# -*- coding:utf-8 -*- """ pro init Created on 2018/07/01 @author: Jimmy Liu @group : https://tushare.pro @contact: jimmysoa@sina.cn """ from __future__ import division import datetime from tushare.pro import client from tushare.util import upass from tushare.util.formula import MA PRICE_COLS = ['open', 'close', 'high', 'low', 'pre_close'] FORMAT = lambda x: '%.2f' % x FREQS = {'D': '1DAY', 'W': '1WEEK', 'Y': '1YEAR', } FACT_LIST = { 'tor': 'turnover_rate', 'turnover_rate': 'turnover_rate', 'vr': 'volume_ratio', 'volume_ratio': 'volume_ratio', 'pe': 'pe', 'pe_ttm': 'pe_ttm', } def pro_api(token='', timeout=30): """ 初始化pro API,第一次可以通过ts.set_token('your token')来记录自己的token凭证，临时token可以通过本参数传入 """ if token == '' or token is None: token = upass.get_token() if token is not None and token != '': pro = client.DataApi(token=token, timeout=timeout) return pro else: raise Exception('api init error.') def pro_bar(ts_code='', api=None, start_date='', end_date='', freq='D', asset='E', exchange='', adj = None, ma = [], factors = None, adjfactor = False, offset = None, limit = None, fields = '', contract_type = '', retry_count = 3): """ BAR数据 Parameters: ------------ ts_code:证券代码，支持股票,ETF/LOF,期货/期权,港股,数字货币 start_date:开始日期 YYYYMMDD end_date:结束日期 YYYYMMDD freq:支持1/5/15/30/60分钟,周/月/季/年 asset:证券类型 E:股票和交易所基金，I:沪深指数,C:数字货币,FT:期货 FD:基金/O期权/H港股/CB可转债 exchange:市场代码，用户数字货币行情 adj:复权类型,None不复权,qfq:前复权,hfq:后复权 ma:均线,支持自定义均线频度，如：ma5/ma10/ma20/ma60/maN offset:开始行数（分页功能，从第几行开始取数据） limit: 本次提取数据行数 factors因子数据，目前支持以下两种： vr:量比,默认不返回，返回需指定：factor=['vr'] tor:换手率，默认不返回，返回需指定：factor=['tor'] 以上两种都需要：factor=['vr', 'tor'] retry_count:网络重试次数 Return ---------- DataFrame code:代码 open：开盘close/high/low/vol成交量/amount成交额/maN均价/vr量比/tor换手率 期货(asset='FT') code/open/close/high/low/avg_price：均价 position：持仓量 vol：成交总量 """ if (ts_code=='' or ts_code is None) and (adj is not None): print('提取复权行情必须输入ts_code参数') return if len(freq.strip())>=3: freq = freq.strip().lower() else: freq = freq.strip().upper() if asset != 'C' else freq.strip().lower() if 'min' not in freq: today= datetime.datetime.today().date() today = str(today)[0:10] start_date = '' if start_date is None else start_date end_date = today if end_date == '' or end_date is None else end_date start_date = start_date.replace('-', '') end_date = end_date.replace('-', '') ts_code = ts_code.strip().upper() if asset != 'C' else ts_code.strip().lower() asset = asset.strip().upper() api = api if api is not None else pro_api() for _ in range(retry_count): try: if asset == 'E': if freq == 'D': data = api.daily(ts_code=ts_code, start_date=start_date, end_date=end_date, offset=offset, limit=limit) if factors is not None and len(factors) >0 : ds = api.daily_basic(ts_code=ts_code, start_date=start_date, end_date=end_date)[['trade_date', 'turnover_rate', 'volume_ratio']] ds = ds.set_index('trade_date') data = data.set_index('trade_date') data = data.merge(ds, left_index=True, right_index=True) data = data.reset_index() if ('tor' in factors) and ('vr' not in factors): data = data.drop('volume_ratio', axis=1) if ('vr' in factors) and ('tor' not in factors): data = data.drop('turnover_rate', axis=1) if freq == 'W': data = api.weekly(ts_code=ts_code, start_date=start_date, end_date=end_date, offset=offset, limit=limit) if freq == 'M': data = api.monthly(ts_code=ts_code, start_date=start_date, end_date=end_date, offset=offset, limit=limit) if 'min' in freq: data = api.stk_mins(ts_code=ts_code, start_date=start_date, end_date=end_date, freq=freq, offset=offset, limit=limit) data['trade_date'] = data['trade_time'].map(lambda x: x.replace('-', '')[0:8]) data['pre_close'] = data['close'].shift(-1) if adj is not None: fcts = api.adj_factor(ts_code=ts_code, start_date=start_date, end_date=end_date)[['trade_date', 'adj_factor']] if fcts.shape[0] == 0: return None data = data.set_index('trade_date', drop=False).merge(fcts.set_index('trade_date'), left_index=True, right_index=True, how='left') if 'min' in freq: data = data.sort_values('trade_time', ascending=False) data['adj_factor'] = data['adj_factor'].fillna(method='bfill') for col in PRICE_COLS: if adj == 'hfq': data[col] = data[col] * data['adj_factor'] if adj == 'qfq': data[col] = data[col] * data['adj_factor'] / float(fcts['adj_factor'][0]) data[col] = data[col].map(FORMAT) data[col] = data[col].astype(float) if adjfactor is False: data = data.drop('adj_factor', axis=1) if 'min' not in freq: data['change'] = data['close'] - data['pre_close'] data['pct_chg'] = data['change'] / data['pre_close'] * 100 data['pct_chg'] = data['pct_chg'].map(lambda x: FORMAT(x)).astype(float) else: data = data.drop(['trade_date', 'pre_close'], axis=1) else: data['pre_close'] = data['close'].shift(-1) data['change'] = data['close'] - data['pre_close'] data['pct_chg'] = data['change'] / data['pre_close'] * 100 data['pct_chg'] = data['pct_chg'].map(lambda x: FORMAT(x)).astype(float) elif asset == 'I': if freq == 'D': data = api.index_daily(ts_code=ts_code, start_date=start_date, end_date=end_date, offset=offset, limit=limit) if freq == 'W': data = api.index_weekly(ts_code=ts_code, start_date=start_date, end_date=end_date, offset=offset, limit=limit) if freq == 'M': data = api.index_monthly(ts_code=ts_code, start_date=start_date, end_date=end_date, offset=offset, limit=limit) if 'min' in freq: data = api.stk_mins(ts_code=ts_code, start_date=start_date, end_date=end_date, freq=freq, offset=offset, limit=limit) elif asset == 'FT': if freq == 'D': data = api.fut_daily(ts_code=ts_code, start_date=start_date, end_date=end_date, exchange=exchange, offset=offset, limit=limit) if 'min' in freq: data = api.ft_mins(ts_code=ts_code, start_date=start_date, end_date=end_date, freq=freq, offset=offset, limit=limit) elif asset == 'O': if freq == 'D': data = api.opt_daily(ts_code=ts_code, start_date=start_date, end_date=end_date, exchange=exchange, offset=offset, limit=limit) if 'min' in freq: data = api.opt_mins(ts_code=ts_code, start_date=start_date, end_date=end_date, freq=freq, offset=offset, limit=limit) elif asset == 'CB': if freq == 'D': data = api.cb_daily(ts_code=ts_code, start_date=start_date, end_date=end_date, offset=offset, limit=limit) elif asset == 'FD': if freq == 'D': data = api.fund_daily(ts_code=ts_code, start_date=start_date, end_date=end_date, offset=offset, limit=limit) if 'min' in freq: data = api.stk_mins(ts_code=ts_code, start_date=start_date, end_date=end_date, freq=freq, offset=offset, limit=limit) if asset == 'C': if freq == 'd': freq = 'daily' elif freq == 'w': freq = 'week' data = api.coinbar(exchange=exchange, symbol=ts_code, freq=freq, start_dae=start_date, end_date=end_date, contract_type=contract_type) if ma is not None and len(ma) > 0: for a in ma: if isinstance(a, int): data['ma%s'%a] = MA(data['close'], a).map(FORMAT).shift(-(a-1)) data['ma%s'%a] = data['ma%s'%a].astype(float) data['ma_v_%s'%a] = MA(data['vol'], a).map(FORMAT).shift(-(a-1)) data['ma_v_%s'%a] = data['ma_v_%s'%a].astype(float) data = data.reset_index(drop=True) except Exception as e: print(e) else: if fields is not None and fields != '': f_list = [col.strip() for col in fields.split(',')] data = data[f_list] return data raise IOError('ERROR.') def pro_api(token='', timeout=30): """ 初始化pro API,第一次可以通过ts.set_token('your token')来记录自己的token凭证，临时token可以通过本参数传入 """ if token == '' or token is None: token = upass.get_token() if token is not None and token != '': pro = client.DataApi(token=token, timeout=timeout) return pro else: raise Exception('api init error.') def pro_bar_vip(ts_code='', api=None, start_date='', end_date='', freq='D', asset='E', exchange='', adj = None, ma = [], factors = None, adjfactor = False, offset = None, limit = None, fields = '', contract_type = '', retry_count = 3): """ BAR数据 Parameters: ------------ ts_code:证券代码，支持股票,ETF/LOF,期货/期权,港股,数字货币 start_date:开始日期 YYYYMMDD end_date:结束日期 YYYYMMDD freq:支持1/5/15/30/60分钟,周/月/季/年 asset:证券类型 E:股票和交易所基金，I:沪深指数,C:数字货币,FT:期货 FD:基金/O期权/H港股/CB可转债 exchange:市场代码，用户数字货币行情 adj:复权类型,None不复权,qfq:前复权,hfq:后复权 ma:均线,支持自定义均线频度，如：ma5/ma10/ma20/ma60/maN offset:开始行数（分页功能，从第几行开始取数据） limit: 本次提取数据行数 factors因子数据，目前支持以下两种： vr:量比,默认不返回，返回需指定：factor=['vr'] tor:换手率，默认不返回，返回需指定：factor=['tor'] 以上两种都需要：factor=['vr', 'tor'] retry_count:网络重试次数 Return ---------- DataFrame code:代码 open：开盘close/high/low/vol成交量/amount成交额/maN均价/vr量比/tor换手率 期货(asset='FT') code/open/close/high/low/avg_price：均价 position：持仓量 vol：成交总量 """ if (ts_code=='' or ts_code is None) and (adj is not None): print('提取复权行情必须输入ts_code参数') return if len(freq.strip())>=3: freq = freq.strip().lower() else: freq = freq.strip().upper() if asset != 'C' else freq.strip().lower() if 'min' not in freq: today= datetime.datetime.today().date() today = str(today)[0:10] start_date = '' if start_date is None else start_date end_date = today if end_date == '' or end_date is None else end_date start_date = start_date.replace('-', '') end_date = end_date.replace('-', '') ts_code = ts_code.strip().upper() if asset != 'C' else ts_code.strip().lower() asset = asset.strip().upper() api = api if api is not None else pro_api() for _ in range(retry_count): try: if asset == 'E': if freq == 'D': data = api.daily_vip(ts_code=ts_code, start_date=start_date, end_date=end_date, offset=offset, limit=limit) if factors is not None and len(factors) >0 : ds = api.daily_basic_vip(ts_code=ts_code, start_date=start_date, end_date=end_date)[['trade_date', 'turnover_rate', 'volume_ratio']] ds = ds.set_index('trade_date') data = data.set_index('trade_date') data = data.merge(ds, left_index=True, right_index=True) data = data.reset_index() if ('tor' in factors) and ('vr' not in factors): data = data.drop('volume_ratio', axis=1) if ('vr' in factors) and ('tor' not in factors): data = data.drop('turnover_rate', axis=1) if freq == 'W': data = api.weekly_vip(ts_code=ts_code, start_date=start_date, end_date=end_date, offset=offset, limit=limit) if freq == 'M': data = api.monthly_vip(ts_code=ts_code, start_date=start_date, end_date=end_date, offset=offset, limit=limit) if 'min' in freq: data = api.stk_mins_vip(ts_code=ts_code, start_date=start_date, end_date=end_date, freq=freq, offset=offset, limit=limit) data['trade_date'] = data['trade_time'].map(lambda x: x.replace('-', '')[0:8]) data['pre_close'] = data['close'].shift(-1) if adj is not None: fcts = api.adj_factor_vip(ts_code=ts_code, start_date=start_date, end_date=end_date)[['trade_date', 'adj_factor']] if fcts.shape[0] == 0: return None data = data.set_index('trade_date', drop=False).merge(fcts.set_index('trade_date'), left_index=True, right_index=True, how='left') if 'min' in freq: data = data.sort_values('trade_time', ascending=False) data['adj_factor'] = data['adj_factor'].fillna(method='bfill') for col in PRICE_COLS: if adj == 'hfq': data[col] = data[col] * data['adj_factor'] if adj == 'qfq': data[col] = data[col] * data['adj_factor'] / float(fcts['adj_factor'][0]) data[col] = data[col].map(FORMAT) data[col] = data[col].astype(float) if adjfactor is False: data = data.drop('adj_factor', axis=1) if 'min' not in freq: data['change'] = data['close'] - data['pre_close'] data['pct_chg'] = data['change'] / data['pre_close'] * 100 data['pct_chg'] = data['pct_chg'].map(lambda x: FORMAT(x)).astype(float) else: data = data.drop(['trade_date', 'pre_close'], axis=1) else: data['pre_close'] = data['close'].shift(-1) data['change'] = data['close'] - data['pre_close'] data['pct_chg'] = data['change'] / data['pre_close'] * 100 data['pct_chg'] = data['pct_chg'].map(lambda x: FORMAT(x)).astype(float) elif asset == 'I': if freq == 'D': data = api.index_daily_vip(ts_code=ts_code, start_date=start_date, end_date=end_date, offset=offset, limit=limit) if freq == 'W': data = api.index_weekly_vip(ts_code=ts_code, start_date=start_date, end_date=end_date, offset=offset, limit=limit) if freq == 'M': data = api.index_monthly_vip(ts_code=ts_code, start_date=start_date, end_date=end_date, offset=offset, limit=limit) if 'min' in freq: data = api.stk_mins_vip(ts_code=ts_code, start_date=start_date, end_date=end_date, freq=freq, offset=offset, limit=limit) elif asset == 'FT': if freq == 'D': data = api.fut_daily_vip(ts_code=ts_code, start_date=start_date, end_date=end_date, exchange=exchange, offset=offset, limit=limit) if 'min' in freq: data = api.ft_mins_vip(ts_code=ts_code, start_date=start_date, end_date=end_date, freq=freq, offset=offset, limit=limit) elif asset == 'O': if freq == 'D': data = api.opt_daily_vip(ts_code=ts_code, start_date=start_date, end_date=end_date, exchange=exchange, offset=offset, limit=limit) if 'min' in freq: data = api.opt_mins_vip(ts_code=ts_code, start_date=start_date, end_date=end_date, freq=freq, offset=offset, limit=limit) elif asset == 'CB': if freq == 'D': data = api.cb_daily_vip(ts_code=ts_code, start_date=start_date, end_date=end_date, offset=offset, limit=limit) elif asset == 'FD': if freq == 'D': data = api.fund_daily_vip(ts_code=ts_code, start_date=start_date, end_date=end_date, offset=offset, limit=limit) if 'min' in freq: data = api.stk_mins_vip(ts_code=ts_code, start_date=start_date, end_date=end_date, freq=freq, offset=offset, limit=limit) if asset == 'C': if freq == 'd': freq = 'daily' elif freq == 'w': freq = 'week' data = api.coinbar(exchange=exchange, symbol=ts_code, freq=freq, start_dae=start_date, end_date=end_date, contract_type=contract_type) if ma is not None and len(ma) > 0: for a in ma: if isinstance(a, int): data['ma%s'%a] = MA(data['close'], a).map(FORMAT).shift(-(a-1)) data['ma%s'%a] = data['ma%s'%a].astype(float) data['ma_v_%s'%a] = MA(data['vol'], a).map(FORMAT).shift(-(a-1)) data['ma_v_%s'%a] = data['ma_v_%s'%a].astype(float) data = data.reset_index(drop=True) except Exception as e: print(e) else: if fields is not None and fields != '': f_list = [col.strip() for col in fields.split(',')] data = data[f_list] return data raise IOError('ERROR.') def subs(token=''): if token == '' or token is None: token = upass.get_token() from tushare.subs.ts_subs.subscribe import TsSubscribe app = TsSubscribe(token=token) return app def ht_subs(username, password): from tushare.subs.ht_subs.subscribe import InsightSubscribe app = InsightSubscribe(username, password) return app if __name__ == '__main__': # upass.set_token('') pro = pro_api() df = pro_bar(ts_code='688539.SH', adj='qfq') print(df)