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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 copy
from collections import Counter, Iterator, Mapping, OrderedDict
from itertools import chain, count, product
from string import ascii_uppercase
from django.core.exceptions import FieldDoesNotExist, FieldError
from django.db import DEFAULT_DB_ALIAS, 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.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, EmptyResultSet, Join, MultiJoin,
from django.db.models.sql.where import (
AND, OR, ExtraWhere, NothingNode, WhereNode,
from django.utils.encoding import force_text
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()
class RawQuery:
A single raw SQL query
def __init__(self, sql, using, params=None, context=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 = {}
self.context = context or {}
def clone(self, using):
return RawQuery(self.sql, using, params=self.params, context=self.context.copy())
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])
query_terms = QUERY_TERMS
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 = {}
# 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.tables = [] # Aliases in the order they are created.
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 list 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_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 = (set(), True)
self.context = {}
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 __str__(self):
Returns 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):
Returns 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):
result = self.clone(memo=memo)
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):
Returns 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, klass=None, memo=None, **kwargs):
Creates a copy of the current instance. The 'kwargs' parameter can be
used by clients to update attributes after copying has taken place.
obj = Empty()
obj.__class__ = klass or self.__class__
obj.model = self.model
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.default_cols = self.default_cols
obj.default_ordering = self.default_ordering
obj.standard_ordering = self.standard_ordering =[:]
obj.tables = self.tables[:]
obj.where = self.where.clone()
obj.where_class = self.where_class
if self.group_by is None:
obj.group_by = None
elif self.group_by is True:
obj.group_by = True
obj.group_by = self.group_by[:]
obj.order_by = self.order_by[:]
obj.low_mark, obj.high_mark = self.low_mark, self.high_mark
obj.distinct = self.distinct
obj.distinct_fields = self.distinct_fields[:]
obj.select_for_update = self.select_for_update
obj.select_for_update_nowait = self.select_for_update_nowait
obj.select_for_update_skip_locked = self.select_for_update_skip_locked
obj.select_related = self.select_related
obj.values_select = self.values_select[:]
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.max_depth = self.max_depth
obj.combinator = self.combinator
obj.combinator_all = self.combinator_all
obj.combined_queries = self.combined_queries
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()
obj.extra_tables = self.extra_tables
obj.extra_order_by = self.extra_order_by
obj.deferred_loading = copy.copy(self.deferred_loading[0]), self.deferred_loading[1]
if self.filter_is_sticky and self.used_aliases:
obj.used_aliases = self.used_aliases.copy()
obj.used_aliases = set()
obj.filter_is_sticky = False
obj.subquery = self.subquery
if 'alias_prefix' in self.__dict__:
obj.alias_prefix = self.alias_prefix
if 'subq_aliases' in self.__dict__:
obj.subq_aliases = self.subq_aliases.copy()
if hasattr(obj, '_setup_query'):
obj.context = self.context.copy()
return obj
def add_context(self, key, value):
self.context[key] = value
def get_context(self, key, default=None):
return self.context.get(key, default)
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):
Returns 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, then those operations must be
# done in a subquery so that we are aggregating on the limit and/or
# distinct results instead of applying the distinct and limit after the
# aggregation.
if (isinstance(self.group_by, list) or has_limit or has_existing_annotations or
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.tables}
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 for q in outer_query.annotation_select.items()]
converters = compiler.get_converters(outer_query.annotation_select.values())
result = compiler.apply_converters(result, converters)
return {
alias: val
for (alias, annotation), val
in zip(outer_query.annotation_select.items(), result)
def get_count(self, using):
Performs 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.tables)
# 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).
for alias in rhs.tables[1:]:
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'. = []
for col in
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[:] if rhs.order_by else self.order_by
self.extra_order_by = rhs.extra_order_by or self.extra_order_by
def deferred_to_data(self, target, callback):
Converts 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
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.fields:
if field 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():
if model not in seen:
seen[model] = set()
for model, values in seen.items():
callback(target, model, values)
def table_alias(self, table_name, create=False):
Returns 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 = table_name
self.table_map[alias] = [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):
Promotes recursively the join type of given aliases and its children to
an outer join. If 'unconditional' is False, the join is only promoted 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.keys()
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):
This method will reset reference counts for aliases so that they match
the value passed in :param 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):
Changes 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.keys()).intersection(set(change_map.values())) == set()
# 1. Update references in "select" (normal columns plus aliases),
# "group by" and "where".
if isinstance(self.group_by, list):
self.group_by = [col.relabeled_clone(change_map) for col in self.group_by] = [col.relabeled_clone(change_map) for col in]
if self._annotations:
self._annotations = 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):
Changes 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():
Generates 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.tables):
new_alias = '%s%d' % (self.alias_prefix, pos)
change_map[alias] = new_alias
self.tables[pos] = new_alias
def get_initial_alias(self):
Returns the first alias for this query, after increasing its reference
if self.tables:
alias = self.tables[0]
alias = self.join(BaseTable(self.get_meta().db_table, None))
return alias
def count_active_tables(self):
Returns the number of tables in this query with a non-zero reference
count. Note that 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):
Returns an alias for the join in 'connection', either reusing an
existing alias for that join or creating a new one. 'connection' is a
tuple (lhs, table, join_cols) where 'lhs' is either an existing
table alias or a table name. 'join_cols' is a tuple of tuples containing
columns to join on ((l_id1, r_id1), (l_id2, r_id2)). The join corresponds
to the SQL equivalent of::
lhs.l_id1 = table.r_id1 AND lhs.l_id2 = table.r_id2
The 'reuse' parameter can be either None which means all joins
(matching the connection) are reusable, or it can be a set containing
the aliases that can be reused.
A join is always created as LOUTER if the lhs alias is LOUTER to make
sure we do not generate chains like t1 LOUTER t2 INNER t3. All new
joins are created as LOUTER if nullable is True.
If 'nullable' is True, the join can potentially involve NULL values and
is a candidate for promotion (to "left outer") when combining querysets.
The 'join_field' is the field we are joining along (if any).
reuse = [a for a, j in self.alias_map.items()
if (reuse is None or a in reuse) and j == join]
if reuse:
return reuse[0]
# No reuse is possible, so we need a new alias.
alias, _ = self.table_alias(join.table_name, create=True)
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):
Makes 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)
_, _, _, joins, _ = self.setup_joins(
[], curr_opts, alias)
curr_opts = int_model._meta
alias = seen[int_model] = joins[-1]
return alias or seen[None]
def add_annotation(self, annotation, alias, is_summary=False):
Adds a single annotation expression to the Query
annotation = annotation.resolve_expression(self, allow_joins=True, reuse=None,
self.annotations[alias] = annotation
def _prepare_as_filter_value(self):
return self.clone()
def prepare_lookup_value(self, value, lookups, can_reuse, allow_joins=True):
# Default lookup if none given is exact.
used_joins = []
if len(lookups) == 0:
lookups = ['exact']
# Interpret '__exact=None' as the sql 'is NULL'; otherwise, reject all
# uses of None as a query value.
if value is None:
if lookups[-1] not in ('exact', 'iexact'):
raise ValueError("Cannot use None as a query value")
return True, ['isnull'], used_joins
elif hasattr(value, 'resolve_expression'):
pre_joins = self.alias_refcount.copy()
value = value.resolve_expression(self, reuse=can_reuse, allow_joins=allow_joins)
used_joins = [k for k, v in self.alias_refcount.items() if v > pre_joins.get(k, 0)]
elif isinstance(value, (list, tuple)):
# The items of the iterable may be expressions and therefore need
# to be resolved independently.
processed_values = []
used_joins = set()
for sub_value in value:
if hasattr(sub_value, 'resolve_expression'):
pre_joins = self.alias_refcount.copy()
sub_value.resolve_expression(self, reuse=can_reuse, allow_joins=allow_joins)
# The used_joins for a tuple of expressions is the union of
# the used_joins for the individual expressions.
used_joins |= set(k for k, v in self.alias_refcount.items() if v > pre_joins.get(k, 0))
# Subqueries need to use a different set of aliases than the
# outer query. Call bump_prefix to change aliases of the inner
# query (the value).
if hasattr(value, '_prepare_as_filter_value'):
value = value._prepare_as_filter_value()
# For Oracle '' is equivalent to null. The check needs to be done
# at this stage because join promotion can't be done at compiler
# stage. Using DEFAULT_DB_ALIAS isn't nice, but it is the best we
# can do here. Similar thing is done in is_nullable(), too.
if (connections[DEFAULT_DB_ALIAS].features.interprets_empty_strings_as_nulls and
lookups[-1] == 'exact' and value == ''):
value = True
lookups[-1] = 'isnull'
return value, lookups, used_joins
def solve_lookup_type(self, lookup):
Solve the lookup type from the lookup (eg: '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) == 0:
lookup_parts = ['exact']
elif len(lookup_parts) > 1:
if 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):
Checks whether the object passed while querying is of the correct type.
If not, it raises 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):
Checks 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 _forced_pk isn't set, this isn't a queryset query or values()
# or values_list() was specified by the developer in which case
# that choice is trusted.
if (getattr(value, '_forced_pk', False) 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):
Tries 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().
lookups = lookups[:]
while lookups:
name = lookups[0]
# If there is just one part left, try first get_lookup() so
# that if the lhs supports both transform and lookup for the
# name, then lookup will be picked.
if len(lookups) == 1:
final_lookup = lhs.get_lookup(name)
if not final_lookup:
# We didn't find a lookup. We are going to interpret
# the name as transform, and do an Exact lookup against
# it.
lhs = self.try_transform(lhs, name, lookups)
final_lookup = lhs.get_lookup('exact')
return final_lookup(lhs, rhs)
lhs = self.try_transform(lhs, name, lookups)
lookups = lookups[1:]
def try_transform(self, lhs, name, rest_of_lookups):
Helper method for build_lookup. Tries 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, connector=AND, allow_joins=True, split_subq=True):
Builds a WhereNode for a single filter clause, but doesn'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_netageted 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.
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 allow_joins and len(parts) > 1:
raise FieldError("Joined field references are not permitted in this query")
# Work out the lookup type and remove it from the end of 'parts',
# if necessary.
value, lookups, used_joins = self.prepare_lookup_value(value, lookups, can_reuse, allow_joins)
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
field, sources, opts, join_list, path = 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(field, value, opts)
# split_exclude() needs to know which joins were generated for the
# lookup parts
self._lookup_joins = join_list
except MultiJoin as e:
return self.split_exclude(filter_expr, LOOKUP_SEP.join(parts[:e.level]),
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.
used_joins = set(used_joins).union(set(join_list))
targets, alias, join_list = self.trim_joins(sources, join_list, path)
if can_reuse is not None:
if 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]))
assert num_lookups > 0 # Likely a bug in Django if this fails.
lookup_class = field.get_lookup(lookups[0])
if lookup_class is None:
raise FieldError('Related Field got invalid lookup: {}'.format(lookups[0]))
if len(targets) == 1:
lhs = targets[0].get_col(alias, field)
lhs = MultiColSource(alias, targets, sources, field)
condition = lookup_class(lhs, value)
lookup_type = lookup_class.lookup_name
col = targets[0].get_col(alias, field)
condition = self.build_lookup(lookups, col, value)
lookup_type = condition.lookup_name
clause.add(condition, AND)
require_outer = lookup_type == 'isnull' and value is True and not current_negated
if current_negated and (lookup_type != 'isnull' or value 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, sources[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 = set(
(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):
Adds 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, connector=connector,
allow_joins=allow_joins, split_subq=split_subq,
if child_clause:
target_clause.add(child_clause, connector)
needed_inner = joinpromoter.update_join_types(self)
return target_clause, needed_inner
def names_to_path(self, names, opts, allow_many=True, fail_on_missing=False):
Walks the list of names and turns them into PathInfo tuples. Note that
a single name in 'names' can generate multiple PathInfos (m2m for
'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.
Returns a list of PathInfo tuples. In addition returns 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, the method returns
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
field = opts.get_field(name)
except FieldDoesNotExist:
if name in self.annotation_select:
field = self.annotation_select[name].output_field
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()
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().
If 'allow_many' is False, then any reverse foreign key seen will
generate a MultiJoin exception.
Returns the final field involved in the joins, the target field (used
for any 'where' constraint), the final 'opts' value, the joins and the
field path travelled to generate the joins.
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]
# First, generate the path for the names
path, final_field, targets, rest = self.names_to_path(
names, opts, allow_many, fail_on_missing=True)
# 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:
opts = join.to_opts
nullable = self.is_nullable(join.join_field)
nullable = True
connection = Join(opts.db_table, alias, None, INNER, join.join_field, nullable)
reuse = can_reuse if join.m2m else None
alias = self.join(connection, reuse=reuse)
return final_field, targets, opts, joins, path
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.
Returns the final target field and table alias and the new active
We will always trim any direct join if we have the target column
available already in the previous table. Reverse joins can't be
trimmed as we don't know if there is anything on the other side of
the join.
joins = joins[:]
for pos, info in enumerate(reversed(path)):
if len(joins) == 1 or not
join_targets = set(t.column for t in info.join_field.foreign_related_fields)
cur_targets = set(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.annotation_select[name]
field_list = name.split(LOOKUP_SEP)
field, sources, opts, join_list, path = self.setup_joins(
field_list, self.get_meta(),
self.get_initial_alias(), reuse)
targets, _, join_list = self.trim_joins(sources, join_list, 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], sources[0])
return col
def split_exclude(self, filter_expr, prefix, 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.
As an example we could have original filter ~Q(child__name='foo').
We would get here with filter_expr = child__name, prefix = child 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):
Adjusts the limits on the rows retrieved. We use low/high to set these,
as it makes it more Pythonic to read and write. When the SQL query is
created, they are converted to the appropriate offset and limit values.
Any limits passed in here are applied relative to the existing
constraints. So low is added to the current low value and both will be
clamped 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):
Clears any existing limits.
self.low_mark, self.high_mark = 0, None
def can_filter(self):
Returns 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):
Removes all fields from SELECT clause.
""" = []
self.default_cols = False
self.select_related = False
def clear_select_fields(self):
Clears 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 add_select(self, col):
self.default_cols = False
def set_select(self, cols):
self.default_cols = False = cols
def add_distinct_fields(self, *field_names):
Adds and resolves 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):
Adds the given (model) fields to the select set. The field names are
added in the order specified.
alias = self.get_initial_alias()
opts = self.get_meta()
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.
_, targets, _, joins, path = self.setup_joins(
name.split(LOOKUP_SEP), opts, alias, allow_many=allow_m2m)
targets, final_alias, joins = self.trim_joins(targets, joins, path)
for target in targets:
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))
raise FieldError("Cannot resolve keyword %r into field. "
"Choices are: %s" % (name, ", ".join(names)))
def add_ordering(self, *ordering):
Adds 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, all ordering is cleared 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.default_ordering = False
def clear_ordering(self, force_empty):
Removes 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):
Expands 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.
self.group_by = []
for col in
if self.annotation_select:
for alias, annotation in self.annotation_select.items():
for col in annotation.get_group_by_cols():
def add_select_related(self, fields):
Sets 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):
Adds 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 = (set(), 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. The new field names are added 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, those
names are removed 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 = field_names, False
def get_loaded_field_names(self):
If any fields are marked to be deferred, returns 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, returns 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 actually 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,
we don't actually remove them from the Query since they might be used
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 = field_names
self.add_fields(field_names, True)
def annotation_select(self):
"""The OrderedDict of aggregate columns that are not masked, and should
be used in the SELECT clause.
This result is cached for optimization purposes.
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):
Trims 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 sets 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().
Returns a lookup usable for doing outerq.filter(lookup=self). Returns
also 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.tables if t in self._lookup_joins or t == self.tables[0]]
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.tables:
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):
A helper to 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.
if connections[DEFAULT_DB_ALIAS].features.interprets_empty_strings_as_nulls and field.empty_strings_allowed:
return True
return field.null
def as_subquery_filter(self, db):
self._db = db
self.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 self
def get_order_dir(field, default='ASC'):
Returns 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):
A helper function to add "value" to the set of values for "key", whether or
not "key" already exists.
if key in data:
data[key] = {value}
def is_reverse_o2o(field):
A little helper to 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