158 lines
4.7 KiB
Python
158 lines
4.7 KiB
Python
"""
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Classes to represent the default SQL aggregate functions
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"""
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import copy
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import warnings
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from django.db.models.fields import IntegerField, FloatField
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from django.db.models.lookups import RegisterLookupMixin
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from django.utils.deprecation import RemovedInDjango20Warning
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from django.utils.functional import cached_property
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__all__ = ['Aggregate', 'Avg', 'Count', 'Max', 'Min', 'StdDev', 'Sum', 'Variance']
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warnings.warn(
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"django.db.models.sql.aggregates is deprecated. Use "
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"django.db.models.aggregates instead.",
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RemovedInDjango20Warning, stacklevel=2)
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class Aggregate(RegisterLookupMixin):
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"""
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Default SQL Aggregate.
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"""
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is_ordinal = False
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is_computed = False
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sql_template = '%(function)s(%(field)s)'
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def __init__(self, col, source=None, is_summary=False, **extra):
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"""Instantiate an SQL aggregate
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* col is a column reference describing the subject field
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of the aggregate. It can be an alias, or a tuple describing
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a table and column name.
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* source is the underlying field or aggregate definition for
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the column reference. If the aggregate is not an ordinal or
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computed type, this reference is used to determine the coerced
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output type of the aggregate.
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* extra is a dictionary of additional data to provide for the
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aggregate definition
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Also utilizes the class variables:
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* sql_function, the name of the SQL function that implements the
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aggregate.
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* sql_template, a template string that is used to render the
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aggregate into SQL.
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* is_ordinal, a boolean indicating if the output of this aggregate
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is an integer (e.g., a count)
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* is_computed, a boolean indicating if this output of this aggregate
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is a computed float (e.g., an average), regardless of the input
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type.
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"""
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self.col = col
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self.source = source
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self.is_summary = is_summary
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self.extra = extra
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# Follow the chain of aggregate sources back until you find an
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# actual field, or an aggregate that forces a particular output
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# type. This type of this field will be used to coerce values
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# retrieved from the database.
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tmp = self
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while tmp and isinstance(tmp, Aggregate):
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if getattr(tmp, 'is_ordinal', False):
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tmp = self._ordinal_aggregate_field
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elif getattr(tmp, 'is_computed', False):
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tmp = self._computed_aggregate_field
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else:
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tmp = tmp.source
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self.field = tmp
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# Two fake fields used to identify aggregate types in data-conversion operations.
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@cached_property
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def _ordinal_aggregate_field(self):
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return IntegerField()
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@cached_property
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def _computed_aggregate_field(self):
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return FloatField()
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def relabeled_clone(self, change_map):
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clone = copy.copy(self)
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if isinstance(self.col, (list, tuple)):
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clone.col = (change_map.get(self.col[0], self.col[0]), self.col[1])
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return clone
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def as_sql(self, qn, connection):
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"Return the aggregate, rendered as SQL with parameters."
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params = []
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if hasattr(self.col, 'as_sql'):
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field_name, params = self.col.as_sql(qn, connection)
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elif isinstance(self.col, (list, tuple)):
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field_name = '.'.join(qn(c) for c in self.col)
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else:
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field_name = qn(self.col)
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substitutions = {
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'function': self.sql_function,
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'field': field_name
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}
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substitutions.update(self.extra)
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return self.sql_template % substitutions, params
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def get_group_by_cols(self):
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return []
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@property
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def output_field(self):
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return self.field
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class Avg(Aggregate):
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is_computed = True
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sql_function = 'AVG'
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class Count(Aggregate):
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is_ordinal = True
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sql_function = 'COUNT'
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sql_template = '%(function)s(%(distinct)s%(field)s)'
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def __init__(self, col, distinct=False, **extra):
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super(Count, self).__init__(col, distinct='DISTINCT ' if distinct else '', **extra)
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class Max(Aggregate):
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sql_function = 'MAX'
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class Min(Aggregate):
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sql_function = 'MIN'
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class StdDev(Aggregate):
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is_computed = True
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def __init__(self, col, sample=False, **extra):
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super(StdDev, self).__init__(col, **extra)
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self.sql_function = 'STDDEV_SAMP' if sample else 'STDDEV_POP'
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class Sum(Aggregate):
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sql_function = 'SUM'
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class Variance(Aggregate):
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is_computed = True
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def __init__(self, col, sample=False, **extra):
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super(Variance, self).__init__(col, **extra)
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self.sql_function = 'VAR_SAMP' if sample else 'VAR_POP'
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