def test_get_growth_data(self):
mt = ts.Master()
df = mt.TradeCal(exchangeCD='XSHG',
beginDate='20150928',
endDate='20151010',
field='calendarDate,isOpen,prevTradeDate')
print(df)
def load_Internet_data(self):
mt = ts.Master()
df = mt.SecID(assetClass='E', field=','.join(FETCH_FIELDS))
df[FETCH_FIELDS[0]] = df[FETCH_FIELDS[0]].astype('string')
df.rename(columns={
FETCH_FIELDS[0]: TICKER_FIELD,
FETCH_FIELDS[1]: NAME_FIELD,
FETCH_FIELDS[2]: EXCHANGE_FIELD,
FETCH_FIELDS[3]: STATUS_FIELD,
FETCH_FIELDS[4]: LIST_DATE_FIELD
},
inplace=True)
df = df[df[EXCHANGE_FIELD].isin(
[gs.SHANGHAI_EXCHANGE, gs.SHENZHEN_EXCHANGE])]
df.index = Series(range(1, len(df) + 1))
return df
def load_data(self):
mt = ts.Master()
# Fetch data from tushare
df = mt.SecID(assetClass='E', field=','.join(self.fields_map.keys()))
# Change dtype of ticker to string
ticker_field = self.fields_map.keys()[0]
df[ticker_field] = df[ticker_field].astype('string')
# Filter stocks not in Shanghai exchagne and Shenzhen exchange
exchange_field = self.fields_map.keys()[2]
df = df[df[exchange_field].isin([gs.SHANGHAI_EXCHANGE, gs.SHENZHEN_EXCHANGE])]
# Recount index from 1 to len(df) + 1
df.index = Series(range(1, len(df) + 1))
self.data = df
# -*- coding: utf-8 -*-
from datetime import datetime, timedelta
print(datetime.now())
import tushare as ts
import pandas as pd
import numpy as np
import os
ts.set_token(
'1075d9a4eb51461266520905807f7d68806f68511ad0c90d938dc81af9ea6dee')
ts.Master().TradeCal(exchangeCD='XSHG,XSHE',
beginDate='20130101').to_csv('TradeCal.csv')
import tushare as tus
from pandas import DataFrame
import datetime
from talib import SMA
import traceback
tus.set_token(
'4b35b6b552ea66ef08186d267e693c86ed4726227979720aac8fb2d42a1c242a')
tl = tus.Master()
maPeriods = [10, 20, 60]
def mas_are_thrusted(ticker,
date=datetime.datetime.now().strftime("%Y-%m-%d")):
headDay = datetime.datetime.strftime(
datetime.datetime.strptime(date, "%Y-%m-%d") -
datetime.timedelta(days=365), "%Y-%m-%d")
dMktD = tus.get_k_data(ticker, headDay, date)
if dMktD.empty:
return False
closed = dMktD['close'].values
maVals = ma_vals(maPeriods, closed)
todayOpen = dMktD['open'].values.tolist()[-1]
todayClose = closed.tolist()[-1]
return todayClose > max(maVals) and todayOpen < min(maVals)
def ma_vals(maperiods, closed):
client = pymongo.MongoClient("localhost", 27017)
#
DB_GETRICH = client.GETRICH
db_SecID_coll = DB_GETRICH.SecID ## 证券编码及基本上市信息
db_TradeCal_coll = DB_GETRICH.TradeCal ## 交易所交易日历
db_SecTypeRel_coll = DB_GETRICH.SecTypeRel ## 证券板块成分
db_EquInfo_coll = DB_GETRICH.EquInfo ## 沪深股票键盘精灵
db_SecTypeRegionRel_coll = DB_GETRICH.SecTypeRegionRel ## 沪深股票地域分类
db_SecType_coll = DB_GETRICH.SecType ## 证券板块
db_SecTypeRegion_coll = DB_GETRICH.SecTypeRegion ## 地域分类
# 得到交易日
tlMaster = ts.Master()
# 证券编码及基本上市信息
stocksType = ['E','B','F','IDX','FU','OP'] # E 股票,B 债券,F 基金,IDX 指数,FU 期货,OP 期权；
for types in stocksType:
df = tlMaster.SecID(assetClass=types)
js_df = df[1:].to_json(orient="records")
db_json = json.loads(js_df)
db_SecID_coll.insert(db_json)
# 交易所交易日历
# XSHG表示上海证券交易所，XSHE表示深圳证券交易所，CCFX表示中国金融期货交易所，XDCE表示大连商品交易所，XSGE表示上海期货交易所，XZCE表示郑州商品交易所，XHKG表示香港证券交易所
#exchangeType = ['XSHG','XSHE','CCFX','XDCE','XSGE','XZCE','XHKG']
exchangeType = ['XSHG','XSHE']
for types in exchangeType:
df = tlMaster.TradeCal(exchangeCD=types, beginDate='20150928', endDate='20151010')
#df = df['calendarDate'].apply(lambda x: x.replace('-', ''))
opener.addheaders = []
for key, ele in headers.items():
opener.addheaders += [(key, ele)]
data = opener.open(url).read()
indexSoup = BeautifulSoup(data)
statusSoup = BeautifulSoup(indexSoup.prettify().decode("utf-8"))
import tushare as ts
ts.set_token(
'6cbc132dcf304322dc7b6f1d714d792fe224049b2038abf29e7711bf71334b52')
'''
通联数据
没有分时数据 也没有黄金延期
'''
mt = ts.Master()
code_info = mt.SecID(
assetClass='FU',
field='secID,ticker,secShortName,assetClass,exchangeCD,transCurrCD')
st = ts.Market()
AGTD = st.MktFutd(
tradeDate='20160229',
field='secID,tradeDate,ticker,secShortName,openPrice,closePrice')
F_product = st.MktMFutd(
tradeDate='20160229',
field='secID,tradeDate,ticker,secShortName,openPrice,closePrice')
# -*- coding: utf-8 -*-
from datetime import datetime, timedelta
print(datetime.now())
import tushare as ts
import pandas as pd
import numpy as np
import os
ts.set_token(
'1075d9a4eb51461266520905807f7d68806f68511ad0c90d938dc81af9ea6dee')
#get all stock code, name ticker,secShortName,exchangeCD,listDate
b01 = ts.Master().SecID(assetClass='E', field='ticker,exchangeCD')
b01 = b01[((b01['exchangeCD'] == 'XSHE') | (b01['exchangeCD'] == 'XSHG'))
& (b01['ticker'].str.len() == 6)].rename(columns={u'ticker': 'code'})
b02 = ts.get_stock_basics().loc[:, ['name', 'outstanding', 'timeToMarket']]
b02['code'] = b02.index.values
b0 = pd.merge(b02, b01, how='left', on='code')
b1 = list(b0.code)
#get Adj factor
adj0 = pd.DataFrame()
for i in list(range(len(b1)))[::451]:
adj1 = ts.Market().MktAdjf(ticker=','.join(b1[i:min(i + 450, len(b1))]),
field='ticker,exDivDate,adjFactor')
if adj0.empty:
adj0 = adj1
else:
