# Copyright 2023 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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.

"""CIC-IDS2017"""

import os
import csv
import pandas as pd
import pyarrow.csv
import datasets

_DESCRIPTION = ""

_HOMEPAGE = ""

_URLS = {
    "Network-Flows": "Network-Flows/CICIDS-Flow.csv",
    "Packet-Bytes": "Packet-Bytes/Packet_Bytes_File_1.csv",
    "Packet-Fields": "Packet-Fields/Packet_Fields_File_1.csv",
    "Payload-Bytes": "Payload-Bytes/Payload_Bytes_File_1.csv",
}

class NewDataset(datasets.GeneratorBasedBuilder):
    VERSION = datasets.Version("1.0.0")

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(name="Network-Flows", version=VERSION, description="Network-Flows"),
        datasets.BuilderConfig(name="Packet-Bytes", version=VERSION, description="Packet-Bytes"),
        datasets.BuilderConfig(name="Packet-Fields", version=VERSION, description="Packet-Fields"),
        datasets.BuilderConfig(name="Payload-Bytes", version=VERSION, description="Payload-Bytes"),
    ]

    DEFAULT_CONFIG_NAME = "Network-Flows"

    def _info(self):
        filepath = _URLS[self.config.name]
        csv_file = pyarrow.csv.open_csv(filepath)
        schema = csv_file.schema
        features = datasets.Features.from_arrow_schema(schema)
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(features),
            homepage=_HOMEPAGE,
        )
    
    def _split_generators(self, dl_manager):
        url = _URLS[self.config.name]
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "filepath": url,
                },
            ),
        ]

    def _generate_examples(self, filepath):
        with open(filepath, encoding="utf-8") as f:
            reader = csv.DictReader(f)
            numerical_columns = ['flow_id', 'packet_id', 'source_port', 'destination_port', 'payload_length'] + [f'payload_byte_{i}' for i in range(1, 1600)] + ['Flow Duration', 'Total Fwd Packets', 'Total Backward Packets',
       'Total Length of Fwd Packets', 'Total Length of Bwd Packets',
       'Fwd Packet Length Max', 'Fwd Packet Length Min',
       'Fwd Packet Length Mean', 'Fwd Packet Length Std',
       'Bwd Packet Length Max', 'Bwd Packet Length Min',
       'Bwd Packet Length Mean', 'Bwd Packet Length Std', 'Flow Bytes/s',
       'Flow Packets/s', 'Flow IAT Mean', 'Flow IAT Std', 'Flow IAT Max',
       'Flow IAT Min', 'Fwd IAT Total', 'Fwd IAT Mean', 'Fwd IAT Std',
       'Fwd IAT Max', 'Fwd IAT Min', 'Bwd IAT Total', 'Bwd IAT Mean',
       'Bwd IAT Std', 'Bwd IAT Max', 'Bwd IAT Min', 'Fwd PSH Flags',
       'Bwd PSH Flags', 'Fwd URG Flags', 'Bwd URG Flags', 'Fwd Header Length',
       'Bwd Header Length', 'Fwd Packets/s', 'Bwd Packets/s',
       'Min Packet Length', 'Max Packet Length', 'Packet Length Mean',
       'Packet Length Std', 'Packet Length Variance', 'FIN Flag Count',
       'SYN Flag Count', 'RST Flag Count', 'PSH Flag Count', 'ACK Flag Count',
       'URG Flag Count', 'CWE Flag Count', 'ECE Flag Count', 'Down/Up Ratio',
       'Average Packet Size', 'Avg Fwd Segment Size', 'Avg Bwd Segment Size',
       'Fwd Avg Bytes/Bulk', 'Fwd Avg Packets/Bulk', 'Fwd Avg Bulk Rate',
       'Bwd Avg Bytes/Bulk', 'Bwd Avg Packets/Bulk', 'Bwd Avg Bulk Rate',
       'Subflow Fwd Packets', 'Subflow Fwd Bytes', 'Subflow Bwd Packets',
       'Subflow Bwd Bytes', 'Init_Win_bytes_forward',
       'Init_Win_bytes_backward', 'act_data_pkt_fwd', 'min_seg_size_forward',
       'Active Mean', 'Active Std', 'Active Max', 'Active Min', 'Idle Mean',
       'Idle Std', 'Idle Max', 'Idle Min'] + [f'packet_byte_{i}' for i in range(1, 1601)]
            for key, row in enumerate(reader):
                processed_row = {}
                for column, value in row.items():
                    if column in numerical_columns:
                        try:
                            processed_value = int(value) if float(value).is_integer() else float(value)
                        except ValueError:
                            processed_value = 0
                    else:
                        processed_value = value
                    processed_row[column] = processed_value
                yield key, processed_row