import tkinter as tk
from tkinter import filedialog
import os
from datetime import datetime
from zoneinfo import ZoneInfo
import pandas as pd
import sys

#pyinstaller main.py --onefile --windowed --icon=icon.ico

false = False
true = True

DEBUG = false

def log(s):
    if DEBUG:
        print(s)
    else:
        pass

line = '\n\n--------------------------------------------------------------------------------------'

berlin_tz = ZoneInfo("Europe/Berlin")
eastern_tz = ZoneInfo("America/New_York")

def select_file():
    # Create a Tk root widget
    root = tk.Tk()
    root.withdraw()  # Hide the root window
    # Open a file dialog and get the selected file path
    file_path = filedialog.askopenfilename(title="Select Heldental Trade Report CSV File", filetypes=[("CSV files", "*.csv")])
    return file_path

def get_output_filename(base_name):    
    # Generate a timestamp
    timestamp = datetime.now().strftime("_%m-%d-%Y_%H-%M-%S")
    # Create a new filename with timestamp 
    name, ext = os.path.splitext(base_name)
    new_filename = f"{name}{timestamp}{ext}"
    return new_filename


def process_trades(input_file, output_file):
    trades = pd.read_csv(input_file, sep=';', skiprows=1, skipfooter=2, usecols=[0,1,6,7,8,9,11,12], engine='python')
    trades = trades.iloc[::-1].reset_index(drop=True)

    # Convert 'Date' column to datetime
    trades['Date'] = pd.to_datetime(trades['Date'], format='%d.%m.%Y %H:%M:%S')

    # Extract date part only (without time) and add as a new column
    trades['Time'] = trades['Date'].dt.time
    trades['Date_only'] = trades['Date'].dt.date

    # Group by 'Date_only' and 'Instrument' (stock symbol)
    grouped = trades.groupby(['Date_only', 'Instrument'])

    export = []

    # Loop through each group (date and symbol)
    for (date, symbol), group in grouped:
        log(line)
        log(f"Date: {date}, Symbol: {symbol}")

        strategy = ''
        new_trade = True
        total_qty = 0
        
        # Loop through each transaction within the group
        for _, row in group.iterrows():
            
            log(f"\nrow: {row}")
            log(f"  Time: {row['Time']} - Operation: {row['Operation']} - Price: {row['Price']} - Amount: {row['Amount']}")
        
            qty = row['Amount']

            if new_trade == True:
                log("\n\n------------New Trade--------------------")

            if new_trade == True and row['Operation'] == 'Buy':
                new_trade = False
                strategy = 'long'
                side = 'B'
                total_qty += qty

            elif new_trade == True and row['Operation'] == 'Sell':
                new_trade = False
                strategy = 'short'
                side = 'SS'
                total_qty += -qty

            elif new_trade == False and row['Operation'] == 'Buy':
                if strategy == 'long':
                    side = 'B'
                elif strategy == 'short':
                    side = 'BC'
                total_qty += qty

            elif new_trade == False and row['Operation'] == 'Sell':
                if strategy == 'long':
                    side = 'S'
                elif strategy == 'short':
                    side = 'SS'
                total_qty += -qty
                
            log('\nTotal QTY = ' + str(total_qty) + '\n')

            if total_qty == 0:
                new_trade = True

            date = row['Date']
            date = str(date).split(' ')[0]
            date = datetime.strptime(date, "%Y-%m-%d")
            date = date.strftime("%m/%d/%Y")
            account = row['Account']
                
            exec_time = row['Date']
            exec_time = exec_time.replace(tzinfo=berlin_tz)
            exec_time = exec_time.astimezone(eastern_tz)
            exec_time = str(exec_time).split(' ')[1]
            exec_time = exec_time.split('-')[0]

            symbol = row['Instrument']        

            qty = row['Amount']
            price = row['Price']
            exec_fee = row['Execution fee']
            sign = -1

            gross = round(row['Profit'],2)
            net = round(gross - (sign*exec_fee),2)

            log('Gross= ' + str(gross))
            log('Net= ' + str(net))

            export.append(
            {
                'Account': account,
                'T/D':date,                 # trade date in MM/DD/YYYY format
                'S/D':date,                 # same as T/D, trade date in MM/DD/YYYY format
                'Currency':str('USD'),  
                'Type':str('stock'),
                'Side':side,                # B: Buy / S: Sell / SS: Short / BC: Buy cover
                'Symbol':symbol,            # symbol
                'Qty':str(qty).split('.')[0],    # number of shares executed
                'Price':price,              # price of symbol
                'Exec Time':exec_time,      # trade time in HH:mm:ss format
                'Comm':str('0'),
                'SEC':str('0'),
                'TAF':str('0'),
                'NSCC':str('0'),
                'Nasdaq':(sign*exec_fee),
                'ECN Remove':str('0'),
                'ECN Add':str('0'),
                'Gross Proceeds':gross,     # gross proceeds = shares * price
                'Net Proceeds':net,         # gross proceeds minus commissions and fees = shares * price - fee
                'Clr Broker':str(''),
                'Liq':str(''),
                'Note':total_qty
            })

    export_data = pd.DataFrame(export)
    export_data.to_csv(output_file, index=False, header=True, mode='w', sep=';')
    
    # Delete the last empty line which was generated by the .to_csv function
    with open(output_file) as f:
            lines = f.readlines()
            last = len(lines) - 1
            lines[last] = lines[last].replace('\r','').replace('\n','')
    with open(output_file, 'w') as wr:
            wr.writelines(lines)

if __name__ == "__main__":
    # Prompt the user to select an input file
    input_file = select_file()
    if not input_file:
        print("No file selected. Exiting.")
        sys.exit()

    # Define output filename and append timestamp if necessary
    output_file = get_output_filename("TradeNote_.txt")

    # Process trades
    process_trades(input_file, output_file)