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