""" Classes to represent the default SQL aggregate functions """ import copy from django.db.models.fields import IntegerField, FloatField # Fake fields used to identify aggregate types in data-conversion operations. ordinal_aggregate_field = IntegerField() computed_aggregate_field = FloatField() class Aggregate(object): """ Default SQL Aggregate. """ is_ordinal = False is_computed = False sql_template = '%(function)s(%(field)s)' def __init__(self, col, source=None, is_summary=False, **extra): """Instantiate an SQL aggregate * col is a column reference describing the subject field of the aggregate. It can be an alias, or a tuple describing a table and column name. * source is the underlying field or aggregate definition for the column reference. If the aggregate is not an ordinal or computed type, this reference is used to determine the coerced output type of the aggregate. * extra is a dictionary of additional data to provide for the aggregate definition Also utilizes the class variables: * sql_function, the name of the SQL function that implements the aggregate. * sql_template, a template string that is used to render the aggregate into SQL. * is_ordinal, a boolean indicating if the output of this aggregate is an integer (e.g., a count) * is_computed, a boolean indicating if this output of this aggregate is a computed float (e.g., an average), regardless of the input type. """ self.col = col self.source = source self.is_summary = is_summary self.extra = extra # Follow the chain of aggregate sources back until you find an # actual field, or an aggregate that forces a particular output # type. This type of this field will be used to coerce values # retrieved from the database. tmp = self while tmp and isinstance(tmp, Aggregate): if getattr(tmp, 'is_ordinal', False): tmp = ordinal_aggregate_field elif getattr(tmp, 'is_computed', False): tmp = computed_aggregate_field else: tmp = tmp.source self.field = tmp def relabeled_clone(self, change_map): clone = copy.copy(self) if isinstance(self.col, (list, tuple)): clone.col = (change_map.get(self.col[0], self.col[0]), self.col[1]) return clone def as_sql(self, qn, connection): "Return the aggregate, rendered as SQL with parameters." params = [] if hasattr(self.col, 'as_sql'): field_name, params = self.col.as_sql(qn, connection) elif isinstance(self.col, (list, tuple)): field_name = '.'.join([qn(c) for c in self.col]) else: field_name = self.col substitutions = { 'function': self.sql_function, 'field': field_name } substitutions.update(self.extra) return self.sql_template % substitutions, params class Avg(Aggregate): is_computed = True sql_function = 'AVG' class Count(Aggregate): is_ordinal = True sql_function = 'COUNT' sql_template = '%(function)s(%(distinct)s%(field)s)' def __init__(self, col, distinct=False, **extra): super(Count, self).__init__(col, distinct=distinct and 'DISTINCT ' or '', **extra) class Max(Aggregate): sql_function = 'MAX' class Min(Aggregate): sql_function = 'MIN' class StdDev(Aggregate): is_computed = True def __init__(self, col, sample=False, **extra): super(StdDev, self).__init__(col, **extra) self.sql_function = sample and 'STDDEV_SAMP' or 'STDDEV_POP' class Sum(Aggregate): sql_function = 'SUM' class Variance(Aggregate): is_computed = True def __init__(self, col, sample=False, **extra): super(Variance, self).__init__(col, **extra) self.sql_function = sample and 'VAR_SAMP' or 'VAR_POP'