def buy(self, code, value, date, is_value=True):
"""
:param code: Fcode
:param value:
:param date: datetime obj
:param is_value: bool, default True. whether the quantity in value is counted in value or in share,
only value is supported for funds. 基金无法按份额申购。
:return:
"""
if self.verbose:
print(f"buy {value} of {code} on {date.strftime('%Y-%m-%d')}")
if code in self.trades:
df = self.trades[code].status
cftable = self.trades[code].cftable
cftable = cftable[cftable["date"] <= self.lastdates[code]]
remtable = self.trades[code].remtable
remtable = remtable[remtable["date"] <= self.lastdates[code]]
self.lastdates[code] = date
df2 = pd.DataFrame([[date, value]], columns=["date", self.get_code(code)])
df = df.append(df2)
self.trades[code] = trade(
self.infos[code],
df,
cftable=cftable,
remtable=remtable,
)
else:
self.lastdates[code] = date
if code not in self.infos:
self.infos[code] = self.get_info(code)
df = pd.DataFrame({"date": [date], self.get_code(code): [value]})
self.trades[code] = trade(self.infos[code], df)
def __init__(self,
*fundtradeobj,
status=None,
fetch=False,
save=False,
path="",
form="csv"):
if not fundtradeobj:
# warning: not a very good way to automatic generate these fund obj
# because there might be some funds use round_down for share calculation, ie, label=2 must be given
# unless you are sure corresponding funds are added to the droplist
fundtradeobj = []
for code in status.columns[1:]:
try:
fundtradeobj.append(
trade(
fundinfo(code,
fetch=fetch,
save=save,
path=path,
form=form),
status,
))
except FundTypeError:
fundtradeobj.append(
trade(
mfundinfo(code,
fetch=fetch,
save=save,
path=path,
form=form),
status,
))
self.fundtradeobj = tuple(fundtradeobj)
self.totcftable = self._mergecftb()
def __init__(self,
*fundtradeobj,
status=None,
property=None,
fetch=False,
save=False,
path="",
form="csv"):
if isinstance(status, record):
if not property:
property = getattr(status, "property", {})
status = status.status
elif not property:
property = {}
if not fundtradeobj:
# warning: not a very good way to automatic generate these fund obj
# because there might be some funds use round_down for share calculation, ie, label=2 must be given
# unless you are sure corresponding funds are added to the droplist
fundtradeobj = []
for code in status.columns[1:]:
# r1, d2, v4 p = r+d+v
p = property.get(code, 0)
round_label = p % 2
dividend_label = ((p - round_label) / 2) % 2
value_label = ((p - round_label - dividend_label) / 4) % 2
try:
fundtradeobj.append(
trade(
fundinfo(
code,
round_label=round_label,
dividend_label=dividend_label,
fetch=fetch,
save=save,
path=path,
form=form,
),
status,
))
except FundTypeError:
fundtradeobj.append(
trade(
mfundinfo(
code,
round_label=round_label,
value_label=value_label,
fetch=fetch,
save=save,
path=path,
form=form,
),
status,
))
self.fundtradeobj = tuple(fundtradeobj)
self.totcftable = self._mergecftb()
def sell(self, code, share, date, is_value=False):
"""
:param code:
:param share:
:param date: datetime obj
:param is_value: bool, default False. 货币基金可按照金额赎回
:return:
"""
share = abs(share)
if self.verbose:
print(f"sell {share} of {code} on {date.strftime('%Y-%m-%d')}")
if code not in self.trades:
raise TradeBehaviorError("You are selling something that you don't have")
df = self.trades[code].status
cftable = self.trades[code].cftable
cftable = cftable[cftable["date"] <= self.lastdates[code]]
remtable = self.trades[code].remtable
remtable = remtable[remtable["date"] <= self.lastdates[code]]
self.lastdates[code] = date
self.lastdates[code] = date
df2 = pd.DataFrame([[date, -share]], columns=["date", self.get_code(code)])
df = df.append(df2)
if is_value:
self.set_fund(code, value_label=1)
self.trades[code] = trade(
self.infos[code],
df,
cftable=cftable,
remtable=remtable,
)
if is_value:
self.set_fund(code, value_label=0)
def __init__(self, policylist, namelist=None, date=today()):
self.warn = []
self.message = []
self.policylist = policylist
if namelist is None:
self.namelist = [i for i in range(len(policylist))]
else:
self.namelist = namelist
assert len(self.policylist) == len(self.namelist)
for i, policy in enumerate(policylist):
row = policy.status[policy.status["date"] == date]
if len(row) == 1:
warn = (
policy.aim.name,
policy.aim.code,
row.iloc[0].loc[policy.aim.code],
self.namelist[i],
)
self.warn.append(warn)
if warn[2] > 0:
sug = "买入%s元" % warn[2]
elif warn[2] < 0:
ratio = -warn[2] / 0.005 * 100
share = (trade(fundinfo(warn[1]),
policy.status).briefdailyreport().get(
"currentshare", 0))
share = -warn[2] / 0.005 * share
sug = "卖出%s%%的份额，也即%s份额" % (ratio, share)
self.message.append("根据%s计划，建议%s，%s(%s)" %
(warn[3], sug, warn[0], warn[1]))
self.content = "\n".join(map(str, self.message))
def __init__(self,
*fundtradeobj,
status=None,
fetch=False,
save=False,
path="",
form="csv",
totmoney=100000,
cashobj=None):
super().__init__(*fundtradeobj,
status=status,
fetch=fetch,
save=save,
path=path,
form=form)
if cashobj is None:
cashobj = cashinfo()
self.totmoney = totmoney
nst = mulfix._vcash(totmoney, self.totcftable, cashobj)
cashtrade = trade(cashobj, nst)
# super().__init__(*self.fundtradeobj, cashtrade)
self.fundtradeobj = list(self.fundtradeobj)
self.fundtradeobj.append(cashtrade)
self.fundtradeobj = tuple(self.fundtradeobj)
btnk = bottleneck(self.totcftable)
if btnk > totmoney:
raise TradeBehaviorError("the initial total cash is too low")
self.totcftable = pd.DataFrame(data={
"date": [nst.iloc[0].date],
"cash": [-totmoney]
})
def __init__(self, *fundtradeobj, status=None, fetch=False, save=False, path='', form='csv', totmoney=100000,
cashobj=None):
super().__init__(*fundtradeobj, status=status, fetch=fetch, save=save, path=path, form=form)
if cashobj is None:
cashobj = cashinfo()
self.totmoney = totmoney
nst = mulfix._vcash(totmoney, self.totcftable, cashobj)
cashtrade = trade(cashobj, nst)
# super().__init__(*self.fundtradeobj, cashtrade)
self.fundtradeobj = list(self.fundtradeobj)
self.fundtradeobj.append(cashtrade)
self.fundtradeobj = tuple(self.fundtradeobj)
btnk = bottleneck(self.totcftable)
if btnk > totmoney:
raise Exception('the initial total cash is too low')
self.totcftable = pd.DataFrame(data={'date': [nst.iloc[0].date], 'cash': [-totmoney]})
def __init__(self,
*fundtradeobj,
status=None,
istatus=None,
property=None,
fetch=False,
save=False,
path="",
form="csv"):
if isinstance(status, record):
if not property:
property = getattr(status, "property", {})
status = status.status
elif not property:
property = {}
self.is_in = False
if fundtradeobj:
for t in fundtradeobj:
if isinstance(t, itrade):
self.is_in = True
break
else:
fundtradeobj = []
# warning: not a very good way to automatic generate these fund obj
# because there might be some funds use round_down for share calculation, ie, label=2 must be given
# unless you are sure corresponding funds are added to the droplist
fundcodelist = [f.code for f in fundtradeobj]
if status is not None:
for code in status.columns:
if code == "date":
continue
# r1, d2, v4 p = r+d+v
if code in fundcodelist:
continue
p = property.get(code, 0)
round_label = p % 2
dividend_label = ((p - round_label) / 2) % 2
value_label = ((p - round_label - dividend_label) / 4) % 2
try:
fundtradeobj.append(
trade(
fundinfo(
code,
round_label=round_label,
dividend_label=dividend_label,
fetch=fetch,
save=save,
path=path,
form=form,
),
status,
))
except FundTypeError:
fundtradeobj.append(
trade(
mfundinfo(
code,
round_label=round_label,
value_label=value_label,
fetch=fetch,
save=save,
path=path,
form=form,
),
status,
))
if istatus is not None:
self.is_in = True
if isinstance(istatus, irecord):
istatus = istatus.status
for code in istatus.code.unique():
if code not in fundcodelist and not code.startswith("#"):
fundtradeobj.append(itrade(code, istatus))
self.fundtradeobj = tuple(fundtradeobj)
self.totcftable = self._mergecftb()
