vrutik2809

The backend workflow is illustrated in the following chart: The exporting algorithm for exporting the table will follow as:

• validate the body
  • check whether database exist or not
  • check whether table <schema_name>.<table_name> exist or not
  • check whether given fields are there in the table or not
• create engine using create_mathesar_engine function by passing db_name
• use the created engine to relfect the table with the given schema_name and table_name using reflect_table function
• then it will follow the logic mentioned in the exporting function prototypes(e.g., refer export_table_to_dict function)

vrutik2809

import os.path
from sqlalchemy import create_engine, inspect, Table, MetaData

from google.auth.transport.requests import Request
from google.oauth2.credentials import Credentials
from google_auth_oauthlib.flow import InstalledAppFlow
from googleapiclient.discovery import build
from googleapiclient.errors import HttpError

# If modifying these scopes, delete the file token.json.

vrutik2809

from sqlalchemy import create_engine
from sqlalchemy import inspect, Table, MetaData
from xlsxwriter import Workbook

# TODO replace variable with appropiate values
DB_URL = f"postgresql://{user}:{password}@{hostname}:{port}/{database-name}"

engine = create_engine(DB_URL)

def reflect_table(name, schema, engine, metadata=None, connection_to_use=None):