def get_sina_tick_js_LastPrice(symbols):
symbols_list=''
if len(symbols) == 0:
return ''
if isinstance(symbols, list) or isinstance(symbols, set) or isinstance(symbols, tuple) or isinstance(symbols, pd.Series):
for code in symbols:
symbols_list += cct.code_to_symbol(code) + ','
else:
symbols_list = cct.code_to_symbol(symbols)
# print symbol_str
url="http://hq.sinajs.cn/list=%s"%(symbols_list)
# print url
data = cct.get_url_data(url)
# vollist=re.findall('{data:(\d+)',code)
# print data
ulist=data.split(";")
price_dict={}
for var in range(0,len(ulist)-1):
# print var
if len(ulist)==2:
code=symbols
else:
code=symbols[var]
tempData = re.search('''(")(.+)(")''', ulist[var]).group(2)
stockInfo = tempData.split(",")
# stockName = stockInfo[0] #名称
# stockStart = stockInfo[1] #开盘
stockLastEnd= stockInfo[2] #昨收盘
# stockCur = stockInfo[3] #当前
# stockMax = stockInfo[4] #最高
# stockMin = stockInfo[5] #最低
# price_dict[code]=stockLastEnd
price_dict[code]=float(stockLastEnd)
# stockUp = round(float(stockCur) - float(stockLastEnd), 2)
# stockRange = round(float(stockUp) / float(stockLastEnd), 4) * 100
# stockVolume = round(float(stockInfo[8]) / (100 * 10000), 2)
# stockMoney = round(float(stockInfo[9]) / (100000000), 2)
# stockTime = stockInfo[31]
# dd={}
return price_dict
def get_tdx_Exp_day_to_df(code, type="f", start=None, end=None, dt=None, dl=None):
# start=cct.day8_to_day10(start)
# end=cct.day8_to_day10(end)
# day_path = day_dir % 'sh' if code[:1] in ['5', '6', '9'] else day_dir % 'sz'
code_u = cct.code_to_symbol(code)
log.debug("code:%s code_u:%s" % (code, code_u))
if type == "f":
file_path = exp_path + "forwardp" + path_sep + code_u.upper() + ".txt"
elif type == "b":
file_path = exp_path + "backp" + path_sep + code_u.upper() + ".txt"
else:
return None
log.debug("daypath:%s" % file_path)
# p_day_dir = day_path.replace('/', path_sep).replace('\\', path_sep)
# p_exp_dir = exp_dir.replace('/', path_sep).replace('\\', path_sep)
# print p_day_dir,p_exp_dir
if not os.path.exists(file_path):
# ds = Series(
# {'code': code, 'date': cct.get_today(), 'open': 0, 'high': 0, 'low': 0, 'close': 0, 'amount': 0,
# 'vol': 0})
ds = pd.DataFrame()
log.error("file_path:not exists")
return ds
# ofile = open(file_path, 'rb')
if dt is None and dl is None:
ofile = open(file_path, "rb")
buf = ofile.readlines()
ofile.close()
num = len(buf)
no = num - 1
dt_list = []
for i in xrange(no):
a = buf[i].split(",")
# 01/15/2016,27.57,28.15,26.30,26.97,714833.15,1946604544.000
# da=a[0].split('/')
tdate = a[0]
# tdate = str(a[0])[:4] + '-' + str(a[0])[4:6] + '-' + str(a[0])[6:8]
# tdate=dt.strftime('%Y-%m-%d')
topen = float(a[1])
thigh = float(a[2])
tlow = float(a[3])
tclose = float(a[4])
# tvol = round(float(a[5]) / 10, 2)
tvol = float(a[5])
amount = round(float(a[6].replace("\r\n", "")), 1) # int
# tpre = int(a[7]) # back
if int(amount) == 0:
continue
dt_list.append(
{
"code": code,
"date": tdate,
"open": topen,
"high": thigh,
"low": tlow,
"close": tclose,
"amount": amount,
"vol": tvol,
}
)
# if dt is not None and tdate < dt:
# break
df = pd.DataFrame(dt_list, columns=ct.TDX_Day_columns)
# df.sort_index(ascending=False, inplace=True)
if start is not None and end is not None:
df = df[(df.date >= start) & (df.date <= end)]
elif end is not None:
df = df[df.date <= end]
elif start is not None:
df = df[df.date >= start]
df = df.set_index("date")
return df
elif int(dl) == 1:
# fileSize = os.path.getsize(file_path)
# if fileSize < 60 * newstockdayl:
# return Series()
data = cct.read_last_lines(file_path, int(dl) + 3)
data_l = data.split("\n")
dt_list = Series()
data_l.reverse()
log.debug("day 1:%s" % data_l)
for line in data_l:
a = line.split(",")
# 01/15/2016,27.57,28.15,26.30,26.97,714833.15,1946604544.000
# da=a[0].split('/')
log.debug("day 1 len(a):%s a:%s" % (len(a), a))
if len(a) > 5:
tdate = a[0]
log.debug("day 1 tdate:%s" % tdate)
# tdate = str(a[0])[:4] + '-' + str(a[0])[4:6] + '-' + str(a[0])[6:8]
# tdate=dt.strftime('%Y-%m-%d')
topen = float(a[1])
thigh = float(a[2])
tlow = float(a[3])
tclose = float(a[4])
# tvol = round(float(a[5]) / 10, 2)
tvol = float(a[5])
amount = round(float(a[6].replace("\r\n", "")), 1) # int
# tpre = int(a[7]) # back
if int(amount) == 0:
continue
dt_list = Series(
{
"code": code,
"date": tdate,
"open": topen,
"high": thigh,
"low": tlow,
"close": tclose,
"amount": amount,
"vol": tvol,
}
)
break
else:
continue
# if dt is not None and tdate < dt:
# break
# df = pd.DataFrame(dt_list, columns=ct.TDX_Day_columns)
# df = df.set_index('date')
return dt_list
else:
fileSize = os.path.getsize(file_path)
# if fileSize < 60 * newstockdayl:
# return Series()
data = cct.read_last_lines(file_path, int(dl) + 2)
dt_list = []
data_l = data.split("\n")
data_l.reverse()
for line in data_l:
a = line.split(",")
# 01/15/2016,27.57,28.15,26.30,26.97,714833.15,1946604544.000
# da=a[0].split('/')
if len(a) > 5:
tdate = a[0]
# tdate = str(a[0])[:4] + '-' + str(a[0])[4:6] + '-' + str(a[0])[6:8]
# tdate=dt.strftime('%Y-%m-%d')
topen = float(a[1])
thigh = float(a[2])
tlow = float(a[3])
tclose = float(a[4])
tvol = round(float(a[5]) / 10, 2)
amount = round(float(a[6].replace("\r\n", "")), 1) # int
# tpre = int(a[7]) # back
if int(amount) == 0:
continue
dt_list.append(
{
"code": code,
"date": tdate,
"open": topen,
"high": thigh,
"low": tlow,
"close": tclose,
"amount": amount,
"vol": tvol,
}
)
else:
continue
# if dt is not None and tdate < dt:
# break
df = pd.DataFrame(dt_list, columns=ct.TDX_Day_columns)
# df.sort_index(ascending=False, inplace=True)
# if start is not None and end is not None:
# df = df[(df.date >= start) & (df.date <= end)]
# elif end is not None:
# df = df[df.date <= end]
# elif start is not None:
# df = df[df.date >= start]
df = df.set_index("date")
# print "time:",(time.time()-time_s)*1000
return df
def get_tdx_day_to_df_last(code, dayl=1, type=0, dt=None, ptype="low", dl=None):
"""
:param code:999999
:param dayl:Duration Days
:param type:TDX type
:param dt: Datetime
:param ptype:low or high
:return:Series or df
"""
# dayl=int(dayl)
# type=int(type)
# print "t:",dayl,"type",type
if not type == 0:
f = lambda x: str((1000000 - int(x))) if x.startswith("0") else x
code = f(code)
code_u = cct.code_to_symbol(code)
day_path = day_dir % "sh" if code.startswith(("5", "6", "9")) else day_dir % "sz"
p_day_dir = day_path.replace("/", path_sep).replace("\\", path_sep)
# p_exp_dir=exp_dir.replace('/',path_sep).replace('\\',path_sep)
# print p_day_dir,p_exp_dir
file_path = p_day_dir + code_u + ".day"
if not os.path.exists(file_path):
ds = Series(
{"code": code, "date": cct.get_today(), "open": 0, "high": 0, "low": 0, "close": 0, "amount": 0, "vol": 0}
)
return ds
ofile = file(file_path, "rb")
b = 0
e = 32
if dayl == 1 and dt == None:
log.debug("%s" % (dayl == 1 and dt == None))
fileSize = os.path.getsize(file_path)
if fileSize < 32:
print "why", code
ofile.seek(-e, 2)
buf = ofile.read()
ofile.close()
a = unpack("IIIIIfII", buf[b:e])
tdate = str(a[0])[:4] + "-" + str(a[0])[4:6] + "-" + str(a[0])[6:8]
topen = float(a[1] / 100.0)
thigh = float(a[2] / 100.0)
tlow = float(a[3] / 100.0)
tclose = float(a[4] / 100.0)
amount = float(a[5] / 10.0)
tvol = int(a[6]) # int
# tpre = int(a[7]) # back
dt_list = Series(
{
"code": code,
"date": tdate,
"open": topen,
"high": thigh,
"low": tlow,
"close": tclose,
"amount": amount,
"vol": tvol,
}
)
return dt_list
elif dayl == 1 and dt is not None and dl is not None:
log.debug("dt:%s" % (dt))
dt_list = []
# if len(str(dt)) == 8:
# dt = cct.day8_to_day10(dt)
# else:
# dt=get_duration_price_date(code, ptype=ptype, dt=dt)
# print ("dt:%s"%dt)
fileSize = os.path.getsize(file_path)
if fileSize < 32:
print "why", code
b = fileSize
ofile.seek(-fileSize, 2)
no = int(fileSize / e)
# if no < newstockdayl:
# return Series()
# print no,b,day_cout,fileSize
buf = ofile.read()
ofile.close()
# print repr(buf)
# df=pd.DataFrame()
for i in xrange(no):
a = unpack("IIIIIfII", buf[-e:b])
tdate = str(a[0])[:4] + "-" + str(a[0])[4:6] + "-" + str(a[0])[6:8]
topen = float(a[1] / 100.0)
thigh = float(a[2] / 100.0)
tlow = float(a[3] / 100.0)
tclose = float(a[4] / 100.0)
amount = float(a[5] / 10.0)
tvol = int(a[6]) # int
# tpre = int(a[7]) # back
dt_list.append(
{
"code": code,
"date": tdate,
"open": topen,
"high": thigh,
"low": tlow,
"close": tclose,
"amount": amount,
"vol": tvol,
}
)
# print series
# dSeries.append(series)
# dSeries.append(Series({'code':code,'date':tdate,'open':topen,'high':thigh,'low':tlow,'close':tclose,'amount':amount,'vol':tvol,'pre':tpre}))
b = b - 32
e = e + 32
# print tdate,dt
if tdate < dt:
# print "why"
break
df = pd.DataFrame(dt_list, columns=ct.TDX_Day_columns)
# print "len:%s %s"%(len(df),fileSize)
df = df.set_index("date")
dt = get_duration_price_date(code, ptype=ptype, dt=dt, df=df, dl=dl)
log.debug("last_dt:%s" % dt)
dd = df[df.index == dt]
if len(dd) > 0:
dd = dd[:1]
dt = dd.index.values[0]
dd = dd.T[dt]
dd["date"] = dt
else:
log.warning("no < dt:NULL")
dd = Series()
# dd = Series(
# {'code': code, 'date': cct.get_today(), 'open': 0, 'high': 0, 'low': 0, 'close': 0, 'amount': 0,
# 'vol': 0})
return dd
else:
dt_list = []
fileSize = os.path.getsize(file_path)
# print fileSize
day_cout = abs(e * int(dayl))
# print day_cout
if day_cout > fileSize:
b = fileSize
ofile.seek(-fileSize, 2)
no = int(fileSize / e)
else:
no = int(dayl)
b = day_cout
ofile.seek(-day_cout, 2)
# print no,b,day_cout,fileSize
buf = ofile.read()
ofile.close()
# print repr(buf)
# df=pd.DataFrame()
for i in xrange(no):
a = unpack("IIIIIfII", buf[-e:b])
tdate = str(a[0])[:4] + "-" + str(a[0])[4:6] + "-" + str(a[0])[6:8]
topen = float(a[1] / 100.0)
thigh = float(a[2] / 100.0)
tlow = float(a[3] / 100.0)
tclose = float(a[4] / 100.0)
amount = float(a[5] / 10.0)
tvol = int(a[6]) # int
# tpre = int(a[7]) # back
dt_list.append(
{
"code": code,
"date": tdate,
"open": topen,
"high": thigh,
"low": tlow,
"close": tclose,
"amount": amount,
"vol": tvol,
}
)
# print series
# dSeries.append(series)
# dSeries.append(Series({'code':code,'date':tdate,'open':topen,'high':thigh,'low':tlow,'close':tclose,'amount':amount,'vol':tvol,'pre':tpre}))
b = b - 32
e = e + 32
df = pd.DataFrame(dt_list, columns=ct.TDX_Day_columns)
df = df.set_index("date")
return df
def get_tdx_day_to_df(code):
"""
获取个股历史交易记录
Parameters
------
code:string
股票代码 e.g. 600848
start:string
开始日期 format：YYYY-MM-DD 为空时取到API所提供的最早日期数据
end:string
结束日期 format：YYYY-MM-DD 为空时取到最近一个交易日数据
ktype：string
数据类型，D=日k线 W=周 M=月 5=5分钟 15=15分钟 30=30分钟 60=60分钟，默认为D
retry_count : int, 默认 3
如遇网络等问题重复执行的次数
pause : int, 默认 0
重复请求数据过程中暂停的秒数，防止请求间隔时间太短出现的问题
return
-------
DataFrame
属性:日期 ，开盘价， 最高价， 收盘价， 最低价， 成交量， 价格变动 ，涨跌幅，5日均价，10日均价，20日均价，5日均量，10日均量，20日均量，换手率
"""
# time_s=time.time()
# print code
code_u = cct.code_to_symbol(code)
day_path = day_dir % "sh" if code[:1] in ["5", "6", "9"] else day_dir % "sz"
p_day_dir = day_path.replace("/", path_sep).replace("\\", path_sep)
# p_exp_dir = exp_dir.replace('/', path_sep).replace('\\', path_sep)
# print p_day_dir,p_exp_dir
file_path = p_day_dir + code_u + ".day"
if not os.path.exists(file_path):
ds = Series(
{"code": code, "date": cct.get_today(), "open": 0, "high": 0, "low": 0, "close": 0, "amount": 0, "vol": 0}
)
return ds
ofile = open(file_path, "rb")
buf = ofile.read()
ofile.close()
num = len(buf)
no = int(num / 32)
b = 0
e = 32
dt_list = []
for i in xrange(no):
a = unpack("IIIIIfII", buf[b:e])
# dt=datetime.date(int(str(a[0])[:4]),int(str(a[0])[4:6]),int(str(a[0])[6:8]))
tdate = str(a[0])[:4] + "-" + str(a[0])[4:6] + "-" + str(a[0])[6:8]
# tdate=dt.strftime('%Y-%m-%d')
topen = float(a[1] / 100.0)
thigh = float(a[2] / 100.0)
tlow = float(a[3] / 100.0)
tclose = float(a[4] / 100.0)
amount = float(a[5] / 10.0)
tvol = int(a[6]) # int
tpre = int(a[7]) # back
dt_list.append(
{
"code": code,
"date": tdate,
"open": topen,
"high": thigh,
"low": tlow,
"close": tclose,
"amount": amount,
"vol": tvol,
"pre": tpre,
}
)
b = b + 32
e = e + 32
df = pd.DataFrame(dt_list, columns=ct.TDX_Day_columns)
df = df.set_index("date")
# print "time:",(time.time()-time_s)*1000
return df
