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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def recursively_compute_variable(self, var, start_date=None, end_date=None, time_offset=None, model=None, **DataAttrs):
 """Compute a variable recursively, loading data where needed. An obvious requirement here is that the variable must eventually be able to be expressed in terms of model-native quantities; otherwise the recursion will never stop. Parameters var : Var aospy Var object start_date : datetime.datetime start date for interval end_date : datetime.datetime end date for interval time_offset : dict Option to add a time offset to the time coordinate to correct for incorrect metadata. model : Model aospy Model object (optional) **DataAttrs Attributes needed to identify a unique set of files to load from Returns ------- da : DataArray DataArray for the specified variable, date range, and interval in """

        if var.variables is None:
            return self._load_or_get_from_model(
                var, start_date, end_date, time_offset, model, **DataAttrs)
        else:
            data = [self.recursively_compute_variable(
                v, start_date, end_date, time_offset, model, **DataAttrs)
                    for v in var.variables]
            return var.func(*data).rename(var.name)