def get_zt_list(self,startDate,endDate,page,limit,status):
stocks = pd.DataFrame(columns=('代码', '名称', '日期', '备注', '状态'))
zts = base.get_zt_list(startDate=startDate,endDate=endDate)
industry = base.get_industry_list()
# print(zts)
for code in zts.index:
item = {
'代码': code,
'名称': zts.name[code],
'日期': zts.date[code],
# '隐单': j['yin'],
# '主单': j['zhu'],
# '原因': zts.reason[code],
'状态': zts.status[code],
'备注': zts.remark[code],
'行业': industry.industry[code],
'概念': industry.concept[code]
}
stocks = stocks.append(item, ignore_index=True)
if status == -1:
stocks = stocks[stocks['状态'] < 0]
if status == 1:
stocks = stocks[stocks['状态'] >= 0]
if status == 0:
stocks = stocks[stocks['状态'] >= 0]
# print(zt)
total = len(stocks)
str = stocks[(page - 1) * limit:page * limit].to_json(orient='split')
res = json.loads(str)
res['total'] = total
return json.dumps(res)
pass
def scrapy_yin_zt_tasks(self,startDate,endDate):
stock_list = base.get_zt_list(startDate=startDate, endDate=endDate)
code_list = stock_list.index.values
self.total = len(code_list)
pool = ThreadPool(10)#创建10个容量的线程池并发执行
pool.map(self.stock_yin_scrapy, code_list)
pool.close()
pool.join()
def scrapy_zt_hs_tasks(self, startDate, endDate):
# df = pd.merge(df, base_list,on='日期',how='right')
stock_list = base.get_zt_list(startDate=startDate, endDate=endDate)
observe_list = observe.query()
ob_code_list = observe_list['股票代码'].values
zt_code_list = stock_list.index.values
code_list = np.unique(np.append(ob_code_list, zt_code_list))
code_list = np.append(code_list, '100000')
# print(stock_list)
self.total = len(code_list)
self.endDate = endDate
pool = ThreadPool(10) #创建10个容量的线程池并发执行
pool.map(self.stock_lh_list_scrapy, code_list)
pool.close()
pool.join()
pass
def clear_zt_list(self, startDate, endDate):
collection = self.collection
stocks = pd.DataFrame(columns=('代码', '名称', '日期', '备注', '状态'))
zts = base.get_zt_list(startDate=startDate, endDate=endDate)
industry = base.get_industry_list()
# print(zts)
for code in zts.index:
item = {
'代码': code,
'名称': zts.name[code],
'日期': zts.date[code],
# '隐单': j['yin'],
# '主单': j['zhu'],
'原因': zts.reason[code],
'状态': zts.status[code],
'备注': zts.remark[code],
'行业': industry.industry[code],
'概念': industry.concept[code]
}
if 'ST' in zts.name[code]:
item = {
'code': code,
'date': zts.date[code],
'status': -1,
'remark': 'ST'
}
try:
collection.update(
{
'code': item['code'],
'date': item['date']
}, {"$set": item})
except Exception as e:
print(e)
else:
print("ST")
pass
if zts.date[code] == endDate:
pass
else:
s = base.get_stock_base(code=code,
startDate=zts.date[code],
endDate=endDate)
s = s.set_index(['日期'])
# print(code)
if len(s['成交额'].values) >= 2:
# print(s['成交额'])
pre = s['成交额'].values[-1]
next = s['成交额'].values[-2]
zf = s['涨幅'].values[-2]
# print(pre, next, zf)
if float(zf) < 9 and float(next) / float(pre) >= 1.6:
print(code, '第二天放量')
item = {
'code': code,
'date': zts.date[code],
'status': -1,
'remark': '放量'
}
try:
collection.update(
{
'code': item['code'],
'date': item['date']
}, {"$set": item})
except Exception as e:
print(e)
else:
print("成功")
pass
stocks = stocks.append(item, ignore_index=True)
pass
def query_yin_zt_list(self,startDate,endDate):
file_name_zt = '../files/yin/' + startDate + '|' + endDate + '-zt.xlsx'
if not os.path.exists(file_name_zt):
self.stocks = pd.DataFrame(columns=('代码', '名称', '日期', '涨幅', '隐单', '主单','力度','流通股','概念','行业'))
industry = base.get_industry_list()
base_list = base.get_stock_base_list(endDate)
query = {
'yin': {
'$gte': 100,
# '$lte': time_end
},
# 'zhu': {
# # '$gte': 0,
# '$lte': -100
# },
'zf': {
'$gte': -6.0,
'$lte': 6.0
},
'date': endDate,
# 'pCode':i,
# 'code': code
}
res = self.collection.find(query)
res_list = list(res)
self.total = len(res_list)
zt_list = base.get_zt_list(startDate=startDate, endDate=endDate).index
for j in res_list:
code = j['code']
date = j['date']
yin = float(j['yin'])
zhu = float(j['zhu'])
zj = float(j['zj'])
try:
item = {
'代码': code,
'名称': j['name'],
'日期': endDate,
'隐单': j['yin'],
'主单': j['zhu'],
'涨幅': j['zf'],
'流通股': long(base_list['流通股数'][j['code']]),
'力度': round((long(j['yin']) * 10000) / (long(base_list['流通股数'][j['code']])), 2),
'行业': industry.industry[j['code']],
'概念': industry.concept[j['code']]
}
except Exception as e:
print("出错"+code)
print(e)
continue
# for i, zf in enumerate(zfs):
# # print(i)
# item['第' + str(i + 2) + '天涨幅'] = zf
# if zhu != 0 and yin / abs(zhu) < 0.3:
# continue
# if zhu > 0 and zhu > yin:
# continue
# if abs(zj) <= 100:
# continue
if code in zt_list:
self.stocks = self.stocks.append(item, ignore_index=True)
if round((long(j['yin']) * 10000) / (long(base_list['流通股数'][j['code']])), 2) <= -0.01:
continue
# else:
# global stocks
# stocks = stocks.append(item, ignore_index=True)
# zfs = []
self.index += 1
print(str(self.index)+"/"+str(self.total))
pass
file_name_zt = '../files/yin/' + startDate + '|' + endDate + '-zt.xlsx'
writer_zt = pd.ExcelWriter(file_name_zt)
self.stocks.to_excel(writer_zt, 'Sheet1')
writer_zt.save()
else:
print("存在")
self.stocks = pd.read_excel(file_name_zt,dtype={'代码':str})
# print(self.stocks)
return self.stocks
pass