dataUtils.py

import pandas as pd
# from google_auth_oauthlib.flow import InstalledAppFlow
# from googleapiclient.discovery import build
# from googleapiclient.http import MediaIoBaseDownload
from io import BytesIO

def load_data(filename='./data/input.txt'):
    """
    Loads key-value pairs from a text file where each line is formatted as key=value.
    """
    config = {}
    try:
        with open(filename, 'r') as file:
            for line in file:
                line = line.strip()
                if line and '=' in line:  # Skip empty lines and lines without '='
                    key, value = line.split('=', 1)  # Only split on the first '='
                    config[key.strip()] = value.strip()  # Remove extra spaces
    except FileNotFoundError:
        print(f"Error: The file {filename} was not found.")
    except Exception as e:
        print(f"Error: {e}")
    return config

# def access_data_from_drive(file_id):
#     """
#     Accesses a file from Google Drive using its file ID and returns its content as a DataFrame.
#     """
#     # Define scope for accessing Google Drive
#     SCOPES = ['https://www.googleapis.com/auth/drive.readonly']

#     # Authenticate using OAuth2 credentials
#     flow = InstalledAppFlow.from_client_secrets_file('./credentials.json', SCOPES)
#     creds = flow.run_local_server(port=0)

#     # Build the Google Drive service
#     service = build('drive', 'v3', credentials=creds)

#     # Request file metadata
#     file_metadata = service.files().get(fileId=file_id).execute()
#     print("File Metadata:", file_metadata)

#     # Read the file content into memory
#     file_content = BytesIO()

#     # Request the media content from Google Drive
#     request = service.files().get_media(fileId=file_id)
#     media_downloader = MediaIoBaseDownload(file_content, request)

#     # Download the file content into the buffer
#     done = False
#     while not done:
#         status, done = media_downloader.next_chunk()
#         print(f"Download {int(status.progress() * 100)}% complete.")

#     # Move the buffer's position back to the start
#     file_content.seek(0)

#     # Process the file content as a CSV
#     df = pd.read_csv(file_content)
#     print(df)
#     return df