diff --git a/examples/use_czsc_with_jq.py b/examples/use_czsc_with_jq.py
new file mode 100644
index 0000000000000000000000000000000000000000..28b92dc62da560e1b36327c465773389cb9ccac2
--- /dev/null
+++ b/examples/use_czsc_with_jq.py
@@ -0,0 +1,78 @@
+# coding: utf-8
+import json
+import requests
+import pandas as pd
+from datetime import datetime
+from czsc import KlineAnalyze
+
+
+# 聚宽数据 API
+url = "https://dataapi.joinquant.com/apis"
+mob = "******"  # mob是申请JQData时所填写的手机号
+pwd = "******"  # Password为聚宽官网登录密码，新申请用户默认为手机号后6位
+
+
+def get_token():
+    """获取调用凭证"""
+    body = {
+        "method": "get_current_token",
+        "mob": mob,  # mob是申请JQData时所填写的手机号
+        "pwd": pwd,  # Password为聚宽官网登录密码，新申请用户默认为手机号后6位
+    }
+    response = requests.post(url, data=json.dumps(body))
+    token = response.text
+    return token
+
+
+def text2df(text):
+    rows = [x.split(",") for x in text.strip().split('\n')]
+    df = pd.DataFrame(rows[1:], columns=rows[0])
+    return df
+
+
+def get_kline(symbol, end_date, freq, count=3000):
+    # 1m, 5m, 15m, 30m, 60m, 120m, 1d, 1w, 1M
+    freq_convert = {"1min": "1m", "5min": '5m', '15min': '15m',
+                    "30min": "30m", "60min": '60m', "D": "1d", "W": '1w'}
+    if "-" not in end_date:
+        end_date = datetime.strptime(end_date, "%Y%m%d").strftime("%Y-%m-%d")
+
+    data = {
+        "method": "get_price",
+        "token": get_token(),
+        "code": symbol,
+        "count": count,
+        "unit": freq_convert[freq],
+        "end_date": end_date,
+        "fq_ref_date": "2010-01-01"
+    }
+    r = requests.post(url, data=json.dumps(data))
+    df = text2df(r.text)
+    df['symbol'] = symbol
+    df.rename({'date': 'dt', 'volume': 'vol'}, axis=1, inplace=True)
+    df = df[['symbol', 'dt', 'open', 'close', 'high', 'low', 'vol']]
+    for col in ['open', 'close', 'high', 'low', 'vol']:
+        df.loc[:, col] = df[col].apply(lambda x: round(float(x), 2))
+    return df
+
+
+def use_kline_analyze():
+    kline = get_kline(symbol="000001.XSHG", end_date="20200616", freq="D", count=5000)
+
+    # 输入K线即完成分析
+    ka = KlineAnalyze(kline, name="日线")
+
+    # 查看结果
+    print("分型识别结果：", ka.fx[-3:])
+    print("笔识别结果：", ka.bi[-3:])
+    print("线段识别结果：", ka.xd[-3:])
+    print("中枢识别结果：", ka.zs[-1])
+
+    # 用图片或者HTML可视化
+    ka.to_image("test.png")
+    ka.to_html("test.html")
+
+
+if __name__ == '__main__':
+    use_kline_analyze()
+
diff --git a/examples/use_czsc_with_tq.py b/examples/use_czsc_with_tq.py
new file mode 100644
index 0000000000000000000000000000000000000000..cb4c42007ce8ea8963ed74b52118af8a2c1404e5
--- /dev/null
+++ b/examples/use_czsc_with_tq.py
@@ -0,0 +1,234 @@
+# coding: utf-8
+import os
+from tqsdk import TqApi, TqBacktest, TqSim
+from datetime import date, datetime, timedelta
+from copy import deepcopy
+from pathlib import Path
+import traceback
+from czsc import KlineAnalyze
+from czsc.analyze import create_df
+from czsc.solid import is_xd_buy, is_xd_sell
+from zb.utils import create_logger
+
+# 环境准备： pip install tqsdk zb czsc
+
+
+class TradeAnalyze:
+    """5分钟第三类买卖点 + 1分钟线段买卖点 + 日线分型"""
+    def __init__(self, klines):
+        self.klines = klines
+        self.ka_1min = KlineAnalyze(self.klines['1分钟'], name='1分钟')
+        self.ka_5min = KlineAnalyze(self.klines['5分钟'], name="5分钟")
+        self.ka_D = KlineAnalyze(self.klines['日线'], name='日线')
+        self.symbol = self.ka_1min.symbol
+        self.end_dt = self.ka_1min.end_dt
+        self.latest_price = self.ka_1min.latest_price
+        self.s = self.signals()
+        self.desc = self.__doc__
+
+    def signals(self):
+        """计算交易决策需要的状态信息"""
+        s = {"symbol": self.symbol,
+             "dt": self.end_dt,
+             "base_price": self.ka_5min.xd[-1]['xd'],
+             "latest_price": self.latest_price,
+             "5分钟顶分型后有效跌破MA5": False,
+             "5分钟底分型后有效升破MA5": False,
+             "5分钟三买": False,
+             "5分钟三卖": False,
+             "5分钟线段标记": self.ka_5min.xd[-1]['fx_mark'],
+             "5分钟笔标记": self.ka_5min.bi[-1]['fx_mark'],
+             "日线最后一个分型": self.ka_D.fx[-1]['fx_mark'],
+             "1分钟有线买": False,
+             "1分钟有线卖": False,
+             }
+
+        b1 = is_xd_buy(self.ka_1min, self.ka_5min, pf=True)
+        if b1["操作提示"] == "线买":
+            s['1分钟有线买'] = True
+
+        s1 = is_xd_sell(self.ka_1min, self.ka_5min, pf=True)
+        if s1["操作提示"] == "线卖":
+            s['1分钟有线卖'] = True
+
+        ka = self.ka_5min
+        xds = ka.xd[-6:]
+
+        # 至少需要6个线段标记
+        if len(xds) < 6:
+            return s
+
+        zs_d = max([x['xd'] for x in xds[:4] if x['fx_mark'] == 'd'])
+        zs_g = min([x['xd'] for x in xds[:4] if x['fx_mark'] == 'g'])
+        if zs_g > zs_d:
+            if xds[-1]['fx_mark'] == 'd' and xds[-1]['xd'] > zs_g:
+                s['5分钟三买'] = True
+
+            if xds[-1]['fx_mark'] == 'g' and xds[-1]['xd'] < zs_d:
+                s['5分钟三卖'] = True
+
+        df = create_df(ka, ma_params=(5,))
+        last_fx = ka.fx[-1]
+        df_last = df[df.dt >= last_fx['dt']]
+
+        if last_fx['fx_mark'] == 'g' and df_last.iloc[1]['close'] < df_last.iloc[1]['ma5']:
+            s['5分钟顶分型后有效跌破MA5'] = True
+
+        if last_fx['fx_mark'] == 'd' and df_last.iloc[1]['close'] > df_last.iloc[1]['ma5']:
+            s['5分钟底分型后有效升破MA5'] = True
+
+        return {k: v for k, v in s.items()}
+
+    def long_open(self):
+        s = self.s
+        if s['日线最后一个分型'] == "d" and s['5分钟三买'] and s['5分钟底分型后有效升破MA5'] and s['1分钟有线买']:
+            return True
+        else:
+            return False
+
+    def long_close(self):
+        s = self.s
+        if s['5分钟线段标记'] == "g" and s['5分钟顶分型后有效跌破MA5'] and s['1分钟有线卖']:
+            return True
+        else:
+            return False
+
+    def short_open(self):
+        s = self.s
+        if s['日线最后一个分型'] == "g" and s['5分钟三卖'] and s['5分钟顶分型后有效跌破MA5'] and s['1分钟有线卖']:
+            return True
+        else:
+            return False
+
+    def short_close(self):
+        s = self.s
+        if s['5分钟线段标记'] == 'd' and s['5分钟底分型后有效升破MA5'] and s['1分钟有线买']:
+            return True
+        else:
+            return False
+
+
+def format_kline(kline):
+    """格式化K线"""
+    def __convert_time(t):
+        try:
+            dt = datetime.utcfromtimestamp(t/1000000000)
+            dt = dt + timedelta(hours=8)    # 中国默认时区
+            return dt.strftime("%Y-%m-%d %H:%M:%S")
+        except:
+            return ""
+
+    kline['dt'] = kline['datetime'].apply(__convert_time)
+    kline['vol'] = kline['volume']
+    columns = ['symbol', 'dt', 'open', 'close', 'high', 'low', 'vol']
+    df = kline[columns]
+    df = df.dropna(axis=0)
+    df.sort_values('dt', inplace=True, ascending=True)
+    df.reset_index(drop=True, inplace=True)
+    return df
+
+
+if __name__ == '__main__':
+    start_dt = date(2020, 6, 16)
+    end_dt = date(2020, 6, 16)
+    init_balance = 100000
+    port = '53318'
+    freqs_k_count = {"1分钟": 1000, "5分钟": 1000, "日线": 200}
+
+    max_positions = {
+        "KQ.i@SHFE.au": 1,
+        "KQ.i@DCE.jd": 4,
+    }
+
+    data_path = f"./logs/S05_{datetime.now().strftime('%Y%m%d%H%M%S')}"
+    Path(data_path).mkdir(parents=True, exist_ok=False)
+    file_log = os.path.join(data_path, "backtest.log")
+    file_signals = os.path.join(data_path, "signals.txt")
+
+    logger = create_logger(log_file=file_log, cmd=True, name="S")
+    logger.info(f"标的配置：{max_positions}")
+    logger.info(f"前端地址：http://127.0.0.1:{port}")
+    logger.info(f"策略描述：{TradeAnalyze.__doc__}")
+
+    account = TqSim(init_balance=init_balance)
+    backtest = TqBacktest(start_dt=start_dt, end_dt=end_dt)
+    api = TqApi(account=account, backtest=backtest, web_gui=f":{port}")
+    symbols = list(max_positions.keys())
+    freqs = list(freqs_k_count.keys())
+
+    freq_seconds = {"1分钟": 60, "5分钟": 60 * 5, "15分钟": 60 * 15,
+                    "30分钟": 60 * 30, "60分钟": 60 * 60, "日线": 3600 * 24}
+
+    # 订阅K线
+    symbols_klines = {s: dict() for s in symbols}
+    for symbol in symbols:
+        for freq in freqs:
+            symbols_klines[symbol][freq] = api.get_kline_serial(symbol,
+                                                                freq_seconds[freq],
+                                                                data_length=freqs_k_count[freq])
+
+    account = api.get_account()
+    positions = api.get_position()
+
+    while True:
+        api.wait_update()
+        for symbol in symbols:
+            if api.is_changing(symbols_klines[symbol]["5分钟"]):
+                klines = {k: format_kline(deepcopy(symbols_klines[symbol][k])) for k in freqs}
+                try:
+                    ta = TradeAnalyze(klines)
+                    with open(file_signals, 'a', encoding='utf-8') as f:
+                        f.write(str(ta.s) + "\n")
+                except:
+                    traceback.print_exc()
+                    continue
+
+                cur_pos = positions.get(symbol, None)
+                if cur_pos:
+                    long_pos = {
+                        "dt": ta.end_dt,
+                        "volume": cur_pos.pos_long,
+                        "td_volume": cur_pos.pos_long_today,
+                        "yd_volume": cur_pos.pos_long_his,
+                    }
+                    short_pos = {
+                        "dt": ta.end_dt,
+                        "volume": cur_pos.pos_short,
+                        "td_volume": cur_pos.pos_short_today,
+                        "yd_volume": cur_pos.pos_short_his,
+                    }
+                else:
+                    long_pos = {"dt": ta.end_dt, "volume": 0, "td_volume": 0, "yd_volume": 0}
+                    short_pos = {"dt": ta.end_dt, "volume": 0, "td_volume": 0, "yd_volume": 0}
+
+                logger.info(f"{symbol} - 当前多仓持仓情况：{long_pos}")
+                logger.info(f"{symbol} - 当前空仓持仓情况：{short_pos}")
+
+                # 下单
+                if ta.long_close() and long_pos.get('volume', 0) > 0:
+                    if long_pos.get("td_volume", 0):
+                        order = api.insert_order(symbol=symbol, direction="SELL", offset="CLOSETODAY",
+                                                 volume=long_pos['td_volume'])
+
+                    if long_pos.get("yd_volume", 0):
+                        order = api.insert_order(symbol=symbol, direction="SELL", offset="CLOSE",
+                                                 volume=long_pos['yd_volume'])
+
+                if ta.long_open() and long_pos.get('volume', 0) == 0:
+                    order = api.insert_order(symbol=symbol, direction="BUY", offset="OPEN",
+                                             volume=max_positions[symbol])
+
+                # 平空仓
+                if ta.short_close() and short_pos.get('volume', 0) > 0:
+                    if short_pos.get("td_volume", 0) > 0:
+                        order = api.insert_order(symbol=symbol, direction="BUY", offset="CLOSETODAY",
+                                                 volume=short_pos['td_volume'])
+
+                    if short_pos.get("yd_volume", 0) > 0:
+                        order = api.insert_order(symbol=symbol, direction="BUY", offset="CLOSE",
+                                                 volume=short_pos['yd_volume'])
+
+                # 开空仓
+                if ta.short_open() and short_pos.get('volume', 0) == 0:
+                    order = api.insert_order(symbol=symbol, direction="SELL", offset="OPEN",
+                                             volume=max_positions[symbol])