Source code for pm4py.objects.dfg.importer.importer

'''
    PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation, either version 3 of the
License, or any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License
along with this program.  If not, see this software project's root or
visit <https://www.gnu.org/licenses/>.

Website: https://processintelligence.solutions
Contact: info@processintelligence.solutions
'''
from enum import Enum

from pm4py.objects.dfg.importer.variants import classic
from pm4py.util import exec_utils




class Variants(Enum):
    CLASSIC = classic



DEFAULT_VARIANT = Variants.CLASSIC




def apply(file_path, variant=DEFAULT_VARIANT, parameters=None):
    """
    Import a DFG (along with the start and end activities)

    Parameters
    --------------
    file_path
        Path of the DFG file
    variant
        Variant of the importer, possible values:
            - Variants.CLASSIC: importing from a .dfg file
    parameters
        Possible parameters of the algorithm

    Returns
    --------------
    dfg
        DFG
    start_activities
        Start activities
    end_activities
        End activities
    """
    return exec_utils.get_variant(variant).apply(
        file_path, parameters=parameters
    )





def deserialize(dfg_string, variant=DEFAULT_VARIANT, parameters=None):
    """
    Import a DFG from a binary/textual string

    Parameters
    --------------
    dfg_string
        DFG represented as a string in the .dfg format
    variant
        Variant of the importer, possible values:
            - Variants.CLASSIC: importing from a .dfg file
    parameters
        Possible parameters of the algorithm

    Returns
    --------------
    dfg
        DFG
    start_activities
        Start activities
    end_activities
        End activities
    """
    return exec_utils.get_variant(variant).import_dfg_from_string(
        dfg_string, parameters=parameters
    )