def addStartTimeDB(self, dframe):
'''
Add the start time to the new column labeled Start or frc.start. Each transaction whthin a
trade will share a start time.
:params dframe: The output df to place the data
:return dframe: The same dframe but with the new start data.
'''
rc = self._frc
newTrade = True
oldsymb = ''
oldaccnt = ''
for i, row in dframe.iterrows():
if row[rc.ticker] != oldsymb or row[rc.acct] != oldaccnt or row[
rc.shares] == row[rc.bal]:
newTrade = True
oldsymb = row[rc.ticker]
oldaccnt = row[rc.acct]
if newTrade:
newTrade = True if isNumeric(
row[rc.bal]) and row[rc.bal] == 0 else False
oldTime = dframe.at[i, rc.time]
dframe.at[i, rc.start] = oldTime
else:
dframe.at[i, rc.start] = oldTime
if row[rc.bal] == 0:
newTrade = True
return dframe
def getShares(self):
'''
Utility to get the number of shares in this Trade. Each TradeObject object represents a
single trade, or the part of a trade that happens on one day, with at least 1
transaction/ticket.
'''
if len(self.df.iloc[0][frc.oc]) == 0:
# If we are here, structjour has failed to determine long/short or balance
# With no balance set, we can still set some kind of shares for market val for the day.
# This value provides context info for the user. Set the best we can.
# If shares are unbalanced, this figure will be ok
self.shares = self.df[frc.shares].sum()
# If shares are balanced (This should never run but ...) find max purchase/sell
if self.shares == 0:
maxbuy = self.df[frc.shares].max()
maxsell = self.df[frc.shares].min()
self.shares = maxbuy if max(maxbuy, abs(maxsell)) else maxsell
return self.shares
if self.settings.value('inputType') == 'DB':
return self.getSharesDB()
elif self.shares == 0 or not isNumeric(self.shares):
if self.side.startswith("B") or self.side.startswith("HOLD+"):
self.shares = self.df[frc.bal].max()
else:
self.shares = self.df[frc.bal].min()
return self.shares
def __setMarketValue(self):
'''
Set the market value based on shares * price. For incomplete trades, the info may be
incomplete and a NaN value produced. A value is required. Set to 0
'''
mkt = self.getShares() * self.df.loc[self.ix0][frc.price]
mkt = mkt if isNumeric(mkt) else 0
self.TheTrade.MktVal = mkt
return self.TheTrade
def updateTSID(cls, tid, tsid):
ModelBase.connect(new_session=True)
session = ModelBase.session
q = session.query(Trade).filter_by(id=tid).one_or_none()
if q:
if not isNumeric(q.trade_sum_id) or tsid != q.trade_sum_id:
q.trade_sum_id = tsid
session.add(q)
session.commit()
session.close()
def fixTsid(self, tdf):
if len(tdf['tsid'].unique()) > 1:
therightone = list()
for id in tdf['tsid'].unique():
if isNumeric(id):
therightone.append(id)
if len(therightone) > 1:
# This could be a place for user input...There are confused ids here
# The question is what trade do these transactions belong to.
raise ValueError(
'Programmers exception: Something needs to be done here')
elif len(therightone) == 1:
ibdb = StatementDB()
for i, row in tdf.iterrows():
tdf.at[i, 'tsid'] = therightone[0]
ibdb.updateTSID(row['id'], therightone[0])
# If one of the vals was nan, the column became float
tdf = tdf.astype({'tsid': int})
# Update the db
return tdf
def test_TheTradeObjectSetEntries(self):
rc = FinReqCol()
for tto in self.ttos:
tto._TheTradeObject__setEntries()
# if len(tto.df) < 4:
# self.fail('This test requires a longer sample of transactions to run.')
count = 0
x0 = tto.df.index[0]
long = False
r = tto.df.loc[x0]
if len(r[rc.oc]) < 1 and (r[rc.side].startswith('B') or
r[rc.side].lower().startswith('hold+')):
long = True
elif r[rc.oc] == 'O' and r[rc.shares] > 0 or r[
rc.oc] == 'C' and r[rc.shares] < 0:
long = True
# side = r[rc.side]
for i, row in tto.df.iterrows():
count += 1
if (long and row[rc.shares] > 0) or (not long
and row[rc.shares] < 0):
if row[rc.price] != 0:
entry = 'Entry' + str(count)
ttoprice = tto.TheTrade[entry].unique()[0]
self.assertEqual(ttoprice, row.Price,
"Failed to set entry correctly")
else:
if row[rc.price] != 0:
entry = 'Exit' + str(count)
ttoprice = tto.TheTrade[entry].unique()[0]
self.assertEqual(ttoprice, row[rc.price],
"Failed to set exit correctly")
if row[rc.PL] != 0:
PLname = 'PL' + str(count)
ttopl = tto.TheTrade[PLname].unique()[0]
self.assertEqual(
ttopl, row[rc.PL] if isNumeric(row[rc.PL]) else 0,
"Failed to set pl correctly")
def postProcessingDB(self, ldf):
'''
A few items that need fixing up. Locate and name flipped positions and overnight holds and
change the name appropriately. Look for trades that lack a tsid (foreign key) and fix
:params ldf: A ist of DataFrames, each DataFrame represents a trade defined by the initial
purchase or short of a stock, and all transactions until the transaction which
returns the share balance to 0.
:return (ldf, nt): The updated versions of the list of DataFrames, and the updated single
DataFrame.
'''
rc = self._frc
dframe = pd.DataFrame()
for tdf in ldf:
x0 = tdf.index[0]
xl = tdf.index[-1]
if tdf.at[x0, rc.bal] != tdf.at[x0,
rc.shares] or tdf.at[xl,
rc.bal] != 0:
tdf.at[xl, rc.name] = tdf.at[xl, rc.name] + " OVERNIGHT"
if tdf.at[x0, rc.bal] != 0:
firstrow = True
for i, row in tdf.iterrows():
# Cant fix anythintg if the balance is not set
if row[rc.bal] is None:
break
if firstrow:
side = True if row[rc.bal] > 0 else False
firstrow = False
elif row[rc.bal] != 0 and (row[rc.bal] >= 0) != side:
tdf.at[xl, rc.name] = tdf.at[xl, rc.name] + " FLIPPED"
break
else:
assert len(tdf) == 1
if len(tdf['tsid'].unique()) > 1 or not isNumeric(
tdf['tsid'].unique()[0]):
tdf = self.fixTsid(tdf)
dframe = dframe.append(tdf)
return ldf, dframe
def updateBal(cls, t, balance):
'''Uses an ongoing session. Update balance only if there is no current balance'''
if not isNumeric(t.balance):
t.balance = balance
ModelBase.session.add(t)
return t
