# 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` ## 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。 执行以下代码直接从github安装： ``` pip install git+git://github.com/zengbin93/chan.git -U ``` ## K线数据样例 ```markdown symbol dt open close high low vol 0 002739.SZ 20181105 31.10 31.10 31.10 31.10 17495.00 1 002739.SZ 20181106 27.99 27.99 27.99 27.99 8557.00 2 002739.SZ 20181107 25.19 25.19 25.19 25.19 13163.00 3 002739.SZ 20181108 22.67 22.67 22.67 22.67 109787.00 4 002739.SZ 20181109 20.66 22.17 23.73 20.65 896466.32 5 002739.SZ 20181112 21.19 22.42 22.57 21.01 495463.08 6 002739.SZ 20181113 22.06 23.71 24.50 21.86 497543.55 7 002739.SZ 20181114 23.61 23.35 24.25 23.15 297538.47 8 002739.SZ 20181115 23.50 23.70 23.96 23.30 197008.28 ``` * dt 表示 该周期的交易结束时间 ## 使用方法 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。 ```python from chan import KlineAnalyze ka = KlineAnalyze(kline) # kline 的格式见K先数据样例 # 笔的识别结果 ka.bi # 线段的识别结果 ka.xd # 中枢的识别结果 ka.zs ``` ## 结合 tushare.pro 的数据使用 py 文件地址： examples/combine_with_tushare.py 没有 token，到 https://tushare.pro/register?reg=7 注册下 ```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() ```