新增 examples

README.md

 # chan - 缠论技术分析工具
 >缠论来源于[缠中说缠博客](http://blog.sina.com.cn/chzhshch)，欢迎加微信探讨，我的微信号是 `zengbin93`
 
->在线体验：http://103.235.232.44:8012/
-
 ## 安装
 
 Pypi上已经存在一个名为chan的库，以致于这个库没法上传到Pypi。
@@ -35,7 +33,6 @@ pip install git+git://github.com/zengbin93/chan.git -U
 目前已经实现了缠论的 笔、线段、中枢 的自动识别，核心代码在 `chan.analyze` 中；
 此外，基于这个库，开发了一个web页面，关联 tushare.pro 的数据，输入相应的交易代码等就可以直接查看对应的分析结果。
 
-访问地址：http://103.235.232.44:8012/
 
 ```python
 from chan import KlineAnalyze
@@ -54,5 +51,204 @@ ka.zs
 
 ```
 
+## 结合 tushare.pro 的数据使用
+
+py 文件地址： examples/combine_with_tushare.py
+
+```python
+import tushare as ts
+from datetime import datetime, timedelta
+from chan import KlineAnalyze, SolidAnalyze
+
+# 首次使用，需要在这里设置你的 tushare token，用于获取数据；在同一台机器上，tushare token 只需要设置一次
+# ts.set_token("your tushare token")
+
+
+def _get_start_date(end_date, freq):
+    end_date = datetime.strptime(end_date, '%Y%m%d')
+    if freq == '1min':
+        start_date = end_date - timedelta(days=30)
+    elif freq == '5min':
+        start_date = end_date - timedelta(days=70)
+    elif freq == '30min':
+        start_date = end_date - timedelta(days=500)
+    elif freq == 'D':
+        start_date = end_date - timedelta(weeks=500)
+    elif freq == 'W':
+        start_date = end_date - timedelta(weeks=1000)
+    else:
+        raise ValueError("'freq' value error, current value is %s, "
+                         "optional valid values are ['1min', '5min', '30min', "
+                         "'D', 'W']" % freq)
+    return start_date
+
+
+def get_kline(ts_code, end_date, freq='30min', asset='E'):
+    """获取指定级别的前复权K线
+
+    :param ts_code: str
+        股票代码，如 600122.SH
+    :param freq: str
+        K线级别，可选值 [1min, 5min, 15min, 30min, 60min, D, M, Y]
+    :param end_date: str
+        日期，如 20190610
+    :param asset: str
+        交易资产类型，可选值 E股票 I沪深指数 C数字货币 FT期货 FD基金 O期权 CB可转债（v1.2.39），默认E
+    :return: pd.DataFrame
+        columns = ["symbol", "dt", "open", "close", "high", "low", "vol"]
+    """
+    start_date = _get_start_date(end_date, freq)
+    start_date = start_date.date().__str__().replace("-", "")
+    end_date = datetime.strptime(end_date, '%Y%m%d')
+    end_date = end_date + timedelta(days=1)
+    end_date = end_date.date().__str__().replace("-", "")
+
+    df = ts.pro_bar(ts_code=ts_code, freq=freq, start_date=start_date, end_date=end_date,
+                    adj='qfq', asset=asset)
+
+    # 统一 k 线数据格式为 6 列，分别是 ["symbol", "dt", "open", "close", "high", "low", "vr"]
+    if "min" in freq:
+        df.rename(columns={'ts_code': "symbol", "trade_time": "dt"}, inplace=True)
+    else:
+        df.rename(columns={'ts_code': "symbol", "trade_date": "dt"}, inplace=True)
+
+    df.drop_duplicates(subset='dt', keep='first', inplace=True)
+    df.sort_values('dt', inplace=True)
+    df['dt'] = df.dt.apply(str)
+    if freq.endswith("min"):
+        # 清理 9:30 的空数据
+        df['not_start'] = df.dt.apply(lambda x: not x.endswith("09:30:00"))
+        df = df[df['not_start']]
+    df.reset_index(drop=True, inplace=True)
+
+    k = df[['symbol', 'dt', 'open', 'close', 'high', 'low', 'vol']]
+
+    for col in ['open', 'close', 'high', 'low']:
+        k[col] = k[col].apply(round, args=(2,))
+    return k
+
+
+def get_klines(ts_code, end_date, freqs='1min,5min,30min,D', asset='E'):
+    """获取不同级别K线"""
+    klines = dict()
+    freqs = freqs.split(",")
+    for freq in freqs:
+        df = get_kline(ts_code, end_date, freq=freq, asset=asset)
+        klines[freq] = df
+    return klines
+
+
+def use_kline_analyze():
+    print('=' * 100, '\n')
+    print("KlineAnalyze 的使用方法：\n")
+    kline = get_kline(ts_code="000300.SH", end_date="20200202", freq='D', asset="I")
+    ka = KlineAnalyze(kline)
+    print("线段：", ka.xd, "\n")
+    print("中枢：", ka.zs, "\n")
+
+
+def use_solid_analyze():
+    print('=' * 100, '\n')
+    print("SolidAnalyze 的使用方法：\n")
+    klines = get_klines(ts_code="300455.SZ", end_date="20200202", freqs='1min,5min,30min,D', asset='E')
+    sa = SolidAnalyze(klines)
+
+    # 查看指定级别的三买
+    tb = sa.is_third_buy('30min')
+    print("指定级别三买：", tb, "\n")
+
+    # 查看多个级别的三买
+    tb = sa.check_third_buy(['1min', '5min', '30min', "D"])
+    print("多级别三买：", tb, "\n")
+
+
+if __name__ == '__main__':
+    use_kline_analyze()
+    use_solid_analyze()
+```
+
+## 结合掘金的数据使用
+
+py 文件地址： examples/combine_with_goldminer.py
 
+```python
+
+from gm.api import *
+from datetime import datetime
+from chan import KlineAnalyze, SolidAnalyze
+
+# 在这里设置你的掘金token，用于获取数据
+set_token("your gm token")
+
+
+def get_kline(symbol, end_date=None, freq='1d', k_count=5000):
+    """从掘金获取历史K线数据
+
+    参考： https://www.myquant.cn/docs/python/python_select_api#6fb030ec42984aff
+
+    :param symbol:
+    :param end_date: str
+        交易日期，如 2019-12-31
+    :param freq: str
+        K线级别，如 1d
+    :param k_count: int
+    :return: pd.DataFrame
+    """
+    if not end_date:
+        end_date = datetime.now()
+    df = history_n(symbol=symbol, frequency=freq, end_time=end_date,
+                   fields='symbol,eob,open,close,high,low,volume',
+                   count=k_count, df=True)
+    if freq == '1d':
+        df = df.iloc[:-1]
+    df['dt'] = df['eob']
+    df['vol'] = df['volume']
+    df = df[['symbol', 'dt', 'open', 'close', 'high', 'low', 'vol']]
+    df.sort_values('dt', inplace=True, ascending=True)
+    df['dt'] = df.dt.apply(lambda x: x.strftime(r"%Y-%m-%d %H:%M:%S"))
+    df.reset_index(drop=True, inplace=True)
+
+    for col in ['open', 'close', 'high', 'low']:
+        df[col] = df[col].apply(round, args=(2,))
+    return df
+
+
+def get_klines(symbol, end_date=None, freqs='60s,300s,1800s,1d', k_count=5000):
+    """获取不同级别K线"""
+    klines = dict()
+    freqs = freqs.split(",")
+    for freq in freqs:
+        df = get_kline(symbol, end_date, freq, k_count)
+        klines[freq] = df
+    return klines
+
+
+def use_kline_analyze():
+    print('=' * 100, '\n')
+    print("KlineAnalyze 的使用方法：\n")
+    kline = get_kline(symbol='SHSE.000300', end_date="2020-02-02")
+    ka = KlineAnalyze(kline)
+    print("线段：", ka.xd, "\n")
+    print("中枢：", ka.zs, "\n")
+
+
+def use_solid_analyze():
+    print('=' * 100, '\n')
+    print("SolidAnalyze 的使用方法：\n")
+    klines = get_klines(symbol='SZSE.300455', end_date="2020-02-02")
+    sa = SolidAnalyze(klines)
+
+    # 查看指定级别的三买
+    tb = sa.is_third_buy('1800s')
+    print("指定级别三买：", tb, "\n")
+
+    # 查看多个级别的三买
+    tb = sa.check_third_buy(['60s', '300s', '1800s'])
+    print("多级别三买：", tb, "\n")
+
+
+if __name__ == '__main__':
+    use_kline_analyze()
+    use_solid_analyze()
+```