Release: 2.1.0b1 | Release Date: not released yet

# SQLAlchemy 2.1 Documentation

# SELECT and Related Constructs

The term “selectable” refers to any object that represents database rows. In SQLAlchemy, these objects descend from `Selectable`, the most prominent being `Select`, which represents a SQL SELECT statement. A subset of `Selectable` is `FromClause`, which represents objects that can be within the FROM clause of a `Select` statement. A distinguishing feature of `FromClause` is the `FromClause.c` attribute, which is a namespace of all the columns contained within the FROM clause (these elements are themselves `ColumnElement` subclasses).

## Selectable Foundational Constructors

Top level “FROM clause” and “SELECT” constructors.

Object Name | Description
--- | ---
except_(*selects) | Return an `EXCEPT` of multiple selectables.
except_all(*selects) | Return an `EXCEPT ALL` of multiple selectables.
exists([__argument]) | Construct a new `Exists` construct.
intersect(*selects) | Return an `INTERSECT` of multiple selectables.
intersect_all(*selects) | Return an `INTERSECT ALL` of multiple selectables.
select(*entities, **__kw) | Construct a new `Select`.
table(name, *columns, **kw) | Produce a new `TableClause`.
union(*selects) | Return a `UNION` of multiple selectables.
union_all(*selects) | Return a `UNION ALL` of multiple selectables.
values(*columns, [name, literal_binds]) | Construct a `Values` construct representing the SQL `VALUES` clause.

function sqlalchemy.sql.expression.except_(*selects: _SelectStatementForCompoundArgument[Unpack[_Ts]]) → CompoundSelect[Unpack[_Ts]]

  Return an `EXCEPT` of multiple selectables.

  The returned object is an instance of `CompoundSelect`.

  Parameters:

    *selects – a list of `Select` instances.

function sqlalchemy.sql.expression.except_all(*selects: _SelectStatementForCompoundArgument[Unpack[_Ts]]) → CompoundSelect[Unpack[_Ts]]

  Return an `EXCEPT ALL` of multiple selectables.

  The returned object is an instance of `CompoundSelect`.

  Parameters:

    *selects – a list of `Select` instances.

function sqlalchemy.sql.expression.exists(__argument: _ColumnsClauseArgument[Any] | SelectBase | ScalarSelect[Any] | None = None, /) → Exists

  Construct a new `Exists` construct.

  The `exists()` can be invoked by itself to produce an `Exists` construct, which will accept simple WHERE criteria:

      exists_criteria = exists().where(table1.c.col1 == table2.c.col2)

  However, for greater flexibility in constructing the SELECT, an existing `Select` construct may be converted to an `Exists`, most conveniently by making use of the `SelectBase.exists()` method:

      exists_criteria = (
          select(table2.c.col2).where(table1.c.col1 == table2.c.col2).exists()
      )

  The EXISTS criteria is then used inside of an enclosing SELECT:

      stmt = select(table1.c.col1).where(exists_criteria)

  The above statement will then be of the form:

      SELECT col1 FROM table1 WHERE EXISTS
      (SELECT table2.col2 FROM table2 WHERE table2.col2 = table1.col1)

  See also

  EXISTS subqueries - in the 2.0 style tutorial.

  `SelectBase.exists()` - method to transform a `SELECT` to an `EXISTS` clause.

function sqlalchemy.sql.expression.intersect(*selects: _SelectStatementForCompoundArgument[Unpack[_Ts]]) → CompoundSelect[Unpack[_Ts]]

  Return an `INTERSECT` of multiple selectables.

  The returned object is an instance of `CompoundSelect`.

  Parameters:

    *selects – a list of `Select` instances.

function sqlalchemy.sql.expression.intersect_all(*selects: _SelectStatementForCompoundArgument[Unpack[_Ts]]) → CompoundSelect[Unpack[_Ts]]

  Return an `INTERSECT ALL` of multiple selectables.

  The returned object is an instance of `CompoundSelect`.

  Parameters:

    *selects – a list of `Select` instances.

function sqlalchemy.sql.expression.select(*entities: _ColumnsClauseArgument[Any], **__kw: Any) → Select[Unpack[TupleAny]]

  Construct a new `Select`.

  Added in version 1.4: - The `select()` function now accepts column arguments positionally. The top-level `select()` function will automatically use the 1.x or 2.x style API based on the incoming arguments; using `select()` from the `sqlalchemy.future` module will enforce that only the 2.x style constructor is used.

  Similar functionality is also available via the `FromClause.select()` method on any `FromClause`.

  See also

  Using SELECT Statements - in the SQLAlchemy Unified Tutorial

  Parameters:

    *entities –

    Entities to SELECT from. For Core usage, this is typically a series of `ColumnElement` and / or `FromClause` objects which will form the columns clause of the resulting statement. For those objects that are instances of `FromClause` (typically `Table` or `Alias` objects), the `FromClause.c` collection is extracted to form a collection of `ColumnElement` objects.

    This parameter will also accept `TextClause` constructs as given, as well as ORM-mapped classes.

function sqlalchemy.sql.expression.table(name: str, *columns: ColumnClause[Any], **kw: Any) → TableClause

  Produce a new `TableClause`.

  The object returned is an instance of `TableClause`, which represents the “syntactical” portion of the schema-level `Table` object. It may be used to construct lightweight table constructs.

  Parameters:

    - name – Name of the table.

    - columns – A collection of `column()` constructs.

    - schema – The schema name for this table.

function sqlalchemy.sql.expression.union(*selects: _SelectStatementForCompoundArgument[Unpack[_Ts]]) → CompoundSelect[Unpack[_Ts]]

  Return a `UNION` of multiple selectables.

  The returned object is an instance of `CompoundSelect`.

  A similar `union()` method is available on all `FromClause` subclasses.

  Parameters:

    - *selects – a list of `Select` instances.

    - **kwargs – available keyword arguments are the same as those of `select()`.

function sqlalchemy.sql.expression.union_all(*selects: _SelectStatementForCompoundArgument[Unpack[_Ts]]) → CompoundSelect[Unpack[_Ts]]

  Return a `UNION ALL` of multiple selectables.

  The returned object is an instance of `CompoundSelect`.

  A similar `union_all()` method is available on all `FromClause` subclasses.

  Parameters:

    *selects – a list of `Select` instances.

function sqlalchemy.sql.expression.values(*columns: _OnlyColumnArgument[Any], name: str | None = None, literal_binds: bool = False) → Values

  Construct a `Values` construct representing the SQL `VALUES` clause.

  The column expressions and the actual data for `Values` are given in two separate steps. The constructor receives the column expressions typically as `column()` constructs, and the data is then passed via the `Values.data()` method as a list, which can be called multiple times to add more data, e.g.:

      from sqlalchemy import column
      from sqlalchemy import values
      from sqlalchemy import Integer
      from sqlalchemy import String

      value_expr = (
          values(
              column("id", Integer),
              column("name", String),
          )
          .data([(1, "name1"), (2, "name2")])
          .data([(3, "name3")])
      )

  Would represent a SQL fragment like:

      VALUES(1, "name1"), (2, "name2"), (3, "name3")

  The `values` construct has an optional `values.name` field; when using this field, the PostgreSQL-specific “named VALUES” clause may be generated:

      value_expr = values(
          column("id", Integer), column("name", String), name="somename"
      ).data([(1, "name1"), (2, "name2"), (3, "name3")])

  When selecting from the above construct, the name and column names will be listed out using a PostgreSQL-specific syntax:

      >>> print(value_expr.select())
      SELECT somename.id, somename.name
      FROM (VALUES (:param_1, :param_2), (:param_3, :param_4),
      (:param_5, :param_6)) AS somename (id, name)

  For a more database-agnostic means of SELECTing named columns from a VALUES expression, the `Values.cte()` method may be used, which produces a named CTE with explicit column names against the VALUES construct within; this syntax works on PostgreSQL, SQLite, and MariaDB:

      value_expr = (
          values(
              column("id", Integer),
              column("name", String),
          )
          .data([(1, "name1"), (2, "name2"), (3, "name3")])
          .cte()
      )

  Rendering as:

      >>> print(value_expr.select())
      WITH anon_1(id, name) AS
      (VALUES (:param_1, :param_2), (:param_3, :param_4), (:param_5, :param_6))
      SELECT anon_1.id, anon_1.name
      FROM anon_1

  Added in version 2.0.42: Added the `Values.cte()` method to `Values`

  Parameters:

    - *columns – column expressions, typically composed using `column()` objects.

    - name – the name for this VALUES construct. If omitted, the VALUES construct will be unnamed in a SQL expression. Different backends may have different requirements here.

    - literal_binds – Defaults to False. Whether or not to render the data values inline in the SQL output, rather than using bound parameters.

## Selectable Modifier Constructors

Functions listed here are more commonly available as methods from `FromClause` and `Selectable` elements, for example, the `alias()` function is usually invoked via the `FromClause.alias()` method.

Object Name | Description
--- | ---
alias(selectable[, name, flat]) | Return a named alias of the given `FromClause`.
cte(selectable[, name, recursive]) | Return a new `CTE`, or Common Table Expression instance.
join(left, right[, onclause, isouter, ...]) | Produce a `Join` object, given two `FromClause` expressions.
lateral(selectable[, name]) | Return a `Lateral` object.
outerjoin(left, right[, onclause, full]) | Return an `OUTER JOIN` clause element.
tablesample(selectable, sampling[, name, seed]) | Return a `TableSample` object.

function sqlalchemy.sql.expression.alias(selectable: FromClause, name: str | None = None, flat: bool = False) → NamedFromClause

  Return a named alias of the given `FromClause`.

  For `Table` and `Join` objects, the return type is the `Alias` object. Other kinds of `NamedFromClause` objects may be returned for other kinds of `FromClause` objects.

  The named alias represents any `FromClause` with an alternate name assigned within SQL, typically using the `AS` clause when generated, e.g. `SELECT * FROM table AS aliasname`.

  Equivalent functionality is available via the `FromClause.alias()` method available on all `FromClause` objects.

  Parameters:

    - selectable – any `FromClause` subclass, such as a table, select statement, etc.

    - name – string name to be assigned as the alias. If `None`, a name will be deterministically generated at compile time. Deterministic means the name is guaranteed to be unique against other constructs used in the same statement, and will also be the same name for each successive compilation of the same statement object.

    - flat – Will be passed through to if the given selectable is an instance of `Join` - see `Join.alias()` for details.

function sqlalchemy.sql.expression.cte(selectable: HasCTE, name: str | None = None, recursive: bool = False) → CTE

  Return a new `CTE`, or Common Table Expression instance.

  Please see `HasCTE.cte()` for detail on CTE usage.

function sqlalchemy.sql.expression.join(left: _FromClauseArgument, right: _FromClauseArgument, onclause: _OnClauseArgument | None = None, isouter: bool = False, full: bool = False) → Join

  Produce a `Join` object, given two `FromClause` expressions.

  E.g.:

      j = join(
          user_table, address_table, user_table.c.id == address_table.c.user_id
      )
      stmt = select(user_table).select_from(j)

  would emit SQL along the lines of:

      SELECT user.id, user.name FROM user
      JOIN address ON user.id = address.user_id

  Similar functionality is available given any `FromClause` object (e.g. such as a `Table`) using the `FromClause.join()` method.

  Parameters:

    - left – The left side of the join.

    - right – the right side of the join; this is any `FromClause` object such as a `Table` object, and may also be a selectable-compatible object such as an ORM-mapped class.

    - onclause – a SQL expression representing the ON clause of the join. If left at `None`, `FromClause.join()` will attempt to join the two tables based on a foreign key relationship.

    - isouter – if True, render a LEFT OUTER JOIN, instead of JOIN.

    - full – if True, render a FULL OUTER JOIN, instead of JOIN.

  See also

  `FromClause.join()` - method form, based on a given left side.

  `Join` - the type of object produced.

function sqlalchemy.sql.expression.lateral(selectable: SelectBase | _FromClauseArgument, name: str | None = None) → LateralFromClause

  Return a `Lateral` object.

  `Lateral` is an `Alias` subclass that represents a subquery with the LATERAL keyword applied to it.

  The special behavior of a LATERAL subquery is that it appears in the FROM clause of an enclosing SELECT, but may correlate to other FROM clauses of that SELECT. It is a special case of subquery only supported by a small number of backends, currently more recent PostgreSQL versions.

  See also

  LATERAL correlation - overview of usage.

function sqlalchemy.sql.expression.outerjoin(left: _FromClauseArgument, right: _FromClauseArgument, onclause: _OnClauseArgument | None = None, full: bool = False) → Join

  Return an `OUTER JOIN` clause element.

  The returned object is an instance of `Join`.

  Similar functionality is also available via the `FromClause.outerjoin()` method on any `FromClause`.

  Parameters:

    - left – The left side of the join.

    - right – The right side of the join.

    - onclause – Optional criterion for the `ON` clause, is derived from foreign key relationships established between left and right otherwise.

  To chain joins together, use the `FromClause.join()` or `FromClause.outerjoin()` methods on the resulting `Join` object.

function sqlalchemy.sql.expression.tablesample(selectable: _FromClauseArgument, sampling: float | Function[Any], name: str | None = None, seed: roles.ExpressionElementRole[Any] | None = None) → TableSample

  Return a `TableSample` object.

  `TableSample` is an `Alias` subclass that represents a table with the TABLESAMPLE clause applied to it. `tablesample()` is also available from the `FromClause` class via the `FromClause.tablesample()` method.

  The TABLESAMPLE clause allows selecting a randomly selected approximate percentage of rows from a table. It supports multiple sampling methods, most commonly BERNOULLI and SYSTEM.

  e.g.:

      from sqlalchemy import func

      selectable = people.tablesample(
          func.bernoulli(1), name="alias", seed=func.random()
      )
      stmt = select(selectable.c.people_id)

  Assuming `people` with a column `people_id`, the above statement would render as:

      SELECT alias.people_id FROM
      people AS alias TABLESAMPLE bernoulli(:bernoulli_1)
      REPEATABLE (random())

  Parameters:

    - sampling – a `float` percentage between 0 and 100 or `Function`.

    - name – optional alias name

    - seed – any real-valued SQL expression. When specified, the REPEATABLE sub-clause is also rendered.

## Selectable Class Documentation

The classes here are generated using the constructors listed at Selectable Foundational Constructors and Selectable Modifier Constructors.

Object Name | Description
--- | ---
Alias | Represents an table or selectable alias (AS).
AliasedReturnsRows | Base class of aliases against tables, subqueries, and other selectables.
CompoundSelect | Forms the basis of `UNION`, `UNION ALL`, and other SELECT-based set operations.
CTE | Represent a Common Table Expression.
Executable | Mark a `ClauseElement` as supporting execution.
ExecutableStatement | Executable subclass that implements a lightweight version of `params` that avoids a full cloned traverse.
Exists | Represent an `EXISTS` clause.
FromClause | Represent an element that can be used within the `FROM` clause of a `SELECT` statement.
GenerativeSelect | Base class for SELECT statements where additional elements can be added.
HasCTE | Mixin that declares a class to include CTE support.
HasPrefixes |
HasSuffixes |
Join | Represent a `JOIN` construct between two `FromClause` elements.
Lateral | Represent a LATERAL subquery.
ReturnsRows | The base-most class for Core constructs that have some concept of columns that can represent rows.
ScalarSelect | Represent a scalar subquery.
ScalarValues | Represent a scalar `VALUES` construct that can be used as a COLUMN element in a statement.
Select | Represents a `SELECT` statement.
Selectable | Mark a class as being selectable.
SelectBase | Base class for SELECT statements.
Subquery | Represent a subquery of a SELECT.
TableClause | Represents a minimal “table” construct.
TableSample | Represent a TABLESAMPLE clause.
TableValuedAlias | An alias against a “table valued” SQL function.
TextualSelect | Wrap a `TextClause` construct within a `SelectBase` interface.
Values | Represent a `VALUES` construct that can be used as a FROM element in a statement.

class sqlalchemy.sql.expression.Alias

  inherits from `sqlalchemy.sql.roles.DMLTableRole`, `sqlalchemy.sql.expression.FromClauseAlias`

  Represents an table or selectable alias (AS).

  Represents an alias, as typically applied to any table or sub-select within a SQL statement using the `AS` keyword (or without the keyword on certain databases such as Oracle Database).

  This object is constructed from the `alias()` module level function as well as the `FromClause.alias()` method available on all `FromClause` subclasses.

  See also

  `FromClause.alias()`

  Member Name | Description
  --- | ---
  inherit_cache | Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.

  attribute `sqlalchemy.sql.expression.Alias.`inherit_cache = True

    Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.

    The attribute defaults to `None`, which indicates that a construct has not yet taken into account whether or not its appropriate for it to participate in caching; this is functionally equivalent to setting the value to `False`, except that a warning is also emitted.

    This flag can be set to `True` on a particular class, if the SQL that corresponds to the object does not change based on attributes which are local to this class, and not its superclass.

    See also

    Enabling Caching Support for Custom Constructs - General guideslines for setting the `HasCacheKey.inherit_cache` attribute for third-party or user defined SQL constructs.

class sqlalchemy.sql.expression.AliasedReturnsRows

  inherits from `sqlalchemy.sql.expression.NoInit`, `sqlalchemy.sql.expression.NamedFromClause`

  Base class of aliases against tables, subqueries, and other selectables.

  Member Name | Description
  --- | ---
  description |
  is_derived_from() | Return `True` if this `FromClause` is ‘derived’ from the given `FromClause`.

  attribute `sqlalchemy.sql.expression.AliasedReturnsRows.`description
  method `sqlalchemy.sql.expression.AliasedReturnsRows.`is_derived_from(fromclause: FromClause | None) → bool

    Return `True` if this `FromClause` is ‘derived’ from the given `FromClause`.

    An example would be an Alias of a Table is derived from that Table.

  property original: ReturnsRows

    Legacy for dialects that are referring to Alias.original.

class sqlalchemy.sql.expression.CompoundSelect

  inherits from `sqlalchemy.sql.expression.HasCompileState`, `sqlalchemy.sql.expression.GenerativeSelect`, `sqlalchemy.sql.expression.TypedReturnsRows`

  Forms the basis of `UNION`, `UNION ALL`, and other SELECT-based set operations.

  See also

  `union()`

  `union_all()`

  `intersect()`

  `intersect_all()`

  `except()`

  `except_all()`

  Member Name | Description
  --- | ---
  add_cte() | Add one or more `CTE` constructs to this statement.
  alias() | Return a named subquery against this `SelectBase`.
  argument_for() | Add a new kind of dialect-specific keyword argument for this class.
  as_scalar() |
  compile() | Compile this SQL expression.
  corresponding_column() | Given a `ColumnElement`, return the exported `ColumnElement` object from the `Selectable.exported_columns` collection of this `Selectable` which corresponds to that original `ColumnElement` via a common ancestor column.
  cte() | Return a new `CTE`, or Common Table Expression instance.
  dialect_options | A collection of keyword arguments specified as dialect-specific options to this construct.
  execution_options() | Set non-SQL options for the statement which take effect during execution.
  exists() | Return an `Exists` representation of this selectable, which can be used as a column expression.
  fetch() | Return a new selectable with the given FETCH FIRST criterion applied.
  get_children() | Return immediate child `HasTraverseInternals` elements of this `HasTraverseInternals`.
  get_execution_options() | Get the non-SQL options which will take effect during execution.
  get_label_style() | Retrieve the current label style.
  group_by() | Return a new selectable with the given list of GROUP BY criterion applied.
  inherit_cache | Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.
  into() | Create a `CreateTableAs` construct from this SELECT.
  is_derived_from() | Return `True` if this `ReturnsRows` is ‘derived’ from the given `FromClause`.
  label() | Return a ‘scalar’ representation of this selectable, embedded as a subquery with a label.
  lateral() | Return a LATERAL alias of this `Selectable`.
  limit() | Return a new selectable with the given LIMIT criterion applied.
  name_cte_columns | indicates if this HasCTE as contained within a CTE should compel the CTE to render the column names of this object in the WITH clause.
  offset() | Return a new selectable with the given OFFSET criterion applied.
  options() | Apply options to this statement.
  order_by() | Return a new selectable with the given list of ORDER BY criteria applied.
  params() | Return a copy with the provided bindparam values.
  replace_selectable() | Replace all occurrences of `FromClause` ‘old’ with the given `Alias` object, returning a copy of this `FromClause`.
  scalar_subquery() | Return a ‘scalar’ representation of this selectable, which can be used as a column expression.
  selected_columns | A `ColumnCollection` representing the columns that this SELECT statement or similar construct returns in its result set, not including `TextClause` constructs.
  self_group() | Apply a ‘grouping’ to this `ClauseElement`.
  set_label_style() | Return a new selectable with the specified label style.
  slice() | Apply LIMIT / OFFSET to this statement based on a slice.
  subquery() | Return a subquery of this `SelectBase`.
  with_for_update() | Specify a `FOR UPDATE` clause for this `GenerativeSelect`.

  method `sqlalchemy.sql.expression.CompoundSelect.`add_cte(*ctes: CTE, nest_here: bool = False) → Self

    inherited from the `HasCTE.add_cte()` method of `HasCTE`

    Add one or more `CTE` constructs to this statement.

    This method will associate the given `CTE` constructs with the parent statement such that they will each be unconditionally rendered in the WITH clause of the final statement, even if not referenced elsewhere within the statement or any sub-selects.

    The optional `HasCTE.add_cte.nest_here` parameter when set to True will have the effect that each given `CTE` will render in a WITH clause rendered directly along with this statement, rather than being moved to the top of the ultimate rendered statement, even if this statement is rendered as a subquery within a larger statement.

    This method has two general uses. One is to embed CTE statements that serve some purpose without being referenced explicitly, such as the use case of embedding a DML statement such as an INSERT or UPDATE as a CTE inline with a primary statement that may draw from its results indirectly. The other is to provide control over the exact placement of a particular series of CTE constructs that should remain rendered directly in terms of a particular statement that may be nested in a larger statement.

    E.g.:

        from sqlalchemy import table, column, select

        t = table("t", column("c1"), column("c2"))

        ins = t.insert().values({"c1": "x", "c2": "y"}).cte()

        stmt = select(t).add_cte(ins)

    Would render:

        WITH anon_1 AS (
            INSERT INTO t (c1, c2) VALUES (:param_1, :param_2)
        )
        SELECT t.c1, t.c2
        FROM t

    Above, the “anon_1” CTE is not referenced in the SELECT statement, however still accomplishes the task of running an INSERT statement.

    Similarly in a DML-related context, using the PostgreSQL `Insert` construct to generate an “upsert”:

        from sqlalchemy import table, column
        from sqlalchemy.dialects.postgresql import insert

        t = table("t", column("c1"), column("c2"))

        delete_statement_cte = t.delete().where(t.c.c1 < 1).cte("deletions")

        insert_stmt = insert(t).values({"c1": 1, "c2": 2})
        update_statement = insert_stmt.on_conflict_do_update(
            index_elements=[t.c.c1],
            set_={
                "c1": insert_stmt.excluded.c1,
                "c2": insert_stmt.excluded.c2,
            },
        ).add_cte(delete_statement_cte)

        print(update_statement)

    The above statement renders as:

        WITH deletions AS (
            DELETE FROM t WHERE t.c1 < %(c1_1)s
        )
        INSERT INTO t (c1, c2) VALUES (%(c1)s, %(c2)s)
        ON CONFLICT (c1) DO UPDATE SET c1 = excluded.c1, c2 = excluded.c2

    Added in version 1.4.21.

    Parameters:

      - *ctes –

        zero or more `CTE` constructs.

        Changed in version 2.0: Multiple CTE instances are accepted

      - nest_here –

        if True, the given CTE or CTEs will be rendered as though they specified the `HasCTE.cte.nesting` flag to `True` when they were added to this `HasCTE`. Assuming the given CTEs are not referenced in an outer-enclosing statement as well, the CTEs given should render at the level of this statement when this flag is given.

        Added in version 2.0.

        See also

        `HasCTE.cte.nesting`

  method `sqlalchemy.sql.expression.CompoundSelect.`alias(name: str | None = None, flat: bool = False) → Subquery

    inherited from the `SelectBase.alias()` method of `SelectBase`

    Return a named subquery against this `SelectBase`.

    For a `SelectBase` (as opposed to a `FromClause`), this returns a `Subquery` object which behaves mostly the same as the `Alias` object that is used with a `FromClause`.

    Changed in version 1.4: The `SelectBase.alias()` method is now a synonym for the `SelectBase.subquery()` method.

  classmethod `sqlalchemy.sql.expression.CompoundSelect.`argument_for(dialect_name: str, argument_name: str, default: Any) → None

    inherited from the `DialectKWArgs.argument_for()` method of `DialectKWArgs`

    Add a new kind of dialect-specific keyword argument for this class.

    E.g.:

        Index.argument_for("mydialect", "length", None)

        some_index = Index("a", "b", mydialect_length=5)

    The `DialectKWArgs.argument_for()` method is a per-argument way adding extra arguments to the `DefaultDialect.construct_arguments` dictionary. This dictionary provides a list of argument names accepted by various schema-level constructs on behalf of a dialect.

    New dialects should typically specify this dictionary all at once as a data member of the dialect class. The use case for ad-hoc addition of argument names is typically for end-user code that is also using a custom compilation scheme which consumes the additional arguments.

    Parameters:

      - dialect_name – name of a dialect. The dialect must be locatable, else a `NoSuchModuleError` is raised. The dialect must also include an existing `DefaultDialect.construct_arguments` collection, indicating that it participates in the keyword-argument validation and default system, else `ArgumentError` is raised. If the dialect does not include this collection, then any keyword argument can be specified on behalf of this dialect already. All dialects packaged within SQLAlchemy include this collection, however for third party dialects, support may vary.

      - argument_name – name of the parameter.

      - default – default value of the parameter.

  method `sqlalchemy.sql.expression.CompoundSelect.`as_scalar() → ScalarSelect[Any]

    inherited from the `SelectBase.as_scalar()` method of `SelectBase`

    Deprecated since version 1.4: The `SelectBase.as_scalar()` method is deprecated and will be removed in a future release. Please refer to `SelectBase.scalar_subquery()`.

  method `sqlalchemy.sql.expression.CompoundSelect.`compile(bind: _HasDialect | None = None, dialect: Dialect | None = None, **kw: Any) → Compiled

    inherited from the `CompilerElement.compile()` method of `CompilerElement`

    Compile this SQL expression.

    The return value is a `Compiled` object. Calling `str()` or `unicode()` on the returned value will yield a string representation of the result. The `Compiled` object also can return a dictionary of bind parameter names and values using the `params` accessor.

    Parameters:

      - bind – An `Connection` or `Engine` which can provide a `Dialect` in order to generate a `Compiled` object. If the `bind` and `dialect` parameters are both omitted, a default SQL compiler is used.

      - column_keys – Used for INSERT and UPDATE statements, a list of column names which should be present in the VALUES clause of the compiled statement. If `None`, all columns from the target table object are rendered.

      - dialect – A `Dialect` instance which can generate a `Compiled` object. This argument takes precedence over the `bind` argument.

      - compile_kwargs –

        optional dictionary of additional parameters that will be passed through to the compiler within all “visit” methods. This allows any custom flag to be passed through to a custom compilation construct, for example. It is also used for the case of passing the `literal_binds` flag through:

            from sqlalchemy.sql import table, column, select

            t = table("t", column("x"))

            s = select(t).where(t.c.x == 5)

            print(s.compile(compile_kwargs={"literal_binds": True}))

    See also

    How do I render SQL expressions as strings, possibly with bound parameters inlined?

  method `sqlalchemy.sql.expression.CompoundSelect.`corresponding_column(column: KeyedColumnElement[Any], require_embedded: bool = False) → KeyedColumnElement[Any] | None

    inherited from the `Selectable.corresponding_column()` method of `Selectable`

    Given a `ColumnElement`, return the exported `ColumnElement` object from the `Selectable.exported_columns` collection of this `Selectable` which corresponds to that original `ColumnElement` via a common ancestor column.

    Parameters:

      - column – the target `ColumnElement` to be matched.

      - require_embedded – only return corresponding columns for the given `ColumnElement`, if the given `ColumnElement` is actually present within a sub-element of this `Selectable`. Normally the column will match if it merely shares a common ancestor with one of the exported columns of this `Selectable`.

    See also

    `Selectable.exported_columns` - the `ColumnCollection` that is used for the operation.

    `ColumnCollection.corresponding_column()` - implementation method.

  method `sqlalchemy.sql.expression.CompoundSelect.`cte(name: str | None = None, recursive: bool = False, nesting: bool = False) → CTE

    inherited from the `HasCTE.cte()` method of `HasCTE`

    Return a new `CTE`, or Common Table Expression instance.

    Common table expressions are a SQL standard whereby SELECT statements can draw upon secondary statements specified along with the primary statement, using a clause called “WITH”. Special semantics regarding UNION can also be employed to allow “recursive” queries, where a SELECT statement can draw upon the set of rows that have previously been selected.

    CTEs can also be applied to DML constructs UPDATE, INSERT and DELETE on some databases, both as a source of CTE rows when combined with RETURNING, as well as a consumer of CTE rows.

    SQLAlchemy detects `CTE` objects, which are treated similarly to `Alias` objects, as special elements to be delivered to the FROM clause of the statement as well as to a WITH clause at the top of the statement.

    For special prefixes such as PostgreSQL “MATERIALIZED” and “NOT MATERIALIZED”, the `CTE.prefix_with()` method may be used to establish these.

    Parameters:

      - name – name given to the common table expression. Like `FromClause.alias()`, the name can be left as `None` in which case an anonymous symbol will be used at query compile time.

      - recursive – if `True`, will render `WITH RECURSIVE`. A recursive common table expression is intended to be used in conjunction with UNION ALL in order to derive rows from those already selected.

      - nesting –

        if `True`, will render the CTE locally to the statement in which it is referenced. For more complex scenarios, the `HasCTE.add_cte()` method using the `HasCTE.add_cte.nest_here` parameter may also be used to more carefully control the exact placement of a particular CTE.

        Added in version 1.4.24.

        See also

        `HasCTE.add_cte()`

    The following examples include two from PostgreSQL’s documentation at https://www.postgresql.org/docs/current/static/queries-with.html, as well as additional examples.

    Example 1, non recursive:

        from sqlalchemy import (
            Table,
            Column,
            String,
            Integer,
            MetaData,
            select,
            func,
        )

        metadata = MetaData()

        orders = Table(
            "orders",
            metadata,
            Column("region", String),
            Column("amount", Integer),
            Column("product", String),
            Column("quantity", Integer),
        )

        regional_sales = (
            select(orders.c.region, func.sum(orders.c.amount).label("total_sales"))
            .group_by(orders.c.region)
            .cte("regional_sales")
        )

        top_regions = (
            select(regional_sales.c.region)
            .where(
                regional_sales.c.total_sales
                > select(func.sum(regional_sales.c.total_sales) / 10)
            )
            .cte("top_regions")
        )

        statement = (
            select(
                orders.c.region,
                orders.c.product,
                func.sum(orders.c.quantity).label("product_units"),
                func.sum(orders.c.amount).label("product_sales"),
            )
            .where(orders.c.region.in_(select(top_regions.c.region)))
            .group_by(orders.c.region, orders.c.product)
        )

        result = conn.execute(statement).fetchall()

    Example 2, WITH RECURSIVE:

        from sqlalchemy import (
            Table,
            Column,
            String,
            Integer,
            MetaData,
            select,
            func,
        )

        metadata = MetaData()

        parts = Table(
            "parts",
            metadata,
            Column("part", String),
            Column("sub_part", String),
            Column("quantity", Integer),
        )

        included_parts = (
            select(parts.c.sub_part, parts.c.part, parts.c.quantity)
            .where(parts.c.part == "our part")
            .cte(recursive=True)
        )

        incl_alias = included_parts.alias()
        parts_alias = parts.alias()
        included_parts = included_parts.union_all(
            select(
                parts_alias.c.sub_part, parts_alias.c.part, parts_alias.c.quantity
            ).where(parts_alias.c.part == incl_alias.c.sub_part)
        )

        statement = select(
            included_parts.c.sub_part,
            func.sum(included_parts.c.quantity).label("total_quantity"),
        ).group_by(included_parts.c.sub_part)

        result = conn.execute(statement).fetchall()

    Example 3, an upsert using UPDATE and INSERT with CTEs:

        from datetime import date
        from sqlalchemy import (
            MetaData,
            Table,
            Column,
            Integer,
            Date,
            select,
            literal,
            and_,
            exists,
        )

        metadata = MetaData()

        visitors = Table(
            "visitors",
            metadata,
            Column("product_id", Integer, primary_key=True),
            Column("date", Date, primary_key=True),
            Column("count", Integer),
        )

        # add 5 visitors for the product_id == 1
        product_id = 1
        day = date.today()
        count = 5

        update_cte = (
            visitors.update()
            .where(
                and_(visitors.c.product_id == product_id, visitors.c.date == day)
            )
            .values(count=visitors.c.count + count)
            .returning(literal(1))
            .cte("update_cte")
        )

        upsert = visitors.insert().from_select(
            [visitors.c.product_id, visitors.c.date, visitors.c.count],
            select(literal(product_id), literal(day), literal(count)).where(
                ~exists(update_cte.select())
            ),
        )

        connection.execute(upsert)

    Example 4, Nesting CTE (SQLAlchemy 1.4.24 and above):

        value_a = select(literal("root").label("n")).cte("value_a")

        # A nested CTE with the same name as the root one
        value_a_nested = select(literal("nesting").label("n")).cte(
            "value_a", nesting=True
        )

        # Nesting CTEs takes ascendency locally
        # over the CTEs at a higher level
        value_b = select(value_a_nested.c.n).cte("value_b")

        value_ab = select(value_a.c.n.label("a"), value_b.c.n.label("b"))

    The above query will render the second CTE nested inside the first, shown with inline parameters below as:

        WITH
            value_a AS
                (SELECT 'root' AS n),
            value_b AS
                (WITH value_a AS
                    (SELECT 'nesting' AS n)
                SELECT value_a.n AS n FROM value_a)
        SELECT value_a.n AS a, value_b.n AS b
        FROM value_a, value_b

    The same CTE can be set up using the `HasCTE.add_cte()` method as follows (SQLAlchemy 2.0 and above):

        value_a = select(literal("root").label("n")).cte("value_a")

        # A nested CTE with the same name as the root one
        value_a_nested = select(literal("nesting").label("n")).cte("value_a")

        # Nesting CTEs takes ascendency locally
        # over the CTEs at a higher level
        value_b = (
            select(value_a_nested.c.n)
            .add_cte(value_a_nested, nest_here=True)
            .cte("value_b")
        )

        value_ab = select(value_a.c.n.label("a"), value_b.c.n.label("b"))

    Example 5, Non-Linear CTE (SQLAlchemy 1.4.28 and above):

        edge = Table(
            "edge",
            metadata,
            Column("id", Integer, primary_key=True),
            Column("left", Integer),
            Column("right", Integer),
        )

        root_node = select(literal(1).label("node")).cte("nodes", recursive=True)

        left_edge = select(edge.c.left).join(
            root_node, edge.c.right == root_node.c.node
        )
        right_edge = select(edge.c.right).join(
            root_node, edge.c.left == root_node.c.node
        )

        subgraph_cte = root_node.union(left_edge, right_edge)

        subgraph = select(subgraph_cte)

    The above query will render 2 UNIONs inside the recursive CTE:

        WITH RECURSIVE nodes(node) AS (
                SELECT 1 AS node
            UNION
                SELECT edge."left" AS "left"
                FROM edge JOIN nodes ON edge."right" = nodes.node
            UNION
                SELECT edge."right" AS "right"
                FROM edge JOIN nodes ON edge."left" = nodes.node
        )
        SELECT nodes.node FROM nodes

    See also

    `Query.cte()` - ORM version of `HasCTE.cte()`.

  property dialect_kwargs: _DialectArgView

    A collection of keyword arguments specified as dialect-specific options to this construct.

    The arguments are present here in their original `<dialect>_<kwarg>` format. Only arguments that were actually passed are included; unlike the `DialectKWArgs.dialect_options` collection, which contains all options known by this dialect including defaults.

    The collection is also writable; keys are accepted of the form `<dialect>_<kwarg>` where the value will be assembled into the list of options.

    See also

    `DialectKWArgs.dialect_options` - nested dictionary form

  attribute `sqlalchemy.sql.expression.CompoundSelect.`dialect_options

    inherited from the `DialectKWArgs.dialect_options` attribute of `DialectKWArgs`

    A collection of keyword arguments specified as dialect-specific options to this construct.

    This is a two-level nested registry, keyed to `<dialect_name>` and `<argument_name>`. For example, the `postgresql_where` argument would be locatable as:

        arg = my_object.dialect_options["postgresql"]["where"]

    Added in version 0.9.2.

    See also

    `DialectKWArgs.dialect_kwargs` - flat dictionary form

  method `sqlalchemy.sql.expression.CompoundSelect.`execution_options(**kw: Any) → Self

    inherited from the `Executable.execution_options()` method of `Executable`

    Set non-SQL options for the statement which take effect during execution.

    Execution options can be set at many scopes, including per-statement, per-connection, or per execution, using methods such as `Connection.execution_options()` and parameters which accept a dictionary of options such as `Connection.execute.execution_options` and `Session.execute.execution_options`.

    The primary characteristic of an execution option, as opposed to other kinds of options such as ORM loader options, is that execution options never affect the compiled SQL of a query, only things that affect how the SQL statement itself is invoked or how results are fetched. That is, execution options are not part of what’s accommodated by SQL compilation nor are they considered part of the cached state of a statement.

    The `Executable.execution_options()` method is generative, as is the case for the method as applied to the `Engine` and `Query` objects, which means when the method is called, a copy of the object is returned, which applies the given parameters to that new copy, but leaves the original unchanged:

        statement = select(table.c.x, table.c.y)
        new_statement = statement.execution_options(my_option=True)

    An exception to this behavior is the `Connection` object, where the `Connection.execution_options()` method is explicitly not generative.

    The kinds of options that may be passed to `Executable.execution_options()` and other related methods and parameter dictionaries include parameters that are explicitly consumed by SQLAlchemy Core or ORM, as well as arbitrary keyword arguments not defined by SQLAlchemy, which means the methods and/or parameter dictionaries may be used for user-defined parameters that interact with custom code, which may access the parameters using methods such as `Executable.get_execution_options()` and `Connection.get_execution_options()`, or within selected event hooks using a dedicated `execution_options` event parameter such as `ConnectionEvents.before_execute.execution_options` or `ORMExecuteState.execution_options`, e.g.:

        from sqlalchemy import event

        @event.listens_for(some_engine, "before_execute")
        def _process_opt(conn, statement, multiparams, params, execution_options):
            "run a SQL function before invoking a statement"

            if execution_options.get("do_special_thing", False):
                conn.exec_driver_sql("run_special_function()")

    Within the scope of options that are explicitly recognized by SQLAlchemy, most apply to specific classes of objects and not others. The most common execution options include:

    - `Connection.execution_options.isolation_level` - sets the isolation level for a connection or a class of connections via an `Engine`. This option is accepted only by `Connection` or `Engine`.

    - `Connection.execution_options.stream_results` - indicates results should be fetched using a server side cursor; this option is accepted by `Connection`, by the `Connection.execute.execution_options` parameter on `Connection.execute()`, and additionally by `Executable.execution_options()` on a SQL statement object, as well as by ORM constructs like `Session.execute()`.

    - `Connection.execution_options.compiled_cache` - indicates a dictionary that will serve as the SQL compilation cache for a `Connection` or `Engine`, as well as for ORM methods like `Session.execute()`. Can be passed as `None` to disable caching for statements. This option is not accepted by `Executable.execution_options()` as it is inadvisable to carry along a compilation cache within a statement object.

    - `Connection.execution_options.schema_translate_map` - a mapping of schema names used by the Schema Translate Map feature, accepted by `Connection`, `Engine`, `Executable`, as well as by ORM constructs like `Session.execute()`.

    See also

    `Connection.execution_options()`

    `Connection.execute.execution_options`

    `Session.execute.execution_options`

    ORM Execution Options - documentation on all ORM-specific execution options

  method `sqlalchemy.sql.expression.CompoundSelect.`exists() → Exists

    inherited from the `SelectBase.exists()` method of `SelectBase`

    Return an `Exists` representation of this selectable, which can be used as a column expression.

    The returned object is an instance of `Exists`.

    See also

    `exists()`

    EXISTS subqueries - in the 2.0 style tutorial.

    Added in version 1.4.

  property exported_columns: ReadOnlyColumnCollection[str, ColumnElement[Any]]

    A `ColumnCollection` that represents the “exported” columns of this `Selectable`, not including `TextClause` constructs.

    The “exported” columns for a `SelectBase` object are synonymous with the `SelectBase.selected_columns` collection.

    Added in version 1.4.

    See also

    `Select.exported_columns`

    `Selectable.exported_columns`

    `FromClause.exported_columns`

  method `sqlalchemy.sql.expression.CompoundSelect.`fetch(count: _LimitOffsetType, with_ties: bool = False, percent: bool = False, **dialect_kw: Any) → Self

    inherited from the `GenerativeSelect.fetch()` method of `GenerativeSelect`

    Return a new selectable with the given FETCH FIRST criterion applied.

    This is a numeric value which usually renders as `FETCH {FIRST | NEXT} [ count ] {ROW | ROWS} {ONLY | WITH TIES}` expression in the resulting select. This functionality is is currently implemented for Oracle Database, PostgreSQL, MSSQL.

    Use `GenerativeSelect.offset()` to specify the offset.

    Note

    The `GenerativeSelect.fetch()` method will replace any clause applied with `GenerativeSelect.limit()`.

    Added in version 1.4.

    Parameters:

      - count – an integer COUNT parameter, or a SQL expression that provides an integer result. When `percent=True` this will represent the percentage of rows to return, not the absolute value. Pass `None` to reset it.

      - with_ties – When `True`, the WITH TIES option is used to return any additional rows that tie for the last place in the result set according to the `ORDER BY` clause. The `ORDER BY` may be mandatory in this case. Defaults to `False`

      - percent – When `True`, `count` represents the percentage of the total number of selected rows to return. Defaults to `False`

      - **dialect_kw –

        Additional dialect-specific keyword arguments may be accepted by dialects.

        Added in version 2.0.41.

    See also

    `GenerativeSelect.limit()`

    `GenerativeSelect.offset()`

  method `sqlalchemy.sql.expression.CompoundSelect.`get_children(*, omit_attrs: Tuple[str, ...] = (), **kw: Any) → Iterable[HasTraverseInternals]

    inherited from the `HasTraverseInternals.get_children()` method of `HasTraverseInternals`

    Return immediate child `HasTraverseInternals` elements of this `HasTraverseInternals`.

    This is used for visit traversal.

    **kw may contain flags that change the collection that is returned, for example to return a subset of items in order to cut down on larger traversals, or to return child items from a different context (such as schema-level collections instead of clause-level).

  method `sqlalchemy.sql.expression.CompoundSelect.`get_execution_options() → _ExecuteOptions

    inherited from the `Executable.get_execution_options()` method of `Executable`

    Get the non-SQL options which will take effect during execution.

    See also

    `Executable.execution_options()`

  method `sqlalchemy.sql.expression.CompoundSelect.`get_label_style() → SelectLabelStyle

    inherited from the `GenerativeSelect.get_label_style()` method of `GenerativeSelect`

    Retrieve the current label style.

    Added in version 1.4.

  method `sqlalchemy.sql.expression.CompoundSelect.`group_by(_GenerativeSelect__first: Literal[None, _NoArg.NO_ARG] | _ColumnExpressionOrStrLabelArgument[Any] = _NoArg.NO_ARG, /, *clauses: _ColumnExpressionOrStrLabelArgument[Any]) → Self

    inherited from the `GenerativeSelect.group_by()` method of `GenerativeSelect`

    Return a new selectable with the given list of GROUP BY criterion applied.

    All existing GROUP BY settings can be suppressed by passing `None`.

    e.g.:

        stmt = select(table.c.name, func.max(table.c.stat)).group_by(table.c.name)

    Parameters:

      *clauses –

      a series of `ColumnElement` constructs which will be used to generate an GROUP BY clause.

      Alternatively, an individual entry may also be the string name of a label located elsewhere in the columns clause of the statement which will be matched and rendered in a backend-specific way based on context; see Ordering or Grouping by a Label for background on string label matching in ORDER BY and GROUP BY expressions.

    See also

    Aggregate functions with GROUP BY / HAVING - in the SQLAlchemy Unified Tutorial

    Ordering or Grouping by a Label - in the SQLAlchemy Unified Tutorial

  attribute `sqlalchemy.sql.expression.CompoundSelect.`inherit_cache = None

    inherited from the `HasCacheKey.inherit_cache` attribute of `HasCacheKey`

    Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.

    The attribute defaults to `None`, which indicates that a construct has not yet taken into account whether or not its appropriate for it to participate in caching; this is functionally equivalent to setting the value to `False`, except that a warning is also emitted.

    This flag can be set to `True` on a particular class, if the SQL that corresponds to the object does not change based on attributes which are local to this class, and not its superclass.

    See also

    Enabling Caching Support for Custom Constructs - General guideslines for setting the `HasCacheKey.inherit_cache` attribute for third-party or user defined SQL constructs.

  method `sqlalchemy.sql.expression.CompoundSelect.`into(target: str, *, metadata: 'MetaData' | None = None, schema: str | None = None, temporary: bool = False, if_not_exists: bool = False) → CreateTableAs

    inherited from the `SelectBase.into()` method of `SelectBase`

    Create a `CreateTableAs` construct from this SELECT.

    This method provides a convenient way to create a `CREATE TABLE ... AS` statement from a SELECT, as well as compound SELECTs like UNION. The new table will be created with columns matching the SELECT list.

    Supported on all included backends, the construct emits `CREATE TABLE...AS` for all backends except SQL Server, which instead emits a `SELECT..INTO` statement.

    e.g.:

        from sqlalchemy import select

        # Create a new table from a SELECT
        stmt = (
            select(users.c.id, users.c.name)
            .where(users.c.status == "active")
            .into("active_users")
        )

        with engine.begin() as conn:
            conn.execute(stmt)

        # With optional flags
        stmt = (
            select(users.c.id)
            .where(users.c.status == "inactive")
            .into("inactive_users", schema="analytics", if_not_exists=True)
        )

    Added in version 2.1.

    Parameters:

      - target – Name of the table to create as a string. Must be unqualified; use the `schema` parameter for qualification.

      - metadata – `MetaData`, optional If provided, the `Table` object available via the `CreateTableAs.table` attribute will be associated with this `MetaData`. Otherwise, a new, empty `MetaData` is created.

      - schema – Optional schema name for the new table.

      - temporary – If True, create a temporary table where supported

      - if_not_exists – If True, add IF NOT EXISTS clause where supported

    Returns:

      A `CreateTableAs` construct.

    See also

    Using CreateTableAs or Select.into() - in Describing Databases with MetaData

    `CreateTableAs`

  method `sqlalchemy.sql.expression.CompoundSelect.`is_derived_from(fromclause: FromClause | None) → bool

    Return `True` if this `ReturnsRows` is ‘derived’ from the given `FromClause`.

    An example would be an Alias of a Table is derived from that Table.

  property kwargs: _DialectArgView

    A synonym for `DialectKWArgs.dialect_kwargs`.

  method `sqlalchemy.sql.expression.CompoundSelect.`label(name: str | None) → Label[Any]

    inherited from the `SelectBase.label()` method of `SelectBase`

    Return a ‘scalar’ representation of this selectable, embedded as a subquery with a label.

    See also

    `SelectBase.scalar_subquery()`.

  method `sqlalchemy.sql.expression.CompoundSelect.`lateral(name: str | None = None) → LateralFromClause

    inherited from the `SelectBase.lateral()` method of `SelectBase`

    Return a LATERAL alias of this `Selectable`.

    The return value is the `Lateral` construct also provided by the top-level `lateral()` function.

    See also

    LATERAL correlation - overview of usage.

  method `sqlalchemy.sql.expression.CompoundSelect.`limit(limit: _LimitOffsetType) → Self

    inherited from the `GenerativeSelect.limit()` method of `GenerativeSelect`

    Return a new selectable with the given LIMIT criterion applied.

    This is a numerical value which usually renders as a `LIMIT` expression in the resulting select. Backends that don’t support `LIMIT` will attempt to provide similar functionality.

    Note

    The `GenerativeSelect.limit()` method will replace any clause applied with `GenerativeSelect.fetch()`.

    Parameters:

      limit – an integer LIMIT parameter, or a SQL expression that provides an integer result. Pass `None` to reset it.

    See also

    `GenerativeSelect.fetch()`

    `GenerativeSelect.offset()`

  attribute `sqlalchemy.sql.expression.CompoundSelect.`name_cte_columns = False

    inherited from the `HasCTE.name_cte_columns` attribute of `HasCTE`

    indicates if this HasCTE as contained within a CTE should compel the CTE to render the column names of this object in the WITH clause.

    Added in version 2.0.42.

  method `sqlalchemy.sql.expression.CompoundSelect.`offset(offset: _LimitOffsetType) → Self

    inherited from the `GenerativeSelect.offset()` method of `GenerativeSelect`

    Return a new selectable with the given OFFSET criterion applied.

    This is a numeric value which usually renders as an `OFFSET` expression in the resulting select. Backends that don’t support `OFFSET` will attempt to provide similar functionality.

    Parameters:

      offset – an integer OFFSET parameter, or a SQL expression that provides an integer result. Pass `None` to reset it.

    See also

    `GenerativeSelect.limit()`

    `GenerativeSelect.fetch()`

  method `sqlalchemy.sql.expression.CompoundSelect.`options(*options: ExecutableOption) → Self

    inherited from the `Executable.options()` method of `Executable`

    Apply options to this statement.

    In the general sense, options are any kind of Python object that can be interpreted by systems that consume the statement outside of the regular SQL compiler chain. Specifically, these options are the ORM level options that apply “eager load” and other loading behaviors to an ORM query.

    For background on specific kinds of options for specific kinds of statements, refer to the documentation for those option objects.

    Changed in version 1.4: - added `Executable.options()` to Core statement objects towards the goal of allowing unified Core / ORM querying capabilities.

    See also

    Column Loading Options - refers to options specific to the usage of ORM queries

    Relationship Loading with Loader Options - refers to options specific to the usage of ORM queries

  method `sqlalchemy.sql.expression.CompoundSelect.`order_by(_GenerativeSelect__first: Literal[None, _NoArg.NO_ARG] | _ColumnExpressionOrStrLabelArgument[Any] = _NoArg.NO_ARG, /, *clauses: _ColumnExpressionOrStrLabelArgument[Any]) → Self

    inherited from the `GenerativeSelect.order_by()` method of `GenerativeSelect`

    Return a new selectable with the given list of ORDER BY criteria applied.

    e.g.:

        stmt = select(table).order_by(table.c.id, table.c.name)

    Calling this method multiple times is equivalent to calling it once with all the clauses concatenated. All existing ORDER BY criteria may be cancelled by passing `None` by itself. New ORDER BY criteria may then be added by invoking `Query.order_by()` again, e.g.:

        # will erase all ORDER BY and ORDER BY new_col alone
        stmt = stmt.order_by(None).order_by(new_col)

    Parameters:

      *clauses –

      a series of `ColumnElement` constructs which will be used to generate an ORDER BY clause.

      Alternatively, an individual entry may also be the string name of a label located elsewhere in the columns clause of the statement which will be matched and rendered in a backend-specific way based on context; see Ordering or Grouping by a Label for background on string label matching in ORDER BY and GROUP BY expressions.

    See also

    ORDER BY - in the SQLAlchemy Unified Tutorial

    Ordering or Grouping by a Label - in the SQLAlchemy Unified Tutorial

  method `sqlalchemy.sql.expression.CompoundSelect.`params(_ExecutableStatement__optionaldict: _CoreSingleExecuteParams | None = None, /, **kwargs: Any) → Self

    inherited from the `ExecutableStatement.params()` method of `ExecutableStatement`

    Return a copy with the provided bindparam values.

    Returns a copy of this Executable with bindparam values set to the given dictionary:

        >>> clause = column("x") + bindparam("foo")
        >>> print(clause.compile().params)
        {'foo': None}
        >>> print(clause.params({"foo": 7}).compile().params)
        {'foo': 7}

  method `sqlalchemy.sql.expression.CompoundSelect.`replace_selectable(old: FromClause, alias: Alias) → Self

    inherited from the `Selectable.replace_selectable()` method of `Selectable`

    Replace all occurrences of `FromClause` ‘old’ with the given `Alias` object, returning a copy of this `FromClause`.

    Deprecated since version 1.4: The `Selectable.replace_selectable()` method is deprecated, and will be removed in a future release. Similar functionality is available via the sqlalchemy.sql.visitors module.

  method `sqlalchemy.sql.expression.CompoundSelect.`scalar_subquery() → ScalarSelect[Any]

    inherited from the `SelectBase.scalar_subquery()` method of `SelectBase`

    Return a ‘scalar’ representation of this selectable, which can be used as a column expression.

    The returned object is an instance of `ScalarSelect`.

    Typically, a select statement which has only one column in its columns clause is eligible to be used as a scalar expression. The scalar subquery can then be used in the WHERE clause or columns clause of an enclosing SELECT.

    Note that the scalar subquery differentiates from the FROM-level subquery that can be produced using the `SelectBase.subquery()` method.

    Changed in version 1.4: - the `.as_scalar()` method was renamed to `SelectBase.scalar_subquery()`.

    See also

    Scalar and Correlated Subqueries - in the 2.0 tutorial

  attribute `sqlalchemy.sql.expression.CompoundSelect.`selected_columns

    A `ColumnCollection` representing the columns that this SELECT statement or similar construct returns in its result set, not including `TextClause` constructs.

    For a `CompoundSelect`, the `CompoundSelect.selected_columns` attribute returns the selected columns of the first SELECT statement contained within the series of statements within the set operation.

    See also

    `Select.selected_columns`

    Added in version 1.4.

  method `sqlalchemy.sql.expression.CompoundSelect.`self_group(against: OperatorType | None = None) → GroupedElement

    Apply a ‘grouping’ to this `ClauseElement`.

    This method is overridden by subclasses to return a “grouping” construct, i.e. parenthesis. In particular it’s used by “binary” expressions to provide a grouping around themselves when placed into a larger expression, as well as by `select()` constructs when placed into the FROM clause of another `select()`. (Note that subqueries should be normally created using the `Select.alias()` method, as many platforms require nested SELECT statements to be named).

    As expressions are composed together, the application of `self_group()` is automatic - end-user code should never need to use this method directly. Note that SQLAlchemy’s clause constructs take operator precedence into account - so parenthesis might not be needed, for example, in an expression like `x OR (y AND z)` - AND takes precedence over OR.

    The base `self_group()` method of `ClauseElement` just returns self.

  method `sqlalchemy.sql.expression.CompoundSelect.`set_label_style(style: SelectLabelStyle) → Self

    Return a new selectable with the specified label style.

    There are three “label styles” available, `SelectLabelStyle.LABEL_STYLE_DISAMBIGUATE_ONLY`, `SelectLabelStyle.LABEL_STYLE_TABLENAME_PLUS_COL`, and `SelectLabelStyle.LABEL_STYLE_NONE`. The default style is `SelectLabelStyle.LABEL_STYLE_DISAMBIGUATE_ONLY`.

    In modern SQLAlchemy, there is not generally a need to change the labeling style, as per-expression labels are more effectively used by making use of the `ColumnElement.label()` method. In past versions, `LABEL_STYLE_TABLENAME_PLUS_COL` was used to disambiguate same-named columns from different tables, aliases, or subqueries; the newer `LABEL_STYLE_DISAMBIGUATE_ONLY` now applies labels only to names that conflict with an existing name so that the impact of this labeling is minimal.

    The rationale for disambiguation is mostly so that all column expressions are available from a given `FromClause.c` collection when a subquery is created.

    Added in version 1.4: - the `GenerativeSelect.set_label_style()` method replaces the previous combination of `.apply_labels()`, `.with_labels()` and `use_labels=True` methods and/or parameters.

    See also

    `SelectLabelStyle.LABEL_STYLE_DISAMBIGUATE_ONLY`

    `SelectLabelStyle.LABEL_STYLE_TABLENAME_PLUS_COL`

    `SelectLabelStyle.LABEL_STYLE_NONE`

    `SelectLabelStyle.LABEL_STYLE_DEFAULT`

  method `sqlalchemy.sql.expression.CompoundSelect.`slice(start: int, stop: int) → Self

    inherited from the `GenerativeSelect.slice()` method of `GenerativeSelect`

    Apply LIMIT / OFFSET to this statement based on a slice.

    The start and stop indices behave like the argument to Python’s built-in `range()` function. This method provides an alternative to using `LIMIT`/`OFFSET` to get a slice of the query.

    For example,

        stmt = select(User).order_by(User.id).slice(1, 3)

    renders as

        SELECT users.id AS users_id,
               users.name AS users_name
        FROM users ORDER BY users.id
        LIMIT ? OFFSET ?
        (2, 1)

    Note

    The `GenerativeSelect.slice()` method will replace any clause applied with `GenerativeSelect.fetch()`.

    Added in version 1.4: Added the `GenerativeSelect.slice()` method generalized from the ORM.

    See also

    `GenerativeSelect.limit()`

    `GenerativeSelect.offset()`

    `GenerativeSelect.fetch()`

  method `sqlalchemy.sql.expression.CompoundSelect.`subquery(name: str | None = None) → Subquery

    inherited from the `SelectBase.subquery()` method of `SelectBase`

    Return a subquery of this `SelectBase`.

    A subquery is from a SQL perspective a parenthesized, named construct that can be placed in the FROM clause of another SELECT statement.

    Given a SELECT statement such as:

        stmt = select(table.c.id, table.c.name)

    The above statement might look like:

        SELECT table.id, table.name FROM table

    The subquery form by itself renders the same way, however when embedded into the FROM clause of another SELECT statement, it becomes a named sub-element:

        subq = stmt.subquery()
        new_stmt = select(subq)

    The above renders as:

        SELECT anon_1.id, anon_1.name
        FROM (SELECT table.id, table.name FROM table) AS anon_1

    Historically, `SelectBase.subquery()` is equivalent to calling the `FromClause.alias()` method on a FROM object; however, as a `SelectBase` object is not directly FROM object, the `SelectBase.subquery()` method provides clearer semantics.

    Added in version 1.4.

  method `sqlalchemy.sql.expression.CompoundSelect.`with_for_update(*, nowait: bool = False, read: bool = False, of: _ForUpdateOfArgument | None = None, skip_locked: bool = False, key_share: bool = False) → Self

    inherited from the `GenerativeSelect.with_for_update()` method of `GenerativeSelect`

    Specify a `FOR UPDATE` clause for this `GenerativeSelect`.

    E.g.:

        stmt = select(table).with_for_update(nowait=True)

    On a database like PostgreSQL or Oracle Database, the above would render a statement like:

        SELECT table.a, table.b FROM table FOR UPDATE NOWAIT

    on other backends, the `nowait` option is ignored and instead would produce:

        SELECT table.a, table.b FROM table FOR UPDATE

    When called with no arguments, the statement will render with the suffix `FOR UPDATE`. Additional arguments can then be provided which allow for common database-specific variants.

    Parameters:

      - nowait – boolean; will render `FOR UPDATE NOWAIT` on Oracle Database and PostgreSQL dialects.

      - read – boolean; will render `LOCK IN SHARE MODE` on MySQL, `FOR SHARE` on PostgreSQL. On PostgreSQL, when combined with `nowait`, will render `FOR SHARE NOWAIT`.

      - of – SQL expression or list of SQL expression elements, (typically `Column` objects or a compatible expression, for some backends may also be a table expression) which will render into a `FOR UPDATE OF` clause; supported by PostgreSQL, Oracle Database, some MySQL versions and possibly others. May render as a table or as a column depending on backend.

      - skip_locked – boolean, will render `FOR UPDATE SKIP LOCKED` on Oracle Database and PostgreSQL dialects or `FOR SHARE SKIP LOCKED` if `read=True` is also specified.

      - key_share – boolean, will render `FOR NO KEY UPDATE`, or if combined with `read=True` will render `FOR KEY SHARE`, on the PostgreSQL dialect.

class sqlalchemy.sql.expression.CTE

  inherits from `sqlalchemy.sql.roles.DMLTableRole`, `sqlalchemy.sql.roles.IsCTERole`, `sqlalchemy.sql.expression.Generative`, `sqlalchemy.sql.expression.HasPrefixes`, `sqlalchemy.sql.expression.HasSuffixes`, `sqlalchemy.sql.expression.AliasedReturnsRows`

  Represent a Common Table Expression.

  The `CTE` object is obtained using the `SelectBase.cte()` method from any SELECT statement. A less often available syntax also allows use of the `HasCTE.cte()` method present on DML constructs such as `Insert`, `Update` and `Delete`. See the `HasCTE.cte()` method for usage details on CTEs.

  See also

  Subqueries and CTEs - in the 2.0 tutorial

  `HasCTE.cte()` - examples of calling styles

  Member Name | Description
  --- | ---
  alias() | Return an `Alias` of this `CTE`.
  union() | Return a new `CTE` with a SQL `UNION` of the original CTE against the given selectables provided as positional arguments.
  union_all() | Return a new `CTE` with a SQL `UNION ALL` of the original CTE against the given selectables provided as positional arguments.

  method `sqlalchemy.sql.expression.CTE.`alias(name: str | None = None, flat: bool = False) → CTE

    Return an `Alias` of this `CTE`.

    This method is a CTE-specific specialization of the `FromClause.alias()` method.

    See also

    Using Aliases

    `alias()`

  method `sqlalchemy.sql.expression.CTE.`union(*other: _SelectStatementForCompoundArgument[Any]) → CTE

    Return a new `CTE` with a SQL `UNION` of the original CTE against the given selectables provided as positional arguments.

    Parameters:

      *other –

      one or more elements with which to create a UNION.

      Changed in version 1.4.28: multiple elements are now accepted.

    See also

    `HasCTE.cte()` - examples of calling styles

  method `sqlalchemy.sql.expression.CTE.`union_all(*other: _SelectStatementForCompoundArgument[Any]) → CTE

    Return a new `CTE` with a SQL `UNION ALL` of the original CTE against the given selectables provided as positional arguments.

    Parameters:

      *other –

      one or more elements with which to create a UNION.

      Changed in version 1.4.28: multiple elements are now accepted.

    See also

    `HasCTE.cte()` - examples of calling styles

class sqlalchemy.sql.expression.Executable

  inherits from `sqlalchemy.sql.roles.StatementRole`

  Mark a `ClauseElement` as supporting execution.

  `Executable` is a superclass for all “statement” types of objects, including `select()`, `delete()`, `update()`, `insert()`, `text()`.

  Member Name | Description
  --- | ---
  execution_options() | Set non-SQL options for the statement which take effect during execution.
  get_execution_options() | Get the non-SQL options which will take effect during execution.
  options() | Apply options to this statement.

  method `sqlalchemy.sql.expression.Executable.`execution_options(**kw: Any) → Self

    Set non-SQL options for the statement which take effect during execution.

    Execution options can be set at many scopes, including per-statement, per-connection, or per execution, using methods such as `Connection.execution_options()` and parameters which accept a dictionary of options such as `Connection.execute.execution_options` and `Session.execute.execution_options`.

    The primary characteristic of an execution option, as opposed to other kinds of options such as ORM loader options, is that execution options never affect the compiled SQL of a query, only things that affect how the SQL statement itself is invoked or how results are fetched. That is, execution options are not part of what’s accommodated by SQL compilation nor are they considered part of the cached state of a statement.

    The `Executable.execution_options()` method is generative, as is the case for the method as applied to the `Engine` and `Query` objects, which means when the method is called, a copy of the object is returned, which applies the given parameters to that new copy, but leaves the original unchanged:

        statement = select(table.c.x, table.c.y)
        new_statement = statement.execution_options(my_option=True)

    An exception to this behavior is the `Connection` object, where the `Connection.execution_options()` method is explicitly not generative.

    The kinds of options that may be passed to `Executable.execution_options()` and other related methods and parameter dictionaries include parameters that are explicitly consumed by SQLAlchemy Core or ORM, as well as arbitrary keyword arguments not defined by SQLAlchemy, which means the methods and/or parameter dictionaries may be used for user-defined parameters that interact with custom code, which may access the parameters using methods such as `Executable.get_execution_options()` and `Connection.get_execution_options()`, or within selected event hooks using a dedicated `execution_options` event parameter such as `ConnectionEvents.before_execute.execution_options` or `ORMExecuteState.execution_options`, e.g.:

        from sqlalchemy import event

        @event.listens_for(some_engine, "before_execute")
        def _process_opt(conn, statement, multiparams, params, execution_options):
            "run a SQL function before invoking a statement"

            if execution_options.get("do_special_thing", False):
                conn.exec_driver_sql("run_special_function()")

    Within the scope of options that are explicitly recognized by SQLAlchemy, most apply to specific classes of objects and not others. The most common execution options include:

    - `Connection.execution_options.isolation_level` - sets the isolation level for a connection or a class of connections via an `Engine`. This option is accepted only by `Connection` or `Engine`.

    - `Connection.execution_options.stream_results` - indicates results should be fetched using a server side cursor; this option is accepted by `Connection`, by the `Connection.execute.execution_options` parameter on `Connection.execute()`, and additionally by `Executable.execution_options()` on a SQL statement object, as well as by ORM constructs like `Session.execute()`.

    - `Connection.execution_options.compiled_cache` - indicates a dictionary that will serve as the SQL compilation cache for a `Connection` or `Engine`, as well as for ORM methods like `Session.execute()`. Can be passed as `None` to disable caching for statements. This option is not accepted by `Executable.execution_options()` as it is inadvisable to carry along a compilation cache within a statement object.

    - `Connection.execution_options.schema_translate_map` - a mapping of schema names used by the Schema Translate Map feature, accepted by `Connection`, `Engine`, `Executable`, as well as by ORM constructs like `Session.execute()`.

    See also

    `Connection.execution_options()`

    `Connection.execute.execution_options`

    `Session.execute.execution_options`

    ORM Execution Options - documentation on all ORM-specific execution options

  method `sqlalchemy.sql.expression.Executable.`get_execution_options() → _ExecuteOptions

    Get the non-SQL options which will take effect during execution.

    See also

    `Executable.execution_options()`

  method `sqlalchemy.sql.expression.Executable.`options(*options: ExecutableOption) → Self

    Apply options to this statement.

    In the general sense, options are any kind of Python object that can be interpreted by systems that consume the statement outside of the regular SQL compiler chain. Specifically, these options are the ORM level options that apply “eager load” and other loading behaviors to an ORM query.

    For background on specific kinds of options for specific kinds of statements, refer to the documentation for those option objects.

    Changed in version 1.4: - added `Executable.options()` to Core statement objects towards the goal of allowing unified Core / ORM querying capabilities.

    See also

    Column Loading Options - refers to options specific to the usage of ORM queries

    Relationship Loading with Loader Options - refers to options specific to the usage of ORM queries

class sqlalchemy.sql.expression.ExecutableStatement

  inherits from `sqlalchemy.sql.expression.Executable`

  Executable subclass that implements a lightweight version of `params` that avoids a full cloned traverse.

  Added in version 2.1.

  Member Name | Description
  --- | ---
  params() | Return a copy with the provided bindparam values.

  method `sqlalchemy.sql.expression.ExecutableStatement.`params(_ExecutableStatement__optionaldict: _CoreSingleExecuteParams | None = None, /, **kwargs: Any) → Self

    Return a copy with the provided bindparam values.

    Returns a copy of this Executable with bindparam values set to the given dictionary:

        >>> clause = column("x") + bindparam("foo")
        >>> print(clause.compile().params)
        {'foo': None}
        >>> print(clause.params({"foo": 7}).compile().params)
        {'foo': 7}

class sqlalchemy.sql.expression.Exists

  inherits from `sqlalchemy.sql.expression.UnaryExpression`

  Represent an `EXISTS` clause.

  See `exists()` for a description of usage.

  An `EXISTS` clause can also be constructed from a `select()` instance by calling `SelectBase.exists()`.

  Member Name | Description
  --- | ---
  correlate() | Apply correlation to the subquery noted by this `Exists`.
  correlate_except() | Apply correlation to the subquery noted by this `Exists`.
  inherit_cache | Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.
  select() | Return a SELECT of this `Exists`.
  select_from() | Return a new `Exists` construct, applying the given expression to the `Select.select_from()` method of the select statement contained.
  where() | Return a new `exists()` construct with the given expression added to its WHERE clause, joined to the existing clause via AND, if any.

  method `sqlalchemy.sql.expression.Exists.`correlate(*fromclauses: Literal[None, False] | _FromClauseArgument) → Self

    Apply correlation to the subquery noted by this `Exists`.

    See also

    `ScalarSelect.correlate()`

  method `sqlalchemy.sql.expression.Exists.`correlate_except(*fromclauses: Literal[None, False] | _FromClauseArgument) → Self

    Apply correlation to the subquery noted by this `Exists`.

    See also

    `ScalarSelect.correlate_except()`

  attribute `sqlalchemy.sql.expression.Exists.`inherit_cache = True

    Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.

    The attribute defaults to `None`, which indicates that a construct has not yet taken into account whether or not its appropriate for it to participate in caching; this is functionally equivalent to setting the value to `False`, except that a warning is also emitted.

    This flag can be set to `True` on a particular class, if the SQL that corresponds to the object does not change based on attributes which are local to this class, and not its superclass.

    See also

    Enabling Caching Support for Custom Constructs - General guideslines for setting the `HasCacheKey.inherit_cache` attribute for third-party or user defined SQL constructs.

  method `sqlalchemy.sql.expression.Exists.`select() → Select

    Return a SELECT of this `Exists`.

    e.g.:

        stmt = exists(some_table.c.id).where(some_table.c.id == 5).select()

    This will produce a statement resembling:

        SELECT EXISTS (SELECT id FROM some_table WHERE some_table = :param) AS anon_1

    See also

    `select()` - general purpose method which allows for arbitrary column lists.

  method `sqlalchemy.sql.expression.Exists.`select_from(*froms: _FromClauseArgument) → Self

    Return a new `Exists` construct, applying the given expression to the `Select.select_from()` method of the select statement contained.

    Note

    it is typically preferable to build a `Select` statement first, including the desired WHERE clause, then use the `SelectBase.exists()` method to produce an `Exists` object at once.

  method `sqlalchemy.sql.expression.Exists.`where(*clause: _ColumnExpressionArgument[bool]) → Self

    Return a new `exists()` construct with the given expression added to its WHERE clause, joined to the existing clause via AND, if any.

    Note

    it is typically preferable to build a `Select` statement first, including the desired WHERE clause, then use the `SelectBase.exists()` method to produce an `Exists` object at once.

class sqlalchemy.sql.expression.FromClause

  inherits from `sqlalchemy.sql.roles.AnonymizedFromClauseRole`, `sqlalchemy.sql.expression.Selectable`

  Represent an element that can be used within the `FROM` clause of a `SELECT` statement.

  The most common forms of `FromClause` are the `Table` and the `select()` constructs. Key features common to all `FromClause` objects include:

  - a `c` collection, which provides per-name access to a collection of `ColumnElement` objects.

  - a `primary_key` attribute, which is a collection of all those `ColumnElement` objects that indicate the `primary_key` flag.

  - Methods to generate various derivations of a “from” clause, including `FromClause.alias()`, `FromClause.join()`, `FromClause.select()`.

  Member Name | Description
  --- | ---
  alias() | Return an alias of this `FromClause`.
  c | A synonym for `FromClause.columns`
  columns | A named-based collection of `ColumnElement` objects maintained by this `FromClause`.
  description | A brief description of this `FromClause`.
  entity_namespace | Return a namespace used for name-based access in SQL expressions.
  exported_columns | A `ColumnCollection` that represents the “exported” columns of this `FromClause`.
  foreign_keys | Return the collection of `ForeignKey` marker objects which this FromClause references.
  is_derived_from() | Return `True` if this `FromClause` is ‘derived’ from the given `FromClause`.
  join() | Return a `Join` from this `FromClause` to another `FromClause`.
  outerjoin() | Return a `Join` from this `FromClause` to another `FromClause`, with the “isouter” flag set to True.
  primary_key | Return the iterable collection of `Column` objects which comprise the primary key of this `_selectable.FromClause`.
  schema | Define the ‘schema’ attribute for this `FromClause`.
  select() | Return a SELECT of this `FromClause`.
  tablesample() | Return a TABLESAMPLE alias of this `FromClause`.

  method `sqlalchemy.sql.expression.FromClause.`alias(name: str | None = None, flat: bool = False) → NamedFromClause

    Return an alias of this `FromClause`.

    E.g.:

        a2 = some_table.alias("a2")

    The above code creates an `Alias` object which can be used as a FROM clause in any SELECT statement.

    See also

    Using Aliases

    `alias()`

  attribute `sqlalchemy.sql.expression.FromClause.`c

    A synonym for `FromClause.columns`

    Returns:

      a `ColumnCollection`

  attribute `sqlalchemy.sql.expression.FromClause.`columns

    A named-based collection of `ColumnElement` objects maintained by this `FromClause`.

    The `columns`, or `c` collection, is the gateway to the construction of SQL expressions using table-bound or other selectable-bound columns:

        select(mytable).where(mytable.c.somecolumn == 5)

    Returns:

      a `ColumnCollection` object.

  attribute `sqlalchemy.sql.expression.FromClause.`description

    A brief description of this `FromClause`.

    Used primarily for error message formatting.

  attribute `sqlalchemy.sql.expression.FromClause.`entity_namespace

    Return a namespace used for name-based access in SQL expressions.

    This is the namespace that is used to resolve “filter_by()” type expressions, such as:

        stmt.filter_by(address="some address")

    It defaults to the `.c` collection, however internally it can be overridden using the “entity_namespace” annotation to deliver alternative results.

  attribute `sqlalchemy.sql.expression.FromClause.`exported_columns

    A `ColumnCollection` that represents the “exported” columns of this `FromClause`.

    The “exported” columns for a `FromClause` object are synonymous with the `FromClause.columns` collection.

    Added in version 1.4.

    See also

    `Selectable.exported_columns`

    `SelectBase.exported_columns`

  attribute `sqlalchemy.sql.expression.FromClause.`foreign_keys

    Return the collection of `ForeignKey` marker objects which this FromClause references.

    Each `ForeignKey` is a member of a `Table`-wide `ForeignKeyConstraint`.

    See also

    `Table.foreign_key_constraints`

  method `sqlalchemy.sql.expression.FromClause.`is_derived_from(fromclause: FromClause | None) → bool

    Return `True` if this `FromClause` is ‘derived’ from the given `FromClause`.

    An example would be an Alias of a Table is derived from that Table.

  method `sqlalchemy.sql.expression.FromClause.`join(right: _FromClauseArgument, onclause: _ColumnExpressionArgument[bool] | None = None, isouter: bool = False, full: bool = False) → Join

    Return a `Join` from this `FromClause` to another `FromClause`.

    E.g.:

        from sqlalchemy import join

        j = user_table.join(
            address_table, user_table.c.id == address_table.c.user_id
        )
        stmt = select(user_table).select_from(j)

    would emit SQL along the lines of:

        SELECT user.id, user.name FROM user
        JOIN address ON user.id = address.user_id

    Parameters:

      - right – the right side of the join; this is any `FromClause` object such as a `Table` object, and may also be a selectable-compatible object such as an ORM-mapped class.

      - onclause – a SQL expression representing the ON clause of the join. If left at `None`, `FromClause.join()` will attempt to join the two tables based on a foreign key relationship.

      - isouter – if True, render a LEFT OUTER JOIN, instead of JOIN.

      - full – if True, render a FULL OUTER JOIN, instead of LEFT OUTER JOIN. Implies `FromClause.join.isouter`.

    See also

    `join()` - standalone function

    `Join` - the type of object produced

  method `sqlalchemy.sql.expression.FromClause.`outerjoin(right: _FromClauseArgument, onclause: _ColumnExpressionArgument[bool] | None = None, full: bool = False) → Join

    Return a `Join` from this `FromClause` to another `FromClause`, with the “isouter” flag set to True.

    E.g.:

        from sqlalchemy import outerjoin

        j = user_table.outerjoin(
            address_table, user_table.c.id == address_table.c.user_id
        )

    The above is equivalent to:

        j = user_table.join(
            address_table, user_table.c.id == address_table.c.user_id, isouter=True
        )

    Parameters:

      - right – the right side of the join; this is any `FromClause` object such as a `Table` object, and may also be a selectable-compatible object such as an ORM-mapped class.

      - onclause – a SQL expression representing the ON clause of the join. If left at `None`, `FromClause.join()` will attempt to join the two tables based on a foreign key relationship.

      - full – if True, render a FULL OUTER JOIN, instead of LEFT OUTER JOIN.

    See also

    `FromClause.join()`

    `Join`

  attribute `sqlalchemy.sql.expression.FromClause.`primary_key

    Return the iterable collection of `Column` objects which comprise the primary key of this `_selectable.FromClause`.

    For a `Table` object, this collection is represented by the `PrimaryKeyConstraint` which itself is an iterable collection of `Column` objects.

  attribute `sqlalchemy.sql.expression.FromClause.`schema: str | None = None

    Define the ‘schema’ attribute for this `FromClause`.

    This is typically `None` for most objects except that of `Table`, where it is taken as the value of the `Table.schema` argument.

  method `sqlalchemy.sql.expression.FromClause.`select() → Select

    Return a SELECT of this `FromClause`.

    e.g.:

        stmt = some_table.select().where(some_table.c.id == 5)

    See also

    `select()` - general purpose method which allows for arbitrary column lists.

  method `sqlalchemy.sql.expression.FromClause.`tablesample(sampling: float | Function[Any], name: str | None = None, seed: roles.ExpressionElementRole[Any] | None = None) → TableSample

    Return a TABLESAMPLE alias of this `FromClause`.

    The return value is the `TableSample` construct also provided by the top-level `tablesample()` function.

    See also

    `tablesample()` - usage guidelines and parameters

class sqlalchemy.sql.expression.GenerativeSelect

  inherits from `sqlalchemy.sql.expression.DialectKWArgs`, `sqlalchemy.sql.expression.SelectBase`, `sqlalchemy.sql.expression.Generative`

  Base class for SELECT statements where additional elements can be added.

  This serves as the base for `Select` and `CompoundSelect` where elements such as ORDER BY, GROUP BY can be added and column rendering can be controlled. Compare to `TextualSelect`, which, while it subclasses `SelectBase` and is also a SELECT construct, represents a fixed textual string which cannot be altered at this level, only wrapped as a subquery.

  Member Name | Description
  --- | ---
  fetch() | Return a new selectable with the given FETCH FIRST criterion applied.
  get_label_style() | Retrieve the current label style.
  group_by() | Return a new selectable with the given list of GROUP BY criterion applied.
  limit() | Return a new selectable with the given LIMIT criterion applied.
  offset() | Return a new selectable with the given OFFSET criterion applied.
  order_by() | Return a new selectable with the given list of ORDER BY criteria applied.
  set_label_style() | Return a new selectable with the specified label style.
  slice() | Apply LIMIT / OFFSET to this statement based on a slice.
  with_for_update() | Specify a `FOR UPDATE` clause for this `GenerativeSelect`.

  method `sqlalchemy.sql.expression.GenerativeSelect.`fetch(count: _LimitOffsetType, with_ties: bool = False, percent: bool = False, **dialect_kw: Any) → Self

    Return a new selectable with the given FETCH FIRST criterion applied.

    This is a numeric value which usually renders as `FETCH {FIRST | NEXT} [ count ] {ROW | ROWS} {ONLY | WITH TIES}` expression in the resulting select. This functionality is is currently implemented for Oracle Database, PostgreSQL, MSSQL.

    Use `GenerativeSelect.offset()` to specify the offset.

    Note

    The `GenerativeSelect.fetch()` method will replace any clause applied with `GenerativeSelect.limit()`.

    Added in version 1.4.

    Parameters:

      - count – an integer COUNT parameter, or a SQL expression that provides an integer result. When `percent=True` this will represent the percentage of rows to return, not the absolute value. Pass `None` to reset it.

      - with_ties – When `True`, the WITH TIES option is used to return any additional rows that tie for the last place in the result set according to the `ORDER BY` clause. The `ORDER BY` may be mandatory in this case. Defaults to `False`

      - percent – When `True`, `count` represents the percentage of the total number of selected rows to return. Defaults to `False`

      - **dialect_kw –

        Additional dialect-specific keyword arguments may be accepted by dialects.

        Added in version 2.0.41.

    See also

    `GenerativeSelect.limit()`

    `GenerativeSelect.offset()`

  method `sqlalchemy.sql.expression.GenerativeSelect.`get_label_style() → SelectLabelStyle

    Retrieve the current label style.

    Added in version 1.4.

  method `sqlalchemy.sql.expression.GenerativeSelect.`group_by(_GenerativeSelect__first: Literal[None, _NoArg.NO_ARG] | _ColumnExpressionOrStrLabelArgument[Any] = _NoArg.NO_ARG, /, *clauses: _ColumnExpressionOrStrLabelArgument[Any]) → Self

    Return a new selectable with the given list of GROUP BY criterion applied.

    All existing GROUP BY settings can be suppressed by passing `None`.

    e.g.:

        stmt = select(table.c.name, func.max(table.c.stat)).group_by(table.c.name)

    Parameters:

      *clauses –

      a series of `ColumnElement` constructs which will be used to generate an GROUP BY clause.

      Alternatively, an individual entry may also be the string name of a label located elsewhere in the columns clause of the statement which will be matched and rendered in a backend-specific way based on context; see Ordering or Grouping by a Label for background on string label matching in ORDER BY and GROUP BY expressions.

    See also

    Aggregate functions with GROUP BY / HAVING - in the SQLAlchemy Unified Tutorial

    Ordering or Grouping by a Label - in the SQLAlchemy Unified Tutorial

  method `sqlalchemy.sql.expression.GenerativeSelect.`limit(limit: _LimitOffsetType) → Self

    Return a new selectable with the given LIMIT criterion applied.

    This is a numerical value which usually renders as a `LIMIT` expression in the resulting select. Backends that don’t support `LIMIT` will attempt to provide similar functionality.

    Note

    The `GenerativeSelect.limit()` method will replace any clause applied with `GenerativeSelect.fetch()`.

    Parameters:

      limit – an integer LIMIT parameter, or a SQL expression that provides an integer result. Pass `None` to reset it.

    See also

    `GenerativeSelect.fetch()`

    `GenerativeSelect.offset()`

  method `sqlalchemy.sql.expression.GenerativeSelect.`offset(offset: _LimitOffsetType) → Self

    Return a new selectable with the given OFFSET criterion applied.

    This is a numeric value which usually renders as an `OFFSET` expression in the resulting select. Backends that don’t support `OFFSET` will attempt to provide similar functionality.

    Parameters:

      offset – an integer OFFSET parameter, or a SQL expression that provides an integer result. Pass `None` to reset it.

    See also

    `GenerativeSelect.limit()`

    `GenerativeSelect.fetch()`

  method `sqlalchemy.sql.expression.GenerativeSelect.`order_by(_GenerativeSelect__first: Literal[None, _NoArg.NO_ARG] | _ColumnExpressionOrStrLabelArgument[Any] = _NoArg.NO_ARG, /, *clauses: _ColumnExpressionOrStrLabelArgument[Any]) → Self

    Return a new selectable with the given list of ORDER BY criteria applied.

    e.g.:

        stmt = select(table).order_by(table.c.id, table.c.name)

    Calling this method multiple times is equivalent to calling it once with all the clauses concatenated. All existing ORDER BY criteria may be cancelled by passing `None` by itself. New ORDER BY criteria may then be added by invoking `Query.order_by()` again, e.g.:

        # will erase all ORDER BY and ORDER BY new_col alone
        stmt = stmt.order_by(None).order_by(new_col)

    Parameters:

      *clauses –

      a series of `ColumnElement` constructs which will be used to generate an ORDER BY clause.

      Alternatively, an individual entry may also be the string name of a label located elsewhere in the columns clause of the statement which will be matched and rendered in a backend-specific way based on context; see Ordering or Grouping by a Label for background on string label matching in ORDER BY and GROUP BY expressions.

    See also

    ORDER BY - in the SQLAlchemy Unified Tutorial

    Ordering or Grouping by a Label - in the SQLAlchemy Unified Tutorial

  method `sqlalchemy.sql.expression.GenerativeSelect.`set_label_style(style: SelectLabelStyle) → Self

    Return a new selectable with the specified label style.

    There are three “label styles” available, `SelectLabelStyle.LABEL_STYLE_DISAMBIGUATE_ONLY`, `SelectLabelStyle.LABEL_STYLE_TABLENAME_PLUS_COL`, and `SelectLabelStyle.LABEL_STYLE_NONE`. The default style is `SelectLabelStyle.LABEL_STYLE_DISAMBIGUATE_ONLY`.

    In modern SQLAlchemy, there is not generally a need to change the labeling style, as per-expression labels are more effectively used by making use of the `ColumnElement.label()` method. In past versions, `LABEL_STYLE_TABLENAME_PLUS_COL` was used to disambiguate same-named columns from different tables, aliases, or subqueries; the newer `LABEL_STYLE_DISAMBIGUATE_ONLY` now applies labels only to names that conflict with an existing name so that the impact of this labeling is minimal.

    The rationale for disambiguation is mostly so that all column expressions are available from a given `FromClause.c` collection when a subquery is created.

    Added in version 1.4: - the `GenerativeSelect.set_label_style()` method replaces the previous combination of `.apply_labels()`, `.with_labels()` and `use_labels=True` methods and/or parameters.

    See also

    `SelectLabelStyle.LABEL_STYLE_DISAMBIGUATE_ONLY`

    `SelectLabelStyle.LABEL_STYLE_TABLENAME_PLUS_COL`

    `SelectLabelStyle.LABEL_STYLE_NONE`

    `SelectLabelStyle.LABEL_STYLE_DEFAULT`

  method `sqlalchemy.sql.expression.GenerativeSelect.`slice(start: int, stop: int) → Self

    Apply LIMIT / OFFSET to this statement based on a slice.

    The start and stop indices behave like the argument to Python’s built-in `range()` function. This method provides an alternative to using `LIMIT`/`OFFSET` to get a slice of the query.

    For example,

        stmt = select(User).order_by(User.id).slice(1, 3)

    renders as

        SELECT users.id AS users_id,
               users.name AS users_name
        FROM users ORDER BY users.id
        LIMIT ? OFFSET ?
        (2, 1)

    Note

    The `GenerativeSelect.slice()` method will replace any clause applied with `GenerativeSelect.fetch()`.

    Added in version 1.4: Added the `GenerativeSelect.slice()` method generalized from the ORM.

    See also

    `GenerativeSelect.limit()`

    `GenerativeSelect.offset()`

    `GenerativeSelect.fetch()`

  method `sqlalchemy.sql.expression.GenerativeSelect.`with_for_update(*, nowait: bool = False, read: bool = False, of: _ForUpdateOfArgument | None = None, skip_locked: bool = False, key_share: bool = False) → Self

    Specify a `FOR UPDATE` clause for this `GenerativeSelect`.

    E.g.:

        stmt = select(table).with_for_update(nowait=True)

    On a database like PostgreSQL or Oracle Database, the above would render a statement like:

        SELECT table.a, table.b FROM table FOR UPDATE NOWAIT

    on other backends, the `nowait` option is ignored and instead would produce:

        SELECT table.a, table.b FROM table FOR UPDATE

    When called with no arguments, the statement will render with the suffix `FOR UPDATE`. Additional arguments can then be provided which allow for common database-specific variants.

    Parameters:

      - nowait – boolean; will render `FOR UPDATE NOWAIT` on Oracle Database and PostgreSQL dialects.

      - read – boolean; will render `LOCK IN SHARE MODE` on MySQL, `FOR SHARE` on PostgreSQL. On PostgreSQL, when combined with `nowait`, will render `FOR SHARE NOWAIT`.

      - of – SQL expression or list of SQL expression elements, (typically `Column` objects or a compatible expression, for some backends may also be a table expression) which will render into a `FOR UPDATE OF` clause; supported by PostgreSQL, Oracle Database, some MySQL versions and possibly others. May render as a table or as a column depending on backend.

      - skip_locked – boolean, will render `FOR UPDATE SKIP LOCKED` on Oracle Database and PostgreSQL dialects or `FOR SHARE SKIP LOCKED` if `read=True` is also specified.

      - key_share – boolean, will render `FOR NO KEY UPDATE`, or if combined with `read=True` will render `FOR KEY SHARE`, on the PostgreSQL dialect.

class sqlalchemy.sql.expression.HasCTE

  inherits from `sqlalchemy.sql.roles.HasCTERole`, `sqlalchemy.sql.expression.SelectsRows`

  Mixin that declares a class to include CTE support.

  Member Name | Description
  --- | ---
  add_cte() | Add one or more `CTE` constructs to this statement.
  cte() | Return a new `CTE`, or Common Table Expression instance.
  name_cte_columns | indicates if this HasCTE as contained within a CTE should compel the CTE to render the column names of this object in the WITH clause.

  method `sqlalchemy.sql.expression.HasCTE.`add_cte(*ctes: CTE, nest_here: bool = False) → Self

    Add one or more `CTE` constructs to this statement.

    This method will associate the given `CTE` constructs with the parent statement such that they will each be unconditionally rendered in the WITH clause of the final statement, even if not referenced elsewhere within the statement or any sub-selects.

    The optional `HasCTE.add_cte.nest_here` parameter when set to True will have the effect that each given `CTE` will render in a WITH clause rendered directly along with this statement, rather than being moved to the top of the ultimate rendered statement, even if this statement is rendered as a subquery within a larger statement.

    This method has two general uses. One is to embed CTE statements that serve some purpose without being referenced explicitly, such as the use case of embedding a DML statement such as an INSERT or UPDATE as a CTE inline with a primary statement that may draw from its results indirectly. The other is to provide control over the exact placement of a particular series of CTE constructs that should remain rendered directly in terms of a particular statement that may be nested in a larger statement.

    E.g.:

        from sqlalchemy import table, column, select

        t = table("t", column("c1"), column("c2"))

        ins = t.insert().values({"c1": "x", "c2": "y"}).cte()

        stmt = select(t).add_cte(ins)

    Would render:

        WITH anon_1 AS (
            INSERT INTO t (c1, c2) VALUES (:param_1, :param_2)
        )
        SELECT t.c1, t.c2
        FROM t

    Above, the “anon_1” CTE is not referenced in the SELECT statement, however still accomplishes the task of running an INSERT statement.

    Similarly in a DML-related context, using the PostgreSQL `Insert` construct to generate an “upsert”:

        from sqlalchemy import table, column
        from sqlalchemy.dialects.postgresql import insert

        t = table("t", column("c1"), column("c2"))

        delete_statement_cte = t.delete().where(t.c.c1 < 1).cte("deletions")

        insert_stmt = insert(t).values({"c1": 1, "c2": 2})
        update_statement = insert_stmt.on_conflict_do_update(
            index_elements=[t.c.c1],
            set_={
                "c1": insert_stmt.excluded.c1,
                "c2": insert_stmt.excluded.c2,
            },
        ).add_cte(delete_statement_cte)

        print(update_statement)

    The above statement renders as:

        WITH deletions AS (
            DELETE FROM t WHERE t.c1 < %(c1_1)s
        )
        INSERT INTO t (c1, c2) VALUES (%(c1)s, %(c2)s)
        ON CONFLICT (c1) DO UPDATE SET c1 = excluded.c1, c2 = excluded.c2

    Added in version 1.4.21.

    Parameters:

      - *ctes –

        zero or more `CTE` constructs.

        Changed in version 2.0: Multiple CTE instances are accepted

      - nest_here –

        if True, the given CTE or CTEs will be rendered as though they specified the `HasCTE.cte.nesting` flag to `True` when they were added to this `HasCTE`. Assuming the given CTEs are not referenced in an outer-enclosing statement as well, the CTEs given should render at the level of this statement when this flag is given.

        Added in version 2.0.

        See also

        `HasCTE.cte.nesting`

  method `sqlalchemy.sql.expression.HasCTE.`cte(name: str | None = None, recursive: bool = False, nesting: bool = False) → CTE

    Return a new `CTE`, or Common Table Expression instance.

    Common table expressions are a SQL standard whereby SELECT statements can draw upon secondary statements specified along with the primary statement, using a clause called “WITH”. Special semantics regarding UNION can also be employed to allow “recursive” queries, where a SELECT statement can draw upon the set of rows that have previously been selected.

    CTEs can also be applied to DML constructs UPDATE, INSERT and DELETE on some databases, both as a source of CTE rows when combined with RETURNING, as well as a consumer of CTE rows.

    SQLAlchemy detects `CTE` objects, which are treated similarly to `Alias` objects, as special elements to be delivered to the FROM clause of the statement as well as to a WITH clause at the top of the statement.

    For special prefixes such as PostgreSQL “MATERIALIZED” and “NOT MATERIALIZED”, the `CTE.prefix_with()` method may be used to establish these.

    Parameters:

      - name – name given to the common table expression. Like `FromClause.alias()`, the name can be left as `None` in which case an anonymous symbol will be used at query compile time.

      - recursive – if `True`, will render `WITH RECURSIVE`. A recursive common table expression is intended to be used in conjunction with UNION ALL in order to derive rows from those already selected.

      - nesting –

        if `True`, will render the CTE locally to the statement in which it is referenced. For more complex scenarios, the `HasCTE.add_cte()` method using the `HasCTE.add_cte.nest_here` parameter may also be used to more carefully control the exact placement of a particular CTE.

        Added in version 1.4.24.

        See also

        `HasCTE.add_cte()`

    The following examples include two from PostgreSQL’s documentation at https://www.postgresql.org/docs/current/static/queries-with.html, as well as additional examples.

    Example 1, non recursive:

        from sqlalchemy import (
            Table,
            Column,
            String,
            Integer,
            MetaData,
            select,
            func,
        )

        metadata = MetaData()

        orders = Table(
            "orders",
            metadata,
            Column("region", String),
            Column("amount", Integer),
            Column("product", String),
            Column("quantity", Integer),
        )

        regional_sales = (
            select(orders.c.region, func.sum(orders.c.amount).label("total_sales"))
            .group_by(orders.c.region)
            .cte("regional_sales")
        )

        top_regions = (
            select(regional_sales.c.region)
            .where(
                regional_sales.c.total_sales
                > select(func.sum(regional_sales.c.total_sales) / 10)
            )
            .cte("top_regions")
        )

        statement = (
            select(
                orders.c.region,
                orders.c.product,
                func.sum(orders.c.quantity).label("product_units"),
                func.sum(orders.c.amount).label("product_sales"),
            )
            .where(orders.c.region.in_(select(top_regions.c.region)))
            .group_by(orders.c.region, orders.c.product)
        )

        result = conn.execute(statement).fetchall()

    Example 2, WITH RECURSIVE:

        from sqlalchemy import (
            Table,
            Column,
            String,
            Integer,
            MetaData,
            select,
            func,
        )

        metadata = MetaData()

        parts = Table(
            "parts",
            metadata,
            Column("part", String),
            Column("sub_part", String),
            Column("quantity", Integer),
        )

        included_parts = (
            select(parts.c.sub_part, parts.c.part, parts.c.quantity)
            .where(parts.c.part == "our part")
            .cte(recursive=True)
        )

        incl_alias = included_parts.alias()
        parts_alias = parts.alias()
        included_parts = included_parts.union_all(
            select(
                parts_alias.c.sub_part, parts_alias.c.part, parts_alias.c.quantity
            ).where(parts_alias.c.part == incl_alias.c.sub_part)
        )

        statement = select(
            included_parts.c.sub_part,
            func.sum(included_parts.c.quantity).label("total_quantity"),
        ).group_by(included_parts.c.sub_part)

        result = conn.execute(statement).fetchall()

    Example 3, an upsert using UPDATE and INSERT with CTEs:

        from datetime import date
        from sqlalchemy import (
            MetaData,
            Table,
            Column,
            Integer,
            Date,
            select,
            literal,
            and_,
            exists,
        )

        metadata = MetaData()

        visitors = Table(
            "visitors",
            metadata,
            Column("product_id", Integer, primary_key=True),
            Column("date", Date, primary_key=True),
            Column("count", Integer),
        )

        # add 5 visitors for the product_id == 1
        product_id = 1
        day = date.today()
        count = 5

        update_cte = (
            visitors.update()
            .where(
                and_(visitors.c.product_id == product_id, visitors.c.date == day)
            )
            .values(count=visitors.c.count + count)
            .returning(literal(1))
            .cte("update_cte")
        )

        upsert = visitors.insert().from_select(
            [visitors.c.product_id, visitors.c.date, visitors.c.count],
            select(literal(product_id), literal(day), literal(count)).where(
                ~exists(update_cte.select())
            ),
        )

        connection.execute(upsert)

    Example 4, Nesting CTE (SQLAlchemy 1.4.24 and above):

        value_a = select(literal("root").label("n")).cte("value_a")

        # A nested CTE with the same name as the root one
        value_a_nested = select(literal("nesting").label("n")).cte(
            "value_a", nesting=True
        )

        # Nesting CTEs takes ascendency locally
        # over the CTEs at a higher level
        value_b = select(value_a_nested.c.n).cte("value_b")

        value_ab = select(value_a.c.n.label("a"), value_b.c.n.label("b"))

    The above query will render the second CTE nested inside the first, shown with inline parameters below as:

        WITH
            value_a AS
                (SELECT 'root' AS n),
            value_b AS
                (WITH value_a AS
                    (SELECT 'nesting' AS n)
                SELECT value_a.n AS n FROM value_a)
        SELECT value_a.n AS a, value_b.n AS b
        FROM value_a, value_b

    The same CTE can be set up using the `HasCTE.add_cte()` method as follows (SQLAlchemy 2.0 and above):

        value_a = select(literal("root").label("n")).cte("value_a")

        # A nested CTE with the same name as the root one
        value_a_nested = select(literal("nesting").label("n")).cte("value_a")

        # Nesting CTEs takes ascendency locally
        # over the CTEs at a higher level
        value_b = (
            select(value_a_nested.c.n)
            .add_cte(value_a_nested, nest_here=True)
            .cte("value_b")
        )

        value_ab = select(value_a.c.n.label("a"), value_b.c.n.label("b"))

    Example 5, Non-Linear CTE (SQLAlchemy 1.4.28 and above):

        edge = Table(
            "edge",
            metadata,
            Column("id", Integer, primary_key=True),
            Column("left", Integer),
            Column("right", Integer),
        )

        root_node = select(literal(1).label("node")).cte("nodes", recursive=True)

        left_edge = select(edge.c.left).join(
            root_node, edge.c.right == root_node.c.node
        )
        right_edge = select(edge.c.right).join(
            root_node, edge.c.left == root_node.c.node
        )

        subgraph_cte = root_node.union(left_edge, right_edge)

        subgraph = select(subgraph_cte)

    The above query will render 2 UNIONs inside the recursive CTE:

        WITH RECURSIVE nodes(node) AS (
                SELECT 1 AS node
            UNION
                SELECT edge."left" AS "left"
                FROM edge JOIN nodes ON edge."right" = nodes.node
            UNION
                SELECT edge."right" AS "right"
                FROM edge JOIN nodes ON edge."left" = nodes.node
        )
        SELECT nodes.node FROM nodes

    See also

    `Query.cte()` - ORM version of `HasCTE.cte()`.

  attribute `sqlalchemy.sql.expression.HasCTE.`name_cte_columns: bool = False

    indicates if this HasCTE as contained within a CTE should compel the CTE to render the column names of this object in the WITH clause.

    Added in version 2.0.42.

class sqlalchemy.sql.expression.HasPrefixes

  Member Name | Description
  --- | ---
  prefix_with() | Add one or more expressions following the statement keyword, i.e. SELECT, INSERT, UPDATE, or DELETE. Generative.

  method `sqlalchemy.sql.expression.HasPrefixes.`prefix_with(*prefixes: _TextCoercedExpressionArgument[Any], dialect: str = '*') → Self

    Add one or more expressions following the statement keyword, i.e. SELECT, INSERT, UPDATE, or DELETE. Generative.

    This is used to support backend-specific prefix keywords such as those provided by MySQL.

    E.g.:

        stmt = table.insert().prefix_with("LOW_PRIORITY", dialect="mysql")

        # MySQL 5.7 optimizer hints
        stmt = select(table).prefix_with("/*+ BKA(t1) */", dialect="mysql")

    Multiple prefixes can be specified by multiple calls to `HasPrefixes.prefix_with()`.

    Parameters:

      - *prefixes – textual or `ClauseElement` construct which will be rendered following the INSERT, UPDATE, or DELETE keyword.

      - dialect – optional string dialect name which will limit rendering of this prefix to only that dialect.

class sqlalchemy.sql.expression.HasSuffixes

  Member Name | Description
  --- | ---
  suffix_with() | Add one or more expressions following the statement as a whole.

  method `sqlalchemy.sql.expression.HasSuffixes.`suffix_with(*suffixes: _TextCoercedExpressionArgument[Any], dialect: str = '*') → Self

    Add one or more expressions following the statement as a whole.

    This is used to support backend-specific suffix keywords on certain constructs.

    E.g.:

        stmt = (
            select(col1, col2)
            .cte()
            .suffix_with(
                "cycle empno set y_cycle to 1 default 0", dialect="oracle"
            )
        )

    Multiple suffixes can be specified by multiple calls to `HasSuffixes.suffix_with()`.

    Parameters:

      - *suffixes – textual or `ClauseElement` construct which will be rendered following the target clause.

      - dialect – Optional string dialect name which will limit rendering of this suffix to only that dialect.

class sqlalchemy.sql.expression.Join

  inherits from `sqlalchemy.sql.roles.DMLTableRole`, `sqlalchemy.sql.expression.FromClause`

  Represent a `JOIN` construct between two `FromClause` elements.

  The public constructor function for `Join` is the module-level `join()` function, as well as the `FromClause.join()` method of any `FromClause` (e.g. such as `Table`).

  See also

  `join()`

  `FromClause.join()`

  Member Name | Description
  --- | ---
  __init__() | Construct a new `Join`.
  description |
  is_derived_from() | Return `True` if this `FromClause` is ‘derived’ from the given `FromClause`.
  select() | Create a `Select` from this `Join`.
  self_group() | Apply a ‘grouping’ to this `ClauseElement`.

  method `sqlalchemy.sql.expression.Join.`__init__(left: _FromClauseArgument, right: _FromClauseArgument, onclause: _OnClauseArgument | None = None, isouter: bool = False, full: bool = False)

    Construct a new `Join`.

    The usual entrypoint here is the `join()` function or the `FromClause.join()` method of any `FromClause` object.

  attribute `sqlalchemy.sql.expression.Join.`description
  method `sqlalchemy.sql.expression.Join.`is_derived_from(fromclause: FromClause | None) → bool

    Return `True` if this `FromClause` is ‘derived’ from the given `FromClause`.

    An example would be an Alias of a Table is derived from that Table.

  method `sqlalchemy.sql.expression.Join.`select() → Select

    Create a `Select` from this `Join`.

    E.g.:

        stmt = table_a.join(table_b, table_a.c.id == table_b.c.a_id)

        stmt = stmt.select()

    The above will produce a SQL string resembling:

        SELECT table_a.id, table_a.col, table_b.id, table_b.a_id
        FROM table_a JOIN table_b ON table_a.id = table_b.a_id

  method `sqlalchemy.sql.expression.Join.`self_group(against: OperatorType | None = None) → FromGrouping

    Apply a ‘grouping’ to this `ClauseElement`.

    This method is overridden by subclasses to return a “grouping” construct, i.e. parenthesis. In particular it’s used by “binary” expressions to provide a grouping around themselves when placed into a larger expression, as well as by `select()` constructs when placed into the FROM clause of another `select()`. (Note that subqueries should be normally created using the `Select.alias()` method, as many platforms require nested SELECT statements to be named).

    As expressions are composed together, the application of `self_group()` is automatic - end-user code should never need to use this method directly. Note that SQLAlchemy’s clause constructs take operator precedence into account - so parenthesis might not be needed, for example, in an expression like `x OR (y AND z)` - AND takes precedence over OR.

    The base `self_group()` method of `ClauseElement` just returns self.

class sqlalchemy.sql.expression.Lateral

  inherits from `sqlalchemy.sql.expression.FromClauseAlias`, `sqlalchemy.sql.expression.LateralFromClause`

  Represent a LATERAL subquery.

  This object is constructed from the `lateral()` module level function as well as the `FromClause.lateral()` method available on all `FromClause` subclasses.

  While LATERAL is part of the SQL standard, currently only more recent PostgreSQL versions provide support for this keyword.

  See also

  LATERAL correlation - overview of usage.

  Member Name | Description
  --- | ---
  inherit_cache | Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.

  attribute `sqlalchemy.sql.expression.Lateral.`inherit_cache = True

    Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.

    The attribute defaults to `None`, which indicates that a construct has not yet taken into account whether or not its appropriate for it to participate in caching; this is functionally equivalent to setting the value to `False`, except that a warning is also emitted.

    This flag can be set to `True` on a particular class, if the SQL that corresponds to the object does not change based on attributes which are local to this class, and not its superclass.

    See also

    Enabling Caching Support for Custom Constructs - General guideslines for setting the `HasCacheKey.inherit_cache` attribute for third-party or user defined SQL constructs.

class sqlalchemy.sql.expression.ReturnsRows

  inherits from `sqlalchemy.sql.roles.ReturnsRowsRole`, `sqlalchemy.sql.expression.DQLDMLClauseElement`

  The base-most class for Core constructs that have some concept of columns that can represent rows.

  While the SELECT statement and TABLE are the primary things we think of in this category, DML like INSERT, UPDATE and DELETE can also specify RETURNING which means they can be used in CTEs and other forms, and PostgreSQL has functions that return rows also.

  Added in version 1.4.

  Member Name | Description
  --- | ---
  compile() | Compile this SQL expression.
  get_children() | Return immediate child `HasTraverseInternals` elements of this `HasTraverseInternals`.
  inherit_cache | Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.
  is_derived_from() | Return `True` if this `ReturnsRows` is ‘derived’ from the given `FromClause`.

  method `sqlalchemy.sql.expression.ReturnsRows.`compile(bind: _HasDialect | None = None, dialect: Dialect | None = None, **kw: Any) → Compiled

    inherited from the `CompilerElement.compile()` method of `CompilerElement`

    Compile this SQL expression.

    The return value is a `Compiled` object. Calling `str()` or `unicode()` on the returned value will yield a string representation of the result. The `Compiled` object also can return a dictionary of bind parameter names and values using the `params` accessor.

    Parameters:

      - bind – An `Connection` or `Engine` which can provide a `Dialect` in order to generate a `Compiled` object. If the `bind` and `dialect` parameters are both omitted, a default SQL compiler is used.

      - column_keys – Used for INSERT and UPDATE statements, a list of column names which should be present in the VALUES clause of the compiled statement. If `None`, all columns from the target table object are rendered.

      - dialect – A `Dialect` instance which can generate a `Compiled` object. This argument takes precedence over the `bind` argument.

      - compile_kwargs –

        optional dictionary of additional parameters that will be passed through to the compiler within all “visit” methods. This allows any custom flag to be passed through to a custom compilation construct, for example. It is also used for the case of passing the `literal_binds` flag through:

            from sqlalchemy.sql import table, column, select

            t = table("t", column("x"))

            s = select(t).where(t.c.x == 5)

            print(s.compile(compile_kwargs={"literal_binds": True}))

    See also

    How do I render SQL expressions as strings, possibly with bound parameters inlined?

  property exported_columns: ReadOnlyColumnCollection[Any, Any]

    A `ColumnCollection` that represents the “exported” columns of this `ReturnsRows`.

    The “exported” columns represent the collection of `ColumnElement` expressions that are rendered by this SQL construct. There are primary varieties which are the “FROM clause columns” of a FROM clause, such as a table, join, or subquery, the “SELECTed columns”, which are the columns in the “columns clause” of a SELECT statement, and the RETURNING columns in a DML statement..

    Added in version 1.4.

    See also

    `FromClause.exported_columns`

    `SelectBase.exported_columns`

  method `sqlalchemy.sql.expression.ReturnsRows.`get_children(*, omit_attrs: Tuple[str, ...] = (), **kw: Any) → Iterable[HasTraverseInternals]

    inherited from the `HasTraverseInternals.get_children()` method of `HasTraverseInternals`

    Return immediate child `HasTraverseInternals` elements of this `HasTraverseInternals`.

    This is used for visit traversal.

    **kw may contain flags that change the collection that is returned, for example to return a subset of items in order to cut down on larger traversals, or to return child items from a different context (such as schema-level collections instead of clause-level).

  attribute `sqlalchemy.sql.expression.ReturnsRows.`inherit_cache = None

    inherited from the `HasCacheKey.inherit_cache` attribute of `HasCacheKey`

    Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.

    The attribute defaults to `None`, which indicates that a construct has not yet taken into account whether or not its appropriate for it to participate in caching; this is functionally equivalent to setting the value to `False`, except that a warning is also emitted.

    This flag can be set to `True` on a particular class, if the SQL that corresponds to the object does not change based on attributes which are local to this class, and not its superclass.

    See also

    Enabling Caching Support for Custom Constructs - General guideslines for setting the `HasCacheKey.inherit_cache` attribute for third-party or user defined SQL constructs.

  method `sqlalchemy.sql.expression.ReturnsRows.`is_derived_from(fromclause: FromClause | None) → bool

    Return `True` if this `ReturnsRows` is ‘derived’ from the given `FromClause`.

    An example would be an Alias of a Table is derived from that Table.

class sqlalchemy.sql.expression.ScalarSelect

  inherits from `sqlalchemy.sql.roles.InElementRole`, `sqlalchemy.sql.expression.Generative`, `sqlalchemy.sql.expression.GroupedElement`, `sqlalchemy.sql.expression.ColumnElement`

  Represent a scalar subquery.

  A `ScalarSelect` is created by invoking the `SelectBase.scalar_subquery()` method. The object then participates in other SQL expressions as a SQL column expression within the `ColumnElement` hierarchy.

  See also

  `SelectBase.scalar_subquery()`

  Scalar and Correlated Subqueries - in the 2.0 tutorial

  Member Name | Description
  --- | ---
  correlate() | Return a new `ScalarSelect` which will correlate the given FROM clauses to that of an enclosing `Select`.
  correlate_except() | Return a new `ScalarSelect` which will omit the given FROM clauses from the auto-correlation process.
  inherit_cache | Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.
  self_group() | Apply a ‘grouping’ to this `ClauseElement`.
  where() | Apply a WHERE clause to the SELECT statement referred to by this `ScalarSelect`.

  method `sqlalchemy.sql.expression.ScalarSelect.`correlate(*fromclauses: Literal[None, False] | _FromClauseArgument) → Self

    Return a new `ScalarSelect` which will correlate the given FROM clauses to that of an enclosing `Select`.

    This method is mirrored from the `Select.correlate()` method of the underlying `Select`. The method applies the :meth:_sql.Select.correlate` method, then returns a new `ScalarSelect` against that statement.

    Added in version 1.4: Previously, the `ScalarSelect.correlate()` method was only available from `Select`.

    Parameters:

      *fromclauses – a list of one or more `FromClause` constructs, or other compatible constructs (i.e. ORM-mapped classes) to become part of the correlate collection.

    See also

    `ScalarSelect.correlate_except()`

    Scalar and Correlated Subqueries - in the 2.0 tutorial

  method `sqlalchemy.sql.expression.ScalarSelect.`correlate_except(*fromclauses: Literal[None, False] | _FromClauseArgument) → Self

    Return a new `ScalarSelect` which will omit the given FROM clauses from the auto-correlation process.

    This method is mirrored from the `Select.correlate_except()` method of the underlying `Select`. The method applies the :meth:_sql.Select.correlate_except` method, then returns a new `ScalarSelect` against that statement.

    Added in version 1.4: Previously, the `ScalarSelect.correlate_except()` method was only available from `Select`.

    Parameters:

      *fromclauses – a list of one or more `FromClause` constructs, or other compatible constructs (i.e. ORM-mapped classes) to become part of the correlate-exception collection.

    See also

    `ScalarSelect.correlate()`

    Scalar and Correlated Subqueries - in the 2.0 tutorial

  attribute `sqlalchemy.sql.expression.ScalarSelect.`inherit_cache = True

    Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.

    The attribute defaults to `None`, which indicates that a construct has not yet taken into account whether or not its appropriate for it to participate in caching; this is functionally equivalent to setting the value to `False`, except that a warning is also emitted.

    This flag can be set to `True` on a particular class, if the SQL that corresponds to the object does not change based on attributes which are local to this class, and not its superclass.

    See also

    Enabling Caching Support for Custom Constructs - General guideslines for setting the `HasCacheKey.inherit_cache` attribute for third-party or user defined SQL constructs.

  method `sqlalchemy.sql.expression.ScalarSelect.`self_group(against: OperatorType | None = None) → Self

    Apply a ‘grouping’ to this `ClauseElement`.

    This method is overridden by subclasses to return a “grouping” construct, i.e. parenthesis. In particular it’s used by “binary” expressions to provide a grouping around themselves when placed into a larger expression, as well as by `select()` constructs when placed into the FROM clause of another `select()`. (Note that subqueries should be normally created using the `Select.alias()` method, as many platforms require nested SELECT statements to be named).

    As expressions are composed together, the application of `self_group()` is automatic - end-user code should never need to use this method directly. Note that SQLAlchemy’s clause constructs take operator precedence into account - so parenthesis might not be needed, for example, in an expression like `x OR (y AND z)` - AND takes precedence over OR.

    The base `self_group()` method of `ClauseElement` just returns self.

  method `sqlalchemy.sql.expression.ScalarSelect.`where(crit: _ColumnExpressionArgument[bool]) → Self

    Apply a WHERE clause to the SELECT statement referred to by this `ScalarSelect`.

class sqlalchemy.sql.expression.Select

  inherits from `sqlalchemy.sql.expression.HasPrefixes`, `sqlalchemy.sql.expression.HasSuffixes`, `sqlalchemy.sql.expression.HasHints`, `sqlalchemy.sql.expression.HasCompileState`, `sqlalchemy.sql.expression.HasSyntaxExtensions`, `sqlalchemy.sql.expression._SelectFromElements`, `sqlalchemy.sql.expression.GenerativeSelect`, `sqlalchemy.sql.expression.TypedReturnsRows`

  Represents a `SELECT` statement.

  The `Select` object is normally constructed using the `select()` function. See that function for details.

  Available extension points:

  - `post_select`: applies additional logic after the `SELECT` keyword.

  - `pre_columns`: applies additional logic between the `DISTINCT`

      keyword (if any) and the list of columns.

  - `post_criteria`: applies additional logic after the `HAVING` clause.

  - `post_body`: applies additional logic after the `FOR UPDATE` clause.

  See also

  `select()`

  Using SELECT Statements - in the 2.0 tutorial

  Member Name | Description
  --- | ---
  __init__() | Construct a new `Select`.
  add_columns() | Return a new `select()` construct with the given entities appended to its columns clause.
  add_cte() | Add one or more `CTE` constructs to this statement.
  alias() | Return a named subquery against this `SelectBase`.
  apply_syntax_extension_point() | Apply a `SyntaxExtension` to a known extension point.
  argument_for() | Add a new kind of dialect-specific keyword argument for this class.
  as_scalar() |
  column() | Return a new `select()` construct with the given column expression added to its columns clause.
  compile() | Compile this SQL expression.
  correlate() | Return a new `Select` which will correlate the given FROM clauses to that of an enclosing `Select`.
  correlate_except() | Return a new `Select` which will omit the given FROM clauses from the auto-correlation process.
  corresponding_column() | Given a `ColumnElement`, return the exported `ColumnElement` object from the `Selectable.exported_columns` collection of this `Selectable` which corresponds to that original `ColumnElement` via a common ancestor column.
  cte() | Return a new `CTE`, or Common Table Expression instance.
  dialect_options | A collection of keyword arguments specified as dialect-specific options to this construct.
  distinct() | Return a new `select()` construct which will apply DISTINCT to the SELECT statement overall.
  except_() | Return a SQL `EXCEPT` of this select() construct against the given selectable provided as positional arguments.
  except_all() | Return a SQL `EXCEPT ALL` of this select() construct against the given selectables provided as positional arguments.
  execution_options() | Set non-SQL options for the statement which take effect during execution.
  exists() | Return an `Exists` representation of this selectable, which can be used as a column expression.
  ext() | Applies a SQL syntax extension to this statement.
  fetch() | Return a new selectable with the given FETCH FIRST criterion applied.
  filter() | A synonym for the `Select.where()` method.
  filter_by() | Apply the given filtering criterion as a WHERE clause to this select, using keyword expressions.
  from_statement() | Apply the columns which this `Select` would select onto another statement.
  get_children() | Return immediate child `HasTraverseInternals` elements of this `HasTraverseInternals`.
  get_execution_options() | Get the non-SQL options which will take effect during execution.
  get_final_froms() | Compute the final displayed list of `FromClause` elements.
  get_label_style() | Retrieve the current label style.
  group_by() | Return a new selectable with the given list of GROUP BY criterion applied.
  having() | Return a new `select()` construct with the given expression added to its HAVING clause, joined to the existing clause via AND, if any.
  inherit_cache | Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.
  intersect() | Return a SQL `INTERSECT` of this select() construct against the given selectables provided as positional arguments.
  intersect_all() | Return a SQL `INTERSECT ALL` of this select() construct against the given selectables provided as positional arguments.
  into() | Create a `CreateTableAs` construct from this SELECT.
  is_derived_from() | Return `True` if this `ReturnsRows` is ‘derived’ from the given `FromClause`.
  join() | Create a SQL JOIN against this `Select` object’s criterion and apply generatively, returning the newly resulting `Select`.
  join_from() | Create a SQL JOIN against this `Select` object’s criterion and apply generatively, returning the newly resulting `Select`.
  label() | Return a ‘scalar’ representation of this selectable, embedded as a subquery with a label.
  lateral() | Return a LATERAL alias of this `Selectable`.
  limit() | Return a new selectable with the given LIMIT criterion applied.
  name_cte_columns | indicates if this HasCTE as contained within a CTE should compel the CTE to render the column names of this object in the WITH clause.
  offset() | Return a new selectable with the given OFFSET criterion applied.
  options() | Apply options to this statement.
  order_by() | Return a new selectable with the given list of ORDER BY criteria applied.
  outerjoin() | Create a left outer join.
  outerjoin_from() | Create a SQL LEFT OUTER JOIN against this `Select` object’s criterion and apply generatively, returning the newly resulting `Select`.
  params() | Return a copy with the provided bindparam values.
  prefix_with() | Add one or more expressions following the statement keyword, i.e. SELECT, INSERT, UPDATE, or DELETE. Generative.
  reduce_columns() | Return a new `select()` construct with redundantly named, equivalently-valued columns removed from the columns clause.
  replace_selectable() | Replace all occurrences of `FromClause` ‘old’ with the given `Alias` object, returning a copy of this `FromClause`.
  scalar_subquery() | Return a ‘scalar’ representation of this selectable, which can be used as a column expression.
  select_from() | Return a new `select()` construct with the given FROM expression(s) merged into its list of FROM objects.
  selected_columns | A `ColumnCollection` representing the columns that this SELECT statement or similar construct returns in its result set, not including `TextClause` constructs.
  self_group() | Return a ‘grouping’ construct as per the `ClauseElement` specification.
  set_label_style() | Return a new selectable with the specified label style.
  slice() | Apply LIMIT / OFFSET to this statement based on a slice.
  subquery() | Return a subquery of this `SelectBase`.
  suffix_with() | Add one or more expressions following the statement as a whole.
  union() | Return a SQL `UNION` of this select() construct against the given selectables provided as positional arguments.
  union_all() | Return a SQL `UNION ALL` of this select() construct against the given selectables provided as positional arguments.
  where() | Return a new `select()` construct with the given expression added to its WHERE clause, joined to the existing clause via AND, if any.
  with_for_update() | Specify a `FOR UPDATE` clause for this `GenerativeSelect`.
  with_hint() | Add an indexing or other executional context hint for the given selectable to this `Select` or other selectable object.
  with_only_columns() | Return a new `select()` construct with its columns clause replaced with the given entities.
  with_statement_hint() | Add a statement hint to this `Select` or other selectable object.

  method `sqlalchemy.sql.expression.Select.`__init__(*entities: _ColumnsClauseArgument[Any], **dialect_kw: Any)

    Construct a new `Select`.

    The public constructor for `Select` is the `select()` function.

  method `sqlalchemy.sql.expression.Select.`add_columns(*entities: _ColumnsClauseArgument[Any]) → Select[Unpack[TupleAny]]

    Return a new `select()` construct with the given entities appended to its columns clause.

    E.g.:

        my_select = my_select.add_columns(table.c.new_column)

    The original expressions in the columns clause remain in place. To replace the original expressions with new ones, see the method `Select.with_only_columns()`.

    Parameters:

      *entities – column, table, or other entity expressions to be added to the columns clause

    See also

    `Select.with_only_columns()` - replaces existing expressions rather than appending.

    Selecting Multiple ORM Entities Simultaneously - ORM-centric example

  method `sqlalchemy.sql.expression.Select.`add_cte(*ctes: CTE, nest_here: bool = False) → Self

    inherited from the `HasCTE.add_cte()` method of `HasCTE`

    Add one or more `CTE` constructs to this statement.

    This method will associate the given `CTE` constructs with the parent statement such that they will each be unconditionally rendered in the WITH clause of the final statement, even if not referenced elsewhere within the statement or any sub-selects.

    The optional `HasCTE.add_cte.nest_here` parameter when set to True will have the effect that each given `CTE` will render in a WITH clause rendered directly along with this statement, rather than being moved to the top of the ultimate rendered statement, even if this statement is rendered as a subquery within a larger statement.

    This method has two general uses. One is to embed CTE statements that serve some purpose without being referenced explicitly, such as the use case of embedding a DML statement such as an INSERT or UPDATE as a CTE inline with a primary statement that may draw from its results indirectly. The other is to provide control over the exact placement of a particular series of CTE constructs that should remain rendered directly in terms of a particular statement that may be nested in a larger statement.

    E.g.:

        from sqlalchemy import table, column, select

        t = table("t", column("c1"), column("c2"))

        ins = t.insert().values({"c1": "x", "c2": "y"}).cte()

        stmt = select(t).add_cte(ins)

    Would render:

        WITH anon_1 AS (
            INSERT INTO t (c1, c2) VALUES (:param_1, :param_2)
        )
        SELECT t.c1, t.c2
        FROM t

    Above, the “anon_1” CTE is not referenced in the SELECT statement, however still accomplishes the task of running an INSERT statement.

    Similarly in a DML-related context, using the PostgreSQL `Insert` construct to generate an “upsert”:

        from sqlalchemy import table, column
        from sqlalchemy.dialects.postgresql import insert

        t = table("t", column("c1"), column("c2"))

        delete_statement_cte = t.delete().where(t.c.c1 < 1).cte("deletions")

        insert_stmt = insert(t).values({"c1": 1, "c2": 2})
        update_statement = insert_stmt.on_conflict_do_update(
            index_elements=[t.c.c1],
            set_={
                "c1": insert_stmt.excluded.c1,
                "c2": insert_stmt.excluded.c2,
            },
        ).add_cte(delete_statement_cte)

        print(update_statement)

    The above statement renders as:

        WITH deletions AS (
            DELETE FROM t WHERE t.c1 < %(c1_1)s
        )
        INSERT INTO t (c1, c2) VALUES (%(c1)s, %(c2)s)
        ON CONFLICT (c1) DO UPDATE SET c1 = excluded.c1, c2 = excluded.c2

    Added in version 1.4.21.

    Parameters:

      - *ctes –

        zero or more `CTE` constructs.

        Changed in version 2.0: Multiple CTE instances are accepted

      - nest_here –

        if True, the given CTE or CTEs will be rendered as though they specified the `HasCTE.cte.nesting` flag to `True` when they were added to this `HasCTE`. Assuming the given CTEs are not referenced in an outer-enclosing statement as well, the CTEs given should render at the level of this statement when this flag is given.

        Added in version 2.0.

        See also

        `HasCTE.cte.nesting`

  method `sqlalchemy.sql.expression.Select.`alias(name: str | None = None, flat: bool = False) → Subquery

    inherited from the `SelectBase.alias()` method of `SelectBase`

    Return a named subquery against this `SelectBase`.

    For a `SelectBase` (as opposed to a `FromClause`), this returns a `Subquery` object which behaves mostly the same as the `Alias` object that is used with a `FromClause`.

    Changed in version 1.4: The `SelectBase.alias()` method is now a synonym for the `SelectBase.subquery()` method.

  method `sqlalchemy.sql.expression.Select.`apply_syntax_extension_point(apply_fn: Callable[[Sequence[ClauseElement]], Sequence[ClauseElement]], position: _L) → None

    inherited from the `HasSyntaxExtensions.apply_syntax_extension_point()` method of `HasSyntaxExtensions`

    Apply a `SyntaxExtension` to a known extension point.

    Should be used only internally by `SyntaxExtension`.

    E.g.:

        class Qualify(SyntaxExtension, ClauseElement):

            # ...

            def apply_to_select(self, select_stmt: Select) -> None:
                # append self to existing
                select_stmt.apply_extension_point(
                    lambda existing: [*existing, self], "post_criteria"
                )

        class ReplaceExt(SyntaxExtension, ClauseElement):

            # ...

            def apply_to_select(self, select_stmt: Select) -> None:
                # replace any existing elements regardless of type
                select_stmt.apply_extension_point(
                    lambda existing: [self], "post_criteria"
                )

        class ReplaceOfTypeExt(SyntaxExtension, ClauseElement):

            # ...

            def apply_to_select(self, select_stmt: Select) -> None:
                # replace any existing elements of the same type
                select_stmt.apply_extension_point(
                    self.append_replacing_same_type, "post_criteria"
                )

    Parameters:

      - apply_fn – callable function that will receive a sequence of `ClauseElement` that is already populating the extension point (the sequence is empty if there isn’t one), and should return a new sequence of `ClauseElement` that will newly populate that point. The function typically can choose to concatenate the existing values with the new one, or to replace the values that are there with a new one by returning a list of a single element, or to perform more complex operations like removing only the same type element from the input list of merging already existing elements of the same type. Some examples are shown in the examples above

      - position – string name of the position to apply to. This varies per statement type. IDEs should show the possible values for each statement type as it’s typed with a `typing.Literal` per statement.

    See also

    Extending Statements like SELECT, INSERT, etc

  classmethod `sqlalchemy.sql.expression.Select.`argument_for(dialect_name: str, argument_name: str, default: Any) → None

    inherited from the `DialectKWArgs.argument_for()` method of `DialectKWArgs`

    Add a new kind of dialect-specific keyword argument for this class.

    E.g.:

        Index.argument_for("mydialect", "length", None)

        some_index = Index("a", "b", mydialect_length=5)

    The `DialectKWArgs.argument_for()` method is a per-argument way adding extra arguments to the `DefaultDialect.construct_arguments` dictionary. This dictionary provides a list of argument names accepted by various schema-level constructs on behalf of a dialect.

    New dialects should typically specify this dictionary all at once as a data member of the dialect class. The use case for ad-hoc addition of argument names is typically for end-user code that is also using a custom compilation scheme which consumes the additional arguments.

    Parameters:

      - dialect_name – name of a dialect. The dialect must be locatable, else a `NoSuchModuleError` is raised. The dialect must also include an existing `DefaultDialect.construct_arguments` collection, indicating that it participates in the keyword-argument validation and default system, else `ArgumentError` is raised. If the dialect does not include this collection, then any keyword argument can be specified on behalf of this dialect already. All dialects packaged within SQLAlchemy include this collection, however for third party dialects, support may vary.

      - argument_name – name of the parameter.

      - default – default value of the parameter.

  method `sqlalchemy.sql.expression.Select.`as_scalar() → ScalarSelect[Any]

    inherited from the `SelectBase.as_scalar()` method of `SelectBase`

    Deprecated since version 1.4: The `SelectBase.as_scalar()` method is deprecated and will be removed in a future release. Please refer to `SelectBase.scalar_subquery()`.

  method `sqlalchemy.sql.expression.Select.`column(column: _ColumnsClauseArgument[Any]) → Select[Unpack[TupleAny]]

    Return a new `select()` construct with the given column expression added to its columns clause.

    Deprecated since version 1.4: The `Select.column()` method is deprecated and will be removed in a future release. Please use `Select.add_columns()`

    E.g.:

        my_select = my_select.column(table.c.new_column)

    See the documentation for `Select.with_only_columns()` for guidelines on adding /replacing the columns of a `Select` object.

  property column_descriptions: Any

    Return a plugin-enabled ‘column descriptions’ structure referring to the columns which are SELECTed by this statement.

    This attribute is generally useful when using the ORM, as an extended structure which includes information about mapped entities is returned. The section Inspecting entities and columns from ORM-enabled SELECT and DML statements contains more background.

    For a Core-only statement, the structure returned by this accessor is derived from the same objects that are returned by the `Select.selected_columns` accessor, formatted as a list of dictionaries which contain the keys `name`, `type` and `expr`, which indicate the column expressions to be selected:

        >>> stmt = select(user_table)
        >>> stmt.column_descriptions
        [
            {
                'name': 'id',
                'type': Integer(),
                'expr': Column('id', Integer(), ...)},
            {
                'name': 'name',
                'type': String(length=30),
                'expr': Column('name', String(length=30), ...)}
        ]

    Changed in version 1.4.33: The `Select.column_descriptions` attribute returns a structure for a Core-only set of entities, not just ORM-only entities.

    See also

    `UpdateBase.entity_description` - entity information for an `insert()`, `update()`, or `delete()`

    Inspecting entities and columns from ORM-enabled SELECT and DML statements - ORM background

  property columns_clause_froms: List[FromClause]

    Return the set of `FromClause` objects implied by the columns clause of this SELECT statement.

    Added in version 1.4.23.

    See also

    `Select.froms` - “final” FROM list taking the full statement into account

    `Select.with_only_columns()` - makes use of this collection to set up a new FROM list

  method `sqlalchemy.sql.expression.Select.`compile(bind: _HasDialect | None = None, dialect: Dialect | None = None, **kw: Any) → Compiled

    inherited from the `CompilerElement.compile()` method of `CompilerElement`

    Compile this SQL expression.

    The return value is a `Compiled` object. Calling `str()` or `unicode()` on the returned value will yield a string representation of the result. The `Compiled` object also can return a dictionary of bind parameter names and values using the `params` accessor.

    Parameters:

      - bind – An `Connection` or `Engine` which can provide a `Dialect` in order to generate a `Compiled` object. If the `bind` and `dialect` parameters are both omitted, a default SQL compiler is used.

      - column_keys – Used for INSERT and UPDATE statements, a list of column names which should be present in the VALUES clause of the compiled statement. If `None`, all columns from the target table object are rendered.

      - dialect – A `Dialect` instance which can generate a `Compiled` object. This argument takes precedence over the `bind` argument.

      - compile_kwargs –

        optional dictionary of additional parameters that will be passed through to the compiler within all “visit” methods. This allows any custom flag to be passed through to a custom compilation construct, for example. It is also used for the case of passing the `literal_binds` flag through:

            from sqlalchemy.sql import table, column, select

            t = table("t", column("x"))

            s = select(t).where(t.c.x == 5)

            print(s.compile(compile_kwargs={"literal_binds": True}))

    See also

    How do I render SQL expressions as strings, possibly with bound parameters inlined?

  method `sqlalchemy.sql.expression.Select.`correlate(*fromclauses: Literal[None, False] | _FromClauseArgument) → Self

    Return a new `Select` which will correlate the given FROM clauses to that of an enclosing `Select`.

    Calling this method turns off the `Select` object’s default behavior of “auto-correlation”. Normally, FROM elements which appear in a `Select` that encloses this one via its WHERE clause, ORDER BY, HAVING or columns clause will be omitted from this `Select` object’s FROM clause. Setting an explicit correlation collection using the `Select.correlate()` method provides a fixed list of FROM objects that can potentially take place in this process.

    When `Select.correlate()` is used to apply specific FROM clauses for correlation, the FROM elements become candidates for correlation regardless of how deeply nested this `Select` object is, relative to an enclosing `Select` which refers to the same FROM object. This is in contrast to the behavior of “auto-correlation” which only correlates to an immediate enclosing `Select`. Multi-level correlation ensures that the link between enclosed and enclosing `Select` is always via at least one WHERE/ORDER BY/HAVING/columns clause in order for correlation to take place.

    If `None` is passed, the `Select` object will correlate none of its FROM entries, and all will render unconditionally in the local FROM clause.

    Parameters:

      *fromclauses – one or more `FromClause` or other FROM-compatible construct such as an ORM mapped entity to become part of the correlate collection; alternatively pass a single value `None` to remove all existing correlations.

    See also

    `Select.correlate_except()`

    Scalar and Correlated Subqueries

  method `sqlalchemy.sql.expression.Select.`correlate_except(*fromclauses: Literal[None, False] | _FromClauseArgument) → Self

    Return a new `Select` which will omit the given FROM clauses from the auto-correlation process.

    Calling `Select.correlate_except()` turns off the `Select` object’s default behavior of “auto-correlation” for the given FROM elements. An element specified here will unconditionally appear in the FROM list, while all other FROM elements remain subject to normal auto-correlation behaviors.

    If `None` is passed, or no arguments are passed, the `Select` object will correlate all of its FROM entries.

    Parameters:

      *fromclauses – a list of one or more `FromClause` constructs, or other compatible constructs (i.e. ORM-mapped classes) to become part of the correlate-exception collection.

    See also

    `Select.correlate()`

    Scalar and Correlated Subqueries

  method `sqlalchemy.sql.expression.Select.`corresponding_column(column: KeyedColumnElement[Any], require_embedded: bool = False) → KeyedColumnElement[Any] | None

    inherited from the `Selectable.corresponding_column()` method of `Selectable`

    Given a `ColumnElement`, return the exported `ColumnElement` object from the `Selectable.exported_columns` collection of this `Selectable` which corresponds to that original `ColumnElement` via a common ancestor column.

    Parameters:

      - column – the target `ColumnElement` to be matched.

      - require_embedded – only return corresponding columns for the given `ColumnElement`, if the given `ColumnElement` is actually present within a sub-element of this `Selectable`. Normally the column will match if it merely shares a common ancestor with one of the exported columns of this `Selectable`.

    See also

    `Selectable.exported_columns` - the `ColumnCollection` that is used for the operation.

    `ColumnCollection.corresponding_column()` - implementation method.

  method `sqlalchemy.sql.expression.Select.`cte(name: str | None = None, recursive: bool = False, nesting: bool = False) → CTE

    inherited from the `HasCTE.cte()` method of `HasCTE`

    Return a new `CTE`, or Common Table Expression instance.

    Common table expressions are a SQL standard whereby SELECT statements can draw upon secondary statements specified along with the primary statement, using a clause called “WITH”. Special semantics regarding UNION can also be employed to allow “recursive” queries, where a SELECT statement can draw upon the set of rows that have previously been selected.

    CTEs can also be applied to DML constructs UPDATE, INSERT and DELETE on some databases, both as a source of CTE rows when combined with RETURNING, as well as a consumer of CTE rows.

    SQLAlchemy detects `CTE` objects, which are treated similarly to `Alias` objects, as special elements to be delivered to the FROM clause of the statement as well as to a WITH clause at the top of the statement.

    For special prefixes such as PostgreSQL “MATERIALIZED” and “NOT MATERIALIZED”, the `CTE.prefix_with()` method may be used to establish these.

    Parameters:

      - name – name given to the common table expression. Like `FromClause.alias()`, the name can be left as `None` in which case an anonymous symbol will be used at query compile time.

      - recursive – if `True`, will render `WITH RECURSIVE`. A recursive common table expression is intended to be used in conjunction with UNION ALL in order to derive rows from those already selected.

      - nesting –

        if `True`, will render the CTE locally to the statement in which it is referenced. For more complex scenarios, the `HasCTE.add_cte()` method using the `HasCTE.add_cte.nest_here` parameter may also be used to more carefully control the exact placement of a particular CTE.

        Added in version 1.4.24.

        See also

        `HasCTE.add_cte()`

    The following examples include two from PostgreSQL’s documentation at https://www.postgresql.org/docs/current/static/queries-with.html, as well as additional examples.

    Example 1, non recursive:

        from sqlalchemy import (
            Table,
            Column,
            String,
            Integer,
            MetaData,
            select,
            func,
        )

        metadata = MetaData()

        orders = Table(
            "orders",
            metadata,
            Column("region", String),
            Column("amount", Integer),
            Column("product", String),
            Column("quantity", Integer),
        )

        regional_sales = (
            select(orders.c.region, func.sum(orders.c.amount).label("total_sales"))
            .group_by(orders.c.region)
            .cte("regional_sales")
        )

        top_regions = (
            select(regional_sales.c.region)
            .where(
                regional_sales.c.total_sales
                > select(func.sum(regional_sales.c.total_sales) / 10)
            )
            .cte("top_regions")
        )

        statement = (
            select(
                orders.c.region,
                orders.c.product,
                func.sum(orders.c.quantity).label("product_units"),
                func.sum(orders.c.amount).label("product_sales"),
            )
            .where(orders.c.region.in_(select(top_regions.c.region)))
            .group_by(orders.c.region, orders.c.product)
        )

        result = conn.execute(statement).fetchall()

    Example 2, WITH RECURSIVE:

        from sqlalchemy import (
            Table,
            Column,
            String,
            Integer,
            MetaData,
            select,
            func,
        )

        metadata = MetaData()

        parts = Table(
            "parts",
            metadata,
            Column("part", String),
            Column("sub_part", String),
            Column("quantity", Integer),
        )

        included_parts = (
            select(parts.c.sub_part, parts.c.part, parts.c.quantity)
            .where(parts.c.part == "our part")
            .cte(recursive=True)
        )

        incl_alias = included_parts.alias()
        parts_alias = parts.alias()
        included_parts = included_parts.union_all(
            select(
                parts_alias.c.sub_part, parts_alias.c.part, parts_alias.c.quantity
            ).where(parts_alias.c.part == incl_alias.c.sub_part)
        )

        statement = select(
            included_parts.c.sub_part,
            func.sum(included_parts.c.quantity).label("total_quantity"),
        ).group_by(included_parts.c.sub_part)

        result = conn.execute(statement).fetchall()

    Example 3, an upsert using UPDATE and INSERT with CTEs:

        from datetime import date
        from sqlalchemy import (
            MetaData,
            Table,
            Column,
            Integer,
            Date,
            select,
            literal,
            and_,
            exists,
        )

        metadata = MetaData()

        visitors = Table(
            "visitors",
            metadata,
            Column("product_id", Integer, primary_key=True),
            Column("date", Date, primary_key=True),
            Column("count", Integer),
        )

        # add 5 visitors for the product_id == 1
        product_id = 1
        day = date.today()
        count = 5

        update_cte = (
            visitors.update()
            .where(
                and_(visitors.c.product_id == product_id, visitors.c.date == day)
            )
            .values(count=visitors.c.count + count)
            .returning(literal(1))
            .cte("update_cte")
        )

        upsert = visitors.insert().from_select(
            [visitors.c.product_id, visitors.c.date, visitors.c.count],
            select(literal(product_id), literal(day), literal(count)).where(
                ~exists(update_cte.select())
            ),
        )

        connection.execute(upsert)

    Example 4, Nesting CTE (SQLAlchemy 1.4.24 and above):

        value_a = select(literal("root").label("n")).cte("value_a")

        # A nested CTE with the same name as the root one
        value_a_nested = select(literal("nesting").label("n")).cte(
            "value_a", nesting=True
        )

        # Nesting CTEs takes ascendency locally
        # over the CTEs at a higher level
        value_b = select(value_a_nested.c.n).cte("value_b")

        value_ab = select(value_a.c.n.label("a"), value_b.c.n.label("b"))

    The above query will render the second CTE nested inside the first, shown with inline parameters below as:

        WITH
            value_a AS
                (SELECT 'root' AS n),
            value_b AS
                (WITH value_a AS
                    (SELECT 'nesting' AS n)
                SELECT value_a.n AS n FROM value_a)
        SELECT value_a.n AS a, value_b.n AS b
        FROM value_a, value_b

    The same CTE can be set up using the `HasCTE.add_cte()` method as follows (SQLAlchemy 2.0 and above):

        value_a = select(literal("root").label("n")).cte("value_a")

        # A nested CTE with the same name as the root one
        value_a_nested = select(literal("nesting").label("n")).cte("value_a")

        # Nesting CTEs takes ascendency locally
        # over the CTEs at a higher level
        value_b = (
            select(value_a_nested.c.n)
            .add_cte(value_a_nested, nest_here=True)
            .cte("value_b")
        )

        value_ab = select(value_a.c.n.label("a"), value_b.c.n.label("b"))

    Example 5, Non-Linear CTE (SQLAlchemy 1.4.28 and above):

        edge = Table(
            "edge",
            metadata,
            Column("id", Integer, primary_key=True),
            Column("left", Integer),
            Column("right", Integer),
        )

        root_node = select(literal(1).label("node")).cte("nodes", recursive=True)

        left_edge = select(edge.c.left).join(
            root_node, edge.c.right == root_node.c.node
        )
        right_edge = select(edge.c.right).join(
            root_node, edge.c.left == root_node.c.node
        )

        subgraph_cte = root_node.union(left_edge, right_edge)

        subgraph = select(subgraph_cte)

    The above query will render 2 UNIONs inside the recursive CTE:

        WITH RECURSIVE nodes(node) AS (
                SELECT 1 AS node
            UNION
                SELECT edge."left" AS "left"
                FROM edge JOIN nodes ON edge."right" = nodes.node
            UNION
                SELECT edge."right" AS "right"
                FROM edge JOIN nodes ON edge."left" = nodes.node
        )
        SELECT nodes.node FROM nodes

    See also

    `Query.cte()` - ORM version of `HasCTE.cte()`.

  property dialect_kwargs: _DialectArgView

    A collection of keyword arguments specified as dialect-specific options to this construct.

    The arguments are present here in their original `<dialect>_<kwarg>` format. Only arguments that were actually passed are included; unlike the `DialectKWArgs.dialect_options` collection, which contains all options known by this dialect including defaults.

    The collection is also writable; keys are accepted of the form `<dialect>_<kwarg>` where the value will be assembled into the list of options.

    See also

    `DialectKWArgs.dialect_options` - nested dictionary form

  attribute `sqlalchemy.sql.expression.Select.`dialect_options

    inherited from the `DialectKWArgs.dialect_options` attribute of `DialectKWArgs`

    A collection of keyword arguments specified as dialect-specific options to this construct.

    This is a two-level nested registry, keyed to `<dialect_name>` and `<argument_name>`. For example, the `postgresql_where` argument would be locatable as:

        arg = my_object.dialect_options["postgresql"]["where"]

    Added in version 0.9.2.

    See also

    `DialectKWArgs.dialect_kwargs` - flat dictionary form

  method `sqlalchemy.sql.expression.Select.`distinct(*expr: _ColumnExpressionArgument[Any]) → Self

    Return a new `select()` construct which will apply DISTINCT to the SELECT statement overall.

    E.g.:

        from sqlalchemy import select

        stmt = select(users_table.c.id, users_table.c.name).distinct()

    The above would produce an statement resembling:

        SELECT DISTINCT user.id, user.name FROM user

    The method also historically accepted an `*expr` parameter which produced the PostgreSQL dialect-specific `DISTINCT ON` expression. This is now replaced using the `distinct_on()` extension:

        from sqlalchemy import select
        from sqlalchemy.dialects.postgresql import distinct_on

        stmt = select(users_table).ext(distinct_on(users_table.c.name))

    Using this parameter on other backends which don’t support this syntax will raise an error.

    Parameters:

      *expr –

      optional column expressions. When present, the PostgreSQL dialect will render a `DISTINCT ON (<expressions>)` construct. A deprecation warning and/or `CompileError` will be raised on other backends.

      Deprecated since version 2.1: Passing expressions to `Select.distinct()` is deprecated, use `distinct_on()` instead.

      Deprecated since version 1.4: Using *expr in other dialects is deprecated and will raise `CompileError` in a future version.

    See also

    `distinct_on()`

    `HasSyntaxExtensions.ext()`

  method `sqlalchemy.sql.expression.Select.`except_(*other: _SelectStatementForCompoundArgument[Unpack[_Ts]]) → CompoundSelect[Unpack[_Ts]]

    Return a SQL `EXCEPT` of this select() construct against the given selectable provided as positional arguments.

    Parameters:

      *other –

      one or more elements with which to create a UNION.

      Changed in version 1.4.28: multiple elements are now accepted.

  method `sqlalchemy.sql.expression.Select.`except_all(*other: _SelectStatementForCompoundArgument[Unpack[_Ts]]) → CompoundSelect[Unpack[_Ts]]

    Return a SQL `EXCEPT ALL` of this select() construct against the given selectables provided as positional arguments.

    Parameters:

      *other –

      one or more elements with which to create a UNION.

      Changed in version 1.4.28: multiple elements are now accepted.

  method `sqlalchemy.sql.expression.Select.`execution_options(**kw: Any) → Self

    inherited from the `Executable.execution_options()` method of `Executable`

    Set non-SQL options for the statement which take effect during execution.

    Execution options can be set at many scopes, including per-statement, per-connection, or per execution, using methods such as `Connection.execution_options()` and parameters which accept a dictionary of options such as `Connection.execute.execution_options` and `Session.execute.execution_options`.

    The primary characteristic of an execution option, as opposed to other kinds of options such as ORM loader options, is that execution options never affect the compiled SQL of a query, only things that affect how the SQL statement itself is invoked or how results are fetched. That is, execution options are not part of what’s accommodated by SQL compilation nor are they considered part of the cached state of a statement.

    The `Executable.execution_options()` method is generative, as is the case for the method as applied to the `Engine` and `Query` objects, which means when the method is called, a copy of the object is returned, which applies the given parameters to that new copy, but leaves the original unchanged:

        statement = select(table.c.x, table.c.y)
        new_statement = statement.execution_options(my_option=True)

    An exception to this behavior is the `Connection` object, where the `Connection.execution_options()` method is explicitly not generative.

    The kinds of options that may be passed to `Executable.execution_options()` and other related methods and parameter dictionaries include parameters that are explicitly consumed by SQLAlchemy Core or ORM, as well as arbitrary keyword arguments not defined by SQLAlchemy, which means the methods and/or parameter dictionaries may be used for user-defined parameters that interact with custom code, which may access the parameters using methods such as `Executable.get_execution_options()` and `Connection.get_execution_options()`, or within selected event hooks using a dedicated `execution_options` event parameter such as `ConnectionEvents.before_execute.execution_options` or `ORMExecuteState.execution_options`, e.g.:

        from sqlalchemy import event

        @event.listens_for(some_engine, "before_execute")
        def _process_opt(conn, statement, multiparams, params, execution_options):
            "run a SQL function before invoking a statement"

            if execution_options.get("do_special_thing", False):
                conn.exec_driver_sql("run_special_function()")

    Within the scope of options that are explicitly recognized by SQLAlchemy, most apply to specific classes of objects and not others. The most common execution options include:

    - `Connection.execution_options.isolation_level` - sets the isolation level for a connection or a class of connections via an `Engine`. This option is accepted only by `Connection` or `Engine`.

    - `Connection.execution_options.stream_results` - indicates results should be fetched using a server side cursor; this option is accepted by `Connection`, by the `Connection.execute.execution_options` parameter on `Connection.execute()`, and additionally by `Executable.execution_options()` on a SQL statement object, as well as by ORM constructs like `Session.execute()`.

    - `Connection.execution_options.compiled_cache` - indicates a dictionary that will serve as the SQL compilation cache for a `Connection` or `Engine`, as well as for ORM methods like `Session.execute()`. Can be passed as `None` to disable caching for statements. This option is not accepted by `Executable.execution_options()` as it is inadvisable to carry along a compilation cache within a statement object.

    - `Connection.execution_options.schema_translate_map` - a mapping of schema names used by the Schema Translate Map feature, accepted by `Connection`, `Engine`, `Executable`, as well as by ORM constructs like `Session.execute()`.

    See also

    `Connection.execution_options()`

    `Connection.execute.execution_options`

    `Session.execute.execution_options`

    ORM Execution Options - documentation on all ORM-specific execution options

  method `sqlalchemy.sql.expression.Select.`exists() → Exists

    inherited from the `SelectBase.exists()` method of `SelectBase`

    Return an `Exists` representation of this selectable, which can be used as a column expression.

    The returned object is an instance of `Exists`.

    See also

    `exists()`

    EXISTS subqueries - in the 2.0 style tutorial.

    Added in version 1.4.

  property exported_columns: ReadOnlyColumnCollection[str, ColumnElement[Any]]

    A `ColumnCollection` that represents the “exported” columns of this `Selectable`, not including `TextClause` constructs.

    The “exported” columns for a `SelectBase` object are synonymous with the `SelectBase.selected_columns` collection.

    Added in version 1.4.

    See also

    `Select.exported_columns`

    `Selectable.exported_columns`

    `FromClause.exported_columns`

  method `sqlalchemy.sql.expression.Select.`ext(extension: SyntaxExtension) → Self

    inherited from the `HasSyntaxExtensions.ext()` method of `HasSyntaxExtensions`

    Applies a SQL syntax extension to this statement.

    SQL syntax extensions are `ClauseElement` objects that define some vendor-specific syntactical construct that take place in specific parts of a SQL statement. Examples include vendor extensions like PostgreSQL / SQLite’s “ON DUPLICATE KEY UPDATE”, PostgreSQL’s “DISTINCT ON”, and MySQL’s “LIMIT” that can be applied to UPDATE and DELETE statements.

    See also

    Extending Statements like SELECT, INSERT, etc

    `limit()` - DML LIMIT for MySQL

    `distinct_on()` - DISTINCT ON for PostgreSQL

    Added in version 2.1.

  method `sqlalchemy.sql.expression.Select.`fetch(count: _LimitOffsetType, with_ties: bool = False, percent: bool = False, **dialect_kw: Any) → Self

    inherited from the `GenerativeSelect.fetch()` method of `GenerativeSelect`

    Return a new selectable with the given FETCH FIRST criterion applied.

    This is a numeric value which usually renders as `FETCH {FIRST | NEXT} [ count ] {ROW | ROWS} {ONLY | WITH TIES}` expression in the resulting select. This functionality is is currently implemented for Oracle Database, PostgreSQL, MSSQL.

    Use `GenerativeSelect.offset()` to specify the offset.

    Note

    The `GenerativeSelect.fetch()` method will replace any clause applied with `GenerativeSelect.limit()`.

    Added in version 1.4.

    Parameters:

      - count – an integer COUNT parameter, or a SQL expression that provides an integer result. When `percent=True` this will represent the percentage of rows to return, not the absolute value. Pass `None` to reset it.

      - with_ties – When `True`, the WITH TIES option is used to return any additional rows that tie for the last place in the result set according to the `ORDER BY` clause. The `ORDER BY` may be mandatory in this case. Defaults to `False`

      - percent – When `True`, `count` represents the percentage of the total number of selected rows to return. Defaults to `False`

      - **dialect_kw –

        Additional dialect-specific keyword arguments may be accepted by dialects.

        Added in version 2.0.41.

    See also

    `GenerativeSelect.limit()`

    `GenerativeSelect.offset()`

  method `sqlalchemy.sql.expression.Select.`filter(*criteria: _ColumnExpressionArgument[bool]) → Self

    A synonym for the `Select.where()` method.

  method `sqlalchemy.sql.expression.Select.`filter_by(**kwargs: Any) → Self

    Apply the given filtering criterion as a WHERE clause to this select, using keyword expressions.

    E.g.:

        stmt = select(User).filter_by(name="some name")

    Multiple criteria may be specified as comma separated; the effect is that they will be joined together using the `and_()` function:

        stmt = select(User).filter_by(name="some name", id=5)

    The keyword expressions are extracted by searching across all entities present in the FROM clause of the statement. If a keyword name is present in more than one entity, `AmbiguousColumnError` is raised. In this case, use `Select.filter()` or `Select.where()` with explicit column references:

        # both User and Address have an 'id' attribute
        stmt = select(User).join(Address).filter_by(id=5)
        # raises AmbiguousColumnError

        # use filter() with explicit qualification instead
        stmt = select(User).join(Address).filter(Address.id == 5)

    Changed in version 2.1: `Select.filter_by()` now searches across all FROM clause entities rather than only searching the last joined entity or first FROM entity. This allows the method to locate attributes unambiguously across multiple joined tables. The new `AmbiguousColumnError` is raised when an attribute name is present in more than one entity.

    See filter_by() now searches across all FROM clause entities for migration notes.

    See also

    Using SELECT Statements - in the SQLAlchemy Unified Tutorial

    `Select.filter()` - filter on SQL expressions.

    `Select.where()` - filter on SQL expressions.

  method `sqlalchemy.sql.expression.Select.`from_statement(statement: ReturnsRowsRole) → ExecutableReturnsRows

    Apply the columns which this `Select` would select onto another statement.

    This operation is plugin-specific and will raise a not supported exception if this `Select` does not select from plugin-enabled entities.

    The statement is typically either a `text()` or `select()` construct, and should return the set of columns appropriate to the entities represented by this `Select`.

    See also

    Getting ORM Results from Textual Statements - usage examples in the ORM Querying Guide

  property froms: Sequence[FromClause]

    Return the displayed list of `FromClause` elements.

    Deprecated since version 1.4.23: The `Select.froms` attribute is moved to the `Select.get_final_froms()` method.

  method `sqlalchemy.sql.expression.Select.`get_children(**kw: Any) → Iterable[ClauseElement]

    Return immediate child `HasTraverseInternals` elements of this `HasTraverseInternals`.

    This is used for visit traversal.

    **kw may contain flags that change the collection that is returned, for example to return a subset of items in order to cut down on larger traversals, or to return child items from a different context (such as schema-level collections instead of clause-level).

  method `sqlalchemy.sql.expression.Select.`get_execution_options() → _ExecuteOptions

    inherited from the `Executable.get_execution_options()` method of `Executable`

    Get the non-SQL options which will take effect during execution.

    See also

    `Executable.execution_options()`

  method `sqlalchemy.sql.expression.Select.`get_final_froms() → Sequence[FromClause]

    Compute the final displayed list of `FromClause` elements.

    This method will run through the full computation required to determine what FROM elements will be displayed in the resulting SELECT statement, including shadowing individual tables with JOIN objects, as well as full computation for ORM use cases including eager loading clauses.

    For ORM use, this accessor returns the post compilation list of FROM objects; this collection will include elements such as eagerly loaded tables and joins. The objects will not be ORM enabled and not work as a replacement for the `Select.select_froms()` collection; additionally, the method is not well performing for an ORM enabled statement as it will incur the full ORM construction process.

    To retrieve the FROM list that’s implied by the “columns” collection passed to the `Select` originally, use the `Select.columns_clause_froms` accessor.

    To select from an alternative set of columns while maintaining the FROM list, use the `Select.with_only_columns()` method and pass the `Select.with_only_columns.maintain_column_froms` parameter.

    Added in version 1.4.23: - the `Select.get_final_froms()` method replaces the previous `Select.froms` accessor, which is deprecated.

    See also

    `Select.columns_clause_froms`

  method `sqlalchemy.sql.expression.Select.`get_label_style() → SelectLabelStyle

    inherited from the `GenerativeSelect.get_label_style()` method of `GenerativeSelect`

    Retrieve the current label style.

    Added in version 1.4.

  method `sqlalchemy.sql.expression.Select.`group_by(_GenerativeSelect__first: Literal[None, _NoArg.NO_ARG] | _ColumnExpressionOrStrLabelArgument[Any] = _NoArg.NO_ARG, /, *clauses: _ColumnExpressionOrStrLabelArgument[Any]) → Self

    inherited from the `GenerativeSelect.group_by()` method of `GenerativeSelect`

    Return a new selectable with the given list of GROUP BY criterion applied.

    All existing GROUP BY settings can be suppressed by passing `None`.

    e.g.:

        stmt = select(table.c.name, func.max(table.c.stat)).group_by(table.c.name)

    Parameters:

      *clauses –

      a series of `ColumnElement` constructs which will be used to generate an GROUP BY clause.

      Alternatively, an individual entry may also be the string name of a label located elsewhere in the columns clause of the statement which will be matched and rendered in a backend-specific way based on context; see Ordering or Grouping by a Label for background on string label matching in ORDER BY and GROUP BY expressions.

    See also

    Aggregate functions with GROUP BY / HAVING - in the SQLAlchemy Unified Tutorial

    Ordering or Grouping by a Label - in the SQLAlchemy Unified Tutorial

  method `sqlalchemy.sql.expression.Select.`having(*having: _ColumnExpressionArgument[bool]) → Self

    Return a new `select()` construct with the given expression added to its HAVING clause, joined to the existing clause via AND, if any.

  attribute `sqlalchemy.sql.expression.Select.`inherit_cache = None

    inherited from the `HasCacheKey.inherit_cache` attribute of `HasCacheKey`

    Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.

    The attribute defaults to `None`, which indicates that a construct has not yet taken into account whether or not its appropriate for it to participate in caching; this is functionally equivalent to setting the value to `False`, except that a warning is also emitted.

    This flag can be set to `True` on a particular class, if the SQL that corresponds to the object does not change based on attributes which are local to this class, and not its superclass.

    See also

    Enabling Caching Support for Custom Constructs - General guideslines for setting the `HasCacheKey.inherit_cache` attribute for third-party or user defined SQL constructs.

  property inner_columns: _SelectIterable

    An iterator of all `ColumnElement` expressions which would be rendered into the columns clause of the resulting SELECT statement.

    This method is legacy as of 1.4 and is superseded by the `Select.exported_columns` collection.

  method `sqlalchemy.sql.expression.Select.`intersect(*other: _SelectStatementForCompoundArgument[Unpack[_Ts]]) → CompoundSelect[Unpack[_Ts]]

    Return a SQL `INTERSECT` of this select() construct against the given selectables provided as positional arguments.

    Parameters:

      - *other –

        one or more elements with which to create a UNION.

        Changed in version 1.4.28: multiple elements are now accepted.

      - **kwargs – keyword arguments are forwarded to the constructor for the newly created `CompoundSelect` object.

  method `sqlalchemy.sql.expression.Select.`intersect_all(*other: _SelectStatementForCompoundArgument[Unpack[_Ts]]) → CompoundSelect[Unpack[_Ts]]

    Return a SQL `INTERSECT ALL` of this select() construct against the given selectables provided as positional arguments.

    Parameters:

      - *other –

        one or more elements with which to create a UNION.

        Changed in version 1.4.28: multiple elements are now accepted.

      - **kwargs – keyword arguments are forwarded to the constructor for the newly created `CompoundSelect` object.

  method `sqlalchemy.sql.expression.Select.`into(target: str, *, metadata: 'MetaData' | None = None, schema: str | None = None, temporary: bool = False, if_not_exists: bool = False) → CreateTableAs

    inherited from the `SelectBase.into()` method of `SelectBase`

    Create a `CreateTableAs` construct from this SELECT.

    This method provides a convenient way to create a `CREATE TABLE ... AS` statement from a SELECT, as well as compound SELECTs like UNION. The new table will be created with columns matching the SELECT list.

    Supported on all included backends, the construct emits `CREATE TABLE...AS` for all backends except SQL Server, which instead emits a `SELECT..INTO` statement.

    e.g.:

        from sqlalchemy import select

        # Create a new table from a SELECT
        stmt = (
            select(users.c.id, users.c.name)
            .where(users.c.status == "active")
            .into("active_users")
        )

        with engine.begin() as conn:
            conn.execute(stmt)

        # With optional flags
        stmt = (
            select(users.c.id)
            .where(users.c.status == "inactive")
            .into("inactive_users", schema="analytics", if_not_exists=True)
        )

    Added in version 2.1.

    Parameters:

      - target – Name of the table to create as a string. Must be unqualified; use the `schema` parameter for qualification.

      - metadata – `MetaData`, optional If provided, the `Table` object available via the `CreateTableAs.table` attribute will be associated with this `MetaData`. Otherwise, a new, empty `MetaData` is created.

      - schema – Optional schema name for the new table.

      - temporary – If True, create a temporary table where supported

      - if_not_exists – If True, add IF NOT EXISTS clause where supported

    Returns:

      A `CreateTableAs` construct.

    See also

    Using CreateTableAs or Select.into() - in Describing Databases with MetaData

    `CreateTableAs`

  method `sqlalchemy.sql.expression.Select.`is_derived_from(fromclause: FromClause | None) → bool

    Return `True` if this `ReturnsRows` is ‘derived’ from the given `FromClause`.

    An example would be an Alias of a Table is derived from that Table.

  method `sqlalchemy.sql.expression.Select.`join(target: _JoinTargetArgument, onclause: _OnClauseArgument | None = None, *, isouter: bool = False, full: bool = False) → Self

    Create a SQL JOIN against this `Select` object’s criterion and apply generatively, returning the newly resulting `Select`.

    E.g.:

        stmt = select(user_table).join(
            address_table, user_table.c.id == address_table.c.user_id
        )

    The above statement generates SQL similar to:

        SELECT user.id, user.name
        FROM user
        JOIN address ON user.id = address.user_id

    Changed in version 1.4: `Select.join()` now creates a `Join` object between a `FromClause` source that is within the FROM clause of the existing SELECT, and a given target `FromClause`, and then adds this `Join` to the FROM clause of the newly generated SELECT statement. This is completely reworked from the behavior in 1.3, which would instead create a subquery of the entire `Select` and then join that subquery to the target.

    This is a backwards incompatible change as the previous behavior was mostly useless, producing an unnamed subquery rejected by most databases in any case. The new behavior is modeled after that of the very successful `Query.join()` method in the ORM, in order to support the functionality of `Query` being available by using a `Select` object with an `Session`.

    See the notes for this change at select().join() and outerjoin() add JOIN criteria to the current query, rather than creating a subquery.

    Parameters:

      - target – target table to join towards

      - onclause – ON clause of the join. If omitted, an ON clause is generated automatically based on the `ForeignKey` linkages between the two tables, if one can be unambiguously determined, otherwise an error is raised.

      - isouter – if True, generate LEFT OUTER join. Same as `Select.outerjoin()`.

      - full – if True, generate FULL OUTER join.

    See also

    Explicit FROM clauses and JOINs - in the SQLAlchemy Unified Tutorial

    Joins - in the ORM Querying Guide

    `Select.join_from()`

    `Select.outerjoin()`

  method `sqlalchemy.sql.expression.Select.`join_from(from_: _FromClauseArgument, target: _JoinTargetArgument, onclause: _OnClauseArgument | None = None, *, isouter: bool = False, full: bool = False) → Self

    Create a SQL JOIN against this `Select` object’s criterion and apply generatively, returning the newly resulting `Select`.

    E.g.:

        stmt = select(user_table, address_table).join_from(
            user_table, address_table, user_table.c.id == address_table.c.user_id
        )

    The above statement generates SQL similar to:

        SELECT user.id, user.name, address.id, address.email, address.user_id
        FROM user JOIN address ON user.id = address.user_id

    Added in version 1.4.

    Parameters:

      - from_ – the left side of the join, will be rendered in the FROM clause and is roughly equivalent to using the `Select.select_from()` method.

      - target – target table to join towards

      - onclause – ON clause of the join.

      - isouter – if True, generate LEFT OUTER join. Same as `Select.outerjoin()`.

      - full – if True, generate FULL OUTER join.

    See also

    Explicit FROM clauses and JOINs - in the SQLAlchemy Unified Tutorial

    Joins - in the ORM Querying Guide

    `Select.join()`

  property kwargs: _DialectArgView

    A synonym for `DialectKWArgs.dialect_kwargs`.

  method `sqlalchemy.sql.expression.Select.`label(name: str | None) → Label[Any]

    inherited from the `SelectBase.label()` method of `SelectBase`

    Return a ‘scalar’ representation of this selectable, embedded as a subquery with a label.

    See also

    `SelectBase.scalar_subquery()`.

  method `sqlalchemy.sql.expression.Select.`lateral(name: str | None = None) → LateralFromClause

    inherited from the `SelectBase.lateral()` method of `SelectBase`

    Return a LATERAL alias of this `Selectable`.

    The return value is the `Lateral` construct also provided by the top-level `lateral()` function.

    See also

    LATERAL correlation - overview of usage.

  method `sqlalchemy.sql.expression.Select.`limit(limit: _LimitOffsetType) → Self

    inherited from the `GenerativeSelect.limit()` method of `GenerativeSelect`

    Return a new selectable with the given LIMIT criterion applied.

    This is a numerical value which usually renders as a `LIMIT` expression in the resulting select. Backends that don’t support `LIMIT` will attempt to provide similar functionality.

    Note

    The `GenerativeSelect.limit()` method will replace any clause applied with `GenerativeSelect.fetch()`.

    Parameters:

      limit – an integer LIMIT parameter, or a SQL expression that provides an integer result. Pass `None` to reset it.

    See also

    `GenerativeSelect.fetch()`

    `GenerativeSelect.offset()`

  attribute `sqlalchemy.sql.expression.Select.`name_cte_columns = False

    inherited from the `HasCTE.name_cte_columns` attribute of `HasCTE`

    indicates if this HasCTE as contained within a CTE should compel the CTE to render the column names of this object in the WITH clause.

    Added in version 2.0.42.

  method `sqlalchemy.sql.expression.Select.`offset(offset: _LimitOffsetType) → Self

    inherited from the `GenerativeSelect.offset()` method of `GenerativeSelect`

    Return a new selectable with the given OFFSET criterion applied.

    This is a numeric value which usually renders as an `OFFSET` expression in the resulting select. Backends that don’t support `OFFSET` will attempt to provide similar functionality.

    Parameters:

      offset – an integer OFFSET parameter, or a SQL expression that provides an integer result. Pass `None` to reset it.

    See also

    `GenerativeSelect.limit()`

    `GenerativeSelect.fetch()`

  method `sqlalchemy.sql.expression.Select.`options(*options: ExecutableOption) → Self

    inherited from the `Executable.options()` method of `Executable`

    Apply options to this statement.

    In the general sense, options are any kind of Python object that can be interpreted by systems that consume the statement outside of the regular SQL compiler chain. Specifically, these options are the ORM level options that apply “eager load” and other loading behaviors to an ORM query.

    For background on specific kinds of options for specific kinds of statements, refer to the documentation for those option objects.

    Changed in version 1.4: - added `Executable.options()` to Core statement objects towards the goal of allowing unified Core / ORM querying capabilities.

    See also

    Column Loading Options - refers to options specific to the usage of ORM queries

    Relationship Loading with Loader Options - refers to options specific to the usage of ORM queries

  method `sqlalchemy.sql.expression.Select.`order_by(_GenerativeSelect__first: Literal[None, _NoArg.NO_ARG] | _ColumnExpressionOrStrLabelArgument[Any] = _NoArg.NO_ARG, /, *clauses: _ColumnExpressionOrStrLabelArgument[Any]) → Self

    inherited from the `GenerativeSelect.order_by()` method of `GenerativeSelect`

    Return a new selectable with the given list of ORDER BY criteria applied.

    e.g.:

        stmt = select(table).order_by(table.c.id, table.c.name)

    Calling this method multiple times is equivalent to calling it once with all the clauses concatenated. All existing ORDER BY criteria may be cancelled by passing `None` by itself. New ORDER BY criteria may then be added by invoking `Query.order_by()` again, e.g.:

        # will erase all ORDER BY and ORDER BY new_col alone
        stmt = stmt.order_by(None).order_by(new_col)

    Parameters:

      *clauses –

      a series of `ColumnElement` constructs which will be used to generate an ORDER BY clause.

      Alternatively, an individual entry may also be the string name of a label located elsewhere in the columns clause of the statement which will be matched and rendered in a backend-specific way based on context; see Ordering or Grouping by a Label for background on string label matching in ORDER BY and GROUP BY expressions.

    See also

    ORDER BY - in the SQLAlchemy Unified Tutorial

    Ordering or Grouping by a Label - in the SQLAlchemy Unified Tutorial

  method `sqlalchemy.sql.expression.Select.`outerjoin(target: _JoinTargetArgument, onclause: _OnClauseArgument | None = None, *, full: bool = False) → Self

    Create a left outer join.

    Parameters are the same as that of `Select.join()`.

    Changed in version 1.4: `Select.outerjoin()` now creates a `Join` object between a `FromClause` source that is within the FROM clause of the existing SELECT, and a given target `FromClause`, and then adds this `Join` to the FROM clause of the newly generated SELECT statement. This is completely reworked from the behavior in 1.3, which would instead create a subquery of the entire `Select` and then join that subquery to the target.

    This is a backwards incompatible change as the previous behavior was mostly useless, producing an unnamed subquery rejected by most databases in any case. The new behavior is modeled after that of the very successful `Query.join()` method in the ORM, in order to support the functionality of `Query` being available by using a `Select` object with an `Session`.

    See the notes for this change at select().join() and outerjoin() add JOIN criteria to the current query, rather than creating a subquery.

    See also

    Explicit FROM clauses and JOINs - in the SQLAlchemy Unified Tutorial

    Joins - in the ORM Querying Guide

    `Select.join()`

  method `sqlalchemy.sql.expression.Select.`outerjoin_from(from_: _FromClauseArgument, target: _JoinTargetArgument, onclause: _OnClauseArgument | None = None, *, full: bool = False) → Self

    Create a SQL LEFT OUTER JOIN against this `Select` object’s criterion and apply generatively, returning the newly resulting `Select`.

    Usage is the same as that of `Select.join_from()`.

  method `sqlalchemy.sql.expression.Select.`params(_ExecutableStatement__optionaldict: _CoreSingleExecuteParams | None = None, /, **kwargs: Any) → Self

    inherited from the `ExecutableStatement.params()` method of `ExecutableStatement`

    Return a copy with the provided bindparam values.

    Returns a copy of this Executable with bindparam values set to the given dictionary:

        >>> clause = column("x") + bindparam("foo")
        >>> print(clause.compile().params)
        {'foo': None}
        >>> print(clause.params({"foo": 7}).compile().params)
        {'foo': 7}

  method `sqlalchemy.sql.expression.Select.`prefix_with(*prefixes: _TextCoercedExpressionArgument[Any], dialect: str = '*') → Self

    inherited from the `HasPrefixes.prefix_with()` method of `HasPrefixes`

    Add one or more expressions following the statement keyword, i.e. SELECT, INSERT, UPDATE, or DELETE. Generative.

    This is used to support backend-specific prefix keywords such as those provided by MySQL.

    E.g.:

        stmt = table.insert().prefix_with("LOW_PRIORITY", dialect="mysql")

        # MySQL 5.7 optimizer hints
        stmt = select(table).prefix_with("/*+ BKA(t1) */", dialect="mysql")

    Multiple prefixes can be specified by multiple calls to `HasPrefixes.prefix_with()`.

    Parameters:

      - *prefixes – textual or `ClauseElement` construct which will be rendered following the INSERT, UPDATE, or DELETE keyword.

      - dialect – optional string dialect name which will limit rendering of this prefix to only that dialect.

  method `sqlalchemy.sql.expression.Select.`reduce_columns(only_synonyms: bool = True) → Select

    Return a new `select()` construct with redundantly named, equivalently-valued columns removed from the columns clause.

    “Redundant” here means two columns where one refers to the other either based on foreign key, or via a simple equality comparison in the WHERE clause of the statement. The primary purpose of this method is to automatically construct a select statement with all uniquely-named columns, without the need to use table-qualified labels as `Select.set_label_style()` does.

    When columns are omitted based on foreign key, the referred-to column is the one that’s kept. When columns are omitted based on WHERE equivalence, the first column in the columns clause is the one that’s kept.

    Parameters:

      only_synonyms – when True, limit the removal of columns to those which have the same name as the equivalent. Otherwise, all columns that are equivalent to another are removed.

  method `sqlalchemy.sql.expression.Select.`replace_selectable(old: FromClause, alias: Alias) → Self

    inherited from the `Selectable.replace_selectable()` method of `Selectable`

    Replace all occurrences of `FromClause` ‘old’ with the given `Alias` object, returning a copy of this `FromClause`.

    Deprecated since version 1.4: The `Selectable.replace_selectable()` method is deprecated, and will be removed in a future release. Similar functionality is available via the sqlalchemy.sql.visitors module.

  method `sqlalchemy.sql.expression.Select.`scalar_subquery() → ScalarSelect[Any]

    inherited from the `SelectBase.scalar_subquery()` method of `SelectBase`

    Return a ‘scalar’ representation of this selectable, which can be used as a column expression.

    The returned object is an instance of `ScalarSelect`.

    Typically, a select statement which has only one column in its columns clause is eligible to be used as a scalar expression. The scalar subquery can then be used in the WHERE clause or columns clause of an enclosing SELECT.

    Note that the scalar subquery differentiates from the FROM-level subquery that can be produced using the `SelectBase.subquery()` method.

    Changed in version 1.4: - the `.as_scalar()` method was renamed to `SelectBase.scalar_subquery()`.

    See also

    Scalar and Correlated Subqueries - in the 2.0 tutorial

  method `sqlalchemy.sql.expression.Select.`select_from(*froms: _FromClauseArgument) → Self

    Return a new `select()` construct with the given FROM expression(s) merged into its list of FROM objects.

    E.g.:

        table1 = table("t1", column("a"))
        table2 = table("t2", column("b"))
        s = select(table1.c.a).select_from(
            table1.join(table2, table1.c.a == table2.c.b)
        )

    The “from” list is a unique set on the identity of each element, so adding an already present `Table` or other selectable will have no effect. Passing a `Join` that refers to an already present `Table` or other selectable will have the effect of concealing the presence of that selectable as an individual element in the rendered FROM list, instead rendering it into a JOIN clause.

    While the typical purpose of `Select.select_from()` is to replace the default, derived FROM clause with a join, it can also be called with individual table elements, multiple times if desired, in the case that the FROM clause cannot be fully derived from the columns clause:

        select(func.count("*")).select_from(table1)

  attribute `sqlalchemy.sql.expression.Select.`selected_columns

    A `ColumnCollection` representing the columns that this SELECT statement or similar construct returns in its result set, not including `TextClause` constructs.

    This collection differs from the `FromClause.columns` collection of a `FromClause` in that the columns within this collection cannot be directly nested inside another SELECT statement; a subquery must be applied first which provides for the necessary parenthesization required by SQL.

    For a `select()` construct, the collection here is exactly what would be rendered inside the “SELECT” statement, and the `ColumnElement` objects are directly present as they were given, e.g.:

        col1 = column("q", Integer)
        col2 = column("p", Integer)
        stmt = select(col1, col2)

    Above, `stmt.selected_columns` would be a collection that contains the `col1` and `col2` objects directly. For a statement that is against a `Table` or other `FromClause`, the collection will use the `ColumnElement` objects that are in the `FromClause.c` collection of the from element.

    A use case for the `Select.selected_columns` collection is to allow the existing columns to be referenced when adding additional criteria, e.g.:

        def filter_on_id(my_select, id):
            return my_select.where(my_select.selected_columns["id"] == id)

        stmt = select(MyModel)

        # adds "WHERE id=:param" to the statement
        stmt = filter_on_id(stmt, 42)

    Note

    The `Select.selected_columns` collection does not include expressions established in the columns clause using the `text()` construct; these are silently omitted from the collection. To use plain textual column expressions inside of a `Select` construct, use the `literal_column()` construct.

    Added in version 1.4.

  method `sqlalchemy.sql.expression.Select.`self_group(against: OperatorType | None = None) → SelectStatementGrouping | Self

    Return a ‘grouping’ construct as per the `ClauseElement` specification.

    This produces an element that can be embedded in an expression. Note that this method is called automatically as needed when constructing expressions and should not require explicit use.

  method `sqlalchemy.sql.expression.Select.`set_label_style(style: SelectLabelStyle) → Self

    inherited from the `GenerativeSelect.set_label_style()` method of `GenerativeSelect`

    Return a new selectable with the specified label style.

    There are three “label styles” available, `SelectLabelStyle.LABEL_STYLE_DISAMBIGUATE_ONLY`, `SelectLabelStyle.LABEL_STYLE_TABLENAME_PLUS_COL`, and `SelectLabelStyle.LABEL_STYLE_NONE`. The default style is `SelectLabelStyle.LABEL_STYLE_DISAMBIGUATE_ONLY`.

    In modern SQLAlchemy, there is not generally a need to change the labeling style, as per-expression labels are more effectively used by making use of the `ColumnElement.label()` method. In past versions, `LABEL_STYLE_TABLENAME_PLUS_COL` was used to disambiguate same-named columns from different tables, aliases, or subqueries; the newer `LABEL_STYLE_DISAMBIGUATE_ONLY` now applies labels only to names that conflict with an existing name so that the impact of this labeling is minimal.

    The rationale for disambiguation is mostly so that all column expressions are available from a given `FromClause.c` collection when a subquery is created.

    Added in version 1.4: - the `GenerativeSelect.set_label_style()` method replaces the previous combination of `.apply_labels()`, `.with_labels()` and `use_labels=True` methods and/or parameters.

    See also

    `SelectLabelStyle.LABEL_STYLE_DISAMBIGUATE_ONLY`

    `SelectLabelStyle.LABEL_STYLE_TABLENAME_PLUS_COL`

    `SelectLabelStyle.LABEL_STYLE_NONE`

    `SelectLabelStyle.LABEL_STYLE_DEFAULT`

  method `sqlalchemy.sql.expression.Select.`slice(start: int, stop: int) → Self

    inherited from the `GenerativeSelect.slice()` method of `GenerativeSelect`

    Apply LIMIT / OFFSET to this statement based on a slice.

    The start and stop indices behave like the argument to Python’s built-in `range()` function. This method provides an alternative to using `LIMIT`/`OFFSET` to get a slice of the query.

    For example,

        stmt = select(User).order_by(User.id).slice(1, 3)

    renders as

        SELECT users.id AS users_id,
               users.name AS users_name
        FROM users ORDER BY users.id
        LIMIT ? OFFSET ?
        (2, 1)

    Note

    The `GenerativeSelect.slice()` method will replace any clause applied with `GenerativeSelect.fetch()`.

    Added in version 1.4: Added the `GenerativeSelect.slice()` method generalized from the ORM.

    See also

    `GenerativeSelect.limit()`

    `GenerativeSelect.offset()`

    `GenerativeSelect.fetch()`

  method `sqlalchemy.sql.expression.Select.`subquery(name: str | None = None) → Subquery

    inherited from the `SelectBase.subquery()` method of `SelectBase`

    Return a subquery of this `SelectBase`.

    A subquery is from a SQL perspective a parenthesized, named construct that can be placed in the FROM clause of another SELECT statement.

    Given a SELECT statement such as:

        stmt = select(table.c.id, table.c.name)

    The above statement might look like:

        SELECT table.id, table.name FROM table

    The subquery form by itself renders the same way, however when embedded into the FROM clause of another SELECT statement, it becomes a named sub-element:

        subq = stmt.subquery()
        new_stmt = select(subq)

    The above renders as:

        SELECT anon_1.id, anon_1.name
        FROM (SELECT table.id, table.name FROM table) AS anon_1

    Historically, `SelectBase.subquery()` is equivalent to calling the `FromClause.alias()` method on a FROM object; however, as a `SelectBase` object is not directly FROM object, the `SelectBase.subquery()` method provides clearer semantics.

    Added in version 1.4.

  method `sqlalchemy.sql.expression.Select.`suffix_with(*suffixes: _TextCoercedExpressionArgument[Any], dialect: str = '*') → Self

    inherited from the `HasSuffixes.suffix_with()` method of `HasSuffixes`

    Add one or more expressions following the statement as a whole.

    This is used to support backend-specific suffix keywords on certain constructs.

    E.g.:

        stmt = (
            select(col1, col2)
            .cte()
            .suffix_with(
                "cycle empno set y_cycle to 1 default 0", dialect="oracle"
            )
        )

    Multiple suffixes can be specified by multiple calls to `HasSuffixes.suffix_with()`.

    Parameters:

      - *suffixes – textual or `ClauseElement` construct which will be rendered following the target clause.

      - dialect – Optional string dialect name which will limit rendering of this suffix to only that dialect.

  method `sqlalchemy.sql.expression.Select.`union(*other: _SelectStatementForCompoundArgument[Unpack[_Ts]]) → CompoundSelect[Unpack[_Ts]]

    Return a SQL `UNION` of this select() construct against the given selectables provided as positional arguments.

    Parameters:

      - *other –

        one or more elements with which to create a UNION.

        Changed in version 1.4.28: multiple elements are now accepted.

      - **kwargs – keyword arguments are forwarded to the constructor for the newly created `CompoundSelect` object.

  method `sqlalchemy.sql.expression.Select.`union_all(*other: _SelectStatementForCompoundArgument[Unpack[_Ts]]) → CompoundSelect[Unpack[_Ts]]

    Return a SQL `UNION ALL` of this select() construct against the given selectables provided as positional arguments.

    Parameters:

      - *other –

        one or more elements with which to create a UNION.

        Changed in version 1.4.28: multiple elements are now accepted.

      - **kwargs – keyword arguments are forwarded to the constructor for the newly created `CompoundSelect` object.

  method `sqlalchemy.sql.expression.Select.`where(*whereclause: _ColumnExpressionArgument[bool]) → Self

    Return a new `select()` construct with the given expression added to its WHERE clause, joined to the existing clause via AND, if any.

  property whereclause: ColumnElement[Any] | None

    Return the completed WHERE clause for this `Select` statement.

    This assembles the current collection of WHERE criteria into a single `BooleanClauseList` construct.

    Added in version 1.4.

  method `sqlalchemy.sql.expression.Select.`with_for_update(*, nowait: bool = False, read: bool = False, of: _ForUpdateOfArgument | None = None, skip_locked: bool = False, key_share: bool = False) → Self

    inherited from the `GenerativeSelect.with_for_update()` method of `GenerativeSelect`

    Specify a `FOR UPDATE` clause for this `GenerativeSelect`.

    E.g.:

        stmt = select(table).with_for_update(nowait=True)

    On a database like PostgreSQL or Oracle Database, the above would render a statement like:

        SELECT table.a, table.b FROM table FOR UPDATE NOWAIT

    on other backends, the `nowait` option is ignored and instead would produce:

        SELECT table.a, table.b FROM table FOR UPDATE

    When called with no arguments, the statement will render with the suffix `FOR UPDATE`. Additional arguments can then be provided which allow for common database-specific variants.

    Parameters:

      - nowait – boolean; will render `FOR UPDATE NOWAIT` on Oracle Database and PostgreSQL dialects.

      - read – boolean; will render `LOCK IN SHARE MODE` on MySQL, `FOR SHARE` on PostgreSQL. On PostgreSQL, when combined with `nowait`, will render `FOR SHARE NOWAIT`.

      - of – SQL expression or list of SQL expression elements, (typically `Column` objects or a compatible expression, for some backends may also be a table expression) which will render into a `FOR UPDATE OF` clause; supported by PostgreSQL, Oracle Database, some MySQL versions and possibly others. May render as a table or as a column depending on backend.

      - skip_locked – boolean, will render `FOR UPDATE SKIP LOCKED` on Oracle Database and PostgreSQL dialects or `FOR SHARE SKIP LOCKED` if `read=True` is also specified.

      - key_share – boolean, will render `FOR NO KEY UPDATE`, or if combined with `read=True` will render `FOR KEY SHARE`, on the PostgreSQL dialect.

  method `sqlalchemy.sql.expression.Select.`with_hint(selectable: _FromClauseArgument, text: str, dialect_name: str = '*') → Self

    inherited from the `HasHints.with_hint()` method of `HasHints`

    Add an indexing or other executional context hint for the given selectable to this `Select` or other selectable object.

    Tip

    The `Select.with_hint()` method adds hints that are specific to a single table to a statement, in a location that is dialect-specific. To add generic optimizer hints to the beginning of a statement ahead of the SELECT keyword such as for MySQL or Oracle Database, use the `Select.prefix_with()` method. To add optimizer hints to the end of a statement such as for PostgreSQL, use the `Select.with_statement_hint()` method.

    The text of the hint is rendered in the appropriate location for the database backend in use, relative to the given `Table` or `Alias` passed as the `selectable` argument. The dialect implementation typically uses Python string substitution syntax with the token `%(name)s` to render the name of the table or alias. E.g. when using Oracle Database, the following:

        select(mytable).with_hint(mytable, "index(%(name)s ix_mytable)")

    Would render SQL as:

        select /*+ index(mytable ix_mytable) */ ... from mytable

    The `dialect_name` option will limit the rendering of a particular hint to a particular backend. Such as, to add hints for both Oracle Database and MSSql simultaneously:

        select(mytable).with_hint(
            mytable, "index(%(name)s ix_mytable)", "oracle"
        ).with_hint(mytable, "WITH INDEX ix_mytable", "mssql")

    See also

    `Select.with_statement_hint()`

    `Select.prefix_with()` - generic SELECT prefixing which also can suit some database-specific HINT syntaxes such as MySQL or Oracle Database optimizer hints

  method `sqlalchemy.sql.expression.Select.`with_only_columns(*entities: _ColumnsClauseArgument[Any], maintain_column_froms: bool = False, **_Select__kw: Any) → Select[Unpack[TupleAny]]

    Return a new `select()` construct with its columns clause replaced with the given entities.

    By default, this method is exactly equivalent to as if the original `select()` had been called with the given entities. E.g. a statement:

        s = select(table1.c.a, table1.c.b)
        s = s.with_only_columns(table1.c.b)

    should be exactly equivalent to:

        s = select(table1.c.b)

    In this mode of operation, `Select.with_only_columns()` will also dynamically alter the FROM clause of the statement if it is not explicitly stated. To maintain the existing set of FROMs including those implied by the current columns clause, add the `Select.with_only_columns.maintain_column_froms` parameter:

        s = select(table1.c.a, table2.c.b)
        s = s.with_only_columns(table1.c.a, maintain_column_froms=True)

    The above parameter performs a transfer of the effective FROMs in the columns collection to the `Select.select_from()` method, as though the following were invoked:

        s = select(table1.c.a, table2.c.b)
        s = s.select_from(table1, table2).with_only_columns(table1.c.a)

    The `Select.with_only_columns.maintain_column_froms` parameter makes use of the `Select.columns_clause_froms` collection and performs an operation equivalent to the following:

        s = select(table1.c.a, table2.c.b)
        s = s.select_from(*s.columns_clause_froms).with_only_columns(table1.c.a)

    Parameters:

      - *entities – column expressions to be used.

      - maintain_column_froms –

        boolean parameter that will ensure the FROM list implied from the current columns clause will be transferred to the `Select.select_from()` method first.

        Added in version 1.4.23.

  method `sqlalchemy.sql.expression.Select.`with_statement_hint(text: str, dialect_name: str = '*') → Self

    inherited from the `HasHints.with_statement_hint()` method of `HasHints`

    Add a statement hint to this `Select` or other selectable object.

    Tip

    `Select.with_statement_hint()` generally adds hints at the trailing end of a SELECT statement. To place dialect-specific hints such as optimizer hints at the front of the SELECT statement after the SELECT keyword, use the `Select.prefix_with()` method for an open-ended space, or for table-specific hints the `Select.with_hint()` may be used, which places hints in a dialect-specific location.

    This method is similar to `Select.with_hint()` except that it does not require an individual table, and instead applies to the statement as a whole.

    Hints here are specific to the backend database and may include directives such as isolation levels, file directives, fetch directives, etc.

    See also

    `Select.with_hint()`

    `Select.prefix_with()` - generic SELECT prefixing which also can suit some database-specific HINT syntaxes such as MySQL or Oracle Database optimizer hints

class sqlalchemy.sql.expression.Selectable

  inherits from `sqlalchemy.sql.expression.ReturnsRows`

  Mark a class as being selectable.

  Member Name | Description
  --- | ---
  compile() | Compile this SQL expression.
  corresponding_column() | Given a `ColumnElement`, return the exported `ColumnElement` object from the `Selectable.exported_columns` collection of this `Selectable` which corresponds to that original `ColumnElement` via a common ancestor column.
  get_children() | Return immediate child `HasTraverseInternals` elements of this `HasTraverseInternals`.
  inherit_cache | Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.
  is_derived_from() | Return `True` if this `ReturnsRows` is ‘derived’ from the given `FromClause`.
  lateral() | Return a LATERAL alias of this `Selectable`.
  replace_selectable() | Replace all occurrences of `FromClause` ‘old’ with the given `Alias` object, returning a copy of this `FromClause`.

  method `sqlalchemy.sql.expression.Selectable.`compile(bind: _HasDialect | None = None, dialect: Dialect | None = None, **kw: Any) → Compiled

    inherited from the `CompilerElement.compile()` method of `CompilerElement`

    Compile this SQL expression.

    The return value is a `Compiled` object. Calling `str()` or `unicode()` on the returned value will yield a string representation of the result. The `Compiled` object also can return a dictionary of bind parameter names and values using the `params` accessor.

    Parameters:

      - bind – An `Connection` or `Engine` which can provide a `Dialect` in order to generate a `Compiled` object. If the `bind` and `dialect` parameters are both omitted, a default SQL compiler is used.

      - column_keys – Used for INSERT and UPDATE statements, a list of column names which should be present in the VALUES clause of the compiled statement. If `None`, all columns from the target table object are rendered.

      - dialect – A `Dialect` instance which can generate a `Compiled` object. This argument takes precedence over the `bind` argument.

      - compile_kwargs –

        optional dictionary of additional parameters that will be passed through to the compiler within all “visit” methods. This allows any custom flag to be passed through to a custom compilation construct, for example. It is also used for the case of passing the `literal_binds` flag through:

            from sqlalchemy.sql import table, column, select

            t = table("t", column("x"))

            s = select(t).where(t.c.x == 5)

            print(s.compile(compile_kwargs={"literal_binds": True}))

    See also

    How do I render SQL expressions as strings, possibly with bound parameters inlined?

  method `sqlalchemy.sql.expression.Selectable.`corresponding_column(column: KeyedColumnElement[Any], require_embedded: bool = False) → KeyedColumnElement[Any] | None

    Given a `ColumnElement`, return the exported `ColumnElement` object from the `Selectable.exported_columns` collection of this `Selectable` which corresponds to that original `ColumnElement` via a common ancestor column.

    Parameters:

      - column – the target `ColumnElement` to be matched.

      - require_embedded – only return corresponding columns for the given `ColumnElement`, if the given `ColumnElement` is actually present within a sub-element of this `Selectable`. Normally the column will match if it merely shares a common ancestor with one of the exported columns of this `Selectable`.

    See also

    `Selectable.exported_columns` - the `ColumnCollection` that is used for the operation.

    `ColumnCollection.corresponding_column()` - implementation method.

  property exported_columns: ReadOnlyColumnCollection[Any, Any]

    A `ColumnCollection` that represents the “exported” columns of this `ReturnsRows`.

    The “exported” columns represent the collection of `ColumnElement` expressions that are rendered by this SQL construct. There are primary varieties which are the “FROM clause columns” of a FROM clause, such as a table, join, or subquery, the “SELECTed columns”, which are the columns in the “columns clause” of a SELECT statement, and the RETURNING columns in a DML statement..

    Added in version 1.4.

    See also

    `FromClause.exported_columns`

    `SelectBase.exported_columns`

  method `sqlalchemy.sql.expression.Selectable.`get_children(*, omit_attrs: Tuple[str, ...] = (), **kw: Any) → Iterable[HasTraverseInternals]

    inherited from the `HasTraverseInternals.get_children()` method of `HasTraverseInternals`

    Return immediate child `HasTraverseInternals` elements of this `HasTraverseInternals`.

    This is used for visit traversal.

    **kw may contain flags that change the collection that is returned, for example to return a subset of items in order to cut down on larger traversals, or to return child items from a different context (such as schema-level collections instead of clause-level).

  attribute `sqlalchemy.sql.expression.Selectable.`inherit_cache = None

    inherited from the `HasCacheKey.inherit_cache` attribute of `HasCacheKey`

    Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.

    The attribute defaults to `None`, which indicates that a construct has not yet taken into account whether or not its appropriate for it to participate in caching; this is functionally equivalent to setting the value to `False`, except that a warning is also emitted.

    This flag can be set to `True` on a particular class, if the SQL that corresponds to the object does not change based on attributes which are local to this class, and not its superclass.

    See also

    Enabling Caching Support for Custom Constructs - General guideslines for setting the `HasCacheKey.inherit_cache` attribute for third-party or user defined SQL constructs.

  method `sqlalchemy.sql.expression.Selectable.`is_derived_from(fromclause: FromClause | None) → bool

    inherited from the `ReturnsRows.is_derived_from()` method of `ReturnsRows`

    Return `True` if this `ReturnsRows` is ‘derived’ from the given `FromClause`.

    An example would be an Alias of a Table is derived from that Table.

  method `sqlalchemy.sql.expression.Selectable.`lateral(name: str | None = None) → LateralFromClause

    Return a LATERAL alias of this `Selectable`.

    The return value is the `Lateral` construct also provided by the top-level `lateral()` function.

    See also

    LATERAL correlation - overview of usage.

  method `sqlalchemy.sql.expression.Selectable.`replace_selectable(old: FromClause, alias: Alias) → Self

    Replace all occurrences of `FromClause` ‘old’ with the given `Alias` object, returning a copy of this `FromClause`.

    Deprecated since version 1.4: The `Selectable.replace_selectable()` method is deprecated, and will be removed in a future release. Similar functionality is available via the sqlalchemy.sql.visitors module.

class sqlalchemy.sql.expression.SelectBase

  inherits from `sqlalchemy.sql.roles.SelectStatementRole`, `sqlalchemy.sql.roles.DMLSelectRole`, `sqlalchemy.sql.roles.CompoundElementRole`, `sqlalchemy.sql.roles.InElementRole`, `sqlalchemy.sql.expression.HasCTE`, `sqlalchemy.sql.annotation.SupportsCloneAnnotations`, `sqlalchemy.sql.expression.Selectable`

  Base class for SELECT statements.

  This includes `Select`, `CompoundSelect` and `TextualSelect`.

  Member Name | Description
  --- | ---
  add_cte() | Add one or more `CTE` constructs to this statement.
  alias() | Return a named subquery against this `SelectBase`.
  as_scalar() |
  compile() | Compile this SQL expression.
  corresponding_column() | Given a `ColumnElement`, return the exported `ColumnElement` object from the `Selectable.exported_columns` collection of this `Selectable` which corresponds to that original `ColumnElement` via a common ancestor column.
  cte() | Return a new `CTE`, or Common Table Expression instance.
  exists() | Return an `Exists` representation of this selectable, which can be used as a column expression.
  get_children() | Return immediate child `HasTraverseInternals` elements of this `HasTraverseInternals`.
  get_label_style() | Retrieve the current label style.
  inherit_cache | Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.
  into() | Create a `CreateTableAs` construct from this SELECT.
  is_derived_from() | Return `True` if this `ReturnsRows` is ‘derived’ from the given `FromClause`.
  label() | Return a ‘scalar’ representation of this selectable, embedded as a subquery with a label.
  lateral() | Return a LATERAL alias of this `Selectable`.
  name_cte_columns | indicates if this HasCTE as contained within a CTE should compel the CTE to render the column names of this object in the WITH clause.
  replace_selectable() | Replace all occurrences of `FromClause` ‘old’ with the given `Alias` object, returning a copy of this `FromClause`.
  scalar_subquery() | Return a ‘scalar’ representation of this selectable, which can be used as a column expression.
  selected_columns | A `ColumnCollection` representing the columns that this SELECT statement or similar construct returns in its result set.
  set_label_style() | Return a new selectable with the specified label style.
  subquery() | Return a subquery of this `SelectBase`.

  method `sqlalchemy.sql.expression.SelectBase.`add_cte(*ctes: CTE, nest_here: bool = False) → Self

    inherited from the `HasCTE.add_cte()` method of `HasCTE`

    Add one or more `CTE` constructs to this statement.

    This method will associate the given `CTE` constructs with the parent statement such that they will each be unconditionally rendered in the WITH clause of the final statement, even if not referenced elsewhere within the statement or any sub-selects.

    The optional `HasCTE.add_cte.nest_here` parameter when set to True will have the effect that each given `CTE` will render in a WITH clause rendered directly along with this statement, rather than being moved to the top of the ultimate rendered statement, even if this statement is rendered as a subquery within a larger statement.

    This method has two general uses. One is to embed CTE statements that serve some purpose without being referenced explicitly, such as the use case of embedding a DML statement such as an INSERT or UPDATE as a CTE inline with a primary statement that may draw from its results indirectly. The other is to provide control over the exact placement of a particular series of CTE constructs that should remain rendered directly in terms of a particular statement that may be nested in a larger statement.

    E.g.:

        from sqlalchemy import table, column, select

        t = table("t", column("c1"), column("c2"))

        ins = t.insert().values({"c1": "x", "c2": "y"}).cte()

        stmt = select(t).add_cte(ins)

    Would render:

        WITH anon_1 AS (
            INSERT INTO t (c1, c2) VALUES (:param_1, :param_2)
        )
        SELECT t.c1, t.c2
        FROM t

    Above, the “anon_1” CTE is not referenced in the SELECT statement, however still accomplishes the task of running an INSERT statement.

    Similarly in a DML-related context, using the PostgreSQL `Insert` construct to generate an “upsert”:

        from sqlalchemy import table, column
        from sqlalchemy.dialects.postgresql import insert

        t = table("t", column("c1"), column("c2"))

        delete_statement_cte = t.delete().where(t.c.c1 < 1).cte("deletions")

        insert_stmt = insert(t).values({"c1": 1, "c2": 2})
        update_statement = insert_stmt.on_conflict_do_update(
            index_elements=[t.c.c1],
            set_={
                "c1": insert_stmt.excluded.c1,
                "c2": insert_stmt.excluded.c2,
            },
        ).add_cte(delete_statement_cte)

        print(update_statement)

    The above statement renders as:

        WITH deletions AS (
            DELETE FROM t WHERE t.c1 < %(c1_1)s
        )
        INSERT INTO t (c1, c2) VALUES (%(c1)s, %(c2)s)
        ON CONFLICT (c1) DO UPDATE SET c1 = excluded.c1, c2 = excluded.c2

    Added in version 1.4.21.

    Parameters:

      - *ctes –

        zero or more `CTE` constructs.

        Changed in version 2.0: Multiple CTE instances are accepted

      - nest_here –

        if True, the given CTE or CTEs will be rendered as though they specified the `HasCTE.cte.nesting` flag to `True` when they were added to this `HasCTE`. Assuming the given CTEs are not referenced in an outer-enclosing statement as well, the CTEs given should render at the level of this statement when this flag is given.

        Added in version 2.0.

        See also

        `HasCTE.cte.nesting`

  method `sqlalchemy.sql.expression.SelectBase.`alias(name: str | None = None, flat: bool = False) → Subquery

    Return a named subquery against this `SelectBase`.

    For a `SelectBase` (as opposed to a `FromClause`), this returns a `Subquery` object which behaves mostly the same as the `Alias` object that is used with a `FromClause`.

    Changed in version 1.4: The `SelectBase.alias()` method is now a synonym for the `SelectBase.subquery()` method.

  method `sqlalchemy.sql.expression.SelectBase.`as_scalar() → ScalarSelect[Any]

    Deprecated since version 1.4: The `SelectBase.as_scalar()` method is deprecated and will be removed in a future release. Please refer to `SelectBase.scalar_subquery()`.

  method `sqlalchemy.sql.expression.SelectBase.`compile(bind: _HasDialect | None = None, dialect: Dialect | None = None, **kw: Any) → Compiled

    inherited from the `CompilerElement.compile()` method of `CompilerElement`

    Compile this SQL expression.

    The return value is a `Compiled` object. Calling `str()` or `unicode()` on the returned value will yield a string representation of the result. The `Compiled` object also can return a dictionary of bind parameter names and values using the `params` accessor.

    Parameters:

      - bind – An `Connection` or `Engine` which can provide a `Dialect` in order to generate a `Compiled` object. If the `bind` and `dialect` parameters are both omitted, a default SQL compiler is used.

      - column_keys – Used for INSERT and UPDATE statements, a list of column names which should be present in the VALUES clause of the compiled statement. If `None`, all columns from the target table object are rendered.

      - dialect – A `Dialect` instance which can generate a `Compiled` object. This argument takes precedence over the `bind` argument.

      - compile_kwargs –

        optional dictionary of additional parameters that will be passed through to the compiler within all “visit” methods. This allows any custom flag to be passed through to a custom compilation construct, for example. It is also used for the case of passing the `literal_binds` flag through:

            from sqlalchemy.sql import table, column, select

            t = table("t", column("x"))

            s = select(t).where(t.c.x == 5)

            print(s.compile(compile_kwargs={"literal_binds": True}))

    See also

    How do I render SQL expressions as strings, possibly with bound parameters inlined?

  method `sqlalchemy.sql.expression.SelectBase.`corresponding_column(column: KeyedColumnElement[Any], require_embedded: bool = False) → KeyedColumnElement[Any] | None

    inherited from the `Selectable.corresponding_column()` method of `Selectable`

    Given a `ColumnElement`, return the exported `ColumnElement` object from the `Selectable.exported_columns` collection of this `Selectable` which corresponds to that original `ColumnElement` via a common ancestor column.

    Parameters:

      - column – the target `ColumnElement` to be matched.

      - require_embedded – only return corresponding columns for the given `ColumnElement`, if the given `ColumnElement` is actually present within a sub-element of this `Selectable`. Normally the column will match if it merely shares a common ancestor with one of the exported columns of this `Selectable`.

    See also

    `Selectable.exported_columns` - the `ColumnCollection` that is used for the operation.

    `ColumnCollection.corresponding_column()` - implementation method.

  method `sqlalchemy.sql.expression.SelectBase.`cte(name: str | None = None, recursive: bool = False, nesting: bool = False) → CTE

    inherited from the `HasCTE.cte()` method of `HasCTE`

    Return a new `CTE`, or Common Table Expression instance.

    Common table expressions are a SQL standard whereby SELECT statements can draw upon secondary statements specified along with the primary statement, using a clause called “WITH”. Special semantics regarding UNION can also be employed to allow “recursive” queries, where a SELECT statement can draw upon the set of rows that have previously been selected.

    CTEs can also be applied to DML constructs UPDATE, INSERT and DELETE on some databases, both as a source of CTE rows when combined with RETURNING, as well as a consumer of CTE rows.

    SQLAlchemy detects `CTE` objects, which are treated similarly to `Alias` objects, as special elements to be delivered to the FROM clause of the statement as well as to a WITH clause at the top of the statement.

    For special prefixes such as PostgreSQL “MATERIALIZED” and “NOT MATERIALIZED”, the `CTE.prefix_with()` method may be used to establish these.

    Parameters:

      - name – name given to the common table expression. Like `FromClause.alias()`, the name can be left as `None` in which case an anonymous symbol will be used at query compile time.

      - recursive – if `True`, will render `WITH RECURSIVE`. A recursive common table expression is intended to be used in conjunction with UNION ALL in order to derive rows from those already selected.

      - nesting –

        if `True`, will render the CTE locally to the statement in which it is referenced. For more complex scenarios, the `HasCTE.add_cte()` method using the `HasCTE.add_cte.nest_here` parameter may also be used to more carefully control the exact placement of a particular CTE.

        Added in version 1.4.24.

        See also

        `HasCTE.add_cte()`

    The following examples include two from PostgreSQL’s documentation at https://www.postgresql.org/docs/current/static/queries-with.html, as well as additional examples.

    Example 1, non recursive:

        from sqlalchemy import (
            Table,
            Column,
            String,
            Integer,
            MetaData,
            select,
            func,
        )

        metadata = MetaData()

        orders = Table(
            "orders",
            metadata,
            Column("region", String),
            Column("amount", Integer),
            Column("product", String),
            Column("quantity", Integer),
        )

        regional_sales = (
            select(orders.c.region, func.sum(orders.c.amount).label("total_sales"))
            .group_by(orders.c.region)
            .cte("regional_sales")
        )

        top_regions = (
            select(regional_sales.c.region)
            .where(
                regional_sales.c.total_sales
                > select(func.sum(regional_sales.c.total_sales) / 10)
            )
            .cte("top_regions")
        )

        statement = (
            select(
                orders.c.region,
                orders.c.product,
                func.sum(orders.c.quantity).label("product_units"),
                func.sum(orders.c.amount).label("product_sales"),
            )
            .where(orders.c.region.in_(select(top_regions.c.region)))
            .group_by(orders.c.region, orders.c.product)
        )

        result = conn.execute(statement).fetchall()

    Example 2, WITH RECURSIVE:

        from sqlalchemy import (
            Table,
            Column,
            String,
            Integer,
            MetaData,
            select,
            func,
        )

        metadata = MetaData()

        parts = Table(
            "parts",
            metadata,
            Column("part", String),
            Column("sub_part", String),
            Column("quantity", Integer),
        )

        included_parts = (
            select(parts.c.sub_part, parts.c.part, parts.c.quantity)
            .where(parts.c.part == "our part")
            .cte(recursive=True)
        )

        incl_alias = included_parts.alias()
        parts_alias = parts.alias()
        included_parts = included_parts.union_all(
            select(
                parts_alias.c.sub_part, parts_alias.c.part, parts_alias.c.quantity
            ).where(parts_alias.c.part == incl_alias.c.sub_part)
        )

        statement = select(
            included_parts.c.sub_part,
            func.sum(included_parts.c.quantity).label("total_quantity"),
        ).group_by(included_parts.c.sub_part)

        result = conn.execute(statement).fetchall()

    Example 3, an upsert using UPDATE and INSERT with CTEs:

        from datetime import date
        from sqlalchemy import (
            MetaData,
            Table,
            Column,
            Integer,
            Date,
            select,
            literal,
            and_,
            exists,
        )

        metadata = MetaData()

        visitors = Table(
            "visitors",
            metadata,
            Column("product_id", Integer, primary_key=True),
            Column("date", Date, primary_key=True),
            Column("count", Integer),
        )

        # add 5 visitors for the product_id == 1
        product_id = 1
        day = date.today()
        count = 5

        update_cte = (
            visitors.update()
            .where(
                and_(visitors.c.product_id == product_id, visitors.c.date == day)
            )
            .values(count=visitors.c.count + count)
            .returning(literal(1))
            .cte("update_cte")
        )

        upsert = visitors.insert().from_select(
            [visitors.c.product_id, visitors.c.date, visitors.c.count],
            select(literal(product_id), literal(day), literal(count)).where(
                ~exists(update_cte.select())
            ),
        )

        connection.execute(upsert)

    Example 4, Nesting CTE (SQLAlchemy 1.4.24 and above):

        value_a = select(literal("root").label("n")).cte("value_a")

        # A nested CTE with the same name as the root one
        value_a_nested = select(literal("nesting").label("n")).cte(
            "value_a", nesting=True
        )

        # Nesting CTEs takes ascendency locally
        # over the CTEs at a higher level
        value_b = select(value_a_nested.c.n).cte("value_b")

        value_ab = select(value_a.c.n.label("a"), value_b.c.n.label("b"))

    The above query will render the second CTE nested inside the first, shown with inline parameters below as:

        WITH
            value_a AS
                (SELECT 'root' AS n),
            value_b AS
                (WITH value_a AS
                    (SELECT 'nesting' AS n)
                SELECT value_a.n AS n FROM value_a)
        SELECT value_a.n AS a, value_b.n AS b
        FROM value_a, value_b

    The same CTE can be set up using the `HasCTE.add_cte()` method as follows (SQLAlchemy 2.0 and above):

        value_a = select(literal("root").label("n")).cte("value_a")

        # A nested CTE with the same name as the root one
        value_a_nested = select(literal("nesting").label("n")).cte("value_a")

        # Nesting CTEs takes ascendency locally
        # over the CTEs at a higher level
        value_b = (
            select(value_a_nested.c.n)
            .add_cte(value_a_nested, nest_here=True)
            .cte("value_b")
        )

        value_ab = select(value_a.c.n.label("a"), value_b.c.n.label("b"))

    Example 5, Non-Linear CTE (SQLAlchemy 1.4.28 and above):

        edge = Table(
            "edge",
            metadata,
            Column("id", Integer, primary_key=True),
            Column("left", Integer),
            Column("right", Integer),
        )

        root_node = select(literal(1).label("node")).cte("nodes", recursive=True)

        left_edge = select(edge.c.left).join(
            root_node, edge.c.right == root_node.c.node
        )
        right_edge = select(edge.c.right).join(
            root_node, edge.c.left == root_node.c.node
        )

        subgraph_cte = root_node.union(left_edge, right_edge)

        subgraph = select(subgraph_cte)

    The above query will render 2 UNIONs inside the recursive CTE:

        WITH RECURSIVE nodes(node) AS (
                SELECT 1 AS node
            UNION
                SELECT edge."left" AS "left"
                FROM edge JOIN nodes ON edge."right" = nodes.node
            UNION
                SELECT edge."right" AS "right"
                FROM edge JOIN nodes ON edge."left" = nodes.node
        )
        SELECT nodes.node FROM nodes

    See also

    `Query.cte()` - ORM version of `HasCTE.cte()`.

  method `sqlalchemy.sql.expression.SelectBase.`exists() → Exists

    Return an `Exists` representation of this selectable, which can be used as a column expression.

    The returned object is an instance of `Exists`.

    See also

    `exists()`

    EXISTS subqueries - in the 2.0 style tutorial.

    Added in version 1.4.

  property exported_columns: ReadOnlyColumnCollection[str, ColumnElement[Any]]

    A `ColumnCollection` that represents the “exported” columns of this `Selectable`, not including `TextClause` constructs.

    The “exported” columns for a `SelectBase` object are synonymous with the `SelectBase.selected_columns` collection.

    Added in version 1.4.

    See also

    `Select.exported_columns`

    `Selectable.exported_columns`

    `FromClause.exported_columns`

  method `sqlalchemy.sql.expression.SelectBase.`get_children(*, omit_attrs: Tuple[str, ...] = (), **kw: Any) → Iterable[HasTraverseInternals]

    inherited from the `HasTraverseInternals.get_children()` method of `HasTraverseInternals`

    Return immediate child `HasTraverseInternals` elements of this `HasTraverseInternals`.

    This is used for visit traversal.

    **kw may contain flags that change the collection that is returned, for example to return a subset of items in order to cut down on larger traversals, or to return child items from a different context (such as schema-level collections instead of clause-level).

  method `sqlalchemy.sql.expression.SelectBase.`get_label_style() → SelectLabelStyle

    Retrieve the current label style.

    Implemented by subclasses.

  attribute `sqlalchemy.sql.expression.SelectBase.`inherit_cache = None

    inherited from the `HasCacheKey.inherit_cache` attribute of `HasCacheKey`

    Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.

    The attribute defaults to `None`, which indicates that a construct has not yet taken into account whether or not its appropriate for it to participate in caching; this is functionally equivalent to setting the value to `False`, except that a warning is also emitted.

    This flag can be set to `True` on a particular class, if the SQL that corresponds to the object does not change based on attributes which are local to this class, and not its superclass.

    See also

    Enabling Caching Support for Custom Constructs - General guideslines for setting the `HasCacheKey.inherit_cache` attribute for third-party or user defined SQL constructs.

  method `sqlalchemy.sql.expression.SelectBase.`into(target: str, *, metadata: 'MetaData' | None = None, schema: str | None = None, temporary: bool = False, if_not_exists: bool = False) → CreateTableAs

    Create a `CreateTableAs` construct from this SELECT.

    This method provides a convenient way to create a `CREATE TABLE ... AS` statement from a SELECT, as well as compound SELECTs like UNION. The new table will be created with columns matching the SELECT list.

    Supported on all included backends, the construct emits `CREATE TABLE...AS` for all backends except SQL Server, which instead emits a `SELECT..INTO` statement.

    e.g.:

        from sqlalchemy import select

        # Create a new table from a SELECT
        stmt = (
            select(users.c.id, users.c.name)
            .where(users.c.status == "active")
            .into("active_users")
        )

        with engine.begin() as conn:
            conn.execute(stmt)

        # With optional flags
        stmt = (
            select(users.c.id)
            .where(users.c.status == "inactive")
            .into("inactive_users", schema="analytics", if_not_exists=True)
        )

    Added in version 2.1.

    Parameters:

      - target – Name of the table to create as a string. Must be unqualified; use the `schema` parameter for qualification.

      - metadata – `MetaData`, optional If provided, the `Table` object available via the `CreateTableAs.table` attribute will be associated with this `MetaData`. Otherwise, a new, empty `MetaData` is created.

      - schema – Optional schema name for the new table.

      - temporary – If True, create a temporary table where supported

      - if_not_exists – If True, add IF NOT EXISTS clause where supported

    Returns:

      A `CreateTableAs` construct.

    See also

    Using CreateTableAs or Select.into() - in Describing Databases with MetaData

    `CreateTableAs`

  method `sqlalchemy.sql.expression.SelectBase.`is_derived_from(fromclause: FromClause | None) → bool

    inherited from the `ReturnsRows.is_derived_from()` method of `ReturnsRows`

    Return `True` if this `ReturnsRows` is ‘derived’ from the given `FromClause`.

    An example would be an Alias of a Table is derived from that Table.

  method `sqlalchemy.sql.expression.SelectBase.`label(name: str | None) → Label[Any]

    Return a ‘scalar’ representation of this selectable, embedded as a subquery with a label.

    See also

    `SelectBase.scalar_subquery()`.

  method `sqlalchemy.sql.expression.SelectBase.`lateral(name: str | None = None) → LateralFromClause

    Return a LATERAL alias of this `Selectable`.

    The return value is the `Lateral` construct also provided by the top-level `lateral()` function.

    See also

    LATERAL correlation - overview of usage.

  attribute `sqlalchemy.sql.expression.SelectBase.`name_cte_columns = False

    inherited from the `HasCTE.name_cte_columns` attribute of `HasCTE`

    indicates if this HasCTE as contained within a CTE should compel the CTE to render the column names of this object in the WITH clause.

    Added in version 2.0.42.

  method `sqlalchemy.sql.expression.SelectBase.`replace_selectable(old: FromClause, alias: Alias) → Self

    inherited from the `Selectable.replace_selectable()` method of `Selectable`

    Replace all occurrences of `FromClause` ‘old’ with the given `Alias` object, returning a copy of this `FromClause`.

    Deprecated since version 1.4: The `Selectable.replace_selectable()` method is deprecated, and will be removed in a future release. Similar functionality is available via the sqlalchemy.sql.visitors module.

  method `sqlalchemy.sql.expression.SelectBase.`scalar_subquery() → ScalarSelect[Any]

    Return a ‘scalar’ representation of this selectable, which can be used as a column expression.

    The returned object is an instance of `ScalarSelect`.

    Typically, a select statement which has only one column in its columns clause is eligible to be used as a scalar expression. The scalar subquery can then be used in the WHERE clause or columns clause of an enclosing SELECT.

    Note that the scalar subquery differentiates from the FROM-level subquery that can be produced using the `SelectBase.subquery()` method.

    Changed in version 1.4: - the `.as_scalar()` method was renamed to `SelectBase.scalar_subquery()`.

    See also

    Scalar and Correlated Subqueries - in the 2.0 tutorial

  attribute `sqlalchemy.sql.expression.SelectBase.`selected_columns

    A `ColumnCollection` representing the columns that this SELECT statement or similar construct returns in its result set.

    This collection differs from the `FromClause.columns` collection of a `FromClause` in that the columns within this collection cannot be directly nested inside another SELECT statement; a subquery must be applied first which provides for the necessary parenthesization required by SQL.

    Note

    The `SelectBase.selected_columns` collection does not include expressions established in the columns clause using the `text()` construct; these are silently omitted from the collection. To use plain textual column expressions inside of a `Select` construct, use the `literal_column()` construct.

    See also

    `Select.selected_columns`

    Added in version 1.4.

  method `sqlalchemy.sql.expression.SelectBase.`set_label_style(style: SelectLabelStyle) → Self

    Return a new selectable with the specified label style.

    Implemented by subclasses.

  method `sqlalchemy.sql.expression.SelectBase.`subquery(name: str | None = None) → Subquery

    Return a subquery of this `SelectBase`.

    A subquery is from a SQL perspective a parenthesized, named construct that can be placed in the FROM clause of another SELECT statement.

    Given a SELECT statement such as:

        stmt = select(table.c.id, table.c.name)

    The above statement might look like:

        SELECT table.id, table.name FROM table

    The subquery form by itself renders the same way, however when embedded into the FROM clause of another SELECT statement, it becomes a named sub-element:

        subq = stmt.subquery()
        new_stmt = select(subq)

    The above renders as:

        SELECT anon_1.id, anon_1.name
        FROM (SELECT table.id, table.name FROM table) AS anon_1

    Historically, `SelectBase.subquery()` is equivalent to calling the `FromClause.alias()` method on a FROM object; however, as a `SelectBase` object is not directly FROM object, the `SelectBase.subquery()` method provides clearer semantics.

    Added in version 1.4.

class sqlalchemy.sql.expression.Subquery

  inherits from `sqlalchemy.sql.expression.AliasedReturnsRows`

  Represent a subquery of a SELECT.

  A `Subquery` is created by invoking the `SelectBase.subquery()` method, or for convenience the `SelectBase.alias()` method, on any `SelectBase` subclass which includes `Select`, `CompoundSelect`, and `TextualSelect`. As rendered in a FROM clause, it represents the body of the SELECT statement inside of parenthesis, followed by the usual “AS <somename>” that defines all “alias” objects.

  The `Subquery` object is very similar to the `Alias` object and can be used in an equivalent way. The difference between `Alias` and `Subquery` is that `Alias` always contains a `FromClause` object whereas `Subquery` always contains a `SelectBase` object.

  Added in version 1.4: The `Subquery` class was added which now serves the purpose of providing an aliased version of a SELECT statement.

  Member Name | Description
  --- | ---
  as_scalar() |
  inherit_cache | Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.

  method `sqlalchemy.sql.expression.Subquery.`as_scalar() → ScalarSelect[Any]

    Deprecated since version 1.4: The `Subquery.as_scalar()` method, which was previously `Alias.as_scalar()` prior to version 1.4, is deprecated and will be removed in a future release; Please use the `Select.scalar_subquery()` method of the `select()` construct before constructing a subquery object, or with the ORM use the `Query.scalar_subquery()` method.

  attribute `sqlalchemy.sql.expression.Subquery.`inherit_cache = True

    Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.

    The attribute defaults to `None`, which indicates that a construct has not yet taken into account whether or not its appropriate for it to participate in caching; this is functionally equivalent to setting the value to `False`, except that a warning is also emitted.

    This flag can be set to `True` on a particular class, if the SQL that corresponds to the object does not change based on attributes which are local to this class, and not its superclass.

    See also

    Enabling Caching Support for Custom Constructs - General guideslines for setting the `HasCacheKey.inherit_cache` attribute for third-party or user defined SQL constructs.

class sqlalchemy.sql.expression.TableClause

  inherits from `sqlalchemy.sql.roles.DMLTableRole`, `sqlalchemy.sql.expression.Immutable`, `sqlalchemy.sql.expression.NamedFromClause`

  Represents a minimal “table” construct.

  This is a lightweight table object that has only a name, a collection of columns, which are typically produced by the `column()` function, and a schema:

      from sqlalchemy import table, column

      user = table(
          "user",
          column("id"),
          column("name"),
          column("description"),
      )

  The `TableClause` construct serves as the base for the more commonly used `Table` object, providing the usual set of `FromClause` services including the `.c.` collection and statement generation methods.

  It does not provide all the additional schema-level services of `Table`, including constraints, references to other tables, or support for `MetaData`-level services. It’s useful on its own as an ad-hoc construct used to generate quick SQL statements when a more fully fledged `Table` is not on hand.

  Member Name | Description
  --- | ---
  alias() | Return an alias of this `FromClause`.
  c | A synonym for `FromClause.columns`
  columns | A named-based collection of `ColumnElement` objects maintained by this `FromClause`.
  compare() | Compare this `ClauseElement` to the given `ClauseElement`.
  compile() | Compile this SQL expression.
  corresponding_column() | Given a `ColumnElement`, return the exported `ColumnElement` object from the `Selectable.exported_columns` collection of this `Selectable` which corresponds to that original `ColumnElement` via a common ancestor column.
  delete() | Generate a `delete()` construct against this `TableClause`.
  description |
  entity_namespace | Return a namespace used for name-based access in SQL expressions.
  exported_columns | A `ColumnCollection` that represents the “exported” columns of this `FromClause`.
  foreign_keys | Return the collection of `ForeignKey` marker objects which this FromClause references.
  get_children() | Return immediate child `HasTraverseInternals` elements of this `HasTraverseInternals`.
  implicit_returning | `TableClause` doesn’t support having a primary key or column -level defaults, so implicit returning doesn’t apply.
  inherit_cache | Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.
  insert() | Generate an `Insert` construct against this `TableClause`.
  is_derived_from() | Return `True` if this `FromClause` is ‘derived’ from the given `FromClause`.
  join() | Return a `Join` from this `FromClause` to another `FromClause`.
  lateral() | Return a LATERAL alias of this `Selectable`.
  outerjoin() | Return a `Join` from this `FromClause` to another `FromClause`, with the “isouter” flag set to True.
  params() | Return a copy with `bindparam()` elements replaced.
  primary_key | Return the iterable collection of `Column` objects which comprise the primary key of this `_selectable.FromClause`.
  replace_selectable() | Replace all occurrences of `FromClause` ‘old’ with the given `Alias` object, returning a copy of this `FromClause`.
  schema | Define the ‘schema’ attribute for this `FromClause`.
  select() | Return a SELECT of this `FromClause`.
  self_group() | Apply a ‘grouping’ to this `ClauseElement`.
  table_valued() | Return a `TableValuedColumn` object for this `FromClause`.
  tablesample() | Return a TABLESAMPLE alias of this `FromClause`.
  unique_params() | Return a copy with `bindparam()` elements replaced.
  update() | Generate an `update()` construct against this `TableClause`.

  method `sqlalchemy.sql.expression.TableClause.`alias(name: str | None = None, flat: bool = False) → NamedFromClause

    inherited from the `FromClause.alias()` method of `FromClause`

    Return an alias of this `FromClause`.

    E.g.:

        a2 = some_table.alias("a2")

    The above code creates an `Alias` object which can be used as a FROM clause in any SELECT statement.

    See also

    Using Aliases

    `alias()`

  attribute `sqlalchemy.sql.expression.TableClause.`c

    inherited from the `FromClause.c` attribute of `FromClause`

    A synonym for `FromClause.columns`

    Returns:

      a `ColumnCollection`

  attribute `sqlalchemy.sql.expression.TableClause.`columns

    inherited from the `FromClause.columns` attribute of `FromClause`

    A named-based collection of `ColumnElement` objects maintained by this `FromClause`.

    The `columns`, or `c` collection, is the gateway to the construction of SQL expressions using table-bound or other selectable-bound columns:

        select(mytable).where(mytable.c.somecolumn == 5)

    Returns:

      a `ColumnCollection` object.

  method `sqlalchemy.sql.expression.TableClause.`compare(other: ClauseElement, **kw: Any) → bool

    inherited from the `ClauseElement.compare()` method of `ClauseElement`

    Compare this `ClauseElement` to the given `ClauseElement`.

    Subclasses should override the default behavior, which is a straight identity comparison.

    **kw are arguments consumed by subclass `compare()` methods and may be used to modify the criteria for comparison (see `ColumnElement`).

  method `sqlalchemy.sql.expression.TableClause.`compile(bind: _HasDialect | None = None, dialect: Dialect | None = None, **kw: Any) → Compiled

    inherited from the `CompilerElement.compile()` method of `CompilerElement`

    Compile this SQL expression.

    The return value is a `Compiled` object. Calling `str()` or `unicode()` on the returned value will yield a string representation of the result. The `Compiled` object also can return a dictionary of bind parameter names and values using the `params` accessor.

    Parameters:

      - bind – An `Connection` or `Engine` which can provide a `Dialect` in order to generate a `Compiled` object. If the `bind` and `dialect` parameters are both omitted, a default SQL compiler is used.

      - column_keys – Used for INSERT and UPDATE statements, a list of column names which should be present in the VALUES clause of the compiled statement. If `None`, all columns from the target table object are rendered.

      - dialect – A `Dialect` instance which can generate a `Compiled` object. This argument takes precedence over the `bind` argument.

      - compile_kwargs –

        optional dictionary of additional parameters that will be passed through to the compiler within all “visit” methods. This allows any custom flag to be passed through to a custom compilation construct, for example. It is also used for the case of passing the `literal_binds` flag through:

            from sqlalchemy.sql import table, column, select

            t = table("t", column("x"))

            s = select(t).where(t.c.x == 5)

            print(s.compile(compile_kwargs={"literal_binds": True}))

    See also

    How do I render SQL expressions as strings, possibly with bound parameters inlined?

  method `sqlalchemy.sql.expression.TableClause.`corresponding_column(column: KeyedColumnElement[Any], require_embedded: bool = False) → KeyedColumnElement[Any] | None

    inherited from the `Selectable.corresponding_column()` method of `Selectable`

    Given a `ColumnElement`, return the exported `ColumnElement` object from the `Selectable.exported_columns` collection of this `Selectable` which corresponds to that original `ColumnElement` via a common ancestor column.

    Parameters:

      - column – the target `ColumnElement` to be matched.

      - require_embedded – only return corresponding columns for the given `ColumnElement`, if the given `ColumnElement` is actually present within a sub-element of this `Selectable`. Normally the column will match if it merely shares a common ancestor with one of the exported columns of this `Selectable`.

    See also

    `Selectable.exported_columns` - the `ColumnCollection` that is used for the operation.

    `ColumnCollection.corresponding_column()` - implementation method.

  method `sqlalchemy.sql.expression.TableClause.`delete() → Delete

    Generate a `delete()` construct against this `TableClause`.

    E.g.:

        table.delete().where(table.c.id == 7)

    See `delete()` for argument and usage information.

  attribute `sqlalchemy.sql.expression.TableClause.`description
  attribute `sqlalchemy.sql.expression.TableClause.`entity_namespace

    inherited from the `FromClause.entity_namespace` attribute of `FromClause`

    Return a namespace used for name-based access in SQL expressions.

    This is the namespace that is used to resolve “filter_by()” type expressions, such as:

        stmt.filter_by(address="some address")

    It defaults to the `.c` collection, however internally it can be overridden using the “entity_namespace” annotation to deliver alternative results.

  attribute `sqlalchemy.sql.expression.TableClause.`exported_columns

    inherited from the `FromClause.exported_columns` attribute of `FromClause`

    A `ColumnCollection` that represents the “exported” columns of this `FromClause`.

    The “exported” columns for a `FromClause` object are synonymous with the `FromClause.columns` collection.

    Added in version 1.4.

    See also

    `Selectable.exported_columns`

    `SelectBase.exported_columns`

  attribute `sqlalchemy.sql.expression.TableClause.`foreign_keys

    inherited from the `FromClause.foreign_keys` attribute of `FromClause`

    Return the collection of `ForeignKey` marker objects which this FromClause references.

    Each `ForeignKey` is a member of a `Table`-wide `ForeignKeyConstraint`.

    See also

    `Table.foreign_key_constraints`

  method `sqlalchemy.sql.expression.TableClause.`get_children(*, omit_attrs: Tuple[str, ...] = (), **kw: Any) → Iterable[HasTraverseInternals]

    inherited from the `HasTraverseInternals.get_children()` method of `HasTraverseInternals`

    Return immediate child `HasTraverseInternals` elements of this `HasTraverseInternals`.

    This is used for visit traversal.

    **kw may contain flags that change the collection that is returned, for example to return a subset of items in order to cut down on larger traversals, or to return child items from a different context (such as schema-level collections instead of clause-level).

  attribute `sqlalchemy.sql.expression.TableClause.`implicit_returning = False

    `TableClause` doesn’t support having a primary key or column -level defaults, so implicit returning doesn’t apply.

  attribute `sqlalchemy.sql.expression.TableClause.`inherit_cache = None

    inherited from the `HasCacheKey.inherit_cache` attribute of `HasCacheKey`

    Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.

    The attribute defaults to `None`, which indicates that a construct has not yet taken into account whether or not its appropriate for it to participate in caching; this is functionally equivalent to setting the value to `False`, except that a warning is also emitted.

    This flag can be set to `True` on a particular class, if the SQL that corresponds to the object does not change based on attributes which are local to this class, and not its superclass.

    See also

    Enabling Caching Support for Custom Constructs - General guideslines for setting the `HasCacheKey.inherit_cache` attribute for third-party or user defined SQL constructs.

  method `sqlalchemy.sql.expression.TableClause.`insert() → Insert

    Generate an `Insert` construct against this `TableClause`.

    E.g.:

        table.insert().values(name="foo")

    See `insert()` for argument and usage information.

  method `sqlalchemy.sql.expression.TableClause.`is_derived_from(fromclause: FromClause | None) → bool

    inherited from the `FromClause.is_derived_from()` method of `FromClause`

    Return `True` if this `FromClause` is ‘derived’ from the given `FromClause`.

    An example would be an Alias of a Table is derived from that Table.

  method `sqlalchemy.sql.expression.TableClause.`join(right: _FromClauseArgument, onclause: _ColumnExpressionArgument[bool] | None = None, isouter: bool = False, full: bool = False) → Join

    inherited from the `FromClause.join()` method of `FromClause`

    Return a `Join` from this `FromClause` to another `FromClause`.

    E.g.:

        from sqlalchemy import join

        j = user_table.join(
            address_table, user_table.c.id == address_table.c.user_id
        )
        stmt = select(user_table).select_from(j)

    would emit SQL along the lines of:

        SELECT user.id, user.name FROM user
        JOIN address ON user.id = address.user_id

    Parameters:

      - right – the right side of the join; this is any `FromClause` object such as a `Table` object, and may also be a selectable-compatible object such as an ORM-mapped class.

      - onclause – a SQL expression representing the ON clause of the join. If left at `None`, `FromClause.join()` will attempt to join the two tables based on a foreign key relationship.

      - isouter – if True, render a LEFT OUTER JOIN, instead of JOIN.

      - full – if True, render a FULL OUTER JOIN, instead of LEFT OUTER JOIN. Implies `FromClause.join.isouter`.

    See also

    `join()` - standalone function

    `Join` - the type of object produced

  method `sqlalchemy.sql.expression.TableClause.`lateral(name: str | None = None) → LateralFromClause

    inherited from the `Selectable.lateral()` method of `Selectable`

    Return a LATERAL alias of this `Selectable`.

    The return value is the `Lateral` construct also provided by the top-level `lateral()` function.

    See also

    LATERAL correlation - overview of usage.

  method `sqlalchemy.sql.expression.TableClause.`outerjoin(right: _FromClauseArgument, onclause: _ColumnExpressionArgument[bool] | None = None, full: bool = False) → Join

    inherited from the `FromClause.outerjoin()` method of `FromClause`

    Return a `Join` from this `FromClause` to another `FromClause`, with the “isouter” flag set to True.

    E.g.:

        from sqlalchemy import outerjoin

        j = user_table.outerjoin(
            address_table, user_table.c.id == address_table.c.user_id
        )

    The above is equivalent to:

        j = user_table.join(
            address_table, user_table.c.id == address_table.c.user_id, isouter=True
        )

    Parameters:

      - right – the right side of the join; this is any `FromClause` object such as a `Table` object, and may also be a selectable-compatible object such as an ORM-mapped class.

      - onclause – a SQL expression representing the ON clause of the join. If left at `None`, `FromClause.join()` will attempt to join the two tables based on a foreign key relationship.

      - full – if True, render a FULL OUTER JOIN, instead of LEFT OUTER JOIN.

    See also

    `FromClause.join()`

    `Join`

  method `sqlalchemy.sql.expression.TableClause.`params(*optionaldict: Any, **kwargs: Any) → NoReturn

    inherited from the `Immutable.params()` method of `Immutable`

    Return a copy with `bindparam()` elements replaced.

    Returns a copy of this ClauseElement with `bindparam()` elements replaced with values taken from the given dictionary:

        >>> clause = column("x") + bindparam("foo")
        >>> print(clause.compile().params)
        {'foo':None}
        >>> print(clause.params({"foo": 7}).compile().params)
        {'foo':7}

  attribute `sqlalchemy.sql.expression.TableClause.`primary_key

    inherited from the `FromClause.primary_key` attribute of `FromClause`

    Return the iterable collection of `Column` objects which comprise the primary key of this `_selectable.FromClause`.

    For a `Table` object, this collection is represented by the `PrimaryKeyConstraint` which itself is an iterable collection of `Column` objects.

  method `sqlalchemy.sql.expression.TableClause.`replace_selectable(old: FromClause, alias: Alias) → Self

    inherited from the `Selectable.replace_selectable()` method of `Selectable`

    Replace all occurrences of `FromClause` ‘old’ with the given `Alias` object, returning a copy of this `FromClause`.

    Deprecated since version 1.4: The `Selectable.replace_selectable()` method is deprecated, and will be removed in a future release. Similar functionality is available via the sqlalchemy.sql.visitors module.

  attribute `sqlalchemy.sql.expression.TableClause.`schema = None

    inherited from the `FromClause.schema` attribute of `FromClause`

    Define the ‘schema’ attribute for this `FromClause`.

    This is typically `None` for most objects except that of `Table`, where it is taken as the value of the `Table.schema` argument.

  method `sqlalchemy.sql.expression.TableClause.`select() → Select

    inherited from the `FromClause.select()` method of `FromClause`

    Return a SELECT of this `FromClause`.

    e.g.:

        stmt = some_table.select().where(some_table.c.id == 5)

    See also

    `select()` - general purpose method which allows for arbitrary column lists.

  method `sqlalchemy.sql.expression.TableClause.`self_group(against: OperatorType | None = None) → ClauseElement

    inherited from the `ClauseElement.self_group()` method of `ClauseElement`

    Apply a ‘grouping’ to this `ClauseElement`.

    This method is overridden by subclasses to return a “grouping” construct, i.e. parenthesis. In particular it’s used by “binary” expressions to provide a grouping around themselves when placed into a larger expression, as well as by `select()` constructs when placed into the FROM clause of another `select()`. (Note that subqueries should be normally created using the `Select.alias()` method, as many platforms require nested SELECT statements to be named).

    As expressions are composed together, the application of `self_group()` is automatic - end-user code should never need to use this method directly. Note that SQLAlchemy’s clause constructs take operator precedence into account - so parenthesis might not be needed, for example, in an expression like `x OR (y AND z)` - AND takes precedence over OR.

    The base `self_group()` method of `ClauseElement` just returns self.

  method `sqlalchemy.sql.expression.TableClause.`table_valued() → TableValuedColumn[Any]

    inherited from the `NamedFromClause.table_valued()` method of `NamedFromClause`

    Return a `TableValuedColumn` object for this `FromClause`.

    A `TableValuedColumn` is a `ColumnElement` that represents a complete row in a table. Support for this construct is backend dependent, and is supported in various forms by backends such as PostgreSQL, Oracle Database and SQL Server.

    E.g.:

        >>> from sqlalchemy import select, column, func, table
        >>> a = table("a", column("id"), column("x"), column("y"))
        >>> stmt = select(func.row_to_json(a.table_valued()))
        >>> print(stmt)
        SELECT row_to_json(a) AS row_to_json_1
        FROM a

    Added in version 1.4.0b2.

    See also

    Working with SQL Functions - in the SQLAlchemy Unified Tutorial

  method `sqlalchemy.sql.expression.TableClause.`tablesample(sampling: float | Function[Any], name: str | None = None, seed: roles.ExpressionElementRole[Any] | None = None) → TableSample

    inherited from the `FromClause.tablesample()` method of `FromClause`

    Return a TABLESAMPLE alias of this `FromClause`.

    The return value is the `TableSample` construct also provided by the top-level `tablesample()` function.

    See also

    `tablesample()` - usage guidelines and parameters

  method `sqlalchemy.sql.expression.TableClause.`unique_params(*optionaldict: Any, **kwargs: Any) → NoReturn

    inherited from the `Immutable.unique_params()` method of `Immutable`

    Return a copy with `bindparam()` elements replaced.

    Same functionality as `ClauseElement.params()`, except adds unique=True to affected bind parameters so that multiple statements can be used.

  method `sqlalchemy.sql.expression.TableClause.`update() → Update

    Generate an `update()` construct against this `TableClause`.

    E.g.:

        table.update().where(table.c.id == 7).values(name="foo")

    See `update()` for argument and usage information.

class sqlalchemy.sql.expression.TableSample

  inherits from `sqlalchemy.sql.expression.FromClauseAlias`

  Represent a TABLESAMPLE clause.

  This object is constructed from the `tablesample()` module level function as well as the `FromClause.tablesample()` method available on all `FromClause` subclasses.

  See also

  `tablesample()`

class sqlalchemy.sql.expression.TableValuedAlias

  inherits from `sqlalchemy.sql.expression.LateralFromClause`, `sqlalchemy.sql.expression.Alias`

  An alias against a “table valued” SQL function.

  This construct provides for a SQL function that returns columns to be used in the FROM clause of a SELECT statement. The object is generated using the `FunctionElement.table_valued()` method, e.g.:

      >>> from sqlalchemy import select, func
      >>> fn = func.json_array_elements_text('["one", "two", "three"]').table_valued(
      ...     "value"
      ... )
      >>> print(select(fn.c.value))
      SELECT anon_1.value
      FROM json_array_elements_text(:json_array_elements_text_1) AS anon_1

  Added in version 1.4.0b2.

  See also

  Table-Valued Functions - in the SQLAlchemy Unified Tutorial

  Member Name | Description
  --- | ---
  alias() | Return a new alias of this `TableValuedAlias`.
  column | Return a column expression representing this `TableValuedAlias`.
  lateral() | Return a new `TableValuedAlias` with the lateral flag set, so that it renders as LATERAL.
  render_derived() | Apply “render derived” to this `TableValuedAlias`.

  method `sqlalchemy.sql.expression.TableValuedAlias.`alias(name: str | None = None, flat: bool = False) → TableValuedAlias

    Return a new alias of this `TableValuedAlias`.

    This creates a distinct FROM object that will be distinguished from the original one when used in a SQL statement.

  attribute `sqlalchemy.sql.expression.TableValuedAlias.`column

    Return a column expression representing this `TableValuedAlias`.

    This accessor is used to implement the `FunctionElement.column_valued()` method. See that method for further details.

    E.g.:

        >>> print(select(func.some_func().table_valued("value").column))
        SELECT anon_1 FROM some_func() AS anon_1

    See also

    `FunctionElement.column_valued()`

  method `sqlalchemy.sql.expression.TableValuedAlias.`lateral(name: str | None = None) → LateralFromClause

    Return a new `TableValuedAlias` with the lateral flag set, so that it renders as LATERAL.

    See also

    `lateral()`

  method `sqlalchemy.sql.expression.TableValuedAlias.`render_derived(name: str | None = None, with_types: bool = False) → TableValuedAlias

    Apply “render derived” to this `TableValuedAlias`.

    This has the effect of the individual column names listed out after the alias name in the “AS” sequence, e.g.:

        >>> print(
        ...     select(
        ...         func.unnest(array(["one", "two", "three"]))
        ...         .table_valued("x", with_ordinality="o")
        ...         .render_derived()
        ...     )
        ... )
        SELECT anon_1.x, anon_1.o
        FROM unnest(ARRAY[%(param_1)s, %(param_2)s, %(param_3)s]) WITH ORDINALITY AS anon_1(x, o)

    The `with_types` keyword will render column types inline within the alias expression (this syntax currently applies to the PostgreSQL database):

        >>> print(
        ...     select(
        ...         func.json_to_recordset('[{"a":1,"b":"foo"},{"a":"2","c":"bar"}]')
        ...         .table_valued(column("a", Integer), column("b", String))
        ...         .render_derived(with_types=True)
        ...     )
        ... )
        SELECT anon_1.a, anon_1.b FROM json_to_recordset(:json_to_recordset_1)
        AS anon_1(a INTEGER, b VARCHAR)

    Parameters:

      - name – optional string name that will be applied to the alias generated. If left as None, a unique anonymizing name will be used.

      - with_types – if True, the derived columns will include the datatype specification with each column. This is a special syntax currently known to be required by PostgreSQL for some SQL functions.

class sqlalchemy.sql.expression.TextualSelect

  inherits from `sqlalchemy.sql.expression.SelectBase`, `sqlalchemy.sql.expression.ExecutableReturnsRows`, `sqlalchemy.sql.expression.Generative`

  Wrap a `TextClause` construct within a `SelectBase` interface.

  This allows the `TextClause` object to gain a `.c` collection and other FROM-like capabilities such as `FromClause.alias()`, `SelectBase.cte()`, etc.

  The `TextualSelect` construct is produced via the `TextClause.columns()` method - see that method for details.

  Changed in version 1.4: the `TextualSelect` class was renamed from `TextAsFrom`, to more correctly suit its role as a SELECT-oriented object and not a FROM clause.

  See also

  `text()`

  `TextClause.columns()` - primary creation interface.

  Member Name | Description
  --- | ---
  add_cte() | Add one or more `CTE` constructs to this statement.
  alias() | Return a named subquery against this `SelectBase`.
  as_scalar() |
  compare() | Compare this `ClauseElement` to the given `ClauseElement`.
  compile() | Compile this SQL expression.
  corresponding_column() | Given a `ColumnElement`, return the exported `ColumnElement` object from the `Selectable.exported_columns` collection of this `Selectable` which corresponds to that original `ColumnElement` via a common ancestor column.
  cte() | Return a new `CTE`, or Common Table Expression instance.
  execution_options() | Set non-SQL options for the statement which take effect during execution.
  exists() | Return an `Exists` representation of this selectable, which can be used as a column expression.
  get_children() | Return immediate child `HasTraverseInternals` elements of this `HasTraverseInternals`.
  get_execution_options() | Get the non-SQL options which will take effect during execution.
  get_label_style() | Retrieve the current label style.
  inherit_cache | Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.
  into() | Create a `CreateTableAs` construct from this SELECT.
  is_derived_from() | Return `True` if this `ReturnsRows` is ‘derived’ from the given `FromClause`.
  label() | Return a ‘scalar’ representation of this selectable, embedded as a subquery with a label.
  lateral() | Return a LATERAL alias of this `Selectable`.
  name_cte_columns | indicates if this HasCTE as contained within a CTE should compel the CTE to render the column names of this object in the WITH clause.
  options() | Apply options to this statement.
  params() | Return a copy with the provided bindparam values.
  replace_selectable() | Replace all occurrences of `FromClause` ‘old’ with the given `Alias` object, returning a copy of this `FromClause`.
  scalar_subquery() | Return a ‘scalar’ representation of this selectable, which can be used as a column expression.
  selected_columns | A `ColumnCollection` representing the columns that this SELECT statement or similar construct returns in its result set, not including `TextClause` constructs.
  self_group() | Apply a ‘grouping’ to this `ClauseElement`.
  set_label_style() | Return a new selectable with the specified label style.
  subquery() | Return a subquery of this `SelectBase`.
  unique_params() | Return a copy with `bindparam()` elements replaced.

  method `sqlalchemy.sql.expression.TextualSelect.`add_cte(*ctes: CTE, nest_here: bool = False) → Self

    inherited from the `HasCTE.add_cte()` method of `HasCTE`

    Add one or more `CTE` constructs to this statement.

    This method will associate the given `CTE` constructs with the parent statement such that they will each be unconditionally rendered in the WITH clause of the final statement, even if not referenced elsewhere within the statement or any sub-selects.

    The optional `HasCTE.add_cte.nest_here` parameter when set to True will have the effect that each given `CTE` will render in a WITH clause rendered directly along with this statement, rather than being moved to the top of the ultimate rendered statement, even if this statement is rendered as a subquery within a larger statement.

    This method has two general uses. One is to embed CTE statements that serve some purpose without being referenced explicitly, such as the use case of embedding a DML statement such as an INSERT or UPDATE as a CTE inline with a primary statement that may draw from its results indirectly. The other is to provide control over the exact placement of a particular series of CTE constructs that should remain rendered directly in terms of a particular statement that may be nested in a larger statement.

    E.g.:

        from sqlalchemy import table, column, select

        t = table("t", column("c1"), column("c2"))

        ins = t.insert().values({"c1": "x", "c2": "y"}).cte()

        stmt = select(t).add_cte(ins)

    Would render:

        WITH anon_1 AS (
            INSERT INTO t (c1, c2) VALUES (:param_1, :param_2)
        )
        SELECT t.c1, t.c2
        FROM t

    Above, the “anon_1” CTE is not referenced in the SELECT statement, however still accomplishes the task of running an INSERT statement.

    Similarly in a DML-related context, using the PostgreSQL `Insert` construct to generate an “upsert”:

        from sqlalchemy import table, column
        from sqlalchemy.dialects.postgresql import insert

        t = table("t", column("c1"), column("c2"))

        delete_statement_cte = t.delete().where(t.c.c1 < 1).cte("deletions")

        insert_stmt = insert(t).values({"c1": 1, "c2": 2})
        update_statement = insert_stmt.on_conflict_do_update(
            index_elements=[t.c.c1],
            set_={
                "c1": insert_stmt.excluded.c1,
                "c2": insert_stmt.excluded.c2,
            },
        ).add_cte(delete_statement_cte)

        print(update_statement)

    The above statement renders as:

        WITH deletions AS (
            DELETE FROM t WHERE t.c1 < %(c1_1)s
        )
        INSERT INTO t (c1, c2) VALUES (%(c1)s, %(c2)s)
        ON CONFLICT (c1) DO UPDATE SET c1 = excluded.c1, c2 = excluded.c2

    Added in version 1.4.21.

    Parameters:

      - *ctes –

        zero or more `CTE` constructs.

        Changed in version 2.0: Multiple CTE instances are accepted

      - nest_here –

        if True, the given CTE or CTEs will be rendered as though they specified the `HasCTE.cte.nesting` flag to `True` when they were added to this `HasCTE`. Assuming the given CTEs are not referenced in an outer-enclosing statement as well, the CTEs given should render at the level of this statement when this flag is given.

        Added in version 2.0.

        See also

        `HasCTE.cte.nesting`

  method `sqlalchemy.sql.expression.TextualSelect.`alias(name: str | None = None, flat: bool = False) → Subquery

    inherited from the `SelectBase.alias()` method of `SelectBase`

    Return a named subquery against this `SelectBase`.

    For a `SelectBase` (as opposed to a `FromClause`), this returns a `Subquery` object which behaves mostly the same as the `Alias` object that is used with a `FromClause`.

    Changed in version 1.4: The `SelectBase.alias()` method is now a synonym for the `SelectBase.subquery()` method.

  method `sqlalchemy.sql.expression.TextualSelect.`as_scalar() → ScalarSelect[Any]

    inherited from the `SelectBase.as_scalar()` method of `SelectBase`

    Deprecated since version 1.4: The `SelectBase.as_scalar()` method is deprecated and will be removed in a future release. Please refer to `SelectBase.scalar_subquery()`.

  method `sqlalchemy.sql.expression.TextualSelect.`compare(other: ClauseElement, **kw: Any) → bool

    inherited from the `ClauseElement.compare()` method of `ClauseElement`

    Compare this `ClauseElement` to the given `ClauseElement`.

    Subclasses should override the default behavior, which is a straight identity comparison.

    **kw are arguments consumed by subclass `compare()` methods and may be used to modify the criteria for comparison (see `ColumnElement`).

  method `sqlalchemy.sql.expression.TextualSelect.`compile(bind: _HasDialect | None = None, dialect: Dialect | None = None, **kw: Any) → Compiled

    inherited from the `CompilerElement.compile()` method of `CompilerElement`

    Compile this SQL expression.

    The return value is a `Compiled` object. Calling `str()` or `unicode()` on the returned value will yield a string representation of the result. The `Compiled` object also can return a dictionary of bind parameter names and values using the `params` accessor.

    Parameters:

      - bind – An `Connection` or `Engine` which can provide a `Dialect` in order to generate a `Compiled` object. If the `bind` and `dialect` parameters are both omitted, a default SQL compiler is used.

      - column_keys – Used for INSERT and UPDATE statements, a list of column names which should be present in the VALUES clause of the compiled statement. If `None`, all columns from the target table object are rendered.

      - dialect – A `Dialect` instance which can generate a `Compiled` object. This argument takes precedence over the `bind` argument.

      - compile_kwargs –

        optional dictionary of additional parameters that will be passed through to the compiler within all “visit” methods. This allows any custom flag to be passed through to a custom compilation construct, for example. It is also used for the case of passing the `literal_binds` flag through:

            from sqlalchemy.sql import table, column, select

            t = table("t", column("x"))

            s = select(t).where(t.c.x == 5)

            print(s.compile(compile_kwargs={"literal_binds": True}))

    See also

    How do I render SQL expressions as strings, possibly with bound parameters inlined?

  method `sqlalchemy.sql.expression.TextualSelect.`corresponding_column(column: KeyedColumnElement[Any], require_embedded: bool = False) → KeyedColumnElement[Any] | None

    inherited from the `Selectable.corresponding_column()` method of `Selectable`

    Given a `ColumnElement`, return the exported `ColumnElement` object from the `Selectable.exported_columns` collection of this `Selectable` which corresponds to that original `ColumnElement` via a common ancestor column.

    Parameters:

      - column – the target `ColumnElement` to be matched.

      - require_embedded – only return corresponding columns for the given `ColumnElement`, if the given `ColumnElement` is actually present within a sub-element of this `Selectable`. Normally the column will match if it merely shares a common ancestor with one of the exported columns of this `Selectable`.

    See also

    `Selectable.exported_columns` - the `ColumnCollection` that is used for the operation.

    `ColumnCollection.corresponding_column()` - implementation method.

  method `sqlalchemy.sql.expression.TextualSelect.`cte(name: str | None = None, recursive: bool = False, nesting: bool = False) → CTE

    inherited from the `HasCTE.cte()` method of `HasCTE`

    Return a new `CTE`, or Common Table Expression instance.

    Common table expressions are a SQL standard whereby SELECT statements can draw upon secondary statements specified along with the primary statement, using a clause called “WITH”. Special semantics regarding UNION can also be employed to allow “recursive” queries, where a SELECT statement can draw upon the set of rows that have previously been selected.

    CTEs can also be applied to DML constructs UPDATE, INSERT and DELETE on some databases, both as a source of CTE rows when combined with RETURNING, as well as a consumer of CTE rows.

    SQLAlchemy detects `CTE` objects, which are treated similarly to `Alias` objects, as special elements to be delivered to the FROM clause of the statement as well as to a WITH clause at the top of the statement.

    For special prefixes such as PostgreSQL “MATERIALIZED” and “NOT MATERIALIZED”, the `CTE.prefix_with()` method may be used to establish these.

    Parameters:

      - name – name given to the common table expression. Like `FromClause.alias()`, the name can be left as `None` in which case an anonymous symbol will be used at query compile time.

      - recursive – if `True`, will render `WITH RECURSIVE`. A recursive common table expression is intended to be used in conjunction with UNION ALL in order to derive rows from those already selected.

      - nesting –

        if `True`, will render the CTE locally to the statement in which it is referenced. For more complex scenarios, the `HasCTE.add_cte()` method using the `HasCTE.add_cte.nest_here` parameter may also be used to more carefully control the exact placement of a particular CTE.

        Added in version 1.4.24.

        See also

        `HasCTE.add_cte()`

    The following examples include two from PostgreSQL’s documentation at https://www.postgresql.org/docs/current/static/queries-with.html, as well as additional examples.

    Example 1, non recursive:

        from sqlalchemy import (
            Table,
            Column,
            String,
            Integer,
            MetaData,
            select,
            func,
        )

        metadata = MetaData()

        orders = Table(
            "orders",
            metadata,
            Column("region", String),
            Column("amount", Integer),
            Column("product", String),
            Column("quantity", Integer),
        )

        regional_sales = (
            select(orders.c.region, func.sum(orders.c.amount).label("total_sales"))
            .group_by(orders.c.region)
            .cte("regional_sales")
        )

        top_regions = (
            select(regional_sales.c.region)
            .where(
                regional_sales.c.total_sales
                > select(func.sum(regional_sales.c.total_sales) / 10)
            )
            .cte("top_regions")
        )

        statement = (
            select(
                orders.c.region,
                orders.c.product,
                func.sum(orders.c.quantity).label("product_units"),
                func.sum(orders.c.amount).label("product_sales"),
            )
            .where(orders.c.region.in_(select(top_regions.c.region)))
            .group_by(orders.c.region, orders.c.product)
        )

        result = conn.execute(statement).fetchall()

    Example 2, WITH RECURSIVE:

        from sqlalchemy import (
            Table,
            Column,
            String,
            Integer,
            MetaData,
            select,
            func,
        )

        metadata = MetaData()

        parts = Table(
            "parts",
            metadata,
            Column("part", String),
            Column("sub_part", String),
            Column("quantity", Integer),
        )

        included_parts = (
            select(parts.c.sub_part, parts.c.part, parts.c.quantity)
            .where(parts.c.part == "our part")
            .cte(recursive=True)
        )

        incl_alias = included_parts.alias()
        parts_alias = parts.alias()
        included_parts = included_parts.union_all(
            select(
                parts_alias.c.sub_part, parts_alias.c.part, parts_alias.c.quantity
            ).where(parts_alias.c.part == incl_alias.c.sub_part)
        )

        statement = select(
            included_parts.c.sub_part,
            func.sum(included_parts.c.quantity).label("total_quantity"),
        ).group_by(included_parts.c.sub_part)

        result = conn.execute(statement).fetchall()

    Example 3, an upsert using UPDATE and INSERT with CTEs:

        from datetime import date
        from sqlalchemy import (
            MetaData,
            Table,
            Column,
            Integer,
            Date,
            select,
            literal,
            and_,
            exists,
        )

        metadata = MetaData()

        visitors = Table(
            "visitors",
            metadata,
            Column("product_id", Integer, primary_key=True),
            Column("date", Date, primary_key=True),
            Column("count", Integer),
        )

        # add 5 visitors for the product_id == 1
        product_id = 1
        day = date.today()
        count = 5

        update_cte = (
            visitors.update()
            .where(
                and_(visitors.c.product_id == product_id, visitors.c.date == day)
            )
            .values(count=visitors.c.count + count)
            .returning(literal(1))
            .cte("update_cte")
        )

        upsert = visitors.insert().from_select(
            [visitors.c.product_id, visitors.c.date, visitors.c.count],
            select(literal(product_id), literal(day), literal(count)).where(
                ~exists(update_cte.select())
            ),
        )

        connection.execute(upsert)

    Example 4, Nesting CTE (SQLAlchemy 1.4.24 and above):

        value_a = select(literal("root").label("n")).cte("value_a")

        # A nested CTE with the same name as the root one
        value_a_nested = select(literal("nesting").label("n")).cte(
            "value_a", nesting=True
        )

        # Nesting CTEs takes ascendency locally
        # over the CTEs at a higher level
        value_b = select(value_a_nested.c.n).cte("value_b")

        value_ab = select(value_a.c.n.label("a"), value_b.c.n.label("b"))

    The above query will render the second CTE nested inside the first, shown with inline parameters below as:

        WITH
            value_a AS
                (SELECT 'root' AS n),
            value_b AS
                (WITH value_a AS
                    (SELECT 'nesting' AS n)
                SELECT value_a.n AS n FROM value_a)
        SELECT value_a.n AS a, value_b.n AS b
        FROM value_a, value_b

    The same CTE can be set up using the `HasCTE.add_cte()` method as follows (SQLAlchemy 2.0 and above):

        value_a = select(literal("root").label("n")).cte("value_a")

        # A nested CTE with the same name as the root one
        value_a_nested = select(literal("nesting").label("n")).cte("value_a")

        # Nesting CTEs takes ascendency locally
        # over the CTEs at a higher level
        value_b = (
            select(value_a_nested.c.n)
            .add_cte(value_a_nested, nest_here=True)
            .cte("value_b")
        )

        value_ab = select(value_a.c.n.label("a"), value_b.c.n.label("b"))

    Example 5, Non-Linear CTE (SQLAlchemy 1.4.28 and above):

        edge = Table(
            "edge",
            metadata,
            Column("id", Integer, primary_key=True),
            Column("left", Integer),
            Column("right", Integer),
        )

        root_node = select(literal(1).label("node")).cte("nodes", recursive=True)

        left_edge = select(edge.c.left).join(
            root_node, edge.c.right == root_node.c.node
        )
        right_edge = select(edge.c.right).join(
            root_node, edge.c.left == root_node.c.node
        )

        subgraph_cte = root_node.union(left_edge, right_edge)

        subgraph = select(subgraph_cte)

    The above query will render 2 UNIONs inside the recursive CTE:

        WITH RECURSIVE nodes(node) AS (
                SELECT 1 AS node
            UNION
                SELECT edge."left" AS "left"
                FROM edge JOIN nodes ON edge."right" = nodes.node
            UNION
                SELECT edge."right" AS "right"
                FROM edge JOIN nodes ON edge."left" = nodes.node
        )
        SELECT nodes.node FROM nodes

    See also

    `Query.cte()` - ORM version of `HasCTE.cte()`.

  method `sqlalchemy.sql.expression.TextualSelect.`execution_options(**kw: Any) → Self

    inherited from the `Executable.execution_options()` method of `Executable`

    Set non-SQL options for the statement which take effect during execution.

    Execution options can be set at many scopes, including per-statement, per-connection, or per execution, using methods such as `Connection.execution_options()` and parameters which accept a dictionary of options such as `Connection.execute.execution_options` and `Session.execute.execution_options`.

    The primary characteristic of an execution option, as opposed to other kinds of options such as ORM loader options, is that execution options never affect the compiled SQL of a query, only things that affect how the SQL statement itself is invoked or how results are fetched. That is, execution options are not part of what’s accommodated by SQL compilation nor are they considered part of the cached state of a statement.

    The `Executable.execution_options()` method is generative, as is the case for the method as applied to the `Engine` and `Query` objects, which means when the method is called, a copy of the object is returned, which applies the given parameters to that new copy, but leaves the original unchanged:

        statement = select(table.c.x, table.c.y)
        new_statement = statement.execution_options(my_option=True)

    An exception to this behavior is the `Connection` object, where the `Connection.execution_options()` method is explicitly not generative.

    The kinds of options that may be passed to `Executable.execution_options()` and other related methods and parameter dictionaries include parameters that are explicitly consumed by SQLAlchemy Core or ORM, as well as arbitrary keyword arguments not defined by SQLAlchemy, which means the methods and/or parameter dictionaries may be used for user-defined parameters that interact with custom code, which may access the parameters using methods such as `Executable.get_execution_options()` and `Connection.get_execution_options()`, or within selected event hooks using a dedicated `execution_options` event parameter such as `ConnectionEvents.before_execute.execution_options` or `ORMExecuteState.execution_options`, e.g.:

        from sqlalchemy import event

        @event.listens_for(some_engine, "before_execute")
        def _process_opt(conn, statement, multiparams, params, execution_options):
            "run a SQL function before invoking a statement"

            if execution_options.get("do_special_thing", False):
                conn.exec_driver_sql("run_special_function()")

    Within the scope of options that are explicitly recognized by SQLAlchemy, most apply to specific classes of objects and not others. The most common execution options include:

    - `Connection.execution_options.isolation_level` - sets the isolation level for a connection or a class of connections via an `Engine`. This option is accepted only by `Connection` or `Engine`.

    - `Connection.execution_options.stream_results` - indicates results should be fetched using a server side cursor; this option is accepted by `Connection`, by the `Connection.execute.execution_options` parameter on `Connection.execute()`, and additionally by `Executable.execution_options()` on a SQL statement object, as well as by ORM constructs like `Session.execute()`.

    - `Connection.execution_options.compiled_cache` - indicates a dictionary that will serve as the SQL compilation cache for a `Connection` or `Engine`, as well as for ORM methods like `Session.execute()`. Can be passed as `None` to disable caching for statements. This option is not accepted by `Executable.execution_options()` as it is inadvisable to carry along a compilation cache within a statement object.

    - `Connection.execution_options.schema_translate_map` - a mapping of schema names used by the Schema Translate Map feature, accepted by `Connection`, `Engine`, `Executable`, as well as by ORM constructs like `Session.execute()`.

    See also

    `Connection.execution_options()`

    `Connection.execute.execution_options`

    `Session.execute.execution_options`

    ORM Execution Options - documentation on all ORM-specific execution options

  method `sqlalchemy.sql.expression.TextualSelect.`exists() → Exists

    inherited from the `SelectBase.exists()` method of `SelectBase`

    Return an `Exists` representation of this selectable, which can be used as a column expression.

    The returned object is an instance of `Exists`.

    See also

    `exists()`

    EXISTS subqueries - in the 2.0 style tutorial.

    Added in version 1.4.

  property exported_columns: ReadOnlyColumnCollection[str, ColumnElement[Any]]

    A `ColumnCollection` that represents the “exported” columns of this `Selectable`, not including `TextClause` constructs.

    The “exported” columns for a `SelectBase` object are synonymous with the `SelectBase.selected_columns` collection.

    Added in version 1.4.

    See also

    `Select.exported_columns`

    `Selectable.exported_columns`

    `FromClause.exported_columns`

  method `sqlalchemy.sql.expression.TextualSelect.`get_children(*, omit_attrs: Tuple[str, ...] = (), **kw: Any) → Iterable[HasTraverseInternals]

    inherited from the `HasTraverseInternals.get_children()` method of `HasTraverseInternals`

    Return immediate child `HasTraverseInternals` elements of this `HasTraverseInternals`.

    This is used for visit traversal.

    **kw may contain flags that change the collection that is returned, for example to return a subset of items in order to cut down on larger traversals, or to return child items from a different context (such as schema-level collections instead of clause-level).

  method `sqlalchemy.sql.expression.TextualSelect.`get_execution_options() → _ExecuteOptions

    inherited from the `Executable.get_execution_options()` method of `Executable`

    Get the non-SQL options which will take effect during execution.

    See also

    `Executable.execution_options()`

  method `sqlalchemy.sql.expression.TextualSelect.`get_label_style() → SelectLabelStyle

    inherited from the `SelectBase.get_label_style()` method of `SelectBase`

    Retrieve the current label style.

    Implemented by subclasses.

  attribute `sqlalchemy.sql.expression.TextualSelect.`inherit_cache = None

    inherited from the `HasCacheKey.inherit_cache` attribute of `HasCacheKey`

    Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.

    The attribute defaults to `None`, which indicates that a construct has not yet taken into account whether or not its appropriate for it to participate in caching; this is functionally equivalent to setting the value to `False`, except that a warning is also emitted.

    This flag can be set to `True` on a particular class, if the SQL that corresponds to the object does not change based on attributes which are local to this class, and not its superclass.

    See also

    Enabling Caching Support for Custom Constructs - General guideslines for setting the `HasCacheKey.inherit_cache` attribute for third-party or user defined SQL constructs.

  method `sqlalchemy.sql.expression.TextualSelect.`into(target: str, *, metadata: 'MetaData' | None = None, schema: str | None = None, temporary: bool = False, if_not_exists: bool = False) → CreateTableAs

    inherited from the `SelectBase.into()` method of `SelectBase`

    Create a `CreateTableAs` construct from this SELECT.

    This method provides a convenient way to create a `CREATE TABLE ... AS` statement from a SELECT, as well as compound SELECTs like UNION. The new table will be created with columns matching the SELECT list.

    Supported on all included backends, the construct emits `CREATE TABLE...AS` for all backends except SQL Server, which instead emits a `SELECT..INTO` statement.

    e.g.:

        from sqlalchemy import select

        # Create a new table from a SELECT
        stmt = (
            select(users.c.id, users.c.name)
            .where(users.c.status == "active")
            .into("active_users")
        )

        with engine.begin() as conn:
            conn.execute(stmt)

        # With optional flags
        stmt = (
            select(users.c.id)
            .where(users.c.status == "inactive")
            .into("inactive_users", schema="analytics", if_not_exists=True)
        )

    Added in version 2.1.

    Parameters:

      - target – Name of the table to create as a string. Must be unqualified; use the `schema` parameter for qualification.

      - metadata – `MetaData`, optional If provided, the `Table` object available via the `CreateTableAs.table` attribute will be associated with this `MetaData`. Otherwise, a new, empty `MetaData` is created.

      - schema – Optional schema name for the new table.

      - temporary – If True, create a temporary table where supported

      - if_not_exists – If True, add IF NOT EXISTS clause where supported

    Returns:

      A `CreateTableAs` construct.

    See also

    Using CreateTableAs or Select.into() - in Describing Databases with MetaData

    `CreateTableAs`

  method `sqlalchemy.sql.expression.TextualSelect.`is_derived_from(fromclause: FromClause | None) → bool

    inherited from the `ReturnsRows.is_derived_from()` method of `ReturnsRows`

    Return `True` if this `ReturnsRows` is ‘derived’ from the given `FromClause`.

    An example would be an Alias of a Table is derived from that Table.

  method `sqlalchemy.sql.expression.TextualSelect.`label(name: str | None) → Label[Any]

    inherited from the `SelectBase.label()` method of `SelectBase`

    Return a ‘scalar’ representation of this selectable, embedded as a subquery with a label.

    See also

    `SelectBase.scalar_subquery()`.

  method `sqlalchemy.sql.expression.TextualSelect.`lateral(name: str | None = None) → LateralFromClause

    inherited from the `SelectBase.lateral()` method of `SelectBase`

    Return a LATERAL alias of this `Selectable`.

    The return value is the `Lateral` construct also provided by the top-level `lateral()` function.

    See also

    LATERAL correlation - overview of usage.

  attribute `sqlalchemy.sql.expression.TextualSelect.`name_cte_columns = False

    inherited from the `HasCTE.name_cte_columns` attribute of `HasCTE`

    indicates if this HasCTE as contained within a CTE should compel the CTE to render the column names of this object in the WITH clause.

    Added in version 2.0.42.

  method `sqlalchemy.sql.expression.TextualSelect.`options(*options: ExecutableOption) → Self

    inherited from the `Executable.options()` method of `Executable`

    Apply options to this statement.

    In the general sense, options are any kind of Python object that can be interpreted by systems that consume the statement outside of the regular SQL compiler chain. Specifically, these options are the ORM level options that apply “eager load” and other loading behaviors to an ORM query.

    For background on specific kinds of options for specific kinds of statements, refer to the documentation for those option objects.

    Changed in version 1.4: - added `Executable.options()` to Core statement objects towards the goal of allowing unified Core / ORM querying capabilities.

    See also

    Column Loading Options - refers to options specific to the usage of ORM queries

    Relationship Loading with Loader Options - refers to options specific to the usage of ORM queries

  method `sqlalchemy.sql.expression.TextualSelect.`params(_ExecutableStatement__optionaldict: _CoreSingleExecuteParams | None = None, /, **kwargs: Any) → Self

    inherited from the `ExecutableStatement.params()` method of `ExecutableStatement`

    Return a copy with the provided bindparam values.

    Returns a copy of this Executable with bindparam values set to the given dictionary:

        >>> clause = column("x") + bindparam("foo")
        >>> print(clause.compile().params)
        {'foo': None}
        >>> print(clause.params({"foo": 7}).compile().params)
        {'foo': 7}

  method `sqlalchemy.sql.expression.TextualSelect.`replace_selectable(old: FromClause, alias: Alias) → Self

    inherited from the `Selectable.replace_selectable()` method of `Selectable`

    Replace all occurrences of `FromClause` ‘old’ with the given `Alias` object, returning a copy of this `FromClause`.

    Deprecated since version 1.4: The `Selectable.replace_selectable()` method is deprecated, and will be removed in a future release. Similar functionality is available via the sqlalchemy.sql.visitors module.

  method `sqlalchemy.sql.expression.TextualSelect.`scalar_subquery() → ScalarSelect[Any]

    inherited from the `SelectBase.scalar_subquery()` method of `SelectBase`

    Return a ‘scalar’ representation of this selectable, which can be used as a column expression.

    The returned object is an instance of `ScalarSelect`.

    Typically, a select statement which has only one column in its columns clause is eligible to be used as a scalar expression. The scalar subquery can then be used in the WHERE clause or columns clause of an enclosing SELECT.

    Note that the scalar subquery differentiates from the FROM-level subquery that can be produced using the `SelectBase.subquery()` method.

    Changed in version 1.4: - the `.as_scalar()` method was renamed to `SelectBase.scalar_subquery()`.

    See also

    Scalar and Correlated Subqueries - in the 2.0 tutorial

  attribute `sqlalchemy.sql.expression.TextualSelect.`selected_columns

    A `ColumnCollection` representing the columns that this SELECT statement or similar construct returns in its result set, not including `TextClause` constructs.

    This collection differs from the `FromClause.columns` collection of a `FromClause` in that the columns within this collection cannot be directly nested inside another SELECT statement; a subquery must be applied first which provides for the necessary parenthesization required by SQL.

    For a `TextualSelect` construct, the collection contains the `ColumnElement` objects that were passed to the constructor, typically via the `TextClause.columns()` method.

    Added in version 1.4.

  method `sqlalchemy.sql.expression.TextualSelect.`self_group(against: OperatorType | None = None) → ClauseElement

    inherited from the `ClauseElement.self_group()` method of `ClauseElement`

    Apply a ‘grouping’ to this `ClauseElement`.

    This method is overridden by subclasses to return a “grouping” construct, i.e. parenthesis. In particular it’s used by “binary” expressions to provide a grouping around themselves when placed into a larger expression, as well as by `select()` constructs when placed into the FROM clause of another `select()`. (Note that subqueries should be normally created using the `Select.alias()` method, as many platforms require nested SELECT statements to be named).

    As expressions are composed together, the application of `self_group()` is automatic - end-user code should never need to use this method directly. Note that SQLAlchemy’s clause constructs take operator precedence into account - so parenthesis might not be needed, for example, in an expression like `x OR (y AND z)` - AND takes precedence over OR.

    The base `self_group()` method of `ClauseElement` just returns self.

  method `sqlalchemy.sql.expression.TextualSelect.`set_label_style(style: SelectLabelStyle) → TextualSelect

    Return a new selectable with the specified label style.

    Implemented by subclasses.

  method `sqlalchemy.sql.expression.TextualSelect.`subquery(name: str | None = None) → Subquery

    inherited from the `SelectBase.subquery()` method of `SelectBase`

    Return a subquery of this `SelectBase`.

    A subquery is from a SQL perspective a parenthesized, named construct that can be placed in the FROM clause of another SELECT statement.

    Given a SELECT statement such as:

        stmt = select(table.c.id, table.c.name)

    The above statement might look like:

        SELECT table.id, table.name FROM table

    The subquery form by itself renders the same way, however when embedded into the FROM clause of another SELECT statement, it becomes a named sub-element:

        subq = stmt.subquery()
        new_stmt = select(subq)

    The above renders as:

        SELECT anon_1.id, anon_1.name
        FROM (SELECT table.id, table.name FROM table) AS anon_1

    Historically, `SelectBase.subquery()` is equivalent to calling the `FromClause.alias()` method on a FROM object; however, as a `SelectBase` object is not directly FROM object, the `SelectBase.subquery()` method provides clearer semantics.

    Added in version 1.4.

  method `sqlalchemy.sql.expression.TextualSelect.`unique_params(_ClauseElement__optionaldict: Dict[str, Any] | None = None, /, **kwargs: Any) → Self

    inherited from the `ClauseElement.unique_params()` method of `ClauseElement`

    Return a copy with `bindparam()` elements replaced.

    Same functionality as `ClauseElement.params()`, except adds unique=True to affected bind parameters so that multiple statements can be used.

class sqlalchemy.sql.expression.Values

  inherits from `sqlalchemy.sql.roles.InElementRole`, `sqlalchemy.sql.expression.HasCTE`, `sqlalchemy.sql.expression.Generative`, `sqlalchemy.sql.expression.LateralFromClause`

  Represent a `VALUES` construct that can be used as a FROM element in a statement.

  The `Values` object is created from the `values()` function.

  Added in version 1.4.

  Member Name | Description
  --- | ---
  add_cte() | Add one or more `CTE` constructs to this statement.
  alias() | Return a new `Values` construct that is a copy of this one with the given name.
  compile() | Compile this SQL expression.
  cte() | Return a new `CTE`, or Common Table Expression instance.
  data() | Return a new `Values` construct, adding the given data to the data list.
  inherit_cache | Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.
  lateral() | Return a new `Values` with the lateral flag set, so that it renders as LATERAL.
  name_cte_columns | indicates if this HasCTE as contained within a CTE should compel the CTE to render the column names of this object in the WITH clause.
  scalar_values() | Returns a scalar `VALUES` construct that can be used as a COLUMN element in a statement.
  table_valued() | Return a `TableValuedColumn` object for this `FromClause`.

  method `sqlalchemy.sql.expression.Values.`add_cte(*ctes: CTE, nest_here: bool = False) → Self

    inherited from the `HasCTE.add_cte()` method of `HasCTE`

    Add one or more `CTE` constructs to this statement.

    This method will associate the given `CTE` constructs with the parent statement such that they will each be unconditionally rendered in the WITH clause of the final statement, even if not referenced elsewhere within the statement or any sub-selects.

    The optional `HasCTE.add_cte.nest_here` parameter when set to True will have the effect that each given `CTE` will render in a WITH clause rendered directly along with this statement, rather than being moved to the top of the ultimate rendered statement, even if this statement is rendered as a subquery within a larger statement.

    This method has two general uses. One is to embed CTE statements that serve some purpose without being referenced explicitly, such as the use case of embedding a DML statement such as an INSERT or UPDATE as a CTE inline with a primary statement that may draw from its results indirectly. The other is to provide control over the exact placement of a particular series of CTE constructs that should remain rendered directly in terms of a particular statement that may be nested in a larger statement.

    E.g.:

        from sqlalchemy import table, column, select

        t = table("t", column("c1"), column("c2"))

        ins = t.insert().values({"c1": "x", "c2": "y"}).cte()

        stmt = select(t).add_cte(ins)

    Would render:

        WITH anon_1 AS (
            INSERT INTO t (c1, c2) VALUES (:param_1, :param_2)
        )
        SELECT t.c1, t.c2
        FROM t

    Above, the “anon_1” CTE is not referenced in the SELECT statement, however still accomplishes the task of running an INSERT statement.

    Similarly in a DML-related context, using the PostgreSQL `Insert` construct to generate an “upsert”:

        from sqlalchemy import table, column
        from sqlalchemy.dialects.postgresql import insert

        t = table("t", column("c1"), column("c2"))

        delete_statement_cte = t.delete().where(t.c.c1 < 1).cte("deletions")

        insert_stmt = insert(t).values({"c1": 1, "c2": 2})
        update_statement = insert_stmt.on_conflict_do_update(
            index_elements=[t.c.c1],
            set_={
                "c1": insert_stmt.excluded.c1,
                "c2": insert_stmt.excluded.c2,
            },
        ).add_cte(delete_statement_cte)

        print(update_statement)

    The above statement renders as:

        WITH deletions AS (
            DELETE FROM t WHERE t.c1 < %(c1_1)s
        )
        INSERT INTO t (c1, c2) VALUES (%(c1)s, %(c2)s)
        ON CONFLICT (c1) DO UPDATE SET c1 = excluded.c1, c2 = excluded.c2

    Added in version 1.4.21.

    Parameters:

      - *ctes –

        zero or more `CTE` constructs.

        Changed in version 2.0: Multiple CTE instances are accepted

      - nest_here –

        if True, the given CTE or CTEs will be rendered as though they specified the `HasCTE.cte.nesting` flag to `True` when they were added to this `HasCTE`. Assuming the given CTEs are not referenced in an outer-enclosing statement as well, the CTEs given should render at the level of this statement when this flag is given.

        Added in version 2.0.

        See also

        `HasCTE.cte.nesting`

  method `sqlalchemy.sql.expression.Values.`alias(name: str | None = None, flat: bool = False) → Self

    Return a new `Values` construct that is a copy of this one with the given name.

    This method is a VALUES-specific specialization of the `FromClause.alias()` method.

    See also

    Using Aliases

    `alias()`

  method `sqlalchemy.sql.expression.Values.`compile(bind: _HasDialect | None = None, dialect: Dialect | None = None, **kw: Any) → Compiled

    inherited from the `CompilerElement.compile()` method of `CompilerElement`

    Compile this SQL expression.

    The return value is a `Compiled` object. Calling `str()` or `unicode()` on the returned value will yield a string representation of the result. The `Compiled` object also can return a dictionary of bind parameter names and values using the `params` accessor.

    Parameters:

      - bind – An `Connection` or `Engine` which can provide a `Dialect` in order to generate a `Compiled` object. If the `bind` and `dialect` parameters are both omitted, a default SQL compiler is used.

      - column_keys – Used for INSERT and UPDATE statements, a list of column names which should be present in the VALUES clause of the compiled statement. If `None`, all columns from the target table object are rendered.

      - dialect – A `Dialect` instance which can generate a `Compiled` object. This argument takes precedence over the `bind` argument.

      - compile_kwargs –

        optional dictionary of additional parameters that will be passed through to the compiler within all “visit” methods. This allows any custom flag to be passed through to a custom compilation construct, for example. It is also used for the case of passing the `literal_binds` flag through:

            from sqlalchemy.sql import table, column, select

            t = table("t", column("x"))

            s = select(t).where(t.c.x == 5)

            print(s.compile(compile_kwargs={"literal_binds": True}))

    See also

    How do I render SQL expressions as strings, possibly with bound parameters inlined?

  method `sqlalchemy.sql.expression.Values.`cte(name: str | None = None, recursive: bool = False, nesting: bool = False) → CTE

    inherited from the `HasCTE.cte()` method of `HasCTE`

    Return a new `CTE`, or Common Table Expression instance.

    Common table expressions are a SQL standard whereby SELECT statements can draw upon secondary statements specified along with the primary statement, using a clause called “WITH”. Special semantics regarding UNION can also be employed to allow “recursive” queries, where a SELECT statement can draw upon the set of rows that have previously been selected.

    CTEs can also be applied to DML constructs UPDATE, INSERT and DELETE on some databases, both as a source of CTE rows when combined with RETURNING, as well as a consumer of CTE rows.

    SQLAlchemy detects `CTE` objects, which are treated similarly to `Alias` objects, as special elements to be delivered to the FROM clause of the statement as well as to a WITH clause at the top of the statement.

    For special prefixes such as PostgreSQL “MATERIALIZED” and “NOT MATERIALIZED”, the `CTE.prefix_with()` method may be used to establish these.

    Parameters:

      - name – name given to the common table expression. Like `FromClause.alias()`, the name can be left as `None` in which case an anonymous symbol will be used at query compile time.

      - recursive – if `True`, will render `WITH RECURSIVE`. A recursive common table expression is intended to be used in conjunction with UNION ALL in order to derive rows from those already selected.

      - nesting –

        if `True`, will render the CTE locally to the statement in which it is referenced. For more complex scenarios, the `HasCTE.add_cte()` method using the `HasCTE.add_cte.nest_here` parameter may also be used to more carefully control the exact placement of a particular CTE.

        Added in version 1.4.24.

        See also

        `HasCTE.add_cte()`

    The following examples include two from PostgreSQL’s documentation at https://www.postgresql.org/docs/current/static/queries-with.html, as well as additional examples.

    Example 1, non recursive:

        from sqlalchemy import (
            Table,
            Column,
            String,
            Integer,
            MetaData,
            select,
            func,
        )

        metadata = MetaData()

        orders = Table(
            "orders",
            metadata,
            Column("region", String),
            Column("amount", Integer),
            Column("product", String),
            Column("quantity", Integer),
        )

        regional_sales = (
            select(orders.c.region, func.sum(orders.c.amount).label("total_sales"))
            .group_by(orders.c.region)
            .cte("regional_sales")
        )

        top_regions = (
            select(regional_sales.c.region)
            .where(
                regional_sales.c.total_sales
                > select(func.sum(regional_sales.c.total_sales) / 10)
            )
            .cte("top_regions")
        )

        statement = (
            select(
                orders.c.region,
                orders.c.product,
                func.sum(orders.c.quantity).label("product_units"),
                func.sum(orders.c.amount).label("product_sales"),
            )
            .where(orders.c.region.in_(select(top_regions.c.region)))
            .group_by(orders.c.region, orders.c.product)
        )

        result = conn.execute(statement).fetchall()

    Example 2, WITH RECURSIVE:

        from sqlalchemy import (
            Table,
            Column,
            String,
            Integer,
            MetaData,
            select,
            func,
        )

        metadata = MetaData()

        parts = Table(
            "parts",
            metadata,
            Column("part", String),
            Column("sub_part", String),
            Column("quantity", Integer),
        )

        included_parts = (
            select(parts.c.sub_part, parts.c.part, parts.c.quantity)
            .where(parts.c.part == "our part")
            .cte(recursive=True)
        )

        incl_alias = included_parts.alias()
        parts_alias = parts.alias()
        included_parts = included_parts.union_all(
            select(
                parts_alias.c.sub_part, parts_alias.c.part, parts_alias.c.quantity
            ).where(parts_alias.c.part == incl_alias.c.sub_part)
        )

        statement = select(
            included_parts.c.sub_part,
            func.sum(included_parts.c.quantity).label("total_quantity"),
        ).group_by(included_parts.c.sub_part)

        result = conn.execute(statement).fetchall()

    Example 3, an upsert using UPDATE and INSERT with CTEs:

        from datetime import date
        from sqlalchemy import (
            MetaData,
            Table,
            Column,
            Integer,
            Date,
            select,
            literal,
            and_,
            exists,
        )

        metadata = MetaData()

        visitors = Table(
            "visitors",
            metadata,
            Column("product_id", Integer, primary_key=True),
            Column("date", Date, primary_key=True),
            Column("count", Integer),
        )

        # add 5 visitors for the product_id == 1
        product_id = 1
        day = date.today()
        count = 5

        update_cte = (
            visitors.update()
            .where(
                and_(visitors.c.product_id == product_id, visitors.c.date == day)
            )
            .values(count=visitors.c.count + count)
            .returning(literal(1))
            .cte("update_cte")
        )

        upsert = visitors.insert().from_select(
            [visitors.c.product_id, visitors.c.date, visitors.c.count],
            select(literal(product_id), literal(day), literal(count)).where(
                ~exists(update_cte.select())
            ),
        )

        connection.execute(upsert)

    Example 4, Nesting CTE (SQLAlchemy 1.4.24 and above):

        value_a = select(literal("root").label("n")).cte("value_a")

        # A nested CTE with the same name as the root one
        value_a_nested = select(literal("nesting").label("n")).cte(
            "value_a", nesting=True
        )

        # Nesting CTEs takes ascendency locally
        # over the CTEs at a higher level
        value_b = select(value_a_nested.c.n).cte("value_b")

        value_ab = select(value_a.c.n.label("a"), value_b.c.n.label("b"))

    The above query will render the second CTE nested inside the first, shown with inline parameters below as:

        WITH
            value_a AS
                (SELECT 'root' AS n),
            value_b AS
                (WITH value_a AS
                    (SELECT 'nesting' AS n)
                SELECT value_a.n AS n FROM value_a)
        SELECT value_a.n AS a, value_b.n AS b
        FROM value_a, value_b

    The same CTE can be set up using the `HasCTE.add_cte()` method as follows (SQLAlchemy 2.0 and above):

        value_a = select(literal("root").label("n")).cte("value_a")

        # A nested CTE with the same name as the root one
        value_a_nested = select(literal("nesting").label("n")).cte("value_a")

        # Nesting CTEs takes ascendency locally
        # over the CTEs at a higher level
        value_b = (
            select(value_a_nested.c.n)
            .add_cte(value_a_nested, nest_here=True)
            .cte("value_b")
        )

        value_ab = select(value_a.c.n.label("a"), value_b.c.n.label("b"))

    Example 5, Non-Linear CTE (SQLAlchemy 1.4.28 and above):

        edge = Table(
            "edge",
            metadata,
            Column("id", Integer, primary_key=True),
            Column("left", Integer),
            Column("right", Integer),
        )

        root_node = select(literal(1).label("node")).cte("nodes", recursive=True)

        left_edge = select(edge.c.left).join(
            root_node, edge.c.right == root_node.c.node
        )
        right_edge = select(edge.c.right).join(
            root_node, edge.c.left == root_node.c.node
        )

        subgraph_cte = root_node.union(left_edge, right_edge)

        subgraph = select(subgraph_cte)

    The above query will render 2 UNIONs inside the recursive CTE:

        WITH RECURSIVE nodes(node) AS (
                SELECT 1 AS node
            UNION
                SELECT edge."left" AS "left"
                FROM edge JOIN nodes ON edge."right" = nodes.node
            UNION
                SELECT edge."right" AS "right"
                FROM edge JOIN nodes ON edge."left" = nodes.node
        )
        SELECT nodes.node FROM nodes

    See also

    `Query.cte()` - ORM version of `HasCTE.cte()`.

  method `sqlalchemy.sql.expression.Values.`data(values: Sequence[Tuple[Any, ...]]) → Self

    Return a new `Values` construct, adding the given data to the data list.

    E.g.:

        my_values = my_values.data([(1, "value 1"), (2, "value2")])

    Parameters:

      values – a sequence (i.e. list) of tuples that map to the column expressions given in the `Values` constructor.

  attribute `sqlalchemy.sql.expression.Values.`inherit_cache = None

    inherited from the `HasCacheKey.inherit_cache` attribute of `HasCacheKey`

    Indicate if this `HasCacheKey` instance should make use of the cache key generation scheme used by its immediate superclass.

    The attribute defaults to `None`, which indicates that a construct has not yet taken into account whether or not its appropriate for it to participate in caching; this is functionally equivalent to setting the value to `False`, except that a warning is also emitted.

    This flag can be set to `True` on a particular class, if the SQL that corresponds to the object does not change based on attributes which are local to this class, and not its superclass.

    See also

    Enabling Caching Support for Custom Constructs - General guideslines for setting the `HasCacheKey.inherit_cache` attribute for third-party or user defined SQL constructs.

  method `sqlalchemy.sql.expression.Values.`lateral(name: str | None = None) → Self

    Return a new `Values` with the lateral flag set, so that it renders as LATERAL.

    See also

    `lateral()`

  attribute `sqlalchemy.sql.expression.Values.`name_cte_columns = True

    indicates if this HasCTE as contained within a CTE should compel the CTE to render the column names of this object in the WITH clause.

    Added in version 2.0.42.

  method `sqlalchemy.sql.expression.Values.`scalar_values() → ScalarValues

    Returns a scalar `VALUES` construct that can be used as a COLUMN element in a statement.

    Added in version 2.0.0b4.

  method `sqlalchemy.sql.expression.Values.`table_valued() → TableValuedColumn[Any]

    inherited from the `NamedFromClause.table_valued()` method of `NamedFromClause`

    Return a `TableValuedColumn` object for this `FromClause`.

    A `TableValuedColumn` is a `ColumnElement` that represents a complete row in a table. Support for this construct is backend dependent, and is supported in various forms by backends such as PostgreSQL, Oracle Database and SQL Server.

    E.g.:

        >>> from sqlalchemy import select, column, func, table
        >>> a = table("a", column("id"), column("x"), column("y"))
        >>> stmt = select(func.row_to_json(a.table_valued()))
        >>> print(stmt)
        SELECT row_to_json(a) AS row_to_json_1
        FROM a

    Added in version 1.4.0b2.

    See also

    Working with SQL Functions - in the SQLAlchemy Unified Tutorial

class sqlalchemy.sql.expression.ScalarValues

  inherits from `sqlalchemy.sql.roles.InElementRole`, `sqlalchemy.sql.expression.GroupedElement`, `sqlalchemy.sql.expression.ColumnElement`

  Represent a scalar `VALUES` construct that can be used as a COLUMN element in a statement.

  The `ScalarValues` object is created from the `Values.scalar_values()` method. It’s also automatically generated when a `Values` is used in an `IN` or `NOT IN` condition.

  Added in version 2.0.0b4.

## Label Style Constants

Constants used with the `GenerativeSelect.set_label_style()` method.

Object Name | Description
--- | ---
SelectLabelStyle | Label style constants that may be passed to `Select.set_label_style()`.

class sqlalchemy.sql.expression.SelectLabelStyle

  inherits from `enum.Enum`

  Label style constants that may be passed to `Select.set_label_style()`.

  Member Name | Description
  --- | ---
  LABEL_STYLE_DEFAULT | The default label style, refers to `LABEL_STYLE_DISAMBIGUATE_ONLY`.
  LABEL_STYLE_DISAMBIGUATE_ONLY | Label style indicating that columns with a name that conflicts with an existing name should be labeled with a semi-anonymizing label when generating the columns clause of a SELECT statement.
  LABEL_STYLE_NONE | Label style indicating no automatic labeling should be applied to the columns clause of a SELECT statement.
  LABEL_STYLE_TABLENAME_PLUS_COL | Label style indicating all columns should be labeled as `<tablename>_<columnname>` when generating the columns clause of a SELECT statement, to disambiguate same-named columns referenced from different tables, aliases, or subqueries.

  attribute `sqlalchemy.sql.expression.SelectLabelStyle.`LABEL_STYLE_DEFAULT = 2

    The default label style, refers to `LABEL_STYLE_DISAMBIGUATE_ONLY`.

    Added in version 1.4.

  attribute `sqlalchemy.sql.expression.SelectLabelStyle.`LABEL_STYLE_DISAMBIGUATE_ONLY = 2

    Label style indicating that columns with a name that conflicts with an existing name should be labeled with a semi-anonymizing label when generating the columns clause of a SELECT statement.

    Below, most column names are left unaffected, except for the second occurrence of the name `columna`, which is labeled using the label `columna_1` to disambiguate it from that of `tablea.columna`:

        >>> from sqlalchemy import (
        ...     table,
        ...     column,
        ...     select,
        ...     true,
        ...     LABEL_STYLE_DISAMBIGUATE_ONLY,
        ... )
        >>> table1 = table("table1", column("columna"), column("columnb"))
        >>> table2 = table("table2", column("columna"), column("columnc"))
        >>> print(
        ...     select(table1, table2)
        ...     .join(table2, true())
        ...     .set_label_style(LABEL_STYLE_DISAMBIGUATE_ONLY)
        ... )
        SELECT table1.columna, table1.columnb, table2.columna AS columna_1, table2.columnc
        FROM table1 JOIN table2 ON true

    Used with the `GenerativeSelect.set_label_style()` method, `LABEL_STYLE_DISAMBIGUATE_ONLY` is the default labeling style for all SELECT statements outside of 1.x style ORM queries.

    Added in version 1.4.

  attribute `sqlalchemy.sql.expression.SelectLabelStyle.`LABEL_STYLE_NONE = 0

    Label style indicating no automatic labeling should be applied to the columns clause of a SELECT statement.

    Below, the columns named `columna` are both rendered as is, meaning that the name `columna` can only refer to the first occurrence of this name within a result set, as well as if the statement were used as a subquery:

        >>> from sqlalchemy import table, column, select, true, LABEL_STYLE_NONE
        >>> table1 = table("table1", column("columna"), column("columnb"))
        >>> table2 = table("table2", column("columna"), column("columnc"))
        >>> print(
        ...     select(table1, table2)
        ...     .join(table2, true())
        ...     .set_label_style(LABEL_STYLE_NONE)
        ... )
        SELECT table1.columna, table1.columnb, table2.columna, table2.columnc
        FROM table1 JOIN table2 ON true

    Used with the `Select.set_label_style()` method.

    Added in version 1.4.

  attribute `sqlalchemy.sql.expression.SelectLabelStyle.`LABEL_STYLE_TABLENAME_PLUS_COL = 1

    Label style indicating all columns should be labeled as `<tablename>_<columnname>` when generating the columns clause of a SELECT statement, to disambiguate same-named columns referenced from different tables, aliases, or subqueries.

    Below, all column names are given a label so that the two same-named columns `columna` are disambiguated as `table1_columna` and `table2_columna`:

        >>> from sqlalchemy import (
        ...     table,
        ...     column,
        ...     select,
        ...     true,
        ...     LABEL_STYLE_TABLENAME_PLUS_COL,
        ... )
        >>> table1 = table("table1", column("columna"), column("columnb"))
        >>> table2 = table("table2", column("columna"), column("columnc"))
        >>> print(
        ...     select(table1, table2)
        ...     .join(table2, true())
        ...     .set_label_style(LABEL_STYLE_TABLENAME_PLUS_COL)
        ... )
        SELECT table1.columna AS table1_columna, table1.columnb AS table1_columnb, table2.columna AS table2_columna, table2.columnc AS table2_columnc
        FROM table1 JOIN table2 ON true

    Used with the `GenerativeSelect.set_label_style()` method. Equivalent to the legacy method `Select.apply_labels()`; `LABEL_STYLE_TABLENAME_PLUS_COL` is SQLAlchemy’s legacy auto-labeling style. `LABEL_STYLE_DISAMBIGUATE_ONLY` provides a less intrusive approach to disambiguation of same-named column expressions.

    Added in version 1.4.

See also

`Select.set_label_style()`

`Select.get_label_style()`