def get_queryset(self):
queryset = []
queryset = HSGTCG.getlist()
self.code = self.request.GET.get('code', '')
if self.code:
queryset = HSGTCG.getlist(self.code)
return queryset.order_by('-tradedate')
def test_everydayCount(self):
Stocktradedate.importList()
for d in [
d[0] for d in set(
list(HSGTCGHold.getlist().values_list('tradedate')))
]:
dcount = HSGTCGHold.getlist(d).count()
print(d, dcount)
from stocks.models import HSGTCG
tdate = HSGTCGHold.getNearestTradedate()
while tdate > convertToDate('2018-5-1'):
dcount = HSGTCGHold.getlist(tdate).count()
dcount1 = HSGTCG.getlist().filter(tradedate=tdate,
hamount__gte=8000).count()
print(tdate, dcount, dcount1, dcount - dcount1)
tdate = HSGTCGHold.getNearestTradedate(tdate -
datetime.timedelta(1))
from stocks.models import HSGTCG
tdate = HSGTCGHold.getNearestTradedate()
while tdate > convertToDate('2018-5-1'):
df1 = pd.DataFrame(list(HSGTCGHold.getlist(tdate).values('code')))
dcount = len(df1)
df2 = pd.DataFrame(
list(HSGTCG.getlist().filter(
tradedate=tdate, hamount__gte=8000).values('code')))
dcount1 = len(df2)
print(tdate, dcount, dcount1, dcount - dcount1)
if dcount - dcount1 != 0 and tdate > convertToDate('2018-6-1'):
print('数据不一致：', end='')
print(list(HSGTCGHold.dfNotInAnotherdf(df1, df2)['code']))
tdate = HSGTCGHold.getNearestTradedate(tdate -
datetime.timedelta(1))
def test_newcomingin(self):
""" 新加入市值八千万的个股
:return:
"""
Stocktradedate.importList()
from stocks.models import HSGTCG
# 2018 - 06 - 04 新增北向持股金额大于八千万
list1 = [
'603658', '600460', '002812', '002557', '600188', '000690',
'600329'
]
tdate = HSGTCGHold.getNearestTradedate()
# tdate = HSGTCGHold.getNearestTradedate('2018-6-4')
tdate1 = HSGTCGHold.getNearestTradedate(tdate - datetime.timedelta(1))
hsg = HSGTCGHold.getlist(tdate)
hsg1 = HSGTCGHold.getlist(tdate1)
list2 = []
for c in hsg.exclude(code__in=hsg1.values_list('code')):
list2.append(c.code)
# 验证是否前一天市值小于八千万
for code in list2:
df = pd.DataFrame(
list(
HSGTCG.getlist(code).filter(tradedate__gte=tdate1).values(
).order_by('-tradedate')))
data1 = float(df.iloc[-2].hamount)
data2 = float(df.iloc[-1].hamount)
if not (data1 >= 8000 and data2 < 8000):
print('不是新增持股金额大于八千万：{} 持股金额：{} {}'.format(code, data1, data2))
tdate = HSGTCGHold.getNearestTradedate()
while tdate > convertToDate('2018-5-2'):
tdate1 = HSGTCGHold.getNearestTradedate(tdate -
datetime.timedelta(1))
hsg = HSGTCGHold.getlist(tdate)
hsg1 = HSGTCGHold.getlist(tdate1)
list2 = []
for c in hsg.exclude(code__in=hsg1.values_list('code')):
list2.append(c.code)
# 验证是否前一天市值小于八千万
for code in list2:
df = pd.DataFrame(
list(
HSGTCG.getlist(code).filter(tradedate__gte=tdate1).
values().order_by('-tradedate')))
if len(df) > 1 and HSGTCG.getlist().filter(
tradedate=tdate1).count() > 0:
# if len(df)> 1 :
data1 = float(df.iloc[-2].hamount)
data2 = float(df.iloc[-1].hamount)
if not (data1 >= 8000 and data2 < 8000):
print('{} 不是新增持股金额大于八千万：{} 持股金额：{} {}'.format(
tdate, code, data1, data2))
tdate = HSGTCGHold.getNearestTradedate(tdate -
datetime.timedelta(1))
def test_importList(self):
"""
测试保存沪深港通持股
:return:
"""
HSGTCG.importList()
hsgtcg = HSGTCG.getlist()
print(hsgtcg)
self.assertTrue(hsgtcg.count() > 10,
'保存的数量： {}'.format(hsgtcg.count()))
print('数据库中保存的记录数量：{}'.format(hsgtcg.count()))
def test_hamountMA(self):
# n日持仓增加
n = 5
malist1 = MAUpper(n)
n = 10
malist2 = MAUpper(n)
HSGTCG.dfNotInAnotherdf(pd.DataFrame(malist1), pd.DataFrame(malist2))
up = list(
HSGTCG.dfNotInAnotherdf(pd.DataFrame(malist1),
pd.DataFrame(malist2))[0])
def test_importListdup(self):
"""
测试保存沪深港通持股
:return:
"""
# HSGTCG.importList()
HSGTCG.importList(firefoxHeadless=False)
hsgtcg = HSGTCG.getlist()
print(hsgtcg)
self.assertTrue(hsgtcg.count() > 1000,
'保存的数量： {}'.format(hsgtcg.count()))
print('数据库中保存的记录数量：{}'.format(hsgtcg.count()))
def MAUpper(n):
import QUANTAXIS as qa
tdate = HSGTCG.getNearestTradedate()
tdate = HSGTCG.getNearestTradedate(tdate, -(n + 100))
# hsg = HSGTCG.getlist().filter(tradedate__gte=(tdate, tdate), hamount__gte=8000)
hsg = HSGTCG.getlist().filter(tradedate__gte=tdate).order_by(
'code', 'tradedate')
df = pd.DataFrame(list(hsg.values('hamount', 'code', 'tradedate')))
results = []
for c in df.code.unique():
v = df[df['code'] == c]
ma1 = qa.MA(v.hamount, n)
if (ma1.iloc[-1] - ma1.iloc[-2]) >= 0:
results.append(v.code.iloc[0])
continue
return results
def test_newcomingin(self):
""" 最近n个交易日，新进市值大于8000万的个股
:return:
"""
n = 5
tdate = HSGTCG.getNearestTradedate()
tdate1 = HSGTCG.getNearestTradedate(tdate, -n)
tdate2 = HSGTCG.getNearestTradedate(tdate1, -n - 1)
yesterdayhsg = HSGTCG.getlist().filter(
tradedate=tdate2,
hamount__gte=8000,
)
hsg = HSGTCG.getlist().filter(tradedate__range=(tdate1, tdate),
hamount__gte=8000)
newcomming = hsg.exclude(
code__in=yesterdayhsg.values_list('code')).values('code')
print(newcomming)
def test_scrapt(self):
""" 个股北向持股
:return:
"""
code = '600066'
code = '000425'
code = '000792'
code = '002493'
url = 'http://data.eastmoney.com/hsgtcg/StockHdStatistics.aspx?stock={}'.format(
code)
browser = webdriver.Firefox()
browser.maximize_window()
try:
browser.get(url)
for x in ['lxml', 'xml', 'html5lib']:
# 可能会出现lxml版本大于4.1.1时，获取不到table
try:
time.sleep(random.random() / 4)
soup = BeautifulSoup(browser.page_source, x)
table = soup.find_all(id='tb_cgtj')[0]
if table:
break
except:
time.sleep(0.1)
print('using BeautifulSoup {}'.format(x))
# soup = BeautifulSoup(browser.page_source, 'lxml')
# table = soup.find_all(id='tb_cgtj')[0]
df = pd.read_html(str(table), header=1)[0]
df.columns = [
'date', 'related', 'close', 'zd', 'hvol', 'hamount',
'hpercent', 'oneday', 'fiveday', 'tenday'
]
for i in df.index:
v = df.iloc[i]
print('{} {} {} {}'.format(v.close, v.hvol, v.hamount,
v.hpercent))
HSGTCG.objects.get_or_create(code=code,
close=v.close,
hvol=str2Float(v.hvol),
hamount=str2Float(v.hamount),
hpercent=v.hpercent,
tradedate=convertToDate(v.date))
finally:
if browser:
browser.close()
hsgtcg = HSGTCG.getlist(code)
# hsgtcg = HSGTCG.getlist()
print(hsgtcg)
self.assertTrue(hsgtcg.count() > 10,
'保存的数量： {}'.format(hsgtcg.count()))
self.assertTrue(isinstance(hsgtcg[0].tradedate, datetime.date))
self.assertTrue(hsgtcg.filter(tradedate=None).count() == 0)
def test_scrapt(self):
""" 个股北向持股
:return:
"""
code = '600066'
url = 'http://data.eastmoney.com/hsgtcg/StockHdStatistics.aspx?stock={}'.format(
code)
opts = Options()
opts.set_headless()
assert opts.headless # operating in headless mode
browser = webdriver.Firefox(options=opts)
browser.maximize_window()
try:
browser.get(url)
soup = BeautifulSoup(browser.page_source, 'lxml')
table = soup.find_all(id='tb_cgtj')[0]
df = pd.read_html(str(table), header=1)[0]
df.columns = [
'date', 'related', 'close', 'zd', 'hvol', 'hamount',
'hpercent', 'oneday', 'fiveday', 'tenday'
]
for i in df.index:
v = df.iloc[i]
print('{} {} {} {}'.format(v.close, v.hvol, v.hamount,
v.hpercent))
HSGTCG.objects.get_or_create(code=code,
close=v.close,
hvol=str2Float(v.hvol),
hamount=str2Float(v.hamount),
hpercent=v.hpercent,
tradedate=v.date)
finally:
if browser:
browser.close()
hsgtcg = HSGTCG.getlist(code)
# hsgtcg = HSGTCG.getlist()
print(hsgtcg)
self.assertTrue(hsgtcg.count() > 10,
'保存的数量： {}'.format(hsgtcg.count()))
self.assertTrue(isinstance(hsgtcg[0].tradedate, datetime.date))
self.assertTrue(hsgtcg.filter(tradedate=None).count() == 0)
def importHSGTCG():
HSGTCGHold.importList()
HSGTCG.importList()