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Create SQL statements for QuerySets.
The code in here encapsulates all of the SQL construction so that QuerySets
themselves do not have to (and could be backed by things other than SQL
databases). The abstraction barrier only works one way: this module has to know
all about the internals of models in order to get the information it needs.
import functools
from collections import Counter, OrderedDict, namedtuple
from import Iterator, Mapping
from itertools import chain, count, product
from string import ascii_uppercase
from django.core.exceptions import (
EmptyResultSet, FieldDoesNotExist, FieldError,
from django.db import DEFAULT_DB_ALIAS, NotSupportedError, connections
from django.db.models.aggregates import Count
from django.db.models.constants import LOOKUP_SEP
from django.db.models.expressions import Col, Ref
from django.db.models.fields import Field
from django.db.models.fields.related_lookups import MultiColSource
from django.db.models.lookups import Lookup
from django.db.models.query_utils import (
Q, check_rel_lookup_compatibility, refs_expression,
from django.db.models.sql.constants import (
from django.db.models.sql.datastructures import (
BaseTable, Empty, Join, MultiJoin,
from django.db.models.sql.where import (
AND, OR, ExtraWhere, NothingNode, WhereNode,
from django.utils.encoding import force_text
from django.utils.functional import cached_property
from django.utils.tree import Node
__all__ = ['Query', 'RawQuery']
def get_field_names_from_opts(opts):
return set(chain.from_iterable(
(, f.attname) if f.concrete else (,)
for f in opts.get_fields()
def get_children_from_q(q):
for child in q.children:
if isinstance(child, Node):
yield from get_children_from_q(child)
yield child
JoinInfo = namedtuple(
('final_field', 'targets', 'opts', 'joins', 'path', 'transform_function')
class RawQuery:
"""A single raw SQL query."""
def __init__(self, sql, using, params=None):
self.params = params or ()
self.sql = sql
self.using = using
self.cursor = None
# Mirror some properties of a normal query so that
# the compiler can be used to process results.
self.low_mark, self.high_mark = 0, None # Used for offset/limit
self.extra_select = {}
self.annotation_select = {}
def chain(self, using):
return self.clone(using)
def clone(self, using):
return RawQuery(self.sql, using, params=self.params)
def get_columns(self):
if self.cursor is None:
converter = connections[self.using].introspection.column_name_converter
return [converter(column_meta[0])
for column_meta in self.cursor.description]
def __iter__(self):
# Always execute a new query for a new iterator.
# This could be optimized with a cache at the expense of RAM.
if not connections[self.using].features.can_use_chunked_reads:
# If the database can't use chunked reads we need to make sure we
# evaluate the entire query up front.
result = list(self.cursor)
result = self.cursor
return iter(result)
def __repr__(self):
return "<%s: %s>" % (self.__class__.__name__, self)
def params_type(self):
return dict if isinstance(self.params, Mapping) else tuple
def __str__(self):
return self.sql % self.params_type(self.params)
def _execute_query(self):
connection = connections[self.using]
# Adapt parameters to the database, as much as possible considering
# that the target type isn't known. See #17755.
params_type = self.params_type
adapter = connection.ops.adapt_unknown_value
if params_type is tuple:
params = tuple(adapter(val) for val in self.params)
elif params_type is dict:
params = {key: adapter(val) for key, val in self.params.items()}
raise RuntimeError("Unexpected params type: %s" % params_type)
self.cursor = connection.cursor()
self.cursor.execute(self.sql, params)
class Query:
"""A single SQL query."""
alias_prefix = 'T'
subq_aliases = frozenset([alias_prefix])
compiler = 'SQLCompiler'
def __init__(self, model, where=WhereNode):
self.model = model
self.alias_refcount = {}
# alias_map is the most important data structure regarding joins.
# It's used for recording which joins exist in the query and what
# types they are. The key is the alias of the joined table (possibly
# the table name) and the value is a Join-like object (see
# sql.datastructures.Join for more information).
self.alias_map = OrderedDict()
# Sometimes the query contains references to aliases in outer queries (as
# a result of split_exclude). Correct alias quoting needs to know these
# aliases too.
self.external_aliases = set()
self.table_map = {} # Maps table names to list of aliases.
self.default_cols = True
self.default_ordering = True
self.standard_ordering = True
self.used_aliases = set()
self.filter_is_sticky = False
self.subquery = False
# SQL-related attributes
# Select and related select clauses are expressions to use in the
# SELECT clause of the query.
# The select is used for cases where we want to set up the select
# clause to contain other than default fields (values(), subqueries...)
# Note that annotations go to annotations dictionary. = ()
self.where = where()
self.where_class = where
# The group_by attribute can have one of the following forms:
# - None: no group by at all in the query
# - A tuple of expressions: group by (at least) those expressions.
# String refs are also allowed for now.
# - True: group by all select fields of the model
# See compiler.get_group_by() for details.
self.group_by = None
self.order_by = ()
self.low_mark, self.high_mark = 0, None # Used for offset/limit
self.distinct = False
self.distinct_fields = ()
self.select_for_update = False
self.select_for_update_nowait = False
self.select_for_update_skip_locked = False
self.select_for_update_of = ()
self.select_related = False
# Arbitrary limit for select_related to prevents infinite recursion.
self.max_depth = 5
# Holds the selects defined by a call to values() or values_list()
# excluding annotation_select and extra_select.
self.values_select = ()
# SQL annotation-related attributes
# The _annotations will be an OrderedDict when used. Due to the cost
# of creating OrderedDict this attribute is created lazily (in
# self.annotations property).
self._annotations = None # Maps alias -> Annotation Expression
self.annotation_select_mask = None
self._annotation_select_cache = None
# Set combination attributes
self.combinator = None
self.combinator_all = False
self.combined_queries = ()
# These are for extensions. The contents are more or less appended
# verbatim to the appropriate clause.
# The _extra attribute is an OrderedDict, lazily created similarly to
# .annotations
self._extra = None # Maps col_alias -> (col_sql, params).
self.extra_select_mask = None
self._extra_select_cache = None
self.extra_tables = ()
self.extra_order_by = ()
# A tuple that is a set of model field names and either True, if these
# are the fields to defer, or False if these are the only fields to
# load.
self.deferred_loading = (frozenset(), True)
self._filtered_relations = {}
def extra(self):
if self._extra is None:
self._extra = OrderedDict()
return self._extra
def annotations(self):
if self._annotations is None:
self._annotations = OrderedDict()
return self._annotations
def has_select_fields(self):
return bool( or self.annotation_select_mask or self.extra_select_mask)
def base_table(self):
for alias in self.alias_map:
return alias
def __str__(self):
Return the query as a string of SQL with the parameter values
substituted in (use sql_with_params() to see the unsubstituted string).
Parameter values won't necessarily be quoted correctly, since that is
done by the database interface at execution time.
sql, params = self.sql_with_params()
return sql % params
def sql_with_params(self):
Return the query as an SQL string and the parameters that will be
substituted into the query.
return self.get_compiler(DEFAULT_DB_ALIAS).as_sql()
def __deepcopy__(self, memo):
"""Limit the amount of work when a Query is deepcopied."""
result = self.clone()
memo[id(self)] = result
return result
def _prepare(self, field):
return self
def get_compiler(self, using=None, connection=None):
if using is None and connection is None:
raise ValueError("Need either using or connection")
if using:
connection = connections[using]
return connection.ops.compiler(self.compiler)(self, connection, using)
def get_meta(self):
Return the Options instance (the model._meta) from which to start
processing. Normally, this is self.model._meta, but it can be changed
by subclasses.
return self.model._meta
def clone(self):
Return a copy of the current Query. A lightweight alternative to
to deepcopy().
obj = Empty()
obj.__class__ = self.__class__
# Copy references to everything.
obj.__dict__ = self.__dict__.copy()
# Clone attributes that can't use shallow copy.
obj.alias_refcount = self.alias_refcount.copy()
obj.alias_map = self.alias_map.copy()
obj.external_aliases = self.external_aliases.copy()
obj.table_map = self.table_map.copy()
obj.where = self.where.clone()
obj._annotations = self._annotations.copy() if self._annotations is not None else None
if self.annotation_select_mask is None:
obj.annotation_select_mask = None
obj.annotation_select_mask = self.annotation_select_mask.copy()
# _annotation_select_cache cannot be copied, as doing so breaks the
# (necessary) state in which both annotations and
# _annotation_select_cache point to the same underlying objects.
# It will get re-populated in the cloned queryset the next time it's
# used.
obj._annotation_select_cache = None
obj._extra = self._extra.copy() if self._extra is not None else None
if self.extra_select_mask is None:
obj.extra_select_mask = None
obj.extra_select_mask = self.extra_select_mask.copy()
if self._extra_select_cache is None:
obj._extra_select_cache = None
obj._extra_select_cache = self._extra_select_cache.copy()
if 'subq_aliases' in self.__dict__:
obj.subq_aliases = self.subq_aliases.copy()
obj.used_aliases = self.used_aliases.copy()
obj._filtered_relations = self._filtered_relations.copy()
# Clear the cached_property
del obj.base_table
except AttributeError:
return obj
def chain(self, klass=None):
Return a copy of the current Query that's ready for another operation.
The klass argument changes the type of the Query, e.g. UpdateQuery.
obj = self.clone()
if klass and obj.__class__ != klass:
obj.__class__ = klass
if not obj.filter_is_sticky:
obj.used_aliases = set()
obj.filter_is_sticky = False
if hasattr(obj, '_setup_query'):
return obj
def relabeled_clone(self, change_map):
clone = self.clone()
return clone
def rewrite_cols(self, annotation, col_cnt):
# We must make sure the inner query has the referred columns in it.
# If we are aggregating over an annotation, then Django uses Ref()
# instances to note this. However, if we are annotating over a column
# of a related model, then it might be that column isn't part of the
# SELECT clause of the inner query, and we must manually make sure
# the column is selected. An example case is:
# .aggregate(Sum('author__awards'))
# Resolving this expression results in a join to author, but there
# is no guarantee the awards column of author is in the select clause
# of the query. Thus we must manually add the column to the inner
# query.
orig_exprs = annotation.get_source_expressions()
new_exprs = []
for expr in orig_exprs:
# FIXME: These conditions are fairly arbitrary. Identify a better
# method of having expressions decide which code path they should
# take.
if isinstance(expr, Ref):
# Its already a Ref to subquery (see resolve_ref() for
# details)
elif isinstance(expr, (WhereNode, Lookup)):
# Decompose the subexpressions further. The code here is
# copied from the else clause, but this condition must appear
# before the contains_aggregate/is_summary condition below.
new_expr, col_cnt = self.rewrite_cols(expr, col_cnt)
elif isinstance(expr, Col) or (expr.contains_aggregate and not expr.is_summary):
# Reference to column. Make sure the referenced column
# is selected.
col_cnt += 1
col_alias = '__col%d' % col_cnt
self.annotations[col_alias] = expr
new_exprs.append(Ref(col_alias, expr))
# Some other expression not referencing database values
# directly. Its subexpression might contain Cols.
new_expr, col_cnt = self.rewrite_cols(expr, col_cnt)
return annotation, col_cnt
def get_aggregation(self, using, added_aggregate_names):
Return the dictionary with the values of the existing aggregations.
if not self.annotation_select:
return {}
has_limit = self.low_mark != 0 or self.high_mark is not None
has_existing_annotations = any(
annotation for alias, annotation
in self.annotations.items()
if alias not in added_aggregate_names
# Decide if we need to use a subquery.
# Existing annotations would cause incorrect results as get_aggregation()
# must produce just one result and thus must not use GROUP BY. But we
# aren't smart enough to remove the existing annotations from the
# query, so those would force us to use GROUP BY.
# If the query has limit or distinct, or uses set operations, then
# those operations must be done in a subquery so that the query
# aggregates on the limit and/or distinct results instead of applying
# the distinct and limit after the aggregation.
if (isinstance(self.group_by, tuple) or has_limit or has_existing_annotations or
self.distinct or self.combinator):
from django.db.models.sql.subqueries import AggregateQuery
outer_query = AggregateQuery(self.model)
inner_query = self.clone()
inner_query.select_for_update = False
inner_query.select_related = False
if not has_limit and not self.distinct_fields:
# Queries with distinct_fields need ordering and when a limit
# is applied we must take the slice from the ordered query.
# Otherwise no need for ordering.
if not inner_query.distinct:
# If the inner query uses default select and it has some
# aggregate annotations, then we must make sure the inner
# query is grouped by the main model's primary key. However,
# clearing the select clause can alter results if distinct is
# used.
if inner_query.default_cols and has_existing_annotations:
inner_query.group_by = (,)
inner_query.default_cols = False
relabels = {t: 'subquery' for t in inner_query.alias_map}
relabels[None] = 'subquery'
# Remove any aggregates marked for reduction from the subquery
# and move them to the outer AggregateQuery.
col_cnt = 0
for alias, expression in list(inner_query.annotation_select.items()):
if expression.is_summary:
expression, col_cnt = inner_query.rewrite_cols(expression, col_cnt)
outer_query.annotations[alias] = expression.relabeled_clone(relabels)
del inner_query.annotations[alias]
# Make sure the annotation_select wont use cached results.
if == () and not inner_query.default_cols and not inner_query.annotation_select_mask:
# In case of Model.objects[0:3].count(), there would be no
# field selected in the inner query, yet we must use a subquery.
# So, make sure at least one field is selected. = (,)
outer_query.add_subquery(inner_query, using)
except EmptyResultSet:
return {
alias: None
for alias in outer_query.annotation_select
outer_query = self = ()
self.default_cols = False
self._extra = {}
outer_query.select_for_update = False
outer_query.select_related = False
compiler = outer_query.get_compiler(using)
result = compiler.execute_sql(SINGLE)
if result is None:
result = [None] * len(outer_query.annotation_select)
converters = compiler.get_converters(outer_query.annotation_select.values())
result = next(compiler.apply_converters((result,), converters))
return dict(zip(outer_query.annotation_select, result))
def get_count(self, using):
Perform a COUNT() query using the current filter constraints.
obj = self.clone()
obj.add_annotation(Count('*'), alias='__count', is_summary=True)
number = obj.get_aggregation(using, ['__count'])['__count']
if number is None:
number = 0
return number
def has_filters(self):
return self.where
def has_results(self, using):
q = self.clone()
if not q.distinct:
if q.group_by is True:
q.add_fields((f.attname for f in self.model._meta.concrete_fields), False)
compiler = q.get_compiler(using=using)
return compiler.has_results()
def combine(self, rhs, connector):
Merge the 'rhs' query into the current one (with any 'rhs' effects
being applied *after* (that is, "to the right of") anything in the
current query. 'rhs' is not modified during a call to this function.
The 'connector' parameter describes how to connect filters from the
'rhs' query.
assert self.model == rhs.model, \
"Cannot combine queries on two different base models."
assert self.can_filter(), \
"Cannot combine queries once a slice has been taken."
assert self.distinct == rhs.distinct, \
"Cannot combine a unique query with a non-unique query."
assert self.distinct_fields == rhs.distinct_fields, \
"Cannot combine queries with different distinct fields."
# Work out how to relabel the rhs aliases, if necessary.
change_map = {}
conjunction = (connector == AND)
# Determine which existing joins can be reused. When combining the
# query with AND we must recreate all joins for m2m filters. When
# combining with OR we can reuse joins. The reason is that in AND
# case a single row can't fulfill a condition like:
# revrel__col=1 & revrel__col=2
# But, there might be two different related rows matching this
# condition. In OR case a single True is enough, so single row is
# enough, too.
# Note that we will be creating duplicate joins for non-m2m joins in
# the AND case. The results will be correct but this creates too many
# joins. This is something that could be fixed later on.
reuse = set() if conjunction else set(self.alias_map)
# Base table must be present in the query - this is the same
# table on both sides.
joinpromoter = JoinPromoter(connector, 2, False)
j for j in self.alias_map if self.alias_map[j].join_type == INNER)
rhs_votes = set()
# Now, add the joins from rhs query into the new query (skipping base
# table).
rhs_tables = list(rhs.alias_map)[1:]
for alias in rhs_tables:
join = rhs.alias_map[alias]
# If the left side of the join was already relabeled, use the
# updated alias.
join = join.relabeled_clone(change_map)
new_alias = self.join(join, reuse=reuse)
if join.join_type == INNER:
# We can't reuse the same join again in the query. If we have two
# distinct joins for the same connection in rhs query, then the
# combined query must have two joins, too.
if alias != new_alias:
change_map[alias] = new_alias
if not rhs.alias_refcount[alias]:
# The alias was unused in the rhs query. Unref it so that it
# will be unused in the new query, too. We have to add and
# unref the alias so that join promotion has information of
# the join type for the unused alias.
# Now relabel a copy of the rhs where-clause and add it to the current
# one.
w = rhs.where.clone()
self.where.add(w, connector)
# Selection columns and extra extensions are those provided by 'rhs'.
self.set_select([col.relabeled_clone(change_map) for col in])
else: = ()
if connector == OR:
# It would be nice to be able to handle this, but the queries don't
# really make sense (or return consistent value sets). Not worth
# the extra complexity when you can write a real query instead.
if self._extra and rhs._extra:
raise ValueError("When merging querysets using 'or', you cannot have extra(select=...) on both sides.")
extra_select_mask = set()
if self.extra_select_mask is not None:
if rhs.extra_select_mask is not None:
if extra_select_mask:
self.extra_tables += rhs.extra_tables
# Ordering uses the 'rhs' ordering, unless it has none, in which case
# the current ordering is used.
self.order_by = rhs.order_by or self.order_by
self.extra_order_by = rhs.extra_order_by or self.extra_order_by
def deferred_to_data(self, target, callback):
Convert the self.deferred_loading data structure to an alternate data
structure, describing the field that *will* be loaded. This is used to
compute the columns to select from the database and also by the
QuerySet class to work out which fields are being initialized on each
model. Models that have all their fields included aren't mentioned in
the result, only those that have field restrictions in place.
The "target" parameter is the instance that is populated (in place).
The "callback" is a function that is called whenever a (model, field)
pair need to be added to "target". It accepts three parameters:
"target", and the model and list of fields being added for that model.
field_names, defer = self.deferred_loading
if not field_names:
orig_opts = self.get_meta()
seen = {}
must_include = {orig_opts.concrete_model: {}}
for field_name in field_names:
parts = field_name.split(LOOKUP_SEP)
cur_model = self.model._meta.concrete_model
opts = orig_opts
for name in parts[:-1]:
old_model = cur_model
if name in self._filtered_relations:
name = self._filtered_relations[name].relation_name
source = opts.get_field(name)
if is_reverse_o2o(source):
cur_model = source.related_model
cur_model = source.remote_field.model
opts = cur_model._meta
# Even if we're "just passing through" this model, we must add
# both the current model's pk and the related reference field
# (if it's not a reverse relation) to the things we select.
if not is_reverse_o2o(source):
add_to_dict(must_include, cur_model,
field = opts.get_field(parts[-1])
is_reverse_object = field.auto_created and not field.concrete
model = field.related_model if is_reverse_object else field.model
model = model._meta.concrete_model
if model == opts.model:
model = cur_model
if not is_reverse_o2o(field):
add_to_dict(seen, model, field)
if defer:
# We need to load all fields for each model, except those that
# appear in "seen" (for all models that appear in "seen"). The only
# slight complexity here is handling fields that exist on parent
# models.
workset = {}
for model, values in seen.items():
for field in model._meta.local_fields:
if field not in values:
m = field.model._meta.concrete_model
add_to_dict(workset, m, field)
for model, values in must_include.items():
# If we haven't included a model in workset, we don't add the
# corresponding must_include fields for that model, since an
# empty set means "include all fields". That's why there's no
# "else" branch here.
if model in workset:
for model, values in workset.items():
callback(target, model, values)
for model, values in must_include.items():
if model in seen:
# As we've passed through this model, but not explicitly
# included any fields, we have to make sure it's mentioned
# so that only the "must include" fields are pulled in.
seen[model] = values
# Now ensure that every model in the inheritance chain is mentioned
# in the parent list. Again, it must be mentioned to ensure that
# only "must include" fields are pulled in.
for model in orig_opts.get_parent_list():
seen.setdefault(model, set())
for model, values in seen.items():
callback(target, model, values)
def table_alias(self, table_name, create=False, filtered_relation=None):
Return a table alias for the given table_name and whether this is a
new alias or not.
If 'create' is true, a new alias is always created. Otherwise, the
most recently created alias for the table (if one exists) is reused.
alias_list = self.table_map.get(table_name)
if not create and alias_list:
alias = alias_list[0]
self.alias_refcount[alias] += 1
return alias, False
# Create a new alias for this table.
if alias_list:
alias = '%s%d' % (self.alias_prefix, len(self.alias_map) + 1)
# The first occurrence of a table uses the table name directly.
alias = filtered_relation.alias if filtered_relation is not None else table_name
self.table_map[table_name] = [alias]
self.alias_refcount[alias] = 1
return alias, True
def ref_alias(self, alias):
"""Increases the reference count for this alias."""
self.alias_refcount[alias] += 1
def unref_alias(self, alias, amount=1):
"""Decreases the reference count for this alias."""
self.alias_refcount[alias] -= amount
def promote_joins(self, aliases):
Promote recursively the join type of given aliases and its children to
an outer join. If 'unconditional' is False, only promote the join if
it is nullable or the parent join is an outer join.
The children promotion is done to avoid join chains that contain a LOUTER
b INNER c. So, if we have currently a INNER b INNER c and a->b is promoted,
then we must also promote b->c automatically, or otherwise the promotion
of a->b doesn't actually change anything in the query results.
aliases = list(aliases)
while aliases:
alias = aliases.pop(0)
if self.alias_map[alias].join_type is None:
# This is the base table (first FROM entry) - this table
# isn't really joined at all in the query, so we should not
# alter its join type.
# Only the first alias (skipped above) should have None join_type
assert self.alias_map[alias].join_type is not None
parent_alias = self.alias_map[alias].parent_alias
parent_louter = parent_alias and self.alias_map[parent_alias].join_type == LOUTER
already_louter = self.alias_map[alias].join_type == LOUTER
if ((self.alias_map[alias].nullable or parent_louter) and
not already_louter):
self.alias_map[alias] = self.alias_map[alias].promote()
# Join type of 'alias' changed, so re-examine all aliases that
# refer to this one.
join for join in self.alias_map
if self.alias_map[join].parent_alias == alias and join not in aliases
def demote_joins(self, aliases):
Change join type from LOUTER to INNER for all joins in aliases.
Similarly to promote_joins(), this method must ensure no join chains
containing first an outer, then an inner join are generated. If we
are demoting b->c join in chain a LOUTER b LOUTER c then we must
demote a->b automatically, or otherwise the demotion of b->c doesn't
actually change anything in the query results. .
aliases = list(aliases)
while aliases:
alias = aliases.pop(0)
if self.alias_map[alias].join_type == LOUTER:
self.alias_map[alias] = self.alias_map[alias].demote()
parent_alias = self.alias_map[alias].parent_alias
if self.alias_map[parent_alias].join_type == INNER:
def reset_refcounts(self, to_counts):
Reset reference counts for aliases so that they match the value passed
in `to_counts`.
for alias, cur_refcount in self.alias_refcount.copy().items():
unref_amount = cur_refcount - to_counts.get(alias, 0)
self.unref_alias(alias, unref_amount)
def change_aliases(self, change_map):
Change the aliases in change_map (which maps old-alias -> new-alias),
relabelling any references to them in select columns and the where
assert set(change_map).isdisjoint(change_map.values())
# 1. Update references in "select" (normal columns plus aliases),
# "group by" and "where".
if isinstance(self.group_by, tuple):
self.group_by = tuple([col.relabeled_clone(change_map) for col in self.group_by]) = tuple([col.relabeled_clone(change_map) for col in])
self._annotations = self._annotations and OrderedDict(
(key, col.relabeled_clone(change_map)) for key, col in self._annotations.items()
# 2. Rename the alias in the internal table/alias datastructures.
for old_alias, new_alias in change_map.items():
if old_alias not in self.alias_map:
alias_data = self.alias_map[old_alias].relabeled_clone(change_map)
self.alias_map[new_alias] = alias_data
self.alias_refcount[new_alias] = self.alias_refcount[old_alias]
del self.alias_refcount[old_alias]
del self.alias_map[old_alias]
table_aliases = self.table_map[alias_data.table_name]
for pos, alias in enumerate(table_aliases):
if alias == old_alias:
table_aliases[pos] = new_alias
self.external_aliases = {change_map.get(alias, alias)
for alias in self.external_aliases}
def bump_prefix(self, outer_query):
Change the alias prefix to the next letter in the alphabet in a way
that the outer query's aliases and this query's aliases will not
conflict. Even tables that previously had no alias will get an alias
after this call.
def prefix_gen():
Generate a sequence of characters in alphabetical order:
-> 'A', 'B', 'C', ...
When the alphabet is finished, the sequence will continue with the
Cartesian product:
-> 'AA', 'AB', 'AC', ...
alphabet = ascii_uppercase
prefix = chr(ord(self.alias_prefix) + 1)
yield prefix
for n in count(1):
seq = alphabet[alphabet.index(prefix):] if prefix else alphabet
for s in product(seq, repeat=n):
yield ''.join(s)
prefix = None
if self.alias_prefix != outer_query.alias_prefix:
# No clashes between self and outer query should be possible.
local_recursion_limit = 127 # explicitly avoid infinite loop
for pos, prefix in enumerate(prefix_gen()):
if prefix not in self.subq_aliases:
self.alias_prefix = prefix
if pos > local_recursion_limit:
raise RuntimeError(
'Maximum recursion depth exceeded: too many subqueries.'
self.subq_aliases = self.subq_aliases.union([self.alias_prefix])
outer_query.subq_aliases = outer_query.subq_aliases.union(self.subq_aliases)
change_map = OrderedDict()
for pos, alias in enumerate(self.alias_map):
new_alias = '%s%d' % (self.alias_prefix, pos)
change_map[alias] = new_alias
def get_initial_alias(self):
Return the first alias for this query, after increasing its reference
if self.alias_map:
alias = self.base_table
alias = self.join(BaseTable(self.get_meta().db_table, None))
return alias
def count_active_tables(self):
Return the number of tables in this query with a non-zero reference
count. After execution, the reference counts are zeroed, so tables
added in compiler will not be seen by this method.
return len([1 for count in self.alias_refcount.values() if count])
def join(self, join, reuse=None, reuse_with_filtered_relation=False):
Return an alias for the 'join', either reusing an existing alias for
that join or creating a new one. 'join' is either a
sql.datastructures.BaseTable or Join.
The 'reuse' parameter can be either None which means all joins are
reusable, or it can be a set containing the aliases that can be reused.
The 'reuse_with_filtered_relation' parameter is used when computing
FilteredRelation instances.
A join is always created as LOUTER if the lhs alias is LOUTER to make
sure chains like t1 LOUTER t2 INNER t3 aren't generated. All new
joins are created as LOUTER if the join is nullable.
if reuse_with_filtered_relation and reuse:
reuse_aliases = [
a for a, j in self.alias_map.items()
if a in reuse and j.equals(join, with_filtered_relation=False)
reuse_aliases = [
a for a, j in self.alias_map.items()
if (reuse is None or a in reuse) and j == join
if reuse_aliases:
return reuse_aliases[0]
# No reuse is possible, so we need a new alias.
alias, _ = self.table_alias(join.table_name, create=True, filtered_relation=join.filtered_relation)
if join.join_type:
if self.alias_map[join.parent_alias].join_type == LOUTER or join.nullable:
join_type = LOUTER
join_type = INNER
join.join_type = join_type
join.table_alias = alias
self.alias_map[alias] = join
return alias
def join_parent_model(self, opts, model, alias, seen):
Make sure the given 'model' is joined in the query. If 'model' isn't
a parent of 'opts' or if it is None this method is a no-op.
The 'alias' is the root alias for starting the join, 'seen' is a dict
of model -> alias of existing joins. It must also contain a mapping
of None -> some alias. This will be returned in the no-op case.
if model in seen:
return seen[model]
chain = opts.get_base_chain(model)
if not chain:
return alias
curr_opts = opts
for int_model in chain:
if int_model in seen:
curr_opts = int_model._meta
alias = seen[int_model]
# Proxy model have elements in base chain
# with no parents, assign the new options
# object and skip to the next base in that
# case
if not curr_opts.parents[int_model]:
curr_opts = int_model._meta
link_field = curr_opts.get_ancestor_link(int_model)
join_info = self.setup_joins([], curr_opts, alias)
curr_opts = int_model._meta
alias = seen[int_model] = join_info.joins[-1]
return alias or seen[None]
def add_annotation(self, annotation, alias, is_summary=False):
"""Add a single annotation expression to the Query."""
annotation = annotation.resolve_expression(self, allow_joins=True, reuse=None,
self.annotations[alias] = annotation
def resolve_expression(self, query, *args, **kwargs):
clone = self.clone()
# Subqueries need to use a different set of aliases than the outer query.
clone.subquery = True
# It's safe to drop ordering if the queryset isn't using slicing,
# distinct(*fields) or select_for_update().
if (self.low_mark == 0 and self.high_mark is None and
not self.distinct_fields and
not self.select_for_update):
return clone
def as_sql(self, compiler, connection):
return self.get_compiler(connection=connection).as_sql()
def resolve_lookup_value(self, value, can_reuse, allow_joins):
if hasattr(value, 'resolve_expression'):
value = value.resolve_expression(self, reuse=can_reuse, allow_joins=allow_joins)
elif isinstance(value, (list, tuple)):
# The items of the iterable may be expressions and therefore need
# to be resolved independently.
for sub_value in value:
if hasattr(sub_value, 'resolve_expression'):
sub_value.resolve_expression(self, reuse=can_reuse, allow_joins=allow_joins)
return value
def solve_lookup_type(self, lookup):
Solve the lookup type from the lookup (e.g.: 'foobar__id__icontains').
lookup_splitted = lookup.split(LOOKUP_SEP)
if self._annotations:
expression, expression_lookups = refs_expression(lookup_splitted, self.annotations)
if expression:
return expression_lookups, (), expression
_, field, _, lookup_parts = self.names_to_path(lookup_splitted, self.get_meta())
field_parts = lookup_splitted[0:len(lookup_splitted) - len(lookup_parts)]
if len(lookup_parts) > 1 and not field_parts:
raise FieldError(
'Invalid lookup "%s" for model %s".' %
(lookup, self.get_meta().model.__name__)
return lookup_parts, field_parts, False
def check_query_object_type(self, value, opts, field):
Check whether the object passed while querying is of the correct type.
If not, raise a ValueError specifying the wrong object.
if hasattr(value, '_meta'):
if not check_rel_lookup_compatibility(value._meta.model, opts, field):
raise ValueError(
'Cannot query "%s": Must be "%s" instance.' %
(value, opts.object_name))
def check_related_objects(self, field, value, opts):
"""Check the type of object passed to query relations."""
if field.is_relation:
# Check that the field and the queryset use the same model in a
# query like .filter(author=Author.objects.all()). For example, the
# opts would be Author's (from the author field) and value.model
# would be Author.objects.all() queryset's .model (Author also).
# The field is the related field on the lhs side.
if (isinstance(value, Query) and not value.has_select_fields and
not check_rel_lookup_compatibility(value.model, opts, field)):
raise ValueError(
'Cannot use QuerySet for "%s": Use a QuerySet for "%s".' %
(value.model._meta.object_name, opts.object_name)
elif hasattr(value, '_meta'):
self.check_query_object_type(value, opts, field)
elif hasattr(value, '__iter__'):
for v in value:
self.check_query_object_type(v, opts, field)
def build_lookup(self, lookups, lhs, rhs):
Try to extract transforms and lookup from given lhs.
The lhs value is something that works like SQLExpression.
The rhs value is what the lookup is going to compare against.
The lookups is a list of names to extract using get_lookup()
and get_transform().
# __exact is the default lookup if one isn't given.
lookups = lookups or ['exact']
for name in lookups[:-1]:
lhs = self.try_transform(lhs, name)
# First try get_lookup() so that the lookup takes precedence if the lhs
# supports both transform and lookup for the name.
lookup_name = lookups[-1]
lookup_class = lhs.get_lookup(lookup_name)
if not lookup_class:
if lhs.field.is_relation:
raise FieldError('Related Field got invalid lookup: {}'.format(lookup_name))
# A lookup wasn't found. Try to interpret the name as a transform
# and do an Exact lookup against it.
lhs = self.try_transform(lhs, lookup_name)
lookup_name = 'exact'
lookup_class = lhs.get_lookup(lookup_name)
if not lookup_class:
lookup = lookup_class(lhs, rhs)
# Interpret '__exact=None' as the sql 'is NULL'; otherwise, reject all
# uses of None as a query value.
if lookup.rhs is None:
if lookup_name not in ('exact', 'iexact'):
raise ValueError("Cannot use None as a query value")
return lhs.get_lookup('isnull')(lhs, True)
# For Oracle '' is equivalent to null. The check must be done at this
# stage because join promotion can't be done in the compiler. Using
# DEFAULT_DB_ALIAS isn't nice but it's the best that can be done here.
# A similar thing is done in is_nullable(), too.
if (connections[DEFAULT_DB_ALIAS].features.interprets_empty_strings_as_nulls and
lookup_name == 'exact' and lookup.rhs == ''):
return lhs.get_lookup('isnull')(lhs, True)
return lookup
def try_transform(self, lhs, name):
Helper method for build_lookup(). Try to fetch and initialize
a transform for name parameter from lhs.
transform_class = lhs.get_transform(name)
if transform_class:
return transform_class(lhs)
raise FieldError(
"Unsupported lookup '%s' for %s or join on the field not "
"permitted." %
(name, lhs.output_field.__class__.__name__))
def build_filter(self, filter_expr, branch_negated=False, current_negated=False,
can_reuse=None, allow_joins=True, split_subq=True,
Build a WhereNode for a single filter clause but don't add it
to this Query. Query.add_q() will then add this filter to the where
The 'branch_negated' tells us if the current branch contains any
negations. This will be used to determine if subqueries are needed.
The 'current_negated' is used to determine if the current filter is
negated or not and this will be used to determine if IS NULL filtering
is needed.
The difference between current_negated and branch_negated is that
branch_negated is set on first negation, but current_negated is
flipped for each negation.
Note that add_filter will not do any negating itself, that is done
upper in the code by add_q().
The 'can_reuse' is a set of reusable joins for multijoins.
If 'reuse_with_filtered_relation' is True, then only joins in can_reuse
will be reused.
The method will create a filter clause that can be added to the current
query. However, if the filter isn't added to the query then the caller
is responsible for unreffing the joins used.
if isinstance(filter_expr, dict):
raise FieldError("Cannot parse keyword query as dict")
arg, value = filter_expr
if not arg:
raise FieldError("Cannot parse keyword query %r" % arg)
lookups, parts, reffed_expression = self.solve_lookup_type(arg)
if not getattr(reffed_expression, 'filterable', True):
raise NotSupportedError(
reffed_expression.__class__.__name__ + ' is disallowed in '
'the filter clause.'
if not allow_joins and len(parts) > 1:
raise FieldError("Joined field references are not permitted in this query")
pre_joins = self.alias_refcount.copy()
value = self.resolve_lookup_value(value, can_reuse, allow_joins)
used_joins = {k for k, v in self.alias_refcount.items() if v > pre_joins.get(k, 0)}
clause = self.where_class()
if reffed_expression:
condition = self.build_lookup(lookups, reffed_expression, value)
clause.add(condition, AND)
return clause, []
opts = self.get_meta()
alias = self.get_initial_alias()
allow_many = not branch_negated or not split_subq
join_info = self.setup_joins(
parts, opts, alias, can_reuse=can_reuse, allow_many=allow_many,
# Prevent iterator from being consumed by check_related_objects()
if isinstance(value, Iterator):
value = list(value)
self.check_related_objects(join_info.final_field, value, join_info.opts)
# split_exclude() needs to know which joins were generated for the
# lookup parts
self._lookup_joins = join_info.joins
except MultiJoin as e:
return self.split_exclude(filter_expr, can_reuse, e.names_with_path)
# Update used_joins before trimming since they are reused to determine
# which joins could be later promoted to INNER.
targets, alias, join_list = self.trim_joins(join_info.targets, join_info.joins, join_info.path)
if can_reuse is not None:
if join_info.final_field.is_relation:
# No support for transforms for relational fields
num_lookups = len(lookups)
if num_lookups > 1:
raise FieldError('Related Field got invalid lookup: {}'.format(lookups[0]))
if len(targets) == 1:
col = targets[0].get_col(alias, join_info.final_field)
col = MultiColSource(alias, targets, join_info.targets, join_info.final_field)
col = targets[0].get_col(alias, join_info.final_field)
condition = self.build_lookup(lookups, col, value)
lookup_type = condition.lookup_name
clause.add(condition, AND)
require_outer = lookup_type == 'isnull' and condition.rhs is True and not current_negated
if current_negated and (lookup_type != 'isnull' or condition.rhs is False):
require_outer = True
if (lookup_type != 'isnull' and (
self.is_nullable(targets[0]) or
self.alias_map[join_list[-1]].join_type == LOUTER)):
# The condition added here will be SQL like this:
# NOT (col IS NOT NULL), where the first NOT is added in
# upper layers of code. The reason for addition is that if col
# is null, then col != someval will result in SQL "unknown"
# which isn't the same as in Python. The Python None handling
# is wanted, and it can be gotten by
# (col IS NULL OR col != someval)
# <=>
# NOT (col IS NOT NULL AND col = someval).
lookup_class = targets[0].get_lookup('isnull')
clause.add(lookup_class(targets[0].get_col(alias, join_info.targets[0]), False), AND)
return clause, used_joins if not require_outer else ()
def add_filter(self, filter_clause):
self.add_q(Q(**{filter_clause[0]: filter_clause[1]}))
def add_q(self, q_object):
A preprocessor for the internal _add_q(). Responsible for doing final
join promotion.
# For join promotion this case is doing an AND for the added q_object
# and existing conditions. So, any existing inner join forces the join
# type to remain inner. Existing outer joins can however be demoted.
# (Consider case where rel_a is LOUTER and rel_a__col=1 is added - if
# rel_a doesn't produce any rows, then the whole condition must fail.
# So, demotion is OK.
existing_inner = {a for a in self.alias_map if self.alias_map[a].join_type == INNER}
clause, _ = self._add_q(q_object, self.used_aliases)
if clause:
self.where.add(clause, AND)
def _add_q(self, q_object, used_aliases, branch_negated=False,
current_negated=False, allow_joins=True, split_subq=True):
"""Add a Q-object to the current filter."""
connector = q_object.connector
current_negated = current_negated ^ q_object.negated
branch_negated = branch_negated or q_object.negated
target_clause = self.where_class(connector=connector,
joinpromoter = JoinPromoter(q_object.connector, len(q_object.children), current_negated)
for child in q_object.children:
if isinstance(child, Node):
child_clause, needed_inner = self._add_q(
child, used_aliases, branch_negated,
current_negated, allow_joins, split_subq)
child_clause, needed_inner = self.build_filter(
child, can_reuse=used_aliases, branch_negated=branch_negated,
current_negated=current_negated, allow_joins=allow_joins,
if child_clause:
target_clause.add(child_clause, connector)
needed_inner = joinpromoter.update_join_types(self)
return target_clause, needed_inner
def build_filtered_relation_q(self, q_object, reuse, branch_negated=False, current_negated=False):
"""Add a FilteredRelation object to the current filter."""
connector = q_object.connector
current_negated ^= q_object.negated
branch_negated = branch_negated or q_object.negated
target_clause = self.where_class(connector=connector, negated=q_object.negated)
for child in q_object.children:
if isinstance(child, Node):
child_clause = self.build_filtered_relation_q(
child, reuse=reuse, branch_negated=branch_negated,
child_clause, _ = self.build_filter(
child, can_reuse=reuse, branch_negated=branch_negated,
allow_joins=True, split_subq=False,
target_clause.add(child_clause, connector)
return target_clause
def add_filtered_relation(self, filtered_relation, alias):
filtered_relation.alias = alias
lookups = dict(get_children_from_q(filtered_relation.condition))
for lookup in chain((filtered_relation.relation_name,), lookups):
lookup_parts, field_parts, _ = self.solve_lookup_type(lookup)
shift = 2 if not lookup_parts else 1
if len(field_parts) > (shift + len(lookup_parts)):
raise ValueError(
"FilteredRelation's condition doesn't support nested "
"relations (got %r)." % lookup
self._filtered_relations[filtered_relation.alias] = filtered_relation
def names_to_path(self, names, opts, allow_many=True, fail_on_missing=False):
Walk the list of names and turns them into PathInfo tuples. A single
name in 'names' can generate multiple PathInfos (m2m, for example).
'names' is the path of names to travel, 'opts' is the model Options we
start the name resolving from, 'allow_many' is as for setup_joins().
If fail_on_missing is set to True, then a name that can't be resolved
will generate a FieldError.
Return a list of PathInfo tuples. In addition return the final field
(the last used join field) and target (which is a field guaranteed to
contain the same value as the final field). Finally, return those names
that weren't found (which are likely transforms and the final lookup).
path, names_with_path = [], []
for pos, name in enumerate(names):
cur_names_with_path = (name, [])
if name == 'pk':
name =
field = None
filtered_relation = None
field = opts.get_field(name)
except FieldDoesNotExist:
if name in self.annotation_select:
field = self.annotation_select[name].output_field
elif name in self._filtered_relations and pos == 0:
filtered_relation = self._filtered_relations[name]
field = opts.get_field(filtered_relation.relation_name)
if field is not None:
# Fields that contain one-to-many relations with a generic
# model (like a GenericForeignKey) cannot generate reverse
# relations and therefore cannot be used for reverse querying.
if field.is_relation and not field.related_model:
raise FieldError(
"Field %r does not generate an automatic reverse "
"relation and therefore cannot be used for reverse "
"querying. If it is a GenericForeignKey, consider "
"adding a GenericRelation." % name
model = field.model._meta.concrete_model
except AttributeError:
# QuerySet.annotate() may introduce fields that aren't
# attached to a model.
model = None
# We didn't find the current field, so move position back
# one step.
pos -= 1
if pos == -1 or fail_on_missing:
field_names = list(get_field_names_from_opts(opts))
available = sorted(
field_names + list(self.annotation_select) +
raise FieldError("Cannot resolve keyword '%s' into field. "
"Choices are: %s" % (name, ", ".join(available)))
# Check if we need any joins for concrete inheritance cases (the
# field lives in parent, but we are currently in one of its
# children)
if model is not opts.model:
path_to_parent = opts.get_path_to_parent(model)
if path_to_parent:
opts = path_to_parent[-1].to_opts
if hasattr(field, 'get_path_info'):
pathinfos = field.get_path_info(filtered_relation)
if not allow_many:
for inner_pos, p in enumerate(pathinfos):
if p.m2m:
cur_names_with_path[1].extend(pathinfos[0:inner_pos + 1])
raise MultiJoin(pos + 1, names_with_path)
last = pathinfos[-1]
final_field = last.join_field
opts = last.to_opts
targets = last.target_fields
# Local non-relational field.
final_field = field
targets = (field,)
if fail_on_missing and pos + 1 != len(names):
raise FieldError(
"Cannot resolve keyword %r into field. Join on '%s'"
" not permitted." % (names[pos + 1], name))
return path, final_field, targets, names[pos + 1:]
def setup_joins(self, names, opts, alias, can_reuse=None, allow_many=True,
Compute the necessary table joins for the passage through the fields
given in 'names'. 'opts' is the Options class for the current model
(which gives the table we are starting from), 'alias' is the alias for
the table to start the joining from.
The 'can_reuse' defines the reverse foreign key joins we can reuse. It
can be None in which case all joins are reusable or a set of aliases
that can be reused. Note that non-reverse foreign keys are always
reusable when using setup_joins().
The 'reuse_with_filtered_relation' can be used to force 'can_reuse'
parameter and force the relation on the given connections.
If 'allow_many' is False, then any reverse foreign key seen will
generate a MultiJoin exception.
Return the final field involved in the joins, the target field (used
for any 'where' constraint), the final 'opts' value, the joins, the
field path traveled to generate the joins, and a transform function
that takes a field and alias and is equivalent to `field.get_col(alias)`
in the simple case but wraps field transforms if they were included in
The target field is the field containing the concrete value. Final
field can be something different, for example foreign key pointing to
that value. Final field is needed for example in some value
conversions (convert 'obj' in fk__id=obj to pk val using the foreign
key field for example).
joins = [alias]
# The transform can't be applied yet, as joins must be trimmed later.
# To avoid making every caller of this method look up transforms
# directly, compute transforms here and and create a partial that
# converts fields to the appropriate wrapped version.
def final_transformer(field, alias):
return field.get_col(alias)
# Try resolving all the names as fields first. If there's an error,
# treat trailing names as lookups until a field can be resolved.
last_field_exception = None
for pivot in range(len(names), 0, -1):
path, final_field, targets, rest = self.names_to_path(
names[:pivot], opts, allow_many, fail_on_missing=True,
except FieldError as exc:
if pivot == 1:
# The first item cannot be a lookup, so it's safe
# to raise the field error here.
last_field_exception = exc
# The transforms are the remaining items that couldn't be
# resolved into fields.
transforms = names[pivot:]
for name in transforms:
def transform(field, alias, *, name, previous):
wrapped = previous(field, alias)
return self.try_transform(wrapped, name)
except FieldError:
# FieldError is raised if the transform doesn't exist.
if isinstance(final_field, Field) and last_field_exception:
raise last_field_exception
final_transformer = functools.partial(transform, name=name, previous=final_transformer)
# Then, add the path to the query's joins. Note that we can't trim
# joins at this stage - we will need the information about join type
# of the trimmed joins.
for join in path:
if join.filtered_relation:
filtered_relation = join.filtered_relation.clone()
table_alias = filtered_relation.alias
filtered_relation = None
table_alias = None
opts = join.to_opts
nullable = self.is_nullable(join.join_field)
nullable = True
connection = Join(
opts.db_table, alias, table_alias, INNER, join.join_field,
nullable, filtered_relation=filtered_relation,
reuse = can_reuse if join.m2m or reuse_with_filtered_relation else None
alias = self.join(
connection, reuse=reuse,
if filtered_relation:
filtered_relation.path = joins[:]
return JoinInfo(final_field, targets, opts, joins, path, final_transformer)
def trim_joins(self, targets, joins, path):
The 'target' parameter is the final field being joined to, 'joins'
is the full list of join aliases. The 'path' contain the PathInfos
used to create the joins.
Return the final target field and table alias and the new active
Always trim any direct join if the target column is already in the
previous table. Can't trim reverse joins as it's unknown if there's
anything on the other side of the join.
joins = joins[:]
for pos, info in enumerate(reversed(path)):
if len(joins) == 1 or not
if info.filtered_relation:
join_targets = {t.column for t in info.join_field.foreign_related_fields}
cur_targets = {t.column for t in targets}
if not cur_targets.issubset(join_targets):
targets_dict = {r[1].column: r[0] for r in info.join_field.related_fields if r[1].column in cur_targets}
targets = tuple(targets_dict[t.column] for t in targets)
return targets, joins[-1], joins
def resolve_ref(self, name, allow_joins=True, reuse=None, summarize=False):
if not allow_joins and LOOKUP_SEP in name:
raise FieldError("Joined field references are not permitted in this query")
if name in self.annotations:
if summarize:
# Summarize currently means we are doing an aggregate() query
# which is executed as a wrapped subquery if any of the
# aggregate() elements reference an existing annotation. In
# that case we need to return a Ref to the subquery's annotation.
return Ref(name, self.annotation_select[name])
return self.annotations[name]
field_list = name.split(LOOKUP_SEP)
join_info = self.setup_joins(field_list, self.get_meta(), self.get_initial_alias(), can_reuse=reuse)
targets, _, join_list = self.trim_joins(join_info.targets, join_info.joins, join_info.path)
if len(targets) > 1:
raise FieldError("Referencing multicolumn fields with F() objects "
"isn't supported")
if reuse is not None:
col = targets[0].get_col(join_list[-1], join_info.targets[0])
return col
def split_exclude(self, filter_expr, can_reuse, names_with_path):
When doing an exclude against any kind of N-to-many relation, we need
to use a subquery. This method constructs the nested query, given the
original exclude filter (filter_expr) and the portion up to the first
N-to-many relation field.
For example, if the origin filter is ~Q(child__name='foo'), filter_expr
is ('child__name', 'foo') and can_reuse is a set of joins usable for
filters in the original query.
We will turn this into equivalent of:
WHERE NOT (pk IN (SELECT parent_id FROM thetable
WHERE name = 'foo' AND parent_id IS NOT NULL))
It might be worth it to consider using WHERE NOT EXISTS as that has
saner null handling, and is easier for the backend's optimizer to
# Generate the inner query.
query = Query(self.model)
# Try to have as simple as possible subquery -> trim leading joins from
# the subquery.
trimmed_prefix, contains_louter = query.trim_start(names_with_path)
# Add extra check to make sure the selected field will not be null
# since we are adding an IN <subquery> clause. This prevents the
# database from tripping over IN (...,NULL,...) selects and returning
# nothing
col =[0]
select_field =
alias = col.alias
if self.is_nullable(select_field):
lookup_class = select_field.get_lookup('isnull')
lookup = lookup_class(select_field.get_col(alias), False)
query.where.add(lookup, AND)
if alias in can_reuse:
pk =
# Need to add a restriction so that outer query's filters are in effect for
# the subquery, too.
lookup_class = select_field.get_lookup('exact')
# Note that the[0].alias is different from alias
# due to bump_prefix above.
lookup = lookup_class(pk.get_col([0].alias),
query.where.add(lookup, AND)
condition, needed_inner = self.build_filter(
('%s__in' % trimmed_prefix, query),
current_negated=True, branch_negated=True, can_reuse=can_reuse)
if contains_louter:
or_null_condition, _ = self.build_filter(
('%s__isnull' % trimmed_prefix, True),
current_negated=True, branch_negated=True, can_reuse=can_reuse)
condition.add(or_null_condition, OR)
# Note that the end result will be:
# (outercol NOT IN innerq AND outercol IS NOT NULL) OR outercol IS NULL.
# This might look crazy but due to how IN works, this seems to be
# correct. If the IS NOT NULL check is removed then outercol NOT
# IN will return UNKNOWN. If the IS NULL check is removed, then if
# outercol IS NULL we will not match the row.
return condition, needed_inner
def set_empty(self):
self.where.add(NothingNode(), AND)
def is_empty(self):
return any(isinstance(c, NothingNode) for c in self.where.children)
def set_limits(self, low=None, high=None):
Adjust the limits on the rows retrieved. Use low/high to set these,
as it makes it more Pythonic to read and write. When the SQL query is
created, convert them to the appropriate offset and limit values.
Apply any limits passed in here to the existing constraints. Add low
to the current low value and clamp both to any existing high value.
if high is not None:
if self.high_mark is not None:
self.high_mark = min(self.high_mark, self.low_mark + high)
self.high_mark = self.low_mark + high
if low is not None:
if self.high_mark is not None:
self.low_mark = min(self.high_mark, self.low_mark + low)
self.low_mark = self.low_mark + low
if self.low_mark == self.high_mark:
def clear_limits(self):
"""Clear any existing limits."""
self.low_mark, self.high_mark = 0, None
def has_limit_one(self):
return self.high_mark is not None and (self.high_mark - self.low_mark) == 1
def can_filter(self):
Return True if adding filters to this instance is still possible.
Typically, this means no limits or offsets have been put on the results.
return not self.low_mark and self.high_mark is None
def clear_select_clause(self):
"""Remove all fields from SELECT clause.""" = ()
self.default_cols = False
self.select_related = False
def clear_select_fields(self):
Clear the list of fields to select (but not extra_select columns).
Some queryset types completely replace any existing list of select
""" = ()
self.values_select = ()
def set_select(self, cols):
self.default_cols = False = tuple(cols)
def add_distinct_fields(self, *field_names):
Add and resolve the given fields to the query's "distinct on" clause.
self.distinct_fields = field_names
self.distinct = True
def add_fields(self, field_names, allow_m2m=True):
Add the given (model) fields to the select set. Add the field names in
the order specified.
alias = self.get_initial_alias()
opts = self.get_meta()
cols = []
for name in field_names:
# Join promotion note - we must not remove any rows here, so
# if there is no existing joins, use outer join.
join_info = self.setup_joins(name.split(LOOKUP_SEP), opts, alias, allow_many=allow_m2m)
targets, final_alias, joins = self.trim_joins(
for target in targets:
cols.append(join_info.transform_function(target, final_alias))
if cols:
except MultiJoin:
raise FieldError("Invalid field name: '%s'" % name)
except FieldError:
if LOOKUP_SEP in name:
# For lookups spanning over relationships, show the error
# from the model on which the lookup failed.
names = sorted(
list(get_field_names_from_opts(opts)) + list(self.extra) +
list(self.annotation_select) + list(self._filtered_relations)
raise FieldError("Cannot resolve keyword %r into field. "
"Choices are: %s" % (name, ", ".join(names)))
def add_ordering(self, *ordering):
Add items from the 'ordering' sequence to the query's "order by"
clause. These items are either field names (not column names) --
possibly with a direction prefix ('-' or '?') -- or OrderBy
If 'ordering' is empty, clear all ordering from the query.
errors = []
for item in ordering:
if not hasattr(item, 'resolve_expression') and not ORDER_PATTERN.match(item):
if getattr(item, 'contains_aggregate', False):
raise FieldError(
'Using an aggregate in order_by() without also including '
'it in annotate() is not allowed: %s' % item
if errors:
raise FieldError('Invalid order_by arguments: %s' % errors)
if ordering:
self.order_by += ordering
self.default_ordering = False
def clear_ordering(self, force_empty):
Remove any ordering settings. If 'force_empty' is True, there will be
no ordering in the resulting query (not even the model's default).
self.order_by = ()
self.extra_order_by = ()
if force_empty:
self.default_ordering = False
def set_group_by(self):
Expand the GROUP BY clause required by the query.
This will usually be the set of all non-aggregate fields in the
return data. If the database backend supports grouping by the
primary key, and the query would be equivalent, the optimization
will be made automatically.
group_by = list(
if self.annotation_select:
for annotation in self.annotation_select.values():
for col in annotation.get_group_by_cols():
self.group_by = tuple(group_by)
def add_select_related(self, fields):
Set up the select_related data structure so that we only select
certain related models (as opposed to all models, when
if isinstance(self.select_related, bool):
field_dict = {}
field_dict = self.select_related
for field in fields:
d = field_dict
for part in field.split(LOOKUP_SEP):
d = d.setdefault(part, {})
self.select_related = field_dict
def add_extra(self, select, select_params, where, params, tables, order_by):
Add data to the various extra_* attributes for user-created additions
to the query.
if select:
# We need to pair any placeholder markers in the 'select'
# dictionary with their parameters in 'select_params' so that
# subsequent updates to the select dictionary also adjust the
# parameters appropriately.
select_pairs = OrderedDict()
if select_params:
param_iter = iter(select_params)
param_iter = iter([])
for name, entry in select.items():
entry = force_text(entry)
entry_params = []
pos = entry.find("%s")
while pos != -1:
if pos == 0 or entry[pos - 1] != '%':
pos = entry.find("%s", pos + 2)
select_pairs[name] = (entry, entry_params)
# This is order preserving, since self.extra_select is an OrderedDict.
if where or params:
self.where.add(ExtraWhere(where, params), AND)
if tables:
self.extra_tables += tuple(tables)
if order_by:
self.extra_order_by = order_by
def clear_deferred_loading(self):
"""Remove any fields from the deferred loading set."""
self.deferred_loading = (frozenset(), True)
def add_deferred_loading(self, field_names):
Add the given list of model field names to the set of fields to
exclude from loading from the database when automatic column selection
is done. Add the new field names to any existing field names that
are deferred (or removed from any existing field names that are marked
as the only ones for immediate loading).
# Fields on related models are stored in the literal double-underscore
# format, so that we can use a set datastructure. We do the foo__bar
# splitting and handling when computing the SQL column names (as part of
# get_columns()).
existing, defer = self.deferred_loading
if defer:
# Add to existing deferred names.
self.deferred_loading = existing.union(field_names), True
# Remove names from the set of any existing "immediate load" names.
self.deferred_loading = existing.difference(field_names), False
def add_immediate_loading(self, field_names):
Add the given list of model field names to the set of fields to
retrieve when the SQL is executed ("immediate loading" fields). The
field names replace any existing immediate loading field names. If
there are field names already specified for deferred loading, remove
those names from the new field_names before storing the new names
for immediate loading. (That is, immediate loading overrides any
existing immediate values, but respects existing deferrals.)
existing, defer = self.deferred_loading
field_names = set(field_names)
if 'pk' in field_names:
if defer:
# Remove any existing deferred names from the current set before
# setting the new names.
self.deferred_loading = field_names.difference(existing), False
# Replace any existing "immediate load" field names.
self.deferred_loading = frozenset(field_names), False
def get_loaded_field_names(self):
If any fields are marked to be deferred, return a dictionary mapping
models to a set of names in those fields that will be loaded. If a
model is not in the returned dictionary, none of its fields are
If no fields are marked for deferral, return an empty dictionary.
# We cache this because we call this function multiple times
# (compiler.fill_related_selections, query.iterator)
return self._loaded_field_names_cache
except AttributeError:
collection = {}
self.deferred_to_data(collection, self.get_loaded_field_names_cb)
self._loaded_field_names_cache = collection
return collection
def get_loaded_field_names_cb(self, target, model, fields):
"""Callback used by get_deferred_field_names()."""
target[model] = {f.attname for f in fields}
def set_annotation_mask(self, names):
"""Set the mask of annotations that will be returned by the SELECT."""
if names is None:
self.annotation_select_mask = None
self.annotation_select_mask = set(names)
self._annotation_select_cache = None
def append_annotation_mask(self, names):
if self.annotation_select_mask is not None:
def set_extra_mask(self, names):
Set the mask of extra select items that will be returned by SELECT.
Don't remove them from the Query since they might be used later.
if names is None:
self.extra_select_mask = None
self.extra_select_mask = set(names)
self._extra_select_cache = None
def set_values(self, fields):
self.select_related = False
if self.group_by is True:
self.add_fields((f.attname for f in self.model._meta.concrete_fields), False)
if fields:
field_names = []
extra_names = []
annotation_names = []
if not self._extra and not self._annotations:
# Shortcut - if there are no extra or annotations, then
# the values() clause must be just field names.
field_names = list(fields)
self.default_cols = False
for f in fields:
if f in self.extra_select:
elif f in self.annotation_select:
field_names = [f.attname for f in self.model._meta.concrete_fields]
self.values_select = tuple(field_names)
self.add_fields(field_names, True)
def annotation_select(self):
Return the OrderedDict of aggregate columns that are not masked and
should be used in the SELECT clause. Cache this result for performance.
if self._annotation_select_cache is not None:
return self._annotation_select_cache
elif not self._annotations:
return {}
elif self.annotation_select_mask is not None:
self._annotation_select_cache = OrderedDict(
(k, v) for k, v in self.annotations.items()
if k in self.annotation_select_mask
return self._annotation_select_cache
return self.annotations
def extra_select(self):
if self._extra_select_cache is not None:
return self._extra_select_cache
if not self._extra:
return {}
elif self.extra_select_mask is not None:
self._extra_select_cache = OrderedDict(
(k, v) for k, v in self.extra.items()
if k in self.extra_select_mask
return self._extra_select_cache
return self.extra
def trim_start(self, names_with_path):
Trim joins from the start of the join path. The candidates for trim
are the PathInfos in names_with_path structure that are m2m joins.
Also set the select column so the start matches the join.
This method is meant to be used for generating the subquery joins &
cols in split_exclude().
Return a lookup usable for doing outerq.filter(lookup=self) and a
boolean indicating if the joins in the prefix contain a LEFT OUTER join.
all_paths = []
for _, paths in names_with_path:
contains_louter = False
# Trim and operate only on tables that were generated for
# the lookup part of the query. That is, avoid trimming
# joins generated for F() expressions.
lookup_tables = [
t for t in self.alias_map
if t in self._lookup_joins or t == self.base_table
for trimmed_paths, path in enumerate(all_paths):
if path.m2m:
if self.alias_map[lookup_tables[trimmed_paths + 1]].join_type == LOUTER:
contains_louter = True
alias = lookup_tables[trimmed_paths]
# The path.join_field is a Rel, lets get the other side's field
join_field = path.join_field.field
# Build the filter prefix.
paths_in_prefix = trimmed_paths
trimmed_prefix = []
for name, path in names_with_path:
if paths_in_prefix - len(path) < 0:
paths_in_prefix -= len(path)
trimmed_prefix = LOOKUP_SEP.join(trimmed_prefix)
# Lets still see if we can trim the first join from the inner query
# (that is, self). We can't do this for LEFT JOINs because we would
# miss those rows that have nothing on the outer side.
if self.alias_map[lookup_tables[trimmed_paths + 1]].join_type != LOUTER:
select_fields = [r[0] for r in join_field.related_fields]
select_alias = lookup_tables[trimmed_paths + 1]
extra_restriction = join_field.get_extra_restriction(
self.where_class, None, lookup_tables[trimmed_paths + 1])
if extra_restriction:
self.where.add(extra_restriction, AND)
# TODO: It might be possible to trim more joins from the start of the
# inner query if it happens to have a longer join chain containing the
# values in select_fields. Lets punt this one for now.
select_fields = [r[1] for r in join_field.related_fields]
select_alias = lookup_tables[trimmed_paths]
# The found starting point is likely a Join instead of a BaseTable reference.
# But the first entry in the query's FROM clause must not be a JOIN.
for table in self.alias_map:
if self.alias_refcount[table] > 0:
self.alias_map[table] = BaseTable(self.alias_map[table].table_name, table)
self.set_select([f.get_col(select_alias) for f in select_fields])
return trimmed_prefix, contains_louter
def is_nullable(self, field):
Check if the given field should be treated as nullable.
Some backends treat '' as null and Django treats such fields as
nullable for those backends. In such situations field.null can be
False even if we should treat the field as nullable.
# We need to use DEFAULT_DB_ALIAS here, as QuerySet does not have
# (nor should it have) knowledge of which connection is going to be
# used. The proper fix would be to defer all decisions where
# is_nullable() is needed to the compiler stage, but that is not easy
# to do currently.
return (
connections[DEFAULT_DB_ALIAS].features.interprets_empty_strings_as_nulls and
) or field.null
def get_order_dir(field, default='ASC'):
Return the field name and direction for an order specification. For
example, '-foo' is returned as ('foo', 'DESC').
The 'default' param is used to indicate which way no prefix (or a '+'
prefix) should sort. The '-' prefix always sorts the opposite way.
dirn = ORDER_DIR[default]
if field[0] == '-':
return field[1:], dirn[1]
return field, dirn[0]
def add_to_dict(data, key, value):
Add "value" to the set of values for "key", whether or not "key" already
if key in data:
data[key] = {value}
def is_reverse_o2o(field):
Check if the given field is reverse-o2o. The field is expected to be some
sort of relation field or related object.
return field.is_relation and field.one_to_one and not field.concrete
class JoinPromoter:
A class to abstract away join promotion problems for complex filter
def __init__(self, connector, num_children, negated):
self.connector = connector
self.negated = negated
if self.negated:
if connector == AND:
self.effective_connector = OR
self.effective_connector = AND
self.effective_connector = self.connector
self.num_children = num_children
# Maps of table alias to how many times it is seen as required for
# inner and/or outer joins.
self.votes = Counter()
def add_votes(self, votes):
Add single vote per item to self.votes. Parameter can be any
def update_join_types(self, query):
Change join types so that the generated query is as efficient as
possible, but still correct. So, change as many joins as possible
to INNER, but don't make OUTER joins INNER if that could remove
results from the query.
to_promote = set()
to_demote = set()
# The effective_connector is used so that NOT (a AND b) is treated
# similarly to (a OR b) for join promotion.
for table, votes in self.votes.items():
# We must use outer joins in OR case when the join isn't contained
# in all of the joins. Otherwise the INNER JOIN itself could remove
# valid results. Consider the case where a model with rel_a and
# rel_b relations is queried with rel_a__col=1 | rel_b__col=2. Now,
# if rel_a join doesn't produce any results is null (for example
# reverse foreign key or null value in direct foreign key), and
# there is a matching row in rel_b with col=2, then an INNER join
# to rel_a would remove a valid match from the query. So, we need
# to promote any existing INNER to LOUTER (it is possible this
# promotion in turn will be demoted later on).
if self.effective_connector == 'OR' and votes < self.num_children:
# If connector is AND and there is a filter that can match only
# when there is a joinable row, then use INNER. For example, in
# rel_a__col=1 & rel_b__col=2, if either of the rels produce NULL
# as join output, then the col=1 or col=2 can't match (as
# NULL=anything is always false).
# For the OR case, if all children voted for a join to be inner,
# then we can use INNER for the join. For example:
# (rel_a__col__icontains=Alex | rel_a__col__icontains=Russell)
# then if rel_a doesn't produce any rows, the whole condition
# can't match. Hence we can safely use INNER join.
if self.effective_connector == 'AND' or (
self.effective_connector == 'OR' and votes == self.num_children):
# Finally, what happens in cases where we have:
# (rel_a__col=1|rel_b__col=2) & rel_a__col__gte=0
# Now, we first generate the OR clause, and promote joins for it
# in the first if branch above. Both rel_a and rel_b are promoted
# to LOUTER joins. After that we do the AND case. The OR case
# voted no inner joins but the rel_a__col__gte=0 votes inner join
# for rel_a. We demote it back to INNER join (in AND case a single
# vote is enough). The demotion is OK, if rel_a doesn't produce
# rows, then the rel_a__col__gte=0 clause can't be true, and thus
# the whole clause must be false. So, it is safe to use INNER
# join.
# Note that in this example we could just as well have the __gte
# clause and the OR clause swapped. Or we could replace the __gte
# clause with an OR clause containing rel_a__col=1|rel_a__col=2,
# and again we could safely demote to INNER.
return to_demote