import csv
from collections import defaultdict
from datetime import datetime
from decimal import Decimal
from typing import Dict, List

from trade import Trade
from trade_queue import FIFOQueue


def generate_report(sale_entries, proceeds: float|Decimal, crypto_asset, date_sold):
    report = []
    sell_date = datetime.strptime(date_sold, "%Y-%m-%d").strftime("%d.%m.%Y")
    proceeds = Decimal(proceeds)

    trade: Trade
    for trade in sale_entries:
        buy_date_formatted = datetime.strptime(trade.date, "%Y-%m-%d").strftime("%d.%m.%Y")
        holding_period = (datetime.strptime(date_sold, "%Y-%m-%d") - datetime.strptime(trade.date, "%Y-%m-%d")).days
        short_or_long = "Short" if holding_period < 365 else "Long"
        total_cost = trade.total_cost
        gain_or_loss = proceeds - total_cost

        report.append({
            "Amount": f"{trade.amount:.8f}",
            "Currency": crypto_asset,
            "Date Sold": sell_date,
            "Date Acquired": buy_date_formatted,
            "Short/Long": short_or_long,
            "Buy/Input at": "Kraken",
            "Sell/Output at": "Kraken",
            "Proceeds": f"{proceeds:.2f}",
            "Cost Basis": f"{total_cost:.2f}",
            "Gain/Loss": f"{gain_or_loss:.2f}",
        })

    return report

def process_ledger(file_path, output_path):
    fifo_queues :Dict[str,FIFOQueue] = {}  # Separate FIFO queue per cryptocurrency
    trades_by_refid = defaultdict(list)
    report = []

    with open(file_path, 'r') as file:
        reader = csv.DictReader(file)
        for row in reader:
            # Group trades by refid
            if row["type"] == "trade":
                trades_by_refid[row["refid"]].append(row)

            # Handle deposits
            elif row["type"] == "deposit" and row["asset"] != "EUR":
                currency = row["asset"]
                fifo_queues.setdefault(currency, FIFOQueue())
                amount = float(row["amount"])
                price = 0  # Deposits typically have no associated cost basis
                date = row["time"].split(" ")[0]
                fifo_queues[currency].add(amount, price, date)

        # Process grouped trades
        for refid, trades in trades_by_refid.items():
            if len(trades) == 2:  # Ensure we have two related rows (EUR + crypto)
                eur_trade = next((trade for trade in trades if trade["asset"] == "EUR"), None)
                crypto_trade = next((trade for trade in trades if trade["asset"] != "EUR"), None)

                if eur_trade and crypto_trade:
                    crypto_asset = crypto_trade["asset"]
                    eur_amount = float(eur_trade["amount"])
                    eur_fee = float(eur_trade["fee"])
                    crypto_amount = float(crypto_trade["amount"])
                    crypto_fee = float(crypto_trade["fee"])
                    fifo_queues.setdefault(crypto_asset, FIFOQueue())

                    date_sold = eur_trade["time"].split(" ")[0]

                    if eur_amount < 0:  # Purchase of cryptocurrency
                        stake_amount = -eur_amount - eur_fee  # Account for EUR fees
                        crypto_amount -= crypto_fee  # Adjust for crypto fees
                        fifo_queues[crypto_asset].add(crypto_amount, stake_amount, date_sold)
                    elif eur_amount > 0:  # Sale of cryptocurrency
                        proceeds = eur_amount - eur_fee  # Account for EUR fees
                        sale_entries = fifo_queues[crypto_asset].remove_coins(-crypto_amount)
                        report.extend(generate_report(sale_entries, proceeds, crypto_asset, date_sold))
                else:
                    raise ValueError(f"Unexpected trade grouping for refid {refid}")
            else:
                raise ValueError(f"Unexpected number of trades for refid {refid}")

    # Write report to CSV
    with open(output_path, 'w', newline='') as csvfile:
        fieldnames = [
            "Amount",
            "Currency",
            "Date Sold",
            "Date Acquired",
            "Short/Long",
            "Buy/Input at",
            "Sell/Output at",
            "Proceeds",
            "Cost Basis",
            "Gain/Loss"
        ]
        writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
        writer.writeheader()
        writer.writerows(report)

# Usage
ledger_path = "kraken_ledger.csv"  # Replace with your ledger file path
output_path = "tax_report.csv"  # Replace with your desired output file path
process_ledger(ledger_path, output_path)