UserInput

from neo4j_runway import UserInput

A container for user provided information about the data.

Attributes
----------
general_description : str, optional
    A general description of the CSV data.
data_dictionary : Dict[str, str], optional
    A mapping of the desired columns to their
    descriptions.
    If multi-file, then each file name should contain
    it's own sub dictionary.
    The keys of this argument will determine which CSV
    columns are
    evaluated in discovery and used to generate a data
    model.
use_cases : List[str], optional
    A list of use cases that the final data model should
    be able to answer.

Class Methods

init

A container for user provided information about the data.

Parameters
----------
general_description : str, optional
    A general description of the CSV data, by default =
    ""
data_dictionary : Dict[str, str], optional
    A mapping of the desired columns to their
    descriptions.
    If multi-file, then each file name should contain
    it's own sub dictionary.
    The leaf values of this argument will determine
    which columns are
    evaluated in discovery and used to generate a data
    model.
use_cases : List[str], optional
    A list of use cases that the final data model should
    be able to answer.

validate_data_dictionary

Class Properties

allowed_columns

The allowed columns.

Returns
-------
Union[List[str], Dict[str, List[str]]]
    single file : A list of columns from the DataFrame.
    Multi file  : a dictionary with keys of file names
    and A list of columns for each file.

is_multifile

Whether the data dictionary covers multiple files.

Returns
-------
bool

pretty_use_cases

Format the use cases in a more readable format.

Returns
-------
str
    The formatted use cases as a String.