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Job Types

JobTypes(perfdb)

Class used for handling job types. Can be accessed via perfdb.jobs.types.

Parameters:

  • perfdb

    (PerfDB) –

    Top level object carrying all functionality and the connection handler.

Source code in echo_postgres/perfdb_root.py
Python
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(output_type='dict')

Gets all job types definitions with detailed information.

The most useful keys/columns returned are:

  • id
  • description
  • parameters_schema

Parameters:

  • output_type

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

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

Returns:

  • dict[str, dict[str, Any]] –

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

  • DataFrame –

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

  • DataFrame –

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

Source code in echo_postgres/job_types.py
Python
@validate_call
def get(
    self,
    output_type: Literal["dict", "DataFrame", "pl.DataFrame"] = "dict",
) -> dict[str, dict[str, Any]] | pd.DataFrame | pl.DataFrame:
    """Gets all job types definitions with detailed information.

    The most useful keys/columns returned are:

    - id
    - description
    - parameters_schema

    Parameters
    ----------
    output_type : Literal["dict", "DataFrame", "pl.DataFrame"], optional
        Output type of the data. Can be one of ["dict", "DataFrame", "pl.DataFrame"]
        By default "dict"

    Returns
    -------
    dict[str, dict[str, Any]]
        In case output_type is "dict", returns a dictionary in the format {name: {attribute: value, ...}, ...}
    pd.DataFrame
        In case output_type is "DataFrame", returns a pandas DataFrame with the following format: index = name, columns = [attribute, ...]
    pl.DataFrame
        In case output_type is "pl.DataFrame", returns a Polars DataFrame
    """
    query = sql.SQL("SELECT id, name, description, parameters_schema::TEXT, modified_date FROM performance.job_types ORDER BY name")

    df = self._perfdb.conn.read_to_polars(query)

    # converting parameters_schema from stringified JSON to pl.Object
    df = cast_column_to_object(df, "parameters_schema")

    return convert_output(df, output_type)

get_ids()

Gets all job types and their respective ids.

Returns:

  • dict[str, int] –

    Dictionary with all job types and their respective ids in the format {name: id, ...}.

Source code in echo_postgres/job_types.py
Python
def get_ids(self) -> dict[str, int]:
    """Gets all job types and their respective ids.

    Returns
    -------
    dict[str, int]
        Dictionary with all job types and their respective ids in the format {name: id, ...}.
    """
    query = sql.SQL("SELECT name, id FROM performance.job_types ORDER BY name")

    df = self._perfdb.conn.read_to_polars(query)

    return dict(zip(df["name"].to_list(), df["id"].to_list(), strict=False))