def __handleFoundHoldings(self, start, end, pageNo, retry, pause):
for _ in range(retry):
time.sleep(pause)
if pageNo > 0:
self._writeConsole()
try:
# http://quotes.money.163.com/hs/marketdata/service/jjcgph.php?host=/hs/marketdata/service/jjcgph.php&page=0&query=start:2018-06-30;end:2018-09-30&order=desc&count=60&type=query&req=73259
request = self._session.get(
cf.FUND_HOLDS_URL %
(pageNo, start, end, Utility.random(5)),
timeout=10)
if self._PY3:
request.encoding = 'utf-8'
lines = request.text
lines = lines.replace('--', '0')
lines = json.loads(lines)
data = lines['list']
df = pd.DataFrame(data)
df = df.drop([
'CODE', 'ESYMBOL', 'EXCHANGE', 'NAME', 'RN',
'SHANGQIGUSHU', 'SHANGQISHIZHI', 'SHANGQISHULIANG'
],
axis=1)
for col in ['GUSHU', 'GUSHUBIJIAO', 'SHIZHI', 'SCSTC27']:
df[col] = df[col].astype(float)
df['SCSTC27'] = df['SCSTC27'] * 100
df['GUSHU'] = df['GUSHU'] / 10000
df['GUSHUBIJIAO'] = df['GUSHUBIJIAO'] / 10000
df['SHIZHI'] = df['SHIZHI'] / 10000
df['GUSHU'] = df['GUSHU'].map(cf.FORMAT)
df['GUSHUBIJIAO'] = df['GUSHUBIJIAO'].map(cf.FORMAT)
df['SHIZHI'] = df['SHIZHI'].map(cf.FORMAT)
df['SCSTC27'] = df['SCSTC27'].map(cf.FORMAT)
df.columns = cf.FUND_HOLDS_COLS
df = df[[
'code', 'name', 'date', 'nums', 'nlast', 'count', 'clast',
'amount', 'ratio'
]]
except Exception as e:
print(e)
else:
if pageNo == 0:
return df, int(lines['pagecount'])
else:
return df
raise IOError(cf.NETWORK_URL_ERROR_MSG)
def xrxd(self, date='', retry=3, pause=0.001):
"""
获取股票除权除息信息
Parameters
------
date: string
format：YYYY-MM-DD
retry: 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
------
Dict or None
nd, 对应年份
fh_sh, 分红数额
djr, 股权登记日
cqr, 除权日
FHcontent, 除权除息信息
"""
data = None
if not date:
date = Utility.getToday()
symbol = Utility.symbol(self.__code)
for _ in range(retry):
time.sleep(pause)
url = cf.HISTORY_URL % ('fq', 'qfq', symbol, 'day', date, date,
'qfq', Utility.random(17))
try:
request = self._session.get(url, timeout=10)
pattern = re.compile(r'({"nd".+?})')
result = re.search(pattern, request.text)
if result:
data = eval(result.group(1))
except Exception as e:
print(str(e))
return data
raise IOError(cf.NETWORK_URL_ERROR_MSG)
def marginDetailsAllByDate(self, date, retry=3, pause=0.001):
"""
按日期获取两市融资融券明细列表
Parameters
--------
date : string
选择日期 format：YYYY-MM-DD
retry : 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 or List: [{'code':, 'name':, ...}, ...]
code: 股票代码
name: 名称
rzye: 当日融资余额(元)
rzyezb: 当日融资余额占比(%)
rzmre: 当日融资买入额(元)
rzche: 当日融资偿还额(元)
rzjmre: 当日融资净买入额(元)
rqye: 当日融券余额(元)
rqyl: 当日融券余量(股)
rqmcl: 当日融券卖出量(股)
rqchl: 当日融券偿还量(股)
rqjmcl: 当日融券净卖出量(股)
rzrqye: 当日融资融券余额(元)
rzrqyecz: 当日融资融券余额差值(元)
"""
self._data = pd.DataFrame()
self._writeHead()
self._data = self.__handleMarginDetailsAllByDate(
self._data, date, 1, Utility.random(8), retry, pause)
self._data.rename(columns={
'scode': 'code',
'sname': 'name'
},
inplace=True)
return self._result()
def __parsePage(self, cate='', event=0, num=0, retry=3, pause=0.001):
for _ in range(retry):
time.sleep(pause)
try:
rdInt = Utility.random()
request = self._session.get(cf.MACRO_URL %
(rdInt, cate, event, num, rdInt),
timeout=10)
if self._PY3:
request.encoding = 'gbk'
regSym = re.compile(r'\,count:(.*?)\}')
datastr = regSym.findall(request.text)
datastr = datastr[0]
datastr = datastr.split('data:')[1]
except Exception as e:
print(e)
else:
return datastr
raise IOError(cf.NETWORK_URL_ERROR_MSG)
def szMargins(self, retry=3, pause=0.001):
"""
深市融资融券历史数据
Parameters
--------
retry : 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 or List: [{'date':, 'close':, ...}, ...]
date: 日期
close: 深证成指收盘点数
zdf: 深证成指收盘涨跌幅(%)
rzye: 融资余额(元)
rzyezb: 融资余额占比(%)
rzmre: 融资买入额(元)
rzche: 融资偿还额(元)
rzjmre: 融资净买入额(元)
rqye: 融券余额(元)
rqyl: 融券余量(股)
rqmcl: 融券卖出量(股)
rqchl: 融券偿还量(股)
rqjmcl: 融券净卖出量(股)
rzrqye: 融资融券余额(元)
rzrqyecz: 融资融券余额差值(元)
"""
self._data = pd.DataFrame()
self._writeHead()
self._data = self.__handleMargins(self._data, 1, 'SZ',
Utility.random(8), cf.MAR_COLS,
retry, pause)
self._data.rename(columns={'tdate': 'date'}, inplace=True)
return self._result()
def history(self,
start='',
end='',
ktype='D',
autype='qfq',
index=False,
retry=3,
pause=0.001):
"""
获取股票交易历史数据
---------
Parameters:
start:string
开始日期 format：YYYY-MM-DD 为空时取上市首日
end:string
结束日期 format：YYYY-MM-DD 为空时取最近一个交易日
autype:string
复权类型，qfq-前复权 hfq-后复权 None-不复权，默认为qfq
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: 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 or list: [{'date':, 'open':, ...}, ...]
date 交易日期 (index)
open 开盘价
high 最高价
close 收盘价
low 最低价
volume 成交量
code 股票代码
"""
self._data = pd.DataFrame()
url = ''
dataflag = ''
symbol = cf.INDEX_SYMBOL[self.__code] if index else Utility.symbol(
self.__code)
autype = '' if autype is None else autype
if (start is not None) & (start != ''):
end = Utility.getToday() if end is None or end == '' else end
if ktype.upper() in cf.K_LABELS:
fq = autype if autype is not None else ''
if self.__code[:1] in ('1', '5') or index:
fq = ''
kline = '' if autype is None else 'fq'
if ((start is None or start == '') or
(end is None or end == '')) or (start == end):
# http://web.ifzq.gtimg.cn/appstock/app/fqkline/get?_var=kline_dayqfq¶m=sh600000,day,,,640,qfq&r=0.73327461855388564
urls = [
cf.HISTORY_URL %
(kline, fq, symbol, cf.TT_K_TYPE[ktype.upper()], start,
end, fq, Utility.random(17))
]
else:
years = Utility.ttDates(start, end)
urls = []
for year in years:
startdate = str(year) + '-01-01'
enddate = str(year + 1) + '-12-31'
# http://web.ifzq.gtimg.cn/appstock/app/fqkline/get?_var=kline_dayqfq2008¶m=sh600000,day,2008-01-01,2009-12-31,640,qfq&r=0.73327461855388564
url = cf.HISTORY_URL % (kline, fq + str(year), symbol,
cf.TT_K_TYPE[ktype.upper()],
startdate, enddate, fq,
Utility.random(17))
urls.append(url)
dataflag = '%s%s' % (fq, cf.TT_K_TYPE[ktype.upper()]) # qfqday
elif ktype in cf.K_MIN_LABELS:
# http://ifzq.gtimg.cn/appstock/app/kline/mkline?param=sh600000,m30,,640&_var=m30_today&r=0.5537154641907898
urls = [
cf.HISTORY_MIN_URL % (symbol, ktype, ktype, Utility.random(16))
]
dataflag = 'm%s' % ktype # m30
else:
raise TypeError('ktype input error.')
for url in urls:
self._data = self._data.append(self.__handleHistory(
url, dataflag, symbol, index, ktype, retry, pause),
ignore_index=True)
if ktype not in cf.K_MIN_LABELS:
if ((start is not None) & (start != '')) & ((end is not None) &
(end != '')):
self._data = self._data[(self._data.date >= start)
& (self._data.date <= end)]
return self._result()
raise IOError(cf.NETWORK_URL_ERROR_MSG)
def realtime(self):
"""
获取实时交易数据 getting real time quotes data
用于跟踪交易情况（本次执行的结果-上一次执行的数据）
Parameters
------
stockdata(code) code : string, array-like object (list, tuple, Series).
return
-------
DataFrame or list: [{'name':, 'open':, ...}, ...]
0：name，股票名字
1：open，今日开盘价
2：pre_close，昨日收盘价
3：price，当前价格
4：high，今日最高价
5：low，今日最低价
6：bid，竞买价，即“买一”报价
7：ask，竞卖价，即“卖一”报价
8：volumn，成交量 maybe you need do volumn/100
9：amount，成交金额（元 CNY）
10：b1_v，委买一（笔数 bid volume）
11：b1_p，委买一（价格 bid price）
12：b2_v，“买二”
13：b2_p，“买二”
14：b3_v，“买三”
15：b3_p，“买三”
16：b4_v，“买四”
17：b4_p，“买四”
18：b5_v，“买五”
19：b5_p，“买五”
20：a1_v，委卖一（笔数 ask volume）
21：a1_p，委卖一（价格 ask price）
...
30：date，日期；
31：time，时间；
"""
self._data = pd.DataFrame()
symbols_list = ''
if isinstance(self.__code, list) or isinstance(
self.__code, set) or isinstance(
self.__code, tuple) or isinstance(self.__code, pd.Series):
for code in self.__code:
symbols_list += Utility.symbol(code) + ','
else:
symbols_list = Utility.symbol(self.__code)
symbols_list = symbols_list[:-1] if len(
symbols_list) > 8 else symbols_list
# http://hq.sinajs.cn/rn=4879967949085&list=sh600000,sh600004
request = self._session.get(cf.LIVE_DATA_URL %
(Utility.random(), symbols_list),
timeout=10)
request.encoding = 'gbk'
reg = re.compile(r'\="(.*?)\";')
data = reg.findall(request.text)
regSym = re.compile(r'(?:sh|sz)(.*?)\=')
syms = regSym.findall(request.text)
data_list = []
syms_list = []
for index, row in enumerate(data):
if len(row) > 1:
data_list.append([astr for astr in row.split(',')])
syms_list.append(syms[index])
if len(syms_list) == 0:
return None
self._data = pd.DataFrame(data_list, columns=cf.LIVE_DATA_COLS)
self._data = self._data.drop('s', axis=1)
self._data['code'] = syms_list
ls = [cls for cls in self._data.columns if '_v' in cls]
for txt in ls:
self._data[txt] = self._data[txt].map(lambda x: x[:-2])
# 价格、成交量等转换为浮点类型
for col in [
'open', 'pre_close', 'price', 'high', 'low', 'bid', 'ask',
'volume', 'amount', 'b1_v', 'b1_p', 'b2_v', 'b2_p', 'b3_v',
'b3_p', 'b4_v', 'b4_p', 'b5_v', 'b5_p', 'a1_v', 'a1_p', 'a2_v',
'a2_p', 'a3_v', 'a3_p', 'a4_v', 'a4_p', 'a5_v', 'a5_p'
]:
self._data[col] = self._data[col].astype(float)
return self._result()