# coding: utf-8 import pandas as pd import tushare as ts from datetime import datetime, timedelta pro = ts.pro_api() def set_token(token): """在同一台机器上只需要调用 set_token 一次就可以 :param token: str tushare.pro 的 token，如果没有，请到这里注册：https://tushare.pro/register?reg=7 :return: None """ ts.set_token(token) def get_token(): """获取调用凭证""" return ts.get_token() def get_concepts(): """获取概念列表 https://dataapi.joinquant.com/docs#get_concepts---%E8%8E%B7%E5%8F%96%E6%A6%82%E5%BF%B5%E5%88%97%E8%A1%A8 :return: df """ return pro.concept(src='ts') def get_concept_stocks(symbol, date=None): """获取概念成份股 https://tushare.pro/document/2?doc_id=126 :param symbol: str 如 GN036 :param date: str or datetime 日期，如 2020-08-08 :return: list examples: ------- >>> symbols1 = get_concept_stocks("GN036", date="2020-07-08") >>> symbols2 = get_concept_stocks("GN036", date=datetime.now()) """ del date df = pro.concept_detail(id=symbol, fields='ts_code') return list(set([x + "-E" for x in df.ts_code])) def get_index_stocks(symbol, date=None): """获取指数成份股 https://dataapi.joinquant.com/docs#get_index_stocks---%E8%8E%B7%E5%8F%96%E6%8C%87%E6%95%B0%E6%88%90%E4%BB%BD%E8%82%A1 :param symbol: str 如 399300.SZ :param date: str or datetime 日期，如 2020-08-08 :return: list examples: ------- >>> symbols1 = get_index_stocks("000300.XSHG", date="2020-07-08") >>> symbols2 = get_index_stocks("000300.XSHG", date=datetime.now()) """ if not date: date = datetime.now() if isinstance(date, str): if "-" in date: date = datetime.strptime(date, "%Y-%m-%d") else: date = datetime.strptime(date, "%Y%m%d") start_date = date - timedelta(days=250) end_date = date df = pro.index_weight(index_code=symbol, start_date=start_date.strftime("%Y%m%d"), end_date=end_date.strftime("%Y%m%d")) return list(set([x + "-E" for x in df.con_code])) def _get_start_date(end_date, freq): if isinstance(end_date, str): 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) elif freq == 'M': start_date = end_date - timedelta(weeks=2000) 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(symbol, end_date, freq, start_date=None, count=None): """获取K线数据 :param symbol: str Tushare 标的代码 + Tushare asset 代码，如 000001.SH-I :param start_date: datetime 截止日期 :param end_date: datetime 截止日期 :param freq: str K线级别，可选值 ['1min', '5min', '30min', '60min', 'D', 'W', "M"] :param count: int K线数量，最大值为 5000 :return: pd.DataFrame >>> start_date = datetime.strptime("20200701", "%Y%m%d") >>> end_date = datetime.strptime("20200719", "%Y%m%d") >>> df1 = get_kline(symbol="000001.SH-I", start_date=start_date, end_date=end_date, freq="1min") >>> df2 = get_kline(symbol="000001.SH-I", end_date=end_date, freq="1min", count=1000) """ ts_code, asset = symbol.split("-") if count: start_date = _get_start_date(end_date, freq) start_date = start_date.date().__str__().replace("-", "") if isinstance(end_date, str): end_date = datetime.strptime(end_date, '%Y%m%d') end_date = end_date + timedelta(days=1) end_date = end_date.date().__str__().replace("-", "") if isinstance(end_date, datetime): end_date = end_date.date().__str__().replace("-", "") if isinstance(start_date, datetime): start_date = start_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']] if count: df = df.tail(count) df.reset_index(drop=True, inplace=True) df.loc[:, "dt"] = pd.to_datetime(df['dt']) 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 download_kline(symbol, freq, start_date, end_date, delta, save=True): """下载K线数据 :param save: :param symbol: :param end_date: :param freq: :param start_date: :param delta: :return: >>> start_date = datetime.strptime("20200101", "%Y%m%d") >>> end_date = datetime.strptime("20200719", "%Y%m%d") >>> df = download_kline("000001.SH-I", "1min", start_date, end_date, delta=timedelta(days=10), save=False) """ data = [] end_dt = start_date + delta print("开始下载数据：{} - {} - {}".format(symbol, start_date, end_date)) df_ = get_kline(symbol, start_date=start_date, end_date=end_dt, freq=freq) if not df_.empty: data.append(df_) while end_dt < end_date: df_ = get_kline(symbol, start_date=start_date, end_date=end_dt, freq=freq) if not df_.empty: data.append(df_) start_date = end_dt end_dt += delta print("当前下载进度：{} - {} - {}".format(symbol, start_date, end_dt)) df = pd.concat(data, ignore_index=True) print("{} 去重前K线数量为 {}".format(symbol, len(df))) df.drop_duplicates(['dt'], inplace=True) df.sort_values('dt', ascending=True, inplace=True) df.reset_index(drop=True, inplace=True) print("{} 去重后K线数量为 {}".format(symbol, len(df))) if save: df.to_csv(f"{symbol}_{freq}_{start_date.date()}_{end_date.date()}.csv", index=False, encoding="utf-8") else: return df