缠论来源于缠中说缠博客，欢迎加微信探讨，我的微信号是
zengbin93
- 在线体验
- 参数说明：1）ts_code 是 tushare 的代码；2）asset 现在有两个值，E 表示股票，I 表示指数
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
dt 的格式统一为 %Y-%m-%d %H:%M:%S，如 2020-02-27 00:00:00
symbol dt open close high low vol
0 300803.SZ 2020-01-17 09:31:00 44.08 44.19 44.30 44.01 170160
1 300803.SZ 2020-01-17 09:32:00 44.06 44.24 44.24 43.93 91100
2 300803.SZ 2020-01-17 09:33:00 44.10 43.91 44.17 43.91 90251
3 300803.SZ 2020-01-17 09:34:00 43.90 43.86 43.90 43.81 61100
4 300803.SZ 2020-01-17 09:35:00 43.86 43.66 43.86 43.61 75900
5 300803.SZ 2020-01-17 09:36:00 43.66 43.80 43.86 43.66 56600
6 300803.SZ 2020-01-17 09:37:00 43.81 43.67 43.82 43.67 68600
7 300803.SZ 2020-01-17 09:38:00 43.67 43.60 43.67 43.53 97554
8 300803.SZ 2020-01-17 09:39:00 43.60 43.62 43.70 43.57 118861- dt 表示 该周期的交易结束时间
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。
前端页面（使用Tushare的数据）: https://github.com/waditu/tushare_chan
前端页面（使用掘金的数据）: https://github.com/zengbin93/gm_chan
前端页面（使用聚宽的数据）: https://github.com/zengbin93/jq_chan
py 文件地址： examples/combine_with_tushare.py
没有 token，到 https://tushare.pro/register?reg=7 注册下
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
# 没有 token，到 https://tushare.pro/register?reg=7 注册获取
# 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"""
freq_map = {"1min": "1分钟", "5min": "5分钟", "30min": "30分钟", "D": "日线"}
klines = dict()
freqs = freqs.split(",")
for freq in freqs:
df = get_kline(ts_code, end_date, freq=freq, asset=asset)
klines[freq_map[freq]] = df
return klines
def use_kline_analyze():
print('=' * 100, '\n')
print("KlineAnalyze 的使用方法：\n")
kline = get_kline(ts_code="000009.SZ", end_date="20200210", freq='30min', 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('30分钟')
print("指定级别三买：", tb, "\n")
if __name__ == '__main__':
use_kline_analyze()
use_solid_analyze()py 文件地址： examples/combine_with_goldminer.py
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"""
freq_map = {"60s": "1分钟", "300s": "5分钟", "1800s": "30分钟", "1d": "日线"}
klines = dict()
freqs = freqs.split(",")
for freq in freqs:
df = get_kline(symbol, end_date, freq, k_count)
klines[freq_map[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('30分钟')
print("指定级别三买：", tb, "\n")
if __name__ == '__main__':
use_kline_analyze()
use_solid_analyze()