import csv
from feature_extraction.features import extract_features_from_text


def read_csv_file(csv_file_path, delimiter='\t'):
    """
     This function takes file path as an argument, reads the data file and
     returns a list of DataInstance objects with text and true labels

    :param delimiter: Delimiter for the file. Default is Tab(\t)
    :param csv_file_path: path to the TSV/CSV file
    :return: returns a list of  DataInstance class objects. <utils.models.DataInstance>
    """
    with open(csv_file_path, 'r') as file:
        file_data = csv.reader(file, delimiter=delimiter)
        data = []
        for row in file_data:
            data.append(DataInstance(row[0], row[2], row[3]))
        return data


class DataInstance:
    """
    Model Class for carrying Training and Testing data from tsv/csv file.
    Also carries the extracted features.
    """

    def __init__(self, r_id, text, true_label):
        self.did = r_id
        self.text = text
        self.true_label = true_label
        self.predicted_label = None
        self.features = extract_features_from_text(text)

    def print(self):
        print('\nTrue Label :: ', self.true_label, ' Text :: ', self.text)
        print('Features :: ', self.features)