def post(self):
"""
json str:{"codes": "600008.SH, "fields": "ask1,bid1,asize1,bsize1,volume,amt,pre_close,open,high,low,last", "begin_time": "2017-01-04", "end_time": "2017-02-28", "options": ""}
:return: 返回万得返回数据dict
"""
data_dic = request.json
logger.info('/wst/ data_dic:%s', data_dic)
codes = data_dic['codes']
fields = data_dic['fields']
begin_time = data_dic['begin_time']
end_time = data_dic['end_time']
options = data_dic['options']
if not w.isconnected():
w.start()
if options == "":
options = None
ret_data = w.wst(codes, fields, begin_time, end_time, options)
error_code = ret_data.ErrorCode
if error_code != 0:
msg = ERROR_CODE_MSG_DIC.setdefault(error_code, "")
logger.error('wst("%s", "%s", "%s", "%s", "%s") ErrorCode=%d %s' %
(codes, fields, begin_time, end_time, options,
error_code, msg))
return {'error_code': ret_data.ErrorCode, 'message': msg}, 404
# if ret_data.ErrorCode != 0:
# logger.error('wsd("%s", "%s", "%s", "%s", "%s") ErrorCode=%d' % (
# codes, fields, begin_time, end_time, options, ret_data.ErrorCode))
# return {'error_code': ret_data.ErrorCode}, 404
# 将 Data数据中所有 datetime date 类型的数据转换为 string
data_len = len(ret_data.Data)
for n_data in range(data_len):
data = ret_data.Data[n_data]
data_len2 = len(data)
if data_len2 > 0:
# 取出第一个部位None的数据
for item_check in data:
if item_check is not None:
break
# 进行类型检查，如果发现是 datetime, date 类型之一，则进行类型转换
if item_check is not None and type(item_check) in (datetime,
date):
ret_data.Data[n_data] = [
format_2_datetime_str(dt) for dt in data
]
logger.info('%d column["%s"] date to str', n_data,
ret_data.Fields[n_data])
# 组成 DataFrame
ret_df = pd.DataFrame(
ret_data.Data,
index=ret_data.Fields,
columns=[format_2_datetime_str(dt) for dt in ret_data.Times])
# print(ret_df)
ret_dic = ret_df.to_dict()
# print('ret_dic:\n', ret_dic)
return ret_dic
def get_tick(code, start_time, end_time, dirpath):
try:
data_wind = w.wst(
code,
"pre_close,open,high,low,last,ask,bid,volume,amt,vol_ratio,iopv,limit_up,limit_down,ask5,ask4,ask3,ask2,ask1,bid1,bid2,bid3,bid4,bid5, asize5,asize4,asize3,asize2,asize1,bsize1,bsize2,bsize3,bsize4,bsize5",
start_time, end_time, "")
arr = np.array(data_wind.Data)
df = pd.DataFrame(arr.T,
index=data_wind.Times,
columns=data_wind.Fields)
df["code"] = data_wind.Codes[0]
df.index.name = "datetime"
filepath = dirpath + code + ".csv"
df.to_csv(filepath, encoding="utf_8_sig")
except:
print("{} is not insert".format(code))
return code
def read_data(self):
"""
Desc: 从wind读取期权和标的期货合约当个交易日的盘口数据并存入一个字典
:return: 装有数据的字典，键是合约代码、值是合约对应的盘口数据
"""
# (1) 获取行权价序列
_strike = strike_series(lower_strike=self.lower_strike,
upper_strike=self.upper_strike,
strike_interval=self.strike_interval)
# (2) 构造期货合约代码列表
contract, exchange = self.sec_name.split('.')
_contract = contract + str(self.month)
future_code = [_contract + '.' + exchange]
# (3) 获取期权合约代码列表
if exchange in ["CZC", "SHF"]:
call_option_code = [
_contract + 'C' + str(i) + '.' + exchange for i in _strike
]
put_option_code = [
_contract + 'P' + str(i) + '.' + exchange for i in _strike
]
elif exchange == "DCE":
call_option_code = [
_contract + '-C-' + str(i) + '.' + exchange for i in _strike
]
put_option_code = [
_contract + '-P-' + str(i) + '.' + exchange for i in _strike
]
else:
raise Exception('unexpected exchange')
sec_code = future_code + call_option_code + put_option_code
# (4) 根据上一步中的代码以及起止时间从wind中读取盘口数据
bid_ask_data = {}
for _code in sec_code:
_data = w.wst(_code, "bid1,ask1,bsize1,asize1", self.start_time,
self.end_time, "")
if _data.ErrorCode != 0:
warn('{} wind API error: error code is {}'.format(
_code, _data.ErrorCode))
else:
_df = pd.DataFrame(_data.Data).T
_df.columns = _data.Fields
_df.index = _data.Times
bid_ask_data[_code] = _df
return bid_ask_data
printpy(wsddata1)
# 通过wsd来提取各个报告期财务数据
print('\n\n' + '-----通过wsd来提取各个报告期财务数据-----' + '\n')
wsddata2 = w.wsd("600000.SH", "tot_oper_rev,tot_oper_cost,opprofit,net_profit_is", "2008-01-01",
"2015-12-22", "rptType=1;Period=Q;Days=Alldays;Fill=Previous")
printpy(wsddata2)
# 通过wss来取截面数据
print('\n\n' + '-----通过wss来取截面数据-----' + '\n')
wssdata = w.wss("600000.SH,600007.SH,600016.SH", "ev,total_shares",
"tradeDate=20151222;industryType=1")
printpy(wssdata)
# 通过wst来取日内成交数据
print('\n\n' + '-----通过wst来取日内成交数据-----' + '\n')
wstdata = w.wst("IF.CFE", "last,volume", "2015-12-22 09:00:00", "2015-12-22 14:04:45")
printpy(wstdata)
# 通过wsi来取日内分钟数据
print('\n\n' + '-----通过wsi来取日内分钟数据-----' + '\n')
wsidata = w.wsi("IF.CFE", "open,high,low,close,volume,amt", "2015-12-22 09:00:00",
"2015-12-22 14:06:15")
printpy(wsidata)
# 通过wset来取数据集数据
print('\n\n' + '-----通过wset来取数据集数据,获取沪深300指数权重-----' + '\n')
wsetdata = w.wset("IndexConstituent",
"date=20151222;windcode=000300.SH;field=date,wind_code,i_weight")
printpy(wsetdata)
print('\n\n' + '-----通过wsd来提取各个报告期财务数据-----' + '\n')
wsddata2 = w.wsd("600000.SH",
"tot_oper_rev,tot_oper_cost,opprofit,net_profit_is",
"2008-01-01", "2015-12-22",
"rptType=1;Period=Q;Days=Alldays;Fill=Previous")
printpy(wsddata2)
# 通过wss来取截面数据
print('\n\n' + '-----通过wss来取截面数据-----' + '\n')
wssdata = w.wss("600000.SH,600007.SH,600016.SH", "ev,total_shares",
"tradeDate=20151222;industryType=1")
printpy(wssdata)
# 通过wst来取日内成交数据
print('\n\n' + '-----通过wst来取日内成交数据-----' + '\n')
wstdata = w.wst("IF.CFE", "last,volume", "2015-12-22 09:00:00",
"2015-12-22 14:04:45")
printpy(wstdata)
# 通过wsi来取日内分钟数据
print('\n\n' + '-----通过wsi来取日内分钟数据-----' + '\n')
wsidata = w.wsi("IF.CFE", "open,high,low,close,volume,amt",
"2015-12-22 09:00:00", "2015-12-22 14:06:15")
printpy(wsidata)
# 通过wset来取数据集数据
print('\n\n' + '-----通过wset来取数据集数据,获取沪深300指数权重-----' + '\n')
wsetdata = w.wset(
"IndexConstituent",
"date=20151222;windcode=000300.SH;field=date,wind_code,i_weight")
printpy(wsetdata)
# -*- coding: utf-8 -*-
"""
Created on Wed Jun 07 13:07:33 2017
@author: Think
"""
from WindPy import w
import datetime
w.start()
data = w.wst("600000.SH", "open", "2017-06-06 09:00:00", "2017-06-06 14:04:45")
print data
def post(self):
"""
json str:{"codes": "600008.SH, "fields": "ask1,bid1,asize1,bsize1,volume,amt,pre_close,open,high,low,last",
"begin_time": "2017-01-04", "end_time": "2017-02-28", "options": ""}
:return: 返回万得返回数据dict
"""
args = receive_wst_parser.parse_args()
logger.info('/wst/ args:%s', args)
# codes = args['codes']
# fields = args['fields']
# begin_time = args['begin_time']
# end_time = args['end_time']
# options = args['options']
if args['options'] == "":
args['options'] = None
if not w.isconnected():
w.start()
ret_data = None
for nth in range(2):
ret_data = w.wst(**args)
error_code = ret_data.ErrorCode
if error_code != 0:
if nth == 0 and error_code == -40521010:
w.stop()
w.start()
logger.warning('尝试重新登陆成功，再次调用函数')
continue
msg = ERROR_CODE_MSG_DIC.setdefault(error_code, "")
logger.error('wst(%s) ErrorCode=%d %s' %
(args, error_code, msg))
raise RequestError(msg, None, error_code)
else:
break
else:
if ret_data is None:
msg = 'wst(%s) ret_data is None' % args
logger.error(msg)
raise RequestError(msg, None, 0)
# 将 Data数据中所有 datetime date 类型的数据转换为 string
data_len = len(ret_data.Data)
for n_data in range(data_len):
data = ret_data.Data[n_data]
data_len2 = len(data)
if data_len2 > 0:
# 取出第一个部位None的数据
item_check = None
for item_check in data:
if item_check is not None:
break
# 进行类型检查，如果发现是 datetime, date 类型之一，则进行类型转换
if item_check is not None and type(item_check) in (datetime,
date):
ret_data.Data[n_data] = [
format_2_datetime_str(dt) for dt in data
]
logger.info('%d column["%s"] date to str', n_data,
ret_data.Fields[n_data])
# 组成 DataFrame
ret_df = pd.DataFrame(
ret_data.Data,
index=ret_data.Fields,
columns=[format_2_datetime_str(dt) for dt in ret_data.Times])
# print(ret_df)
ret_dic = ret_df.to_dict()
# print('ret_dic:\n', ret_dic)
return ret_dic
print('\n\n' + '-----通过wsd来提取各个报告期财务数据-----' + '\n')
wsddata2 = w.wsd("600000.SH",
"tot_oper_rev,tot_oper_cost,opprofit,net_profit_is",
"2014-01-01", "2015-12-22",
"rptType=1;Period=Q;Days=Alldays;Fill=Previous")
printpy(wsddata2)
# 通过wss来取截面数据
print('\n\n' + '-----通过wss来取截面数据-----' + '\n')
wssdata = w.wss("600000.SH,600007.SH,600016.SH", "ev,total_shares",
"tradeDate=20151222;industryType=1")
printpy(wssdata)
# 通过wst来取日内成交数据
print('\n\n' + '-----通过wst来取日内成交数据-----' + '\n')
wstdata = w.wst("600001.SH", "last,volume", "2015-12-22 09:00:00",
"2015-12-22 14:04:45")
printpy(wstdata)
# 通过wsi来取日内分钟数据
print('\n\n' + '-----通过wsi来取日内分钟数据-----' + '\n')
wsidata = w.wsi("IF.CFE", "open,high,low,close,volume,amt",
"2015-12-22 09:00:00", "2015-12-22 14:06:15")
printpy(wsidata)
# 通过wset来取数据集数据
print('\n\n' + '-----通过wset来取数据集数据,获取沪深300指数权重-----' + '\n')
wsetdata = w.wset(
"IndexConstituent",
"date=20151222;windcode=000300.SH;field=date,wind_code,i_weight")
printpy(wsetdata)
__author__ = 'aming.tao'
from WindPy import w
from datetime import *
w.start()
data=w.wsd("600000.SH","close,amt","2013-04-30", datetime.today()-timedelta(1))#取浦发银行收盘价等信
data=w.wsd("600000.SH","close,amt", datetime.today()-timedelta(100))#
data=w.wsi("600000.SH","close,amt","2015-10-01 9:00:00")#取浦发银行分钟收盘价等信息
data=w.wst("600000.SH","open", datetime.today()-timedelta(0,2*3600), datetime.now())#取浦发银行tick数据信息
data=w.wss("600000.SH,000001.SZ","eps_ttm,orps,surpluscapitalps","rptDate=20121231")#取浦发银行等财务数据信息
data=w.wset("SectorConstituent",u"date=20130608;sector=全部A股")#取全部A 股股票代码、名称信息
w.wset("IndexConstituent","date=20130608;windcode=000300.SH;field=wind_code,i_weight")#取沪深300 指数中股票代码和权重
w.wset("TradeSuspend","startdate=20130508;enddate=20130608;field=wind_code,sec_name,suspend_type,suspend_reason")#取停牌信息
w.wset("SectorConstituent",u"date=20130608;sector=风险警示股票;field=wind_code,sec_name")#取ST 股票等风险警示股票信息
w.tdays("2013-05-01","2013-06-08")#返回5 月1 日到6 月8 日之间的交易日序列
w.tdays("2013-05-01")#返回5 月1 日到当前时间的交易日序列
w.tdaysoffset(-5,"2013-05-01")#返回5 月1 日前推五个交易日的日期，返回2013-4-19
w.tdaysoffset(-5)#返回当前时间前推五个交易日的日期
w.tdayscount("2013-05-01","2013-06-08")#返回5 月1 日到6 月8 日之间的交易日序列长度，为27
w.stop()
