exchange.GetRecords()

# 方式1：使用周期常量（推荐）
# 常量已自动注入，无需 import，直接使用
records = exchange.GetRecords(period=PERIOD_M5, limit=100)

# 方式2：使用标准格式字符串
records = exchange.GetRecords(period='5m', limit=100)

# 方式3：使用秒数字符串
records = exchange.GetRecords(period='300', limit=100)

# 这些常量已自动注入到策略全局作用域，无需 import
# 就像 exchange、Log、Sleep 一样直接使用

def main():
    # 可用的周期常量：
    # PERIOD_M1, PERIOD_M3, PERIOD_M5, PERIOD_M15, PERIOD_M30
    # PERIOD_H1, PERIOD_H2, PERIOD_H4, PERIOD_H6, PERIOD_H12
    # PERIOD_D1, PERIOD_D3, PERIOD_W1
    
    # 直接使用示例
    records = exchange.GetRecords(period=PERIOD_M5, limit=100)

# 清晰易读
records = exchange.GetRecords(period=PERIOD_M5, limit=100)
records_1h = exchange.GetRecords(period=PERIOD_H1, limit=50)
records_daily = exchange.GetRecords(period=PERIOD_D1, limit=30)

# 可读性差，需要计算
records = exchange.GetRecords(period="300", limit=100)   # 这是几分钟？
records_1h = exchange.GetRecords(period="3600", limit=50)  # 这是多久？

# 周期常量已自动注入，无需 import
def main():
    # 获取5分钟K线
    records_5m = exchange.GetRecords(period=PERIOD_M5, limit=100)
    Log(f"获取到 {len(records_5m)} 条5分钟K线")
    
    # 获取1小时K线
    records_1h = exchange.GetRecords(period=PERIOD_H1, limit=50)
    Log(f"获取到 {len(records_1h)} 条1小时K线")
    
    # 获取日线
    records_daily = exchange.GetRecords(period=PERIOD_D1, limit=30)
    Log(f"获取到 {len(records_daily)} 条日线")
    
    # 获取最新K线
    if len(records_5m) > 0:
        latest = records_5m[-1]
        Log(f"最新价格: {latest['Close']:.2f}")

# 获取最近100根1分钟K线
records = exchange.GetRecords('1m', 100)

latest = records[-1]
Log("最新K线:")
Log(f"  时间: {latest['Time']}")
Log(f"  开: {latest['Open']}")
Log(f"  高: {latest['High']}")
Log(f"  低: {latest['Low']}")
Log(f"  收: {latest['Close']}")
Log(f"  量: {latest['Volume']}")

def analyze_multi_timeframe():
    """使用周期常量进行多周期分析"""
    # 5分钟周期 - 短线信号
    records_5m = exchange.GetRecords(period=PERIOD_M5, limit=100)
    ma5_short = sum([r['Close'] for r in records_5m[-5:]]) / 5
    ma20_short = sum([r['Close'] for r in records_5m[-20:]]) / 20
    
    # 15分钟周期 - 中线信号
    records_15m = exchange.GetRecords(period=PERIOD_M15, limit=100)
    ma5_mid = sum([r['Close'] for r in records_15m[-5:]]) / 5
    ma20_mid = sum([r['Close'] for r in records_15m[-20:]]) / 20
    
    # 1小时周期 - 长线趋势
    records_1h = exchange.GetRecords(period=PERIOD_H1, limit=100)
    ma5_long = sum([r['Close'] for r in records_1h[-5:]]) / 5
    ma20_long = sum([r['Close'] for r in records_1h[-20:]]) / 20
    
    # 多周期共振判断
    short_bullish = ma5_short > ma20_short
    mid_bullish = ma5_mid > ma20_mid
    long_bullish = ma5_long > ma20_long
    
    if short_bullish and mid_bullish and long_bullish:
        Log("多周期共振：多头趋势 ↑↑↑")
        return "BUY"
    elif not short_bullish and not mid_bullish and not long_bullish:
        Log("多周期共振：空头趋势 ↓↓↓")
        return "SELL"
    else:
        Log("多周期不一致：观望")
        return "HOLD"

def main():
    signal = analyze_multi_timeframe()
    Log(f"交易信号: {signal}")

def trend_following():
    """使用日线判断大趋势，小时线寻找入场点"""
    # 使用日线判断大趋势
    daily_records = exchange.GetRecords(period=PERIOD_D1, limit=30)
    if len(daily_records) < 20:
        return
    
    daily_ma20 = sum([r['Close'] for r in daily_records[-20:]]) / 20
    
    # 使用1小时线寻找入场点
    hourly_records = exchange.GetRecords(period=PERIOD_H1, limit=100)
    if len(hourly_records) < 20:
        return
    
    hourly_ma5 = sum([r['Close'] for r in hourly_records[-5:]]) / 5
    hourly_ma20 = sum([r['Close'] for r in hourly_records[-20:]]) / 20
    
    current_price = hourly_records[-1]['Close']
    
    Log(f"日线MA20: {daily_ma20:.2f}")
    Log(f"1小时MA5: {hourly_ma5:.2f}")
    Log(f"1小时MA20: {hourly_ma20:.2f}")
    Log(f"当前价格: {current_price:.2f}")
    
    # 大趋势向上 + 小时线金叉 → 做多
    if current_price > daily_ma20 and hourly_ma5 > hourly_ma20:
        Log("✅ 大趋势向上 + 小时线金叉 → 做多信号")
        return "BUY"
    # 大趋势向下 + 小时线死叉 → 做空
    elif current_price < daily_ma20 and hourly_ma5 < hourly_ma20:
        Log("⚠️ 大趋势向下 + 小时线死叉 → 做空信号")
        return "SELL"
    else:
        Log("➡️ 趋势不明确，观望")
        return "HOLD"

def calculate_ma(records, period=20):
    """计算移动平均线"""
    if len(records) < period:
        return None
    
    closes = [r['Close'] for r in records[-period:]]
    ma = sum(closes) / period
    return ma

# 使用周期常量获取K线
records = exchange.GetRecords(period=PERIOD_H1, limit=200)
ma20 = calculate_ma(records, 20)
ma50 = calculate_ma(records, 50)

Log(f"MA20: {ma20:.2f}")
Log(f"MA50: {ma50:.2f}")

if ma20 > ma50:
    Log("短期均线在长期均线上方，多头排列")
else:
    Log("短期均线在长期均线下方，空头排列")

def is_bullish_engulfing(records):
    """判断是否为看涨吞没形态"""
    if len(records) < 2:
        return False
    
    prev = records[-2]
    curr = records[-1]
    
    # 前一根为阴线，当前为阳线
    prev_bearish = prev['Close'] < prev['Open']
    curr_bullish = curr['Close'] > curr['Open']
    
    # 当前K线实体完全吞没前一根
    engulfing = (curr['Open'] < prev['Close'] and 
                 curr['Close'] > prev['Open'])
    
    return prev_bearish and curr_bullish and engulfing

records = exchange.GetRecords('1h', 100)
if is_bullish_engulfing(records):
    Log("检测到看涨吞没形态！")

def calculate_bollinger_bands(records, period=20, std_dev=2):
    """计算布林带"""
    if len(records) < period:
        return None, None, None
    
    closes = [r['Close'] for r in records[-period:]]
    
    # 计算中轨（移动平均）
    middle = sum(closes) / period
    
    # 计算标准差
    variance = sum((x - middle) ** 2 for x in closes) / period
    std = variance ** 0.5
    
    # 上轨和下轨
    upper = middle + (std_dev * std)
    lower = middle - (std_dev * std)
    
    return upper, middle, lower

records = exchange.GetRecords('1h', 100)
upper, middle, lower = calculate_bollinger_bands(records)

current_price = records[-1]['Close']
Log(f"当前价格: {current_price:.2f}")
Log(f"布林带上轨: {upper:.2f}")
Log(f"布林带中轨: {middle:.2f}")
Log(f"布林带下轨: {lower:.2f}")

if current_price >= upper:
    Log("价格触及上轨，可能超买")
elif current_price <= lower:
    Log("价格触及下轨，可能超卖")

def calculate_rsi(records, period=14):
    """计算RSI相对强弱指标"""
    if len(records) < period + 1:
        return None
    
    closes = [r['Close'] for r in records[-(period+1):]]
    
    gains = []
    losses = []
    
    for i in range(1, len(closes)):
        change = closes[i] - closes[i-1]
        if change > 0:
            gains.append(change)
            losses.append(0)
        else:
            gains.append(0)
            losses.append(abs(change))
    
    avg_gain = sum(gains) / period
    avg_loss = sum(losses) / period
    
    if avg_loss == 0:
        return 100
    
    rs = avg_gain / avg_loss
    rsi = 100 - (100 / (1 + rs))
    
    return rsi

records = exchange.GetRecords('1h', 100)
rsi = calculate_rsi(records, 14)

Log(f"RSI(14): {rsi:.2f}")

if rsi > 70:
    Log("RSI超过70，市场超买")
elif rsi < 30:
    Log("RSI低于30，市场超卖")

# 推荐：检查数据有效性
records = exchange.GetRecords('1h', 100)
if len(records) < 20:
    Log("K线数据不足，无法计算指标")
    # 等待更多数据