#
#  Copyright 2019 The FATE Authors. All Rights Reserved.
#
#  Licensed under the Apache License, Version 2.0 (the "License");
#  you may not use this file except in compliance with the License.
#  You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
#  Unless required by applicable law or agreed to in writing, software
#  distributed under the License is distributed on an "AS IS" BASIS,
#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#  See the License for the specific language governing permissions and
#  limitations under the License.
#

import argparse

from pipeline.backend.pipeline import PipeLine
from pipeline.component import Reader
from pipeline.component import DataTransform
from pipeline.component import SecureInformationRetrieval
from pipeline.interface import Data


from pipeline.utils.tools import load_job_config


def main(config="../../config.yaml", namespace=""):
    # obtain config
    if isinstance(config, str):
        config = load_job_config(config)
    parties = config.parties
    guest = parties.guest[0]
    host = parties.host[0]

    guest_train_data = {"name": "breast_hetero_host", "namespace": f"experiment_sid{namespace}"}
    host_train_data = {"name": "breast_hetero_guest", "namespace": f"experiment_sid{namespace}"}

    # initialize pipeline
    pipeline = PipeLine()
    # set job initiator
    pipeline.set_initiator(role="guest", party_id=guest)
    # set participants information
    pipeline.set_roles(guest=guest, host=host)

    # define Reader components to read in data
    reader_0 = Reader(name="reader_0")
    # configure Reader for guest
    reader_0.get_party_instance(role="guest", party_id=guest).component_param(table=guest_train_data)
    # configure Reader for host
    reader_0.get_party_instance(role="host", party_id=host).component_param(table=host_train_data)

    data_transform_0 = DataTransform(name="datatransform_0", with_match_id=True)
    data_transform_0.get_party_instance(
        role="guest", party_id=guest).component_param(
        with_label=False, output_format="dense")
    data_transform_0.get_party_instance(role="host", party_id=host).component_param(with_label=True)

    param = {
        "security_level": 0.5,
        "oblivious_transfer_protocol": "OT_Hauck",
        "commutative_encryption": "CommutativeEncryptionPohligHellman",
        "non_committing_encryption": "aes",
        "dh_params": {
            "key_length": 1024
        },
        "raw_retrieval": False,
        "target_cols": ["x0", "x3"]
    }
    secure_information_retrieval_0 = SecureInformationRetrieval(name="secure_information_retrieval_0", **param)

    # add components to pipeline, in order of task execution.
    pipeline.add_component(reader_0)
    pipeline.add_component(data_transform_0, data=Data(data=reader_0.output.data))
    pipeline.add_component(secure_information_retrieval_0, data=Data(data=data_transform_0.output.data))

    # compile pipeline once finished adding modules, this step will form conf and dsl files for running job
    pipeline.compile()

    # fit model
    pipeline.fit()


if __name__ == "__main__":
    parser = argparse.ArgumentParser("PIPELINE DEMO")
    parser.add_argument("-config", type=str,
                        help="config file")
    args = parser.parse_args()
    if args.config is not None:
        main(args.config)
    else:
        main()