcomponent_type_name not in final_result[component_type_name]:
            final_result[component_type_name][subcomponent_type_name] = {}
        final_result[component_type_name][subcomponent_type_name][name] = values

    return final_result

get_ids(component_types=None, subcomponent_types=None, subcomponent_models=None, manufacturers=None, filter_type='and')

Method used to get all subcomponent models and their respective ids.

Parameters:

• component_types

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

  Name of the component types to filter the results.

• subcomponent_types

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

  Name of the subcomponent types to filter the results, by default None

• subcomponent_models

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

  Name of the subcomponent models to filter the results, by default None

• manufacturers

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

  Name of the manufacturers to filter the results, by default None

• filter_type

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

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

Returns:

• dict[str, dict[str, dict[str, int]]] –

  Dictionary with all subcomponents types and their respective ids in the format {component_type: {subcomponents_type: {subcomponent_model: id, ...}, ...}, ...}.

Source code in echo_postgres/subcomponent_models.py

@validate_call
def get_ids(
    self,
    component_types: list[str] | None = None,
    subcomponent_types: list[str] | None = None,
    subcomponent_models: list[str] | None = None,
    manufacturers: list[str] | None = None,
    filter_type: Literal["and", "or"] = "and",
) -> dict[str, dict[str, dict[str, int]]]:
    """Method used to get all subcomponent models and their respective ids.

    Parameters
    ----------
    component_types : list[str] | None
        Name of the component types to filter the results.
    subcomponent_types : list[str] | None, optional
        Name of the subcomponent types to filter the results, by default None
    subcomponent_models : list[str] | None, optional
        Name of the subcomponent models to filter the results, by default None
    manufacturers : list[str] | None, optional
        Name of the manufacturers to filter the results, by default None
    filter_type : Literal["and", "or"], optional
        How to treat multiple filters. Can be one of ["and", "or"]. By default "and"

    Returns
    -------
    dict[str, dict[str, dict[str, int]]]
        Dictionary with all subcomponents types and their respective ids in the format {component_type: {subcomponents_type: {subcomponent_model: id, ...}, ...}, ...}.
    """
    # checking inputs
    where = self._check_get_args(
        component_types=component_types,
        subcomponent_models=subcomponent_models,
        subcomponent_types=subcomponent_types,
        filter_type=filter_type,
        manufacturers=manufacturers,
    )

    query = [
        sql.SQL("SELECT component_type_name, subcomponent_type_name, name, id FROM performance.v_subcomponent_models "),
        where,
        sql.SQL(" ORDER BY component_type_name, subcomponent_type_name, name"),
    ]
    query = sql.Composed(query)

    with self._perfdb.conn.reconnect() as conn:
        df = conn.read_to_pandas(query)

    df = df.set_index(["component_type_name", "subcomponent_type_name", "name"])

    result = df.to_dict(orient="index")
    final_result = {}
    for (component_type_name, subcomponent_type_name, name), values in result.items():
        if component_type_name not in final_result:
            final_result[component_type_name] = {}
        if subcomponent_type_name not in final_result[component_type_name]:
            final_result[component_type_name][subcomponent_type_name] = {}
        final_result[component_type_name][subcomponent_type_name][name] = values["id"]

    return final_result