"""
Writes dashboard strategy settings into freqtrade's config.json and generates
a matching strategy .py file so freqtrade picks them up.
"""

import json
from pathlib import Path

from app.config import settings
from app.models import StrategyConfig

STRATEGY_TEMPLATE = '''\
"""Auto-generated strategy from dashboard. Do not edit manually."""
import numpy as np
import pandas as pd
from pandas import DataFrame

from freqtrade.strategy import IStrategy, IntParameter
import talib.abstract as ta
from technical import qtpylib


class DashboardStrategy(IStrategy):
    INTERFACE_VERSION = 3
    can_short = False

    minimal_roi = {{
        "60": 0.01,
        "30": 0.02,
        "0": 0.04,
    }}

    stoploss = {stoploss}
    trailing_stop = False
    timeframe = "{timeframe}"
    process_only_new_candles = True
    startup_candle_count = {startup_candle_count}

    use_exit_signal = True
    exit_profit_only = False
    ignore_roi_if_entry_signal = False

    buy_rsi = IntParameter(low=1, high=100, default={rsi_buy_threshold}, space="buy", optimize=True, load=True)
    sell_rsi = IntParameter(low=1, high=100, default={rsi_sell_threshold}, space="sell", optimize=True, load=True)

    order_types = {{
        "entry": "limit",
        "exit": "limit",
        "stoploss": "market",
        "stoploss_on_exchange": False,
    }}

    order_time_in_force = {{"entry": "GTC", "exit": "GTC"}}

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe["rsi"] = ta.RSI(dataframe, timeperiod={rsi_period})
        dataframe["ema"] = ta.EMA(dataframe, timeperiod={ema_period})

        bollinger = qtpylib.bollinger_bands(
            qtpylib.typical_price(dataframe), window={bollinger_window}, stds={bollinger_deviation}
        )
        dataframe["bb_lowerband"] = bollinger["lower"]
        dataframe["bb_middleband"] = bollinger["mid"]
        dataframe["bb_upperband"] = bollinger["upper"]

        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                (qtpylib.crossed_above(dataframe["rsi"], self.buy_rsi.value))
                & (dataframe["ema"] <= dataframe["bb_middleband"])
                & (dataframe["ema"] > dataframe["ema"].shift(1))
                & (dataframe["volume"] > 0)
            ),
            "enter_long",
        ] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                (qtpylib.crossed_above(dataframe["rsi"], self.sell_rsi.value))
                & (dataframe["ema"] > dataframe["bb_middleband"])
                & (dataframe["ema"] < dataframe["ema"].shift(1))
                & (dataframe["volume"] > 0)
            ),
            "exit_long",
        ] = 1
        return dataframe
'''


def apply_strategy_to_freqtrade(config: StrategyConfig) -> None:
    _write_config_json(config)
    _write_strategy_file(config)


def _write_config_json(config: StrategyConfig) -> None:
    config_path = Path(settings.FREQTRADE_CONFIG_PATH)
    with open(config_path, "r") as f:
        ft_config = json.load(f)

    ft_config["timeframe"] = config.timeframe
    ft_config["max_open_trades"] = config.max_open_trades
    ft_config["stake_amount"] = config.stake_amount
    ft_config["dry_run"] = config.dry_run
    ft_config["dry_run_wallet"] = config.dry_run_wallet

    ft_config["exchange"]["name"] = config.exchange_name
    # Keys are managed via environment variables on the dashboard host,
    # not via per-user strategy configs.
    if settings.FREQTRADE_EXCHANGE_KEY:
        ft_config["exchange"]["key"] = settings.FREQTRADE_EXCHANGE_KEY
    if settings.FREQTRADE_EXCHANGE_SECRET:
        ft_config["exchange"]["secret"] = settings.FREQTRADE_EXCHANGE_SECRET

    with open(config_path, "w") as f:
        json.dump(ft_config, f, indent=4)


def _write_strategy_file(config: StrategyConfig) -> None:
    strategy_dir = Path(settings.FREQTRADE_STRATEGY_DIR)
    strategy_dir.mkdir(parents=True, exist_ok=True)
    strategy_path = strategy_dir / "dashboard_strategy.py"

    startup_candles = max(config.ema_period, config.bollinger_window, config.rsi_period) + 50

    content = STRATEGY_TEMPLATE.format(
        stoploss=config.stoploss,
        timeframe=config.timeframe,
        startup_candle_count=startup_candles,
        rsi_period=config.rsi_period,
        rsi_buy_threshold=config.rsi_buy_threshold,
        rsi_sell_threshold=config.rsi_sell_threshold,
        ema_period=config.ema_period,
        bollinger_window=config.bollinger_window,
        bollinger_deviation=config.bollinger_deviation,
    )

    strategy_path.write_text(content)