import pandas as pd
import json
import os


from s3Ops import read_file_from_s3

from backendAPIs import (
    update_onboarding_status,
    add_performance_record
)

def xlsx_to_df(xlsx_file, sheet_name):
    df = pd.read_excel(xlsx_file, sheet_name = sheet_name, header=2,skiprows=2)
    return df


def process_performance_records(df):
    """
    Process and insert users from an Excel file into MongoDB.

    Args:
        file_path (str): Path to the Excel file.
    """

    entity_id = os.getenv('ENTITY_ID')
    fund_id = os.getenv('FUND_ID')
    role_id = os.getenv('ROLE_ID')

    performance_records = []

    # Iterate through the DataFrame and prepare partner records
    for index, row in df.iterrows():

        print(row.to_dict())

        if row['Type'].strip().lower() == "contribution":
            continue

        tdate = row['Date']
        performance_record = { 
                                "fundId": fund_id,
                                "entityId": entity_id,
                                "roleId": role_id,
                                "receivedDate": tdate.strftime('%m/%d/%Y'),
                                "amount": row['Value'] if row['Value'] >= 0 else row['Value']*-1,
                                "gainLoss": "GAIN" if row['Value'] >= 0 else "LOSS",
                                "type": row['Type'],
                                "partnerExactName": row["Partner"]
                            }
                
        response = add_performance_record(performance_record)
        print(f"Adding joural ledger {index}\n {performance_record}\n\n")
        if 'error' in response:
            print(response)
            print(f"Failed to fetch onboarding status: Error: {response['error']}")
            print(f"Status Code: {response['status_code']}")
            # break # Process next company investment record...
            continue


        performance_records.append(performance_record)
        print(f"Performance record: \n{performance_record}")

        # Test with smaller set of records
        # if index == 1:
        #     break

    return performance_records


def process_fund_performance(file_path):
    # Process partner data
    step_number = 7
    step_number -= 1
    success_message = ""
    error_message = ""
    status = "IN-PROGRESS"

    bucket_name = os.getenv('S3_UPLOAD_BUCKET_NAME')
    print(f"Processing file: {file_path}")
    response = update_onboarding_status(step_number, status, error_message, success_message)
    if 'error' in response:
        print(f"Failed to fetch onboarding status: Error: {response['error']}")
        print(f"Status Code: {response['status_code']}")
        return False
    performance_excel_file = read_file_from_s3(bucket_name, file_path)
    sheet_name = 'Partner Capital Activity Detail'
    performance_df = xlsx_to_df(performance_excel_file, sheet_name)
    print(performance_df)
    perf_records = process_performance_records(performance_df)
    if perf_records:
        item_count = len(perf_records)
        success_message = f"Onboarded {item_count} fund performance records."
        status =  "COMPLETE"
    else:
        error_message = "No transactions were onboaerded."
        status = "FAILED"

    response = update_onboarding_status(step_number, status, error_message, success_message)
    if 'error' in response:
        print(f"Failed to fetch onboarding status: Error: {response['error']}")
        print(f"Status Code: {response['status_code']}")
        return False

    # print(f"Journals list:\n {perf_records}")

    return True


if __name__ == "__main__":

    from dotenv import load_dotenv
    load_dotenv()

    onboardingId = "66ea163564e2f97a059160ef"
    os.environ["ONBOARDING_ID"] = onboardingId
    os.environ["FUND_ID"] = "66c5e6d89ecbf552a05b84fc"

    from initOnboarding import initialize_onboarding
    initialize_onboarding()

    found_files = {'lpa': '66c5e5c99ecbf552a05b84f9/20240917T235220Z/0-Please_DocuSign_CerraCap_II_LP_Limited_Partn.pdf', 'partner': '66c5e5c99ecbf552a05b84f9/20240917T235220Z/0-1-cerracap-ii-lp_2024-07_09_short_partner.xlsx', 'financials': '66c5e5c99ecbf552a05b84f9/20240917T235220Z/2-3-cerracap-ii-lp_2024-08-26_financials.xlsx', 'bankTransactions': '66c5e5c99ecbf552a05b84f9/20240917T235220Z/4-CerraCap_II__LP_bank_transactions_2016-01-01-2024-07-03.xlsx', 'journals': '66c5e5c99ecbf552a05b84f9/20240917T235220Z/5-cerracap-ii-lp_2024-07-09_journals-export.xlsx', 'fund_performance': '66c5e5c99ecbf552a05b84f9/20240917T235220Z/6-cerracap-ii-lp_2024-07-09_fund-performance-report.xlsx'}
    financials_excel_file_path = found_files["fund_performance"]
    process_fund_performance(financials_excel_file_path)