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else:
tmp = FailSafe(symname=symbol,
ind=ind,
val=val,
dt_log=dt_log,
user=user,
comment=comment,
fsnum=next_num)
self.ses.add(tmp)
self.ses.commit()"
1854,"def add_override(self, symbol, ind, val, dt_log=None, user=None, comment=None):
""""""
Appends a single indexed-value pair, to a symbol object, to be
used during the final steps of the aggregation of the datatable.
With default settings Overrides, get applied with highest priority.
Parameters
----------
symbol : Symbol or str
The Symbol to override
ind : obj
The index value where the override should be applied
val : obj
The data value which will be used in the override
dt_log : datetime
A log entry, for saving when this override was created.
user : str
A string representing which user made the override
comment : str
A string to store any notes related to this override.
""""""
self._add_orfs('override', symbol, ind, val, dt_log, user, comment)"
1855,"def get_converted(self, symbol, units='CAD', system=None, tag=None):
""""""
Uses a Symbol's Dataframe, to build a new Dataframe,
with the data converted to the new units
Parameters
----------
symbol : str or tuple of the form (Dataframe, str)
String representing a symbol's name, or a dataframe
with the data required to be converted. If supplying a
dataframe, units must be passed.
units : str, optional
Specify the units to convert the symbol to, default to CAD
system : str, optional
If None, the default system specified at instantiation
is used. System defines which conversion approach to take.
tag : str, optional
Tags define which set of conversion data is used. If None, the
default tag specified at instantiation is used.
""""""
if isinstance(symbol, (str, unicode)):
sym = self.get(symbol)
df = sym.df
curu = sym.units
requ = units
elif isinstance(symbol, tuple):
df = symbol[0]
curu = symbol[1]
requ = units
else:
raise TypeError(""Expected str or (DataFrame, str), found {}"".format(type(symbol)))
system = system or self.default_system
tag = tag or self.default_tag
conv = self.converters[system][tag]
newdf = conv.convert(df, curu, requ)
newdf = pd.merge(df, newdf, left_index=True, right_index=True)
newdf = newdf[df.columns[0] + ""_y""].to_frame()
newdf.columns = df.columns
return newdf"
1856,"def last_cache(self,result='COMPLETE'):
""""""
The date and time of the previous cache.
Parameters
----------
result : string, default 'COMPLETE'
A string to choose which point in the log,
should be returned.
- COMPLETE - the last time a cache was completed
- STARTED - the last time a cache was started
Returns
-------
datetime.datetime
""""""
crit = and_(SymbolLogEvent.event == 'CACHE',
SymbolLogEvent.evresult == result)
qry = self.log.filter(crit)
qry = qry.order_by(SymbolLogEvent.evtime.desc())
t = qry.first()
if t: