def loadTradesFromDB(self, theDate=None):
'''
User tweak-- if DAS or IB import files are checked when the load button is clicked,
Change the selected radio to useDatabase and return. Update will show if there are
any DB trades to load.
'''
if self.sc.ui.dasImport.isChecked() or self.sc.ui.ibImport.isChecked():
self.sc.ui.useDatabase.setChecked(True)
self.sc.dbDefault(True)
return 1
ibdb = StatementDB()
df = ibdb.getStatement(theDate)
tu = DefineTrades('DB')
self.df, ldf = tu.processDBTrades(df)
ts, self.entries = ibdb.getTradeSummariesSA(theDate)
if not ts:
logging.info(
f"No user data has been saved for {theDate.strftime('%A %B %d')}."
)
return None
self.ts = setTradeSummaryHeaders(ts)
logging.info('load up the trade names now')
tradeSummaries = []
self.sc.ui.tradeList.clear()
for key in self.ts:
self.sc.ui.tradeList.addItem(key)
tradeSummaries.append(self.ts[key])
# Load dailyote
dailyNoteModel = DailyNotesCrud(theDate)
note = dailyNoteModel.getNote()
self.dailyNoteModel = dailyNoteModel
if not note:
note = ""
self.sc.ui.dailyNote.setText(note)
inf = self.sc.ui.infileEdit.text()
windowTitle = f"{self.sc.baseWindowTitle}: {inf}: User Data Loaded"
self.sc.setWindowTitle(windowTitle)
# In prep to do the mistake summary and excel export, return the list it uses now
# It might be good to use the dict self.ts instead
return tradeSummaries
def registerTrades(wb, theDate):
ibdb = StatementDB()
df = ibdb.getStatement(theDate)
x = ibdb.getNumTicketsForDaySA(theDate)
if not x[0] or not x[1]:
msg = f'''found {x[0]} tickets and {x[1]} trades. Nothing to process for the date {theDate.strftime('%A %d, %Y')}in the DB'''
return msg
tu = DefineTrades('DB')
df, ldf = tu.processDBTrades(df)
ts, entries = ibdb.getTradeSummariesSA(theDate)
# self.ts = setTradeSummaryHeaders(ts)
drc = DisReqCol(theDate)
tlog = wb["Trade Log"]
account = tlog['I1'].value
startSearch = False
ix = -2
cols = drc.tfcolumns
# Here is a list of the keys to use cols.keys() of the trade log DataFrame
# ['date', 'time', 'side', 'symb', 'entry1', 'acctbal', 'shares',
# 'stoploss', 'targ', 'avgexit', 'pl', 'notes'])
# Not bothering with the abstraction (drc.name) because this is entirely ours.
srf = SumReqFields()
ids = list()
for row in tlog.iter_rows():
# Unconventional loop stuff
anchor = (1, row[0].row)
keys = list(ts.keys())
if startSearch is True:
idcol = cols['id'][0][0] - 1
if row[idcol].value:
ids.append(row[idcol].value)
if not row[0].value:
startSearch = False
ix = 0
if row[0].value == 'Date':
startSearch = True
if ix >= 0 and ix < len(keys):
while True and ix < len(keys):
key = keys[ix]
tdf = ts[key]
if not gotAnyExits(tdf) or tdf['id'].unique()[0] in ids or (
tdf['Account'].unique()[0] != account):
if tdf['Account'].unique()[0] not in ['SIM', 'Live']:
raise ValueError(
'Programmer exception in search of weird data')
# Continue the inner loop -- keep row from the outer loop loop
ix += 1
continue
# date
cell = tcell(cols['date'][0], anchor=anchor)
tlog[cell] = theDate
# time
cell = tcell(cols['time'][0], anchor=anchor)
tim = tdf[srf.start].unique()[0]
tlog[cell] = tim
# side
name = tdf[srf.name].unique()[0]
if name:
cell = tcell(cols['side'][0], anchor=anchor)
tlog[cell] = name.split()[1]
# symb
cell = tcell(cols['symb'][0], anchor=anchor)
tlog[cell] = name.split()[0]
# entry1
cell = tcell(cols['entry1'][0], anchor=anchor)
tlog[cell] = tdf[srf.entry1].unique()[0]
# Account Balance (setting an excel formula)
cell = tcell(cols['acctbal'][0], anchor=anchor)
formula = "=$M$3+SUM($N$7:$N{})".format(row[0].row - 1)
tlog[cell] = formula
# "shares"
cell = tcell(cols['shares'][0], anchor=anchor)
shares = tdf[srf.shares].unique()[0].split()[0]
if len(shares) > 0:
try:
ishares = int(shares)
except ValueError:
ishares = 0
tlog[cell] = ishares
# stoploss
cell = tcell(cols['stoploss'][0], anchor=anchor)
sl = tdf[srf.stoploss].unique()[0]
if isinstance(sl, bytes):
sl = None
tlog[cell] = sl
# target
cell = tcell(cols['targ'][0], anchor=anchor)
target = tdf[srf.targ].unique()[0]
if isinstance(target, bytes):
target = None
tlog[cell] = target
# avgExit
cell = tcell(cols['avgexit'][0], anchor=anchor)
tlog[cell] = getAvgExit(tdf)
# P/L
cell = tcell(cols['pl'][0], anchor=anchor)
pl = tdf[srf.pl].unique()[0]
# Don't know how these are sneaking through-- Is it only on legacy files?
if isinstance(pl, bytes):
pl = 0.0
tlog[cell] = pl
# Strategy
cell = tcell(cols['strat'][0], anchor=anchor)
strat = tdf[srf.strat].unique()[0]
tlog[cell] = strat
# notes (from the mistake note field)
cell = tcell(cols['notes'][0], anchor=anchor)
note = tdf[srf.mstknote].unique()[0]
tlog[cell] = note
# id (from the database)
cell = tcell(cols['id'][0], anchor=anchor)
id = tdf['id'].unique()[0]
tlog[cell] = id
# break the inner loop
break
ix += 1
if ix >= len(keys):
# done with outer loop
break
return None