import importlib from inspect import signature import itertools import random from sqlalchemy import and_ from sqlalchemy import Boolean from sqlalchemy import case from sqlalchemy import cast from sqlalchemy import Column from sqlalchemy import column from sqlalchemy import dialects from sqlalchemy import exists from sqlalchemy import extract from sqlalchemy import Float from sqlalchemy import Integer from sqlalchemy import literal from sqlalchemy import literal_column from sqlalchemy import MetaData from sqlalchemy import or_ from sqlalchemy import PickleType from sqlalchemy import select from sqlalchemy import String from sqlalchemy import Table from sqlalchemy import table from sqlalchemy import testing from sqlalchemy import text from sqlalchemy import tuple_ from sqlalchemy import TypeDecorator from sqlalchemy import union from sqlalchemy import union_all from sqlalchemy import values from sqlalchemy.dialects import mysql from sqlalchemy.dialects import postgresql from sqlalchemy.schema import Sequence from sqlalchemy.sql import bindparam from sqlalchemy.sql import ColumnElement from sqlalchemy.sql import dml from sqlalchemy.sql import False_ from sqlalchemy.sql import func from sqlalchemy.sql import operators from sqlalchemy.sql import roles from sqlalchemy.sql import True_ from sqlalchemy.sql import type_coerce from sqlalchemy.sql import visitors from sqlalchemy.sql.annotation import Annotated from sqlalchemy.sql.base import HasCacheKey from sqlalchemy.sql.base import SingletonConstant from sqlalchemy.sql.elements import _label_reference from sqlalchemy.sql.elements import _textual_label_reference from sqlalchemy.sql.elements import BindParameter from sqlalchemy.sql.elements import ClauseElement from sqlalchemy.sql.elements import ClauseList from sqlalchemy.sql.elements import CollationClause from sqlalchemy.sql.elements import Immutable from sqlalchemy.sql.elements import Null from sqlalchemy.sql.elements import Slice from sqlalchemy.sql.elements import UnaryExpression from sqlalchemy.sql.functions import FunctionElement from sqlalchemy.sql.functions import GenericFunction from sqlalchemy.sql.functions import ReturnTypeFromArgs from sqlalchemy.sql.lambdas import lambda_stmt from sqlalchemy.sql.lambdas import LambdaElement from sqlalchemy.sql.lambdas import LambdaOptions from sqlalchemy.sql.selectable import _OffsetLimitParam from sqlalchemy.sql.selectable import FromGrouping from sqlalchemy.sql.selectable import LABEL_STYLE_NONE from sqlalchemy.sql.selectable import LABEL_STYLE_TABLENAME_PLUS_COL from sqlalchemy.sql.selectable import NoInit from sqlalchemy.sql.selectable import Select from sqlalchemy.sql.selectable import Selectable from sqlalchemy.sql.selectable import SelectStatementGrouping from sqlalchemy.sql.type_api import UserDefinedType from sqlalchemy.sql.visitors import InternalTraversal from sqlalchemy.testing import eq_ from sqlalchemy.testing import fixtures from sqlalchemy.testing import is_ from sqlalchemy.testing import is_false from sqlalchemy.testing import is_not from sqlalchemy.testing import is_true from sqlalchemy.testing import ne_ from sqlalchemy.testing.assertions import expect_warnings from sqlalchemy.testing.util import random_choices from sqlalchemy.types import ARRAY from sqlalchemy.types import JSON from sqlalchemy.util import class_hierarchy meta = MetaData() meta2 = MetaData() table_a = Table("a", meta, Column("a", Integer), Column("b", String)) table_b_like_a = Table("b2", meta, Column("a", Integer), Column("b", String)) table_a_2 = Table("a", meta2, Column("a", Integer), Column("b", String)) table_a_2_fs = Table( "a", meta2, Column("a", Integer), Column("b", String), schema="fs" ) table_a_2_bs = Table( "a", meta2, Column("a", Integer), Column("b", String), schema="bs" ) table_b = Table("b", meta, Column("a", Integer), Column("b", Integer)) table_b_b = Table( "b_b", meta, Column("a", Integer), Column("b", Integer), Column("c", Integer), Column("d", Integer), Column("e", Integer), ) table_c = Table("c", meta, Column("x", Integer), Column("y", Integer)) table_d = Table("d", meta, Column("y", Integer), Column("z", Integer)) def opt1(ctx): pass def opt2(ctx): pass def opt3(ctx): pass class MyEntity(HasCacheKey): def __init__(self, name, element): self.name = name self.element = element _cache_key_traversal = [ ("name", InternalTraversal.dp_string), ("element", InternalTraversal.dp_clauseelement), ] class Foo: x = 10 y = 15 dml.Insert.argument_for("sqlite", "foo", None) dml.Update.argument_for("sqlite", "foo", None) dml.Delete.argument_for("sqlite", "foo", None) class MyType1(TypeDecorator): cache_ok = True impl = String class MyType2(TypeDecorator): cache_ok = True impl = Integer class MyType3(TypeDecorator): impl = Integer cache_ok = True def __init__(self, arg): self.arg = arg class CoreFixtures: # lambdas which return a tuple of ColumnElement objects. # must return at least two objects that should compare differently. # to test more varieties of "difference" additional objects can be added. fixtures = [ lambda: ( column("q"), column("x"), column("q", Integer), column("q", String), ), lambda: (~column("q", Boolean), ~column("p", Boolean)), lambda: ( table_a.c.a.label("foo"), table_a.c.a.label("bar"), table_a.c.b.label("foo"), ), lambda: ( _label_reference(table_a.c.a.desc()), _label_reference(table_a.c.a.asc()), ), lambda: (_textual_label_reference("a"), _textual_label_reference("b")), lambda: ( text("select a, b from table").columns(a=Integer, b=String), text("select a, b, c from table").columns( a=Integer, b=String, c=Integer ), text("select a, b, c from table where foo=:bar").bindparams( bindparam("bar", type_=Integer) ), text("select a, b, c from table where foo=:foo").bindparams( bindparam("foo", type_=Integer) ), text("select a, b, c from table where foo=:bar").bindparams( bindparam("bar", type_=String) ), ), lambda: ( # test #11471 text("select * from table") .columns(a=Integer()) .add_cte(table_b.select().cte()), text("select * from table") .columns(a=Integer()) .add_cte(table_b.select().where(table_b.c.a > 5).cte()), ), lambda: ( union( select(table_a).where(table_a.c.a > 1), select(table_a).where(table_a.c.a < 1), ).add_cte(select(table_b).where(table_b.c.a > 1).cte("ttt")), union( select(table_a).where(table_a.c.a > 1), select(table_a).where(table_a.c.a < 1), ).add_cte(select(table_b).where(table_b.c.a < 1).cte("ttt")), union( select(table_a).where(table_a.c.a > 1), select(table_a).where(table_a.c.a < 1), ) .add_cte(select(table_b).where(table_b.c.a > 1).cte("ttt")) ._annotate({"foo": "bar"}), ), lambda: ( union( select(table_a).where(table_a.c.a > 1), select(table_a).where(table_a.c.a < 1), ).self_group(), union( select(table_a).where(table_a.c.a > 1), select(table_a).where(table_a.c.a < 1), ) .self_group() ._annotate({"foo": "bar"}), ), lambda: ( literal(1).op("+")(literal(1)), literal(1).op("-")(literal(1)), column("q").op("-")(literal(1)), UnaryExpression(table_a.c.b, modifier=operators.neg), UnaryExpression(table_a.c.b, modifier=operators.desc_op), UnaryExpression(table_a.c.b, modifier=operators.custom_op("!")), UnaryExpression(table_a.c.b, modifier=operators.custom_op("~")), ), lambda: ( column("q") == column("x"), column("q") == column("y"), column("z") == column("x"), (column("z") == column("x")).self_group(), (column("q") == column("x")).self_group(), column("z") + column("x"), column("z").op("foo")(column("x")), column("z").op("foo")(literal(1)), column("z").op("bar")(column("x")), column("z") - column("x"), column("x") - column("z"), column("z") > column("x"), column("x").in_([5, 7]), column("x").in_([10, 7, 8]), # note these two are mathematically equivalent but for now they # are considered to be different column("z") >= column("x"), column("x") <= column("z"), column("q").between(5, 6), column("q").between(5, 6, symmetric=True), column("q").like("somstr"), column("q").like("somstr", escape="\\"), column("q").like("somstr", escape="X"), ), lambda: ( column("q").regexp_match("y", flags="ig"), column("q").regexp_match("y", flags="q"), column("q").regexp_match("y"), column("q").regexp_replace("y", "z", flags="ig"), column("q").regexp_replace("y", "z", flags="q"), column("q").regexp_replace("y", "z"), ), lambda: ( column("q", ARRAY(Integer))[3] == 5, column("q", ARRAY(Integer))[3:5] == 5, ), lambda: ( table_a.c.a, table_a.c.a._annotate({"orm": True}), table_a.c.a._annotate({"orm": True})._annotate({"bar": False}), table_a.c.a._annotate( {"orm": True, "parententity": MyEntity("a", table_a)} ), table_a.c.a._annotate( {"orm": True, "parententity": MyEntity("b", table_a)} ), table_a.c.a._annotate( {"orm": True, "parententity": MyEntity("b", select(table_a))} ), table_a.c.a._annotate( { "orm": True, "parententity": MyEntity( "b", select(table_a).where(table_a.c.a == 5) ), } ), ), lambda: ( table_a, table_a._annotate({"orm": True}), table_a._annotate({"orm": True})._annotate({"bar": False}), table_a._annotate( {"orm": True, "parententity": MyEntity("a", table_a)} ), table_a._annotate( {"orm": True, "parententity": MyEntity("b", table_a)} ), table_a._annotate( {"orm": True, "parententity": MyEntity("b", select(table_a))} ), ), lambda: ( table("a", column("x"), column("y")), table("a", column("x"), column("y"), schema="q"), table("a", column("x"), column("y"), schema="y"), table("a", column("x"), column("y"))._annotate({"orm": True}), table("b", column("x"), column("y"))._annotate({"orm": True}), ), lambda: ( cast(column("q"), Integer), cast(column("q"), Float), cast(column("p"), Integer), ), lambda: ( column("x", JSON)["key1"], column("x", JSON)["key1"].as_boolean(), column("x", JSON)["key1"].as_float(), column("x", JSON)["key1"].as_integer(), column("x", JSON)["key1"].as_string(), column("y", JSON)["key1"].as_integer(), column("y", JSON)["key1"].as_string(), ), lambda: ( bindparam("x"), bindparam("x", literal_execute=True), bindparam("y"), bindparam("x", type_=Integer), bindparam("x", type_=String), bindparam(None), ), lambda: (_OffsetLimitParam("x"), _OffsetLimitParam("y")), lambda: (func.foo(), func.foo(5), func.bar()), lambda: ( func.package1.foo(5), func.package2.foo(5), func.packge1.bar(5), func.foo(), ), lambda: (func.current_date(), func.current_time()), lambda: ( func.next_value(Sequence("q")), func.next_value(Sequence("p")), ), lambda: ( func.json_to_recordset("{foo}"), func.json_to_recordset("{foo}").table_valued("a", "b"), func.jsonb_to_recordset("{foo}").table_valued("a", "b"), func.json_to_recordset("{foo}") .table_valued("a", "b") .render_derived(), func.json_to_recordset("{foo}") .table_valued("a", with_ordinality="b") .render_derived(), func.json_to_recordset("{foo}") .table_valued("a", with_ordinality="c") .render_derived(), func.json_to_recordset("{foo}") .table_valued(column("a", Integer), column("b", String)) .render_derived(), func.json_to_recordset("{foo}") .table_valued(column("a", Integer), column("b", String)) .render_derived(with_types=True), func.json_to_recordset("{foo}") .table_valued("b", "c") .render_derived(), func.json_to_recordset("{foo}") .table_valued("a", "b") .alias("foo") .render_derived(with_types=True), func.json_to_recordset("{foo}") .table_valued("a", "b") .alias("foo"), func.json_to_recordset("{foo}").column_valued(), func.json_to_recordset("{foo}").scalar_table_valued("foo"), ), lambda: (table_a.table_valued(), table_b.table_valued()), lambda: (True_(), False_()), lambda: (Null(),), lambda: (ReturnTypeFromArgs("foo"), ReturnTypeFromArgs(5)), lambda: (FunctionElement(5), FunctionElement(5, 6)), lambda: (func.count(), func.not_count()), lambda: (func.char_length("abc"), func.char_length("def")), lambda: (GenericFunction("a", "b"), GenericFunction("a")), lambda: (CollationClause("foobar"), CollationClause("batbar")), lambda: ( type_coerce(column("q", Integer), String), type_coerce(column("q", Integer), Float), type_coerce(column("z", Integer), Float), ), lambda: (table_a.c.a, table_b.c.a), lambda: (tuple_(1, 2), tuple_(3, 4)), lambda: (func.array_agg([1, 2]), func.array_agg([3, 4])), lambda: ( func.aggregate_strings(table_a.c.b, ","), func.aggregate_strings(table_b_like_a.c.b, ","), ), lambda: ( func.percentile_cont(0.5).within_group(table_a.c.a), func.percentile_cont(0.5).within_group(table_a.c.b), func.percentile_cont(0.5).within_group(table_a.c.a, table_a.c.b), func.percentile_cont(0.5).within_group( table_a.c.a, table_a.c.b, column("q") ), ), lambda: ( func.is_equal("a", "b").as_comparison(1, 2), func.is_equal("a", "c").as_comparison(1, 2), func.is_equal("a", "b").as_comparison(2, 1), func.is_equal("a", "b", "c").as_comparison(1, 2), func.foobar("a", "b").as_comparison(1, 2), ), lambda: ( func.row_number().over(order_by=table_a.c.a), func.row_number().over(order_by=table_a.c.a, range_=(0, 10)), func.row_number().over(order_by=table_a.c.a, range_=(None, 10)), func.row_number().over(order_by=table_a.c.a, rows=(None, 20)), func.row_number().over(order_by=table_a.c.a, groups=(None, 20)), func.row_number().over(order_by=table_a.c.b), func.row_number().over( order_by=table_a.c.a, partition_by=table_a.c.b ), ), lambda: ( func.count(1).filter(table_a.c.a == 5), func.count(1).filter(table_a.c.a == 10), func.foob(1).filter(table_a.c.a == 10), ), lambda: ( and_(table_a.c.a == 5, table_a.c.b == table_b.c.a), and_(table_a.c.a == 5, table_a.c.a == table_b.c.a), or_(table_a.c.a == 5, table_a.c.b == table_b.c.a), ClauseList(table_a.c.a == 5, table_a.c.b == table_b.c.a), ClauseList(table_a.c.a == 5, table_a.c.b == table_a.c.a), ), lambda: ( case((table_a.c.a == 5, 10), (table_a.c.a == 10, 20)), case((table_a.c.a == 18, 10), (table_a.c.a == 10, 20)), case((table_a.c.a == 5, 10), (table_a.c.b == 10, 20)), case( (table_a.c.a == 5, 10), (table_a.c.b == 10, 20), (table_a.c.a == 9, 12), ), case( (table_a.c.a == 5, 10), (table_a.c.a == 10, 20), else_=30, ), case({"wendy": "W", "jack": "J"}, value=table_a.c.a, else_="E"), case({"wendy": "W", "jack": "J"}, value=table_a.c.b, else_="E"), case({"wendy_w": "W", "jack": "J"}, value=table_a.c.a, else_="E"), ), lambda: ( extract("foo", table_a.c.a), extract("foo", table_a.c.b), extract("bar", table_a.c.a), ), lambda: ( Slice(1, 2, 5), Slice(1, 5, 5), Slice(1, 5, 10), Slice(2, 10, 15), ), lambda: ( select(table_a.c.a), select(table_a.c.a, table_a.c.b), select(table_a.c.b, table_a.c.a), select(table_a.c.b, table_a.c.a).limit(5), select(table_a.c.b, table_a.c.a).limit(5).offset(10), select(table_a.c.b, table_a.c.a) .limit(literal_column("foobar")) .offset(10), select(table_a.c.b, table_a.c.a).set_label_style( LABEL_STYLE_TABLENAME_PLUS_COL ), select(table_a.c.b, table_a.c.a).set_label_style(LABEL_STYLE_NONE), select(table_a.c.a).where(table_a.c.b == 5), select(table_a.c.a) .where(table_a.c.b == 5) .where(table_a.c.a == 10), select(table_a.c.a).where(table_a.c.b == 5).with_for_update(), select(table_a.c.a) .where(table_a.c.b == 5) .with_for_update(nowait=True), select(table_a.c.a) .where(table_a.c.b == 5) .with_for_update(nowait=True, skip_locked=True), select(table_a.c.a) .where(table_a.c.b == 5) .with_for_update(nowait=True, read=True), select(table_a.c.a) .where(table_a.c.b == 5) .with_for_update(of=table_a.c.a), select(table_a.c.a) .where(table_a.c.b == 5) .with_for_update(of=table_a.c.b), select(table_a.c.a) .where(table_a.c.b == 5) .with_for_update(nowait=True, key_share=True), select(table_a.c.a).where(table_a.c.b == 5).correlate(table_b), select(table_a.c.a) .where(table_a.c.b == 5) .correlate_except(table_b), ), lambda: ( select(table_a.c.a), select(table_a.c.a).limit(2), select(table_a.c.a).limit(3), select(table_a.c.a).fetch(3), select(table_a.c.a).fetch(2), select(table_a.c.a).fetch(2, percent=True), select(table_a.c.a).fetch(2, with_ties=True), select(table_a.c.a).fetch(2, with_ties=True, percent=True), select(table_a.c.a).fetch(2).offset(3), select(table_a.c.a).fetch(2).offset(5), select(table_a.c.a).limit(2).offset(5), select(table_a.c.a).limit(2).offset(3), select(table_a.c.a).union(select(table_a.c.a)).limit(2).offset(3), union(select(table_a.c.a), select(table_a.c.b)).limit(2).offset(3), union(select(table_a.c.a), select(table_a.c.b)).limit(6).offset(3), union(select(table_a.c.a), select(table_a.c.b)).limit(6).offset(8), union(select(table_a.c.a), select(table_a.c.b)).fetch(2).offset(8), union(select(table_a.c.a), select(table_a.c.b)).fetch(6).offset(8), union(select(table_a.c.a), select(table_a.c.b)).fetch(6).offset(3), union(select(table_a.c.a), select(table_a.c.b)) .fetch(6, percent=True) .offset(3), union(select(table_a.c.a), select(table_a.c.b)) .fetch(6, with_ties=True) .offset(3), union(select(table_a.c.a), select(table_a.c.b)) .fetch(6, with_ties=True, percent=True) .offset(3), union(select(table_a.c.a), select(table_a.c.b)).limit(6), union(select(table_a.c.a), select(table_a.c.b)).offset(6), ), lambda: ( select(table_a.c.a), select(table_a.c.a).join(table_b, table_a.c.a == table_b.c.a), select(table_a.c.a).join_from( table_a, table_b, table_a.c.a == table_b.c.a ), select(table_a.c.a).join_from(table_a, table_b), select(table_a.c.a).join_from(table_c, table_b), select(table_a.c.a) .join(table_b, table_a.c.a == table_b.c.a) .join(table_c, table_b.c.b == table_c.c.x), select(table_a.c.a).join(table_b), select(table_a.c.a).join(table_c), select(table_a.c.a).join(table_b, table_a.c.a == table_b.c.b), select(table_a.c.a).join(table_c, table_a.c.a == table_c.c.x), ), lambda: ( select(table_a.c.a), select(table_a.c.a).add_cte(table_b.insert().cte()), table_a.insert(), table_a.delete(), table_a.update(), table_a.insert().add_cte(table_b.insert().cte()), table_a.delete().add_cte(table_b.insert().cte()), table_a.update().add_cte(table_b.insert().cte()), ), lambda: ( select(table_a.c.a).cte(), select(table_a.c.a).cte(nesting=True), select(table_a.c.a).cte(recursive=True), select(table_a.c.a).cte(name="some_cte", recursive=True), select(table_a.c.a).cte(name="some_cte"), select(table_a.c.a).cte(name="some_cte").alias("other_cte"), select(table_a.c.a) .cte(name="some_cte") .union_all(select(table_a.c.a)), select(table_a.c.a) .cte(name="some_cte") .union_all(select(table_a.c.b)), select(table_a.c.a).lateral(), select(table_a.c.a).lateral(name="bar"), table_a.tablesample(0.75), table_a.tablesample(func.bernoulli(1)), table_a.tablesample(func.bernoulli(1), seed=func.random()), table_a.tablesample(func.bernoulli(1), seed=func.other_random()), table_a.tablesample(func.hoho(1)), table_a.tablesample(func.bernoulli(1), name="bar"), table_a.tablesample( func.bernoulli(1), name="bar", seed=func.random() ), ), lambda: ( # test issue #6503 # join from table_a -> table_c, select table_b.c.a select(table_a).join(table_c).with_only_columns(table_b.c.a), # join from table_b -> table_c, select table_b.c.a select(table_b.c.a).join(table_c).with_only_columns(table_b.c.a), select(table_a).with_only_columns(table_b.c.a), ), lambda: ( table_a.insert(), table_a.insert().return_defaults(), table_a.insert().return_defaults(table_a.c.a), table_a.insert().return_defaults(table_a.c.b), table_a.insert().values({})._annotate({"nocache": True}), table_b.insert(), table_b.insert().with_dialect_options(sqlite_foo="some value"), table_b.insert().from_select(["a", "b"], select(table_a)), table_b.insert().from_select( ["a", "b"], select(table_a).where(table_a.c.a > 5) ), table_b.insert().from_select(["a", "b"], select(table_b)), table_b.insert().from_select(["c", "d"], select(table_a)), table_b.insert().returning(table_b.c.a), table_b.insert().returning(table_b.c.a, table_b.c.b), table_b.insert().inline(), table_b.insert().prefix_with("foo"), table_b.insert().with_hint("RUNFAST"), table_b.insert().values(a=5, b=10), table_b.insert().values(a=5), table_b.insert() .values({table_b.c.a: 5, "b": 10}) ._annotate({"nocache": True}), table_b.insert().values(a=7, b=10), table_b.insert().values(a=5, b=10).inline(), table_b.insert() .values([{"a": 5, "b": 10}, {"a": 8, "b": 12}]) ._annotate({"nocache": True}), table_b.insert() .values([{"a": 9, "b": 10}, {"a": 8, "b": 7}]) ._annotate({"nocache": True}), table_b.insert() .values([(5, 10), (8, 12)]) ._annotate({"nocache": True}), table_b.insert() .values([(5, 9), (5, 12)]) ._annotate({"nocache": True}), ), lambda: ( table_b.update(), table_b.update().return_defaults(), table_b.update().return_defaults(table_b.c.a), table_b.update().return_defaults(table_b.c.b), table_b.update().where(table_b.c.a == 5), table_b.update().where(table_b.c.b == 5), table_b.update() .where(table_b.c.b == 5) .with_dialect_options(mysql_limit=10), table_b.update() .where(table_b.c.b == 5) .with_dialect_options(mysql_limit=10, sqlite_foo="some value"), table_b.update().where(table_b.c.a == 5).values(a=5, b=10), table_b.update().where(table_b.c.a == 5).values(a=5, b=10, c=12), table_b.update() .where(table_b.c.b == 5) .values(a=5, b=10) ._annotate({"nocache": True}), table_b.update().values(a=5, b=10), table_b.update() .values({"a": 5, table_b.c.b: 10}) ._annotate({"nocache": True}), table_b.update().values(a=7, b=10), table_b.update().ordered_values(("a", 5), ("b", 10)), table_b.update().ordered_values(("b", 10), ("a", 5)), table_b.update().ordered_values((table_b.c.a, 5), ("b", 10)), ), lambda: ( table_b.delete(), table_b.delete().with_dialect_options(sqlite_foo="some value"), table_b.delete().where(table_b.c.a == 5), table_b.delete().where(table_b.c.b == 5), ), lambda: ( values( column("mykey", Integer), column("mytext", String), column("myint", Integer), name="myvalues", ) .data([(1, "textA", 99), (2, "textB", 88)]) ._annotate({"nocache": True}), values( column("mykey", Integer), column("mytext", String), column("myint", Integer), name="myvalues", literal_binds=True, ) .data([(1, "textA", 99), (2, "textB", 88)]) ._annotate({"nocache": True}), values( column("mykey", Integer), column("mytext", String), column("myint", Integer), name="myothervalues", ) .data([(1, "textA", 99), (2, "textB", 88)]) ._annotate({"nocache": True}), values( column("mykey", Integer), column("mytext", String), column("myint", Integer), name="myvalues", ) .data([(1, "textA", 89), (2, "textG", 88)]) ._annotate({"nocache": True}), values( column("mykey", Integer), column("mynottext", String), column("myint", Integer), name="myvalues", ) .data([(1, "textA", 99), (2, "textB", 88)]) ._annotate({"nocache": True}), # TODO: difference in type # values( # column("mykey", Integer), # column("mytext", Text), # column("myint", Integer), # name="myvalues", # ) # .data([(1, "textA", 99), (2, "textB", 88)]) # ._annotate({"nocache": True}), ), lambda: ( values( column("mykey", Integer), column("mytext", String), column("myint", Integer), name="myvalues", ) .data([(1, "textA", 99), (2, "textB", 88)]) .scalar_values() ._annotate({"nocache": True}), values( column("mykey", Integer), column("mytext", String), column("myint", Integer), name="myvalues", literal_binds=True, ) .data([(1, "textA", 99), (2, "textB", 88)]) .scalar_values() ._annotate({"nocache": True}), values( column("mykey", Integer), column("mytext", String), column("myint", Integer), name="myvalues", ) .data([(1, "textA", 89), (2, "textG", 88)]) .scalar_values() ._annotate({"nocache": True}), values( column("mykey", Integer), column("mynottext", String), column("myint", Integer), name="myvalues", ) .data([(1, "textA", 99), (2, "textB", 88)]) .scalar_values() ._annotate({"nocache": True}), # TODO: difference in type # values( # column("mykey", Integer), # column("mytext", Text), # column("myint", Integer), # name="myvalues", # ) # .data([(1, "textA", 99), (2, "textB", 88)]) # .scalar_values() # ._annotate({"nocache": True}), ), lambda: ( select(table_a.c.a), select(table_a.c.a).prefix_with("foo"), select(table_a.c.a).prefix_with("foo", dialect="mysql"), select(table_a.c.a).prefix_with("foo", dialect="postgresql"), select(table_a.c.a).prefix_with("bar"), select(table_a.c.a).suffix_with("bar"), ), lambda: ( select(table_a_2.c.a), select(table_a_2_fs.c.a), select(table_a_2_bs.c.a), ), lambda: ( select(table_a.c.a), select(table_a.c.a).with_hint(None, "some hint"), select(table_a.c.a).with_hint(None, "some other hint"), select(table_a.c.a).with_hint(table_a, "some hint"), select(table_a.c.a) .with_hint(table_a, "some hint") .with_hint(None, "some other hint"), select(table_a.c.a).with_hint(table_a, "some other hint"), select(table_a.c.a).with_hint( table_a, "some hint", dialect_name="mysql" ), select(table_a.c.a).with_hint( table_a, "some hint", dialect_name="postgresql" ), ), lambda: ( table_a.join(table_b, table_a.c.a == table_b.c.a), table_a.join( table_b, and_(table_a.c.a == table_b.c.a, table_a.c.b == 1) ), table_a.outerjoin(table_b, table_a.c.a == table_b.c.a), ), lambda: ( table_a.alias("a"), table_a.alias("b"), table_a.alias(), table_b.alias("a"), select(table_a.c.a).alias("a"), ), lambda: ( FromGrouping(table_a.alias("a")), FromGrouping(table_a.alias("b")), ), lambda: ( SelectStatementGrouping(select(table_a)), SelectStatementGrouping(select(table_b)), ), lambda: ( select(table_a.c.a).scalar_subquery(), select(table_a.c.a).where(table_a.c.b == 5).scalar_subquery(), ), lambda: ( exists().where(table_a.c.a == 5), exists().where(table_a.c.b == 5), ), lambda: ( union(select(table_a.c.a), select(table_a.c.b)), union(select(table_a.c.a), select(table_a.c.b)).order_by("a"), union_all(select(table_a.c.a), select(table_a.c.b)), union(select(table_a.c.a)), union( select(table_a.c.a), select(table_a.c.b).where(table_a.c.b > 5), ), ), lambda: ( table("a", column("x"), column("y")), table("a", column("y"), column("x")), table("b", column("x"), column("y")), table("a", column("x"), column("y"), column("z")), table("a", column("x"), column("y", Integer)), table("a", column("q"), column("y", Integer)), ), lambda: (table_a, table_b), ] type_cache_key_fixtures = [ lambda: ( column("q") == column("x"), column("q") == column("y"), column("z") == column("x"), column("z", String(50)) == column("x", String(50)), column("z", String(50)) == column("x", String(30)), column("z", String(50)) == column("x", Integer), column("z", MyType1()) == column("x", MyType2()), column("z", MyType1()) == column("x", MyType3("x")), column("z", MyType1()) == column("x", MyType3("y")), ) ] dont_compare_values_fixtures = [ lambda: ( # note the in_(...) all have different column names because # otherwise all IN expressions would compare as equivalent column("x").in_(random_choices(range(10), k=3)), column("y").in_( bindparam( "q", # note that a different cache key is created if # the value given to the bindparam is [], as the type # cannot be inferred for the empty list but can # for the non-empty list as of #6222 random_choices(range(10), k=random.randint(1, 7)), expanding=True, ) ), column("y2").in_( bindparam( "q", # for typed param, empty and not empty param will have # the same type random_choices(range(10), k=random.randint(0, 7)), type_=Integer, expanding=True, ) ), # don't include empty for untyped, will create different cache # key column("z").in_(random_choices(range(10), k=random.randint(1, 7))), # empty is fine for typed, will create the same cache key column("z2", Integer).in_( random_choices(range(10), k=random.randint(0, 7)) ), column("x") == random.randint(0, 10), ) ] def _complex_fixtures(): def one(): a1 = table_a.alias() a2 = table_b_like_a.alias() stmt = ( select(table_a.c.a, a1.c.b, a2.c.b) .where(table_a.c.b == a1.c.b) .where(a1.c.b == a2.c.b) .where(a1.c.a == 5) ) return stmt def one_diff(): a1 = table_b_like_a.alias() a2 = table_a.alias() stmt = ( select(table_a.c.a, a1.c.b, a2.c.b) .where(table_a.c.b == a1.c.b) .where(a1.c.b == a2.c.b) .where(a1.c.a == 5) ) return stmt def two(): inner = one().subquery() stmt = select(table_b.c.a, inner.c.a, inner.c.b).select_from( table_b.join(inner, table_b.c.b == inner.c.b) ) return stmt def three(): a1 = table_a.alias() a2 = table_a.alias() ex = exists().where(table_b.c.b == a1.c.a) stmt = ( select(a1.c.a, a2.c.a) .select_from(a1.join(a2, a1.c.b == a2.c.b)) .where(ex) ) return stmt def four(): stmt = select(table_a.c.a).cte(recursive=True) stmt = stmt.union(select(stmt.c.a + 1).where(stmt.c.a < 10)) return stmt def five(): stmt = select(table_a.c.a).cte(recursive=True, nesting=True) stmt = stmt.union(select(stmt.c.a + 1).where(stmt.c.a < 10)) return stmt return [one(), one_diff(), two(), three(), four(), five()] fixtures.append(_complex_fixtures) def _statements_w_context_options_fixtures(): return [ select(table_a)._add_context_option(opt1, True), select(table_a)._add_context_option(opt1, 5), select(table_a) ._add_context_option(opt1, True) ._add_context_option(opt2, True), select(table_a) ._add_context_option(opt1, True) ._add_context_option(opt2, 5), select(table_a)._add_context_option(opt3, True), ] fixtures.append(_statements_w_context_options_fixtures) def _statements_w_anonymous_col_names(): def one(): c = column("q") l = c.label(None) # new case as of Id810f485c5f7ed971529489b84694e02a3356d6d subq = select(l).subquery() # this creates a ColumnClause as a proxy to the Label() that has # an anonymous name, so the column has one too. anon_col = subq.c[0] # then when BindParameter is created, it checks the label # and doesn't double up on the anonymous name which is uncachable return anon_col > 5 def two(): c = column("p") l = c.label(None) # new case as of Id810f485c5f7ed971529489b84694e02a3356d6d subq = select(l).subquery() # this creates a ColumnClause as a proxy to the Label() that has # an anonymous name, so the column has one too. anon_col = subq.c[0] # then when BindParameter is created, it checks the label # and doesn't double up on the anonymous name which is uncachable return anon_col > 5 def three(): l1, l2 = table_a.c.a.label(None), table_a.c.b.label(None) stmt = select(table_a.c.a, table_a.c.b, l1, l2) subq = stmt.subquery() return select(subq).where(subq.c[2] == 10) return ( one(), two(), three(), ) fixtures.append(_statements_w_anonymous_col_names) def _update_dml_w_dicts(): return ( table_b_b.update().values( { table_b_b.c.a: 5, table_b_b.c.b: 5, table_b_b.c.c: 5, table_b_b.c.d: 5, } ), # equivalent, but testing dictionary insert ordering as cache key # / compare table_b_b.update().values( { table_b_b.c.a: 5, table_b_b.c.c: 5, table_b_b.c.b: 5, table_b_b.c.d: 5, } ), table_b_b.update().values( {table_b_b.c.a: 5, table_b_b.c.b: 5, "c": 5, table_b_b.c.d: 5} ), table_b_b.update().values( { table_b_b.c.a: 5, table_b_b.c.b: 5, table_b_b.c.c: 5, table_b_b.c.d: 5, table_b_b.c.e: 10, } ), table_b_b.update() .values( { table_b_b.c.a: 5, table_b_b.c.b: 5, table_b_b.c.c: 5, table_b_b.c.d: 5, table_b_b.c.e: 10, } ) .where(table_b_b.c.c > 10), ) fixtures.append(_update_dml_w_dicts) def _lambda_fixtures(): def one(): return LambdaElement( lambda: table_a.c.a == column("q"), roles.WhereHavingRole ) def two(): r = random.randint(1, 10) q = 408 return LambdaElement( lambda: table_a.c.a + q == r, roles.WhereHavingRole ) some_value = random.randint(20, 30) def three(y): return LambdaElement( lambda: and_(table_a.c.a == some_value, table_a.c.b > y), roles.WhereHavingRole, ) def four(): return LambdaElement( lambda: and_(table_a.c.a == Foo.x), roles.WhereHavingRole ) def five(): return LambdaElement( lambda: and_(table_a.c.a == Foo.x, table_a.c.b == Foo.y), roles.WhereHavingRole, ) def six(): d = {"g": random.randint(40, 45)} return LambdaElement( lambda: and_(table_a.c.b == d["g"]), roles.WhereHavingRole, opts=LambdaOptions(track_closure_variables=False), ) def seven(): # lambda statements don't collect bindparameter objects # for fixed values, has to be in a variable value = random.randint(10, 20) return lambda_stmt(lambda: select(table_a)) + ( lambda s: s.where(table_a.c.a == value) ) from sqlalchemy.sql import lambdas def eight(): q = 5 return lambdas.DeferredLambdaElement( lambda t: t.c.a > q, roles.WhereHavingRole, lambda_args=(table_a,), ) return [ one(), two(), three(random.randint(5, 10)), four(), five(), six(), seven(), eight(), ] dont_compare_values_fixtures.append(_lambda_fixtures) # like fixture but returns at least two objects that compare equally equal_fixtures = [ lambda: ( select(table_a.c.a).fetch(3), select(table_a.c.a).fetch(2).fetch(3), select(table_a.c.a).fetch(3, percent=False, with_ties=False), select(table_a.c.a).limit(2).fetch(3), select(table_a.c.a).slice(2, 4).fetch(3).offset(None), ), lambda: ( select(table_a.c.a).limit(3), select(table_a.c.a).fetch(2).limit(3), select(table_a.c.a).fetch(2).slice(0, 3).offset(None), ), ] class CacheKeyTest(fixtures.CacheKeyFixture, CoreFixtures, fixtures.TestBase): # we are slightly breaking the policy of not having external dialect # stuff in here, but use pg/mysql as test cases to ensure that these # objects don't report an inaccurate cache key, which is dependent # on the base insert sending out _post_values_clause and the caching # system properly recognizing these constructs as not cacheable @testing.combinations( postgresql.insert(table_a).on_conflict_do_update( index_elements=[table_a.c.a], set_={"name": "foo"} ), mysql.insert(table_a).on_duplicate_key_update(updated_once=None), table_a.insert().values( # multivalues doesn't cache [ {"name": "some name"}, {"name": "some other name"}, {"name": "yet another name"}, ] ), ) def test_dml_not_cached_yet(self, dml_stmt): eq_(dml_stmt._generate_cache_key(), None) def test_values_doesnt_caches_right_now(self): v1 = values( column("mykey", Integer), column("mytext", String), column("myint", Integer), name="myvalues", ).data([(1, "textA", 99), (2, "textB", 88)]) is_(v1._generate_cache_key(), None) large_v1 = values( column("mykey", Integer), column("mytext", String), column("myint", Integer), name="myvalues", ).data([(i, "data %s" % i, i * 5) for i in range(500)]) is_(large_v1._generate_cache_key(), None) @testing.combinations( (lambda: column("x"), lambda: column("x"), lambda: column("y")), ( lambda: func.foo_bar(1, 2, 3), lambda: func.foo_bar(4, 5, 6), lambda: func.foo_bar_bat(1, 2, 3), ), ) def test_cache_key_object_comparators(self, lc1, lc2, lc3): """test ne issue detected as part of #10042""" c1 = lc1() c2 = lc2() c3 = lc3() eq_(c1._generate_cache_key(), c2._generate_cache_key()) ne_(c1._generate_cache_key(), c3._generate_cache_key()) is_true(c1._generate_cache_key() == c2._generate_cache_key()) is_false(c1._generate_cache_key() != c2._generate_cache_key()) is_true(c1._generate_cache_key() != c3._generate_cache_key()) is_false(c1._generate_cache_key() == c3._generate_cache_key()) def test_in_with_none(self): """test #12314""" def fixture(): elements = list( random_choices([1, 2, None, 3, 4], k=random.randint(1, 7)) ) # slight issue. if the first element is None and not an int, # the type of the BindParameter goes from Integer to Nulltype. # but if we set the left side to be Integer then it comes from # that side, and the vast majority of in_() use cases come from # a typed column expression, so this is fine return (column("x", Integer).in_(elements),) self._run_cache_key_fixture(fixture, False) def test_cache_key(self): for fixtures_, compare_values in [ (self.fixtures, True), (self.dont_compare_values_fixtures, False), (self.type_cache_key_fixtures, False), ]: for fixture in fixtures_: self._run_cache_key_fixture(fixture, compare_values) def test_cache_key_equal(self): for fixture in self.equal_fixtures: self._run_cache_key_equal_fixture(fixture, True) def test_literal_binds(self): def fixture(): return ( bindparam(None, value="x", literal_execute=True), bindparam(None, value="y", literal_execute=True), ) self._run_cache_key_fixture( fixture, True, ) def test_bindparam_subclass_nocache(self): # does not implement inherit_cache class _literal_bindparam(BindParameter): pass l1 = _literal_bindparam(None, value="x1") is_(l1._generate_cache_key(), None) def test_bindparam_subclass_ok_cache(self): # implements inherit_cache class _literal_bindparam(BindParameter): inherit_cache = True def fixture(): return ( _literal_bindparam(None, value="x1"), _literal_bindparam(None, value="x2"), _literal_bindparam(None), ) self._run_cache_key_fixture(fixture, True) def test_cache_key_unknown_traverse(self): class Foobar1(ClauseElement): _traverse_internals = [ ("key", InternalTraversal.dp_anon_name), ("type_", InternalTraversal.dp_unknown_structure), ] def __init__(self, key, type_): self.key = key self.type_ = type_ f1 = Foobar1("foo", String()) eq_(f1._generate_cache_key(), None) def test_cache_key_no_method(self): class Foobar1(ClauseElement): pass class Foobar2(ColumnElement): pass # the None for cache key will prevent objects # which contain these elements from being cached. f1 = Foobar1() with expect_warnings( "Class Foobar1 will not make use of SQL compilation caching" ): eq_(f1._generate_cache_key(), None) f2 = Foobar2() with expect_warnings( "Class Foobar2 will not make use of SQL compilation caching" ): eq_(f2._generate_cache_key(), None) s1 = select(column("q"), Foobar2()) # warning is memoized, won't happen the second time eq_(s1._generate_cache_key(), None) def test_get_children_no_method(self): class Foobar1(ClauseElement): pass class Foobar2(ColumnElement): pass f1 = Foobar1() eq_(f1.get_children(), []) f2 = Foobar2() eq_(f2.get_children(), []) def test_copy_internals_no_method(self): class Foobar1(ClauseElement): pass class Foobar2(ColumnElement): pass f1 = Foobar1() f2 = Foobar2() f1._copy_internals() f2._copy_internals() def test_generative_cache_key_regen(self): t1 = table("t1", column("a"), column("b")) s1 = select(t1) ck1 = s1._generate_cache_key() s2 = s1.where(t1.c.a == 5) ck2 = s2._generate_cache_key() ne_(ck1, ck2) is_not(ck1, None) is_not(ck2, None) def test_generative_cache_key_regen_w_del(self): t1 = table("t1", column("a"), column("b")) s1 = select(t1) ck1 = s1._generate_cache_key() s2 = s1.where(t1.c.a == 5) del s1 # there is now a good chance that id(s3) == id(s1), make sure # cache key is regenerated s3 = s2.order_by(t1.c.b) ck3 = s3._generate_cache_key() ne_(ck1, ck3) is_not(ck1, None) is_not(ck3, None) def all_hascachekey_subclasses(ignore_subclasses=()): def find_subclasses(cls: type): for s in class_hierarchy(cls): if ( # class_hierarchy may return values that # aren't subclasses of cls not issubclass(s, cls) or "_traverse_internals" not in s.__dict__ or any(issubclass(s, ignore) for ignore in ignore_subclasses) ): continue yield s return dict.fromkeys(find_subclasses(HasCacheKey)) class HasCacheKeySubclass(fixtures.TestBase): custom_traverse = { "AnnotatedFunctionAsBinary": { "sql_function", "left_index", "right_index", "modifiers", "_annotations", }, "Annotatednext_value": {"sequence", "_annotations"}, "FunctionAsBinary": { "sql_function", "left_index", "right_index", "modifiers", }, "next_value": {"sequence"}, "array": ({"type", "clauses"}), } ignore_keys = { "AnnotatedColumn": {"dialect_options"}, "SelectStatementGrouping": { "_independent_ctes", "_independent_ctes_opts", }, } @testing.combinations(*all_hascachekey_subclasses()) def test_traverse_internals(self, cls: type): super_traverse = {} # ignore_super = self.ignore_super.get(cls.__name__, set()) for s in cls.mro()[1:]: # if s.__name__ in ignore_super: # continue if s.__name__ == "Executable": continue for attr in s.__dict__: if not attr.endswith("_traverse_internals"): continue for k, v in s.__dict__[attr]: if k not in super_traverse: super_traverse[k] = v traverse_dict = dict(cls.__dict__["_traverse_internals"]) eq_(len(cls.__dict__["_traverse_internals"]), len(traverse_dict)) if cls.__name__ in self.custom_traverse: eq_(traverse_dict.keys(), self.custom_traverse[cls.__name__]) else: ignore = self.ignore_keys.get(cls.__name__, set()) left_keys = traverse_dict.keys() | ignore is_true( left_keys >= super_traverse.keys(), f"{left_keys} >= {super_traverse.keys()} - missing: " f"{super_traverse.keys() - left_keys} - ignored {ignore}", ) subset = { k: v for k, v in traverse_dict.items() if k in super_traverse } eq_( subset, {k: v for k, v in super_traverse.items() if k not in ignore}, ) # name -> (traverse names, init args) custom_init = { "BinaryExpression": ( {"right", "operator", "type", "negate", "modifiers", "left"}, {"right", "operator", "type_", "negate", "modifiers", "left"}, ), "BindParameter": ( {"literal_execute", "type", "callable", "value", "key"}, {"required", "isoutparam", "literal_execute", "type_", "callable_"} | {"unique", "expanding", "quote", "value", "key"}, ), "Cast": ({"type", "clause"}, {"type_", "expression"}), "ClauseList": ( {"clauses", "operator"}, {"group_contents", "group", "operator", "clauses"}, ), "ColumnClause": ( {"is_literal", "type", "table", "name"}, {"type_", "is_literal", "text"}, ), "ExpressionClauseList": ( {"clauses", "operator"}, {"type_", "operator", "clauses"}, ), "FromStatement": ( {"_raw_columns", "_with_options", "element"} | {"_propagate_attrs", "_with_context_options"}, {"element", "entities"}, ), "FunctionAsBinary": ( {"modifiers", "sql_function", "right_index", "left_index"}, {"right_index", "left_index", "fn"}, ), "FunctionElement": ( {"clause_expr", "_table_value_type", "_with_ordinality"}, {"clauses"}, ), "Function": ( {"_table_value_type", "clause_expr", "_with_ordinality"} | {"packagenames", "type", "name"}, {"type_", "packagenames", "name", "clauses"}, ), "Label": ({"_element", "type", "name"}, {"type_", "element", "name"}), "LambdaElement": ( {"_resolved"}, {"role", "opts", "apply_propagate_attrs", "fn"}, ), "Load": ( {"propagate_to_loaders", "additional_source_entities"} | {"path", "context"}, {"entity"}, ), "LoaderCriteriaOption": ( {"where_criteria", "entity", "propagate_to_loaders"} | {"root_entity", "include_aliases"}, {"where_criteria", "include_aliases", "propagate_to_loaders"} | {"entity_or_base", "loader_only", "track_closure_variables"}, ), "NullLambdaStatement": ({"_resolved"}, {"statement"}), "ScalarFunctionColumn": ( {"type", "fn", "name"}, {"type_", "name", "fn"}, ), "ScalarValues": ( {"_data", "_column_args", "literal_binds"}, {"columns", "data", "literal_binds"}, ), "Select": ( { "_having_criteria", "_distinct", "_group_by_clauses", "_fetch_clause", "_limit_clause", "_label_style", "_order_by_clauses", "_raw_columns", "_correlate_except", "_statement_hints", "_hints", "_independent_ctes", "_distinct_on", "_with_context_options", "_setup_joins", "_suffixes", "_memoized_select_entities", "_for_update_arg", "_prefixes", "_propagate_attrs", "_with_options", "_independent_ctes_opts", "_offset_clause", "_correlate", "_where_criteria", "_annotations", "_fetch_clause_options", "_from_obj", }, {"entities"}, ), "TableValuedColumn": ( {"scalar_alias", "type", "name"}, {"type_", "scalar_alias"}, ), "TableValueType": ({"_elements"}, {"elements"}), "TextualSelect": ( {"column_args", "_annotations", "_independent_ctes"} | {"element", "_independent_ctes_opts"}, {"positional", "columns", "text"}, ), "Tuple": ({"clauses", "operator"}, {"clauses", "types"}), "TypeClause": ({"type"}, {"type_"}), "TypeCoerce": ({"type", "clause"}, {"type_", "expression"}), "UnaryExpression": ( {"modifier", "element", "operator"}, {"operator", "wraps_column_expression"} | {"type_", "modifier", "element"}, ), "Values": ( {"_column_args", "literal_binds", "name", "_data"}, {"columns", "name", "literal_binds"}, ), "_FrameClause": ( {"upper_integer_bind", "upper_type"} | {"lower_type", "lower_integer_bind"}, {"range_"}, ), "_MemoizedSelectEntities": ( {"_with_options", "_raw_columns", "_setup_joins"}, {"args"}, ), "array": ({"type", "clauses"}, {"clauses", "type_"}), "next_value": ({"sequence"}, {"seq"}), } @testing.combinations( *all_hascachekey_subclasses( ignore_subclasses=[Annotated, NoInit, SingletonConstant] ) ) def test_init_args_in_traversal(self, cls: type): sig = signature(cls.__init__) init_args = set() for p in sig.parameters.values(): if ( p.name == "self" or p.name.startswith("_") or p.kind in (p.VAR_KEYWORD,) ): continue init_args.add(p.name) names = {n for n, _ in cls.__dict__["_traverse_internals"]} if cls.__name__ in self.custom_init: traverse, inits = self.custom_init[cls.__name__] eq_(names, traverse) eq_(init_args, inits) else: is_true(names.issuperset(init_args), f"{names} : {init_args}") class CompareAndCopyTest(CoreFixtures, fixtures.TestBase): @classmethod def setup_test_class(cls): # TODO: we need to get dialects here somehow, perhaps in test_suite? [ importlib.import_module("sqlalchemy.dialects.%s" % d) for d in dialects.__all__ if not d.startswith("_") ] def test_all_present(self): """test for elements that are in SQLAlchemy Core, that they are also included in the fixtures above. """ need = set( cls for cls in all_hascachekey_subclasses( ignore_subclasses=[Annotated, NoInit, SingletonConstant] ) if "orm" not in cls.__module__ and "compiler" not in cls.__module__ and "dialects" not in cls.__module__ and issubclass(cls, (ColumnElement, Selectable, LambdaElement)) ) for fixture in self.fixtures + self.dont_compare_values_fixtures: case_a = fixture() for elem in case_a: for mro in type(elem).__mro__: need.discard(mro) is_false(bool(need), "%d Remaining classes: %r" % (len(need), need)) def test_compare_labels(self): for fixtures_, compare_values in [ (self.fixtures, True), (self.dont_compare_values_fixtures, False), ]: for fixture in fixtures_: case_a = fixture() case_b = fixture() for a, b in itertools.combinations_with_replacement( range(len(case_a)), 2 ): if a == b: is_true( case_a[a].compare( case_b[b], compare_annotations=True, compare_values=compare_values, ), f"{case_a[a]!r} != {case_b[b]!r} (index {a} {b})", ) else: is_false( case_a[a].compare( case_b[b], compare_annotations=True, compare_values=compare_values, ), f"{case_a[a]!r} == {case_b[b]!r} (index {a} {b})", ) def test_compare_col_identity(self): stmt1 = ( select(table_a.c.a, table_b.c.b) .where(table_a.c.a == table_b.c.b) .alias() ) stmt1_c = ( select(table_a.c.a, table_b.c.b) .where(table_a.c.a == table_b.c.b) .alias() ) stmt2 = union(select(table_a), select(table_b)) equivalents = {table_a.c.a: [table_b.c.a]} is_false( stmt1.compare(stmt2, use_proxies=True, equivalents=equivalents) ) is_true( stmt1.compare(stmt1_c, use_proxies=True, equivalents=equivalents) ) is_true( (table_a.c.a == table_b.c.b).compare( stmt1.c.a == stmt1.c.b, use_proxies=True, equivalents=equivalents, ) ) def test_copy_internals(self): for fixtures_, compare_values in [ (self.fixtures, True), (self.dont_compare_values_fixtures, False), ]: for fixture in fixtures_: case_a = fixture() case_b = fixture() for idx in range(len(case_a)): assert case_a[idx].compare( case_b[idx], compare_values=compare_values ) clone = visitors.replacement_traverse( case_a[idx], {}, lambda elem: None ) assert clone.compare( case_b[idx], compare_values=compare_values ) assert case_a[idx].compare( case_b[idx], compare_values=compare_values ) # copy internals of Select is very different than other # elements and additionally this is extremely well tested # in test_selectable and test_external_traversal, so # skip these if isinstance(case_a[idx], Select): continue for elema, elemb in zip( visitors.iterate(case_a[idx], {}), visitors.iterate(clone, {}), ): if isinstance(elema, ClauseElement) and not isinstance( elema, Immutable ): assert elema is not elemb class CompareClausesTest(fixtures.TestBase): def test_compare_metadata_tables_annotations_one(self): # test that cache keys from annotated version of tables refresh # properly t1 = Table("a", MetaData(), Column("q", Integer), Column("p", Integer)) t2 = Table("a", MetaData(), Column("q", Integer), Column("p", Integer)) ne_(t1._generate_cache_key(), t2._generate_cache_key()) eq_(t1._generate_cache_key().key, (t1,)) t2 = t1._annotate({"foo": "bar"}) eq_( t2._generate_cache_key().key, (t1, "_annotations", (("foo", "bar"),)), ) eq_( t2._annotate({"bat": "bar"})._generate_cache_key().key, (t1, "_annotations", (("bat", "bar"), ("foo", "bar"))), ) def test_compare_metadata_tables_annotations_two(self): t1 = Table("a", MetaData(), Column("q", Integer), Column("p", Integer)) t2 = Table("a", MetaData(), Column("q", Integer), Column("p", Integer)) eq_(t2._generate_cache_key().key, (t2,)) t1 = t1._annotate({"orm": True}) t2 = t2._annotate({"orm": True}) ne_(t1._generate_cache_key(), t2._generate_cache_key()) eq_( t1._generate_cache_key().key, (t1, "_annotations", (("orm", True),)), ) def test_compare_adhoc_tables(self): # non-metadata tables compare on their structure. these objects are # not commonly used. # note this test is a bit redundant as we have a similar test # via the fixtures also t1 = table("a", Column("q", Integer), Column("p", Integer)) t2 = table("a", Column("q", Integer), Column("p", Integer)) t3 = table("b", Column("q", Integer), Column("p", Integer)) t4 = table("a", Column("q", Integer), Column("x", Integer)) eq_(t1._generate_cache_key(), t2._generate_cache_key()) ne_(t1._generate_cache_key(), t3._generate_cache_key()) ne_(t1._generate_cache_key(), t4._generate_cache_key()) ne_(t3._generate_cache_key(), t4._generate_cache_key()) def test_compare_comparison_associative(self): l1 = table_c.c.x == table_d.c.y l2 = table_d.c.y == table_c.c.x l3 = table_c.c.x == table_d.c.z is_true(l1.compare(l1)) is_true(l1.compare(l2)) is_false(l1.compare(l3)) def test_compare_comparison_non_commutative_inverses(self): l1 = table_c.c.x >= table_d.c.y l2 = table_d.c.y < table_c.c.x l3 = table_d.c.y <= table_c.c.x # we're not doing this kind of commutativity right now. is_false(l1.compare(l2)) is_false(l1.compare(l3)) def test_compare_clauselist_associative(self): l1 = and_(table_c.c.x == table_d.c.y, table_c.c.y == table_d.c.z) l2 = and_(table_c.c.y == table_d.c.z, table_c.c.x == table_d.c.y) l3 = and_(table_c.c.x == table_d.c.z, table_c.c.y == table_d.c.y) is_true(l1.compare(l1)) is_true(l1.compare(l2)) is_false(l1.compare(l3)) def test_compare_clauselist_not_associative(self): l1 = ClauseList( table_c.c.x, table_c.c.y, table_d.c.y, operator=operators.sub ) l2 = ClauseList( table_d.c.y, table_c.c.x, table_c.c.y, operator=operators.sub ) is_true(l1.compare(l1)) is_false(l1.compare(l2)) def test_compare_clauselist_assoc_different_operator(self): l1 = and_(table_c.c.x == table_d.c.y, table_c.c.y == table_d.c.z) l2 = or_(table_c.c.y == table_d.c.z, table_c.c.x == table_d.c.y) is_false(l1.compare(l2)) def test_compare_clauselist_not_assoc_different_operator(self): l1 = ClauseList( table_c.c.x, table_c.c.y, table_d.c.y, operator=operators.sub ) l2 = ClauseList( table_c.c.x, table_c.c.y, table_d.c.y, operator=operators.truediv ) is_false(l1.compare(l2)) def test_cache_key_limit_offset_values(self): s1 = select(column("q")).limit(10) s2 = select(column("q")).limit(25) s3 = select(column("q")).limit(25).offset(5) s4 = select(column("q")).limit(25).offset(18) s5 = select(column("q")).limit(7).offset(12) s6 = select(column("q")).limit(literal_column("q")).offset(12) for should_eq_left, should_eq_right in [(s1, s2), (s3, s4), (s3, s5)]: eq_( should_eq_left._generate_cache_key().key, should_eq_right._generate_cache_key().key, ) for shouldnt_eq_left, shouldnt_eq_right in [ (s1, s3), (s5, s6), (s2, s3), ]: ne_( shouldnt_eq_left._generate_cache_key().key, shouldnt_eq_right._generate_cache_key().key, ) def test_compare_labels(self): is_true(column("q").label(None).compare(column("q").label(None))) is_false(column("q").label("foo").compare(column("q").label(None))) is_false(column("q").label(None).compare(column("q").label("foo"))) is_false(column("q").label("foo").compare(column("q").label("bar"))) is_true(column("q").label("foo").compare(column("q").label("foo"))) def test_compare_binds(self): b1 = bindparam("foo", type_=Integer()) b1l = bindparam("foo", type_=Integer(), literal_execute=True) b2 = bindparam("foo", type_=Integer()) b3 = bindparam("foo", type_=String()) def c1(): return 5 def c2(): return 6 b4 = bindparam("foo", type_=Integer(), callable_=c1) b4l = bindparam( "foo", type_=Integer(), callable_=c1, literal_execute=True ) b5 = bindparam("foo", type_=Integer(), callable_=c2) b6 = bindparam("foo", type_=Integer(), callable_=c1) b7 = bindparam("foo", type_=Integer, value=5) b8 = bindparam("foo", type_=Integer, value=6) is_false(b1.compare(b4)) is_true(b4.compare(b6)) is_false(b4.compare(b5)) is_true(b1.compare(b2)) # currently not comparing "key", as we often have to compare # anonymous names. however we should really check for that # is_true(b1.compare(b3)) is_false(b1.compare(b3)) is_false(b1.compare(b7)) is_false(b7.compare(b8)) is_true(b7.compare(b7)) # cache key def compare_key(left, right, expected): lk = left._generate_cache_key().key rk = right._generate_cache_key().key is_(lk == rk, expected) compare_key(b1, b4, True) compare_key(b1, b5, True) compare_key(b8, b5, True) compare_key(b8, b7, True) compare_key(b8, b3, False) compare_key(b1, b1l, False) compare_key(b1, b4l, False) compare_key(b4, b4l, False) compare_key(b7, b4l, False) def test_compare_tables(self): is_true(table_a.compare(table_a_2)) # the "proxy" version compares schema tables on metadata identity is_false(table_a.compare(table_a_2, use_proxies=True)) # same for lower case tables since it compares lower case columns # using proxies, which makes it very unlikely to have multiple # table() objects with columns that compare equally is_false( table("a", column("x", Integer), column("q", String)).compare( table("a", column("x", Integer), column("q", String)), use_proxies=True, ) ) def test_compare_annotated_clears_mapping(self): t = table("t", column("x"), column("y")) x_a = t.c.x._annotate({"foo": True}) x_b = t.c.x._annotate({"foo": True}) is_true(x_a.compare(x_b, compare_annotations=True)) is_false( x_a.compare(x_b._annotate({"bar": True}), compare_annotations=True) ) s1 = select(t.c.x)._annotate({"foo": True}) s2 = select(t.c.x)._annotate({"foo": True}) is_true(s1.compare(s2, compare_annotations=True)) is_false( s1.compare(s2._annotate({"bar": True}), compare_annotations=True) ) def test_compare_annotated_wo_annotations(self): t = table("t", column("x"), column("y")) x_a = t.c.x._annotate({}) x_b = t.c.x._annotate({"foo": True}) is_true(t.c.x.compare(x_a)) is_true(x_b.compare(x_a)) is_true(x_a.compare(t.c.x)) is_false(x_a.compare(t.c.y)) is_false(t.c.y.compare(x_a)) is_true((t.c.x == 5).compare(x_a == 5)) is_false((t.c.y == 5).compare(x_a == 5)) s = select(t).subquery() x_p = s.c.x is_false(x_a.compare(x_p)) is_false(t.c.x.compare(x_p)) x_p_a = x_p._annotate({}) is_true(x_p_a.compare(x_p)) is_true(x_p.compare(x_p_a)) is_false(x_p_a.compare(x_a)) class ExecutableFlagsTest(fixtures.TestBase): @testing.combinations( (select(column("a")),), (table("q", column("a")).insert(),), (table("q", column("a")).update(),), (table("q", column("a")).delete(),), (lambda_stmt(lambda: select(column("a"))),), ) def test_is_select(self, case): if isinstance(case, LambdaElement): resolved_case = case._resolved else: resolved_case = case if isinstance(resolved_case, Select): is_true(case.is_select) else: is_false(case.is_select) class TypesTest(fixtures.TestBase): @testing.combinations(TypeDecorator, UserDefinedType) def test_thirdparty_no_cache(self, base): class MyType(base): impl = String expr = column("q", MyType()) == 1 with expect_warnings( r"%s MyType\(\) will not produce a cache key" % base.__name__ ): is_(expr._generate_cache_key(), None) @testing.combinations(TypeDecorator, UserDefinedType) def test_thirdparty_cache_false(self, base): class MyType(base): impl = String cache_ok = False expr = column("q", MyType()) == 1 is_(expr._generate_cache_key(), None) @testing.combinations(TypeDecorator, UserDefinedType) def test_thirdparty_cache_ok(self, base): class MyType(base): impl = String cache_ok = True def go1(): expr = column("q", MyType()) == 1 return expr def go2(): expr = column("p", MyType()) == 1 return expr c1 = go1()._generate_cache_key()[0] c2 = go1()._generate_cache_key()[0] c3 = go2()._generate_cache_key()[0] eq_(c1, c2) ne_(c1, c3) def test_typedec_cache_ok_params(self): class MyType(TypeDecorator): impl = String cache_ok = True def __init__(self, p1, p2): self.p1 = p1 self._p2 = p2 def go1(): expr = column("q", MyType("x", "y")) == 1 return expr def go2(): expr = column("q", MyType("q", "y")) == 1 return expr def go3(): expr = column("q", MyType("x", "z")) == 1 return expr c1 = go1()._generate_cache_key()[0] c2 = go1()._generate_cache_key()[0] c3 = go2()._generate_cache_key()[0] c4 = go3()._generate_cache_key()[0] eq_(c1, c2) ne_(c1, c3) eq_(c1, c4) def test_thirdparty_sub_subclass_no_cache(self): class MyType(PickleType): pass expr = column("q", MyType()) == 1 with expect_warnings( r"TypeDecorator MyType\(\) will not produce a cache key" ): is_(expr._generate_cache_key(), None) def test_userdefined_sub_subclass_no_cache(self): class MyType(UserDefinedType): cache_ok = True class MySubType(MyType): pass expr = column("q", MySubType()) == 1 with expect_warnings( r"UserDefinedType MySubType\(\) will not produce a cache key" ): is_(expr._generate_cache_key(), None) def test_userdefined_sub_subclass_cache_ok(self): class MyType(UserDefinedType): cache_ok = True class MySubType(MyType): cache_ok = True def go1(): expr = column("q", MySubType()) == 1 return expr def go2(): expr = column("p", MySubType()) == 1 return expr c1 = go1()._generate_cache_key()[0] c2 = go1()._generate_cache_key()[0] c3 = go2()._generate_cache_key()[0] eq_(c1, c2) ne_(c1, c3) def test_thirdparty_sub_subclass_cache_ok(self): class MyType(PickleType): cache_ok = True def go1(): expr = column("q", MyType()) == 1 return expr def go2(): expr = column("p", MyType()) == 1 return expr c1 = go1()._generate_cache_key()[0] c2 = go1()._generate_cache_key()[0] c3 = go2()._generate_cache_key()[0] eq_(c1, c2) ne_(c1, c3)