Release: 1.4.44 | Release Date: November 12, 2022

# SQLAlchemy 1.4 Documentation

# Selectables, Tables, FROM objects

The term “selectable” refers to any object that rows can be selected from; in SQLAlchemy, these objects descend from `FromClause` and their distinguishing feature is their `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, **kwargs) | Return an `EXCEPT` of multiple selectables.
except_all(*selects, **kwargs) | Return an `EXCEPT ALL` of multiple selectables.
exists(*args, **kwargs) | Construct a new `Exists` construct.
intersect(*selects, **kwargs) | Return an `INTERSECT` of multiple selectables.
intersect_all(*selects, **kwargs) | Return an `INTERSECT ALL` of multiple selectables.
select(*args, **kw) | Create a `Select` using either the 1.x or 2.0 constructor style.
table(name, *columns, **kw) | Produce a new `TableClause`.
union(*selects, **kwargs) | Return a `UNION` of multiple selectables.
union_all(*selects, **kwargs) | Return a `UNION ALL` of multiple selectables.
values(*columns, **kw) | Construct a `Values` construct.

function sqlalchemy.sql.expression.except_(*selects, **kwargs)

  Return an `EXCEPT` of multiple selectables.

  The returned object is an instance of `CompoundSelect`.

  Parameters:

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

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

function sqlalchemy.sql.expression.except_all(*selects, **kwargs)

  Return an `EXCEPT ALL` of multiple selectables.

  The returned object is an instance of `CompoundSelect`.

  Parameters:

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

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

function sqlalchemy.sql.expression.exists(*args, **kwargs)

  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, **kwargs)

  Return an `INTERSECT` of multiple selectables.

  The returned object is an instance of `CompoundSelect`.

  Parameters:

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

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

function sqlalchemy.sql.expression.intersect_all(*selects, **kwargs)

  Return an `INTERSECT ALL` of multiple selectables.

  The returned object is an instance of `CompoundSelect`.

  Parameters:

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

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

function sqlalchemy.sql.expression.select(*args, **kw)

  Create a `Select` using either the 1.x or 2.0 constructor style.

  For the legacy calling style, see `Select.create_legacy_select()`. If the first argument passed is a Python sequence or if keyword arguments are present, this style is used.

  New in version 2.0: - the `select()` construct is the same construct as the one returned by `select()`, except that the function only accepts the “columns clause” entities up front; the rest of the state of the SELECT should be built up using generative methods.

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

  See also

  Selecting - Core Tutorial description of `select()`.

  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, *columns, **kw)

  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.

  Changed in version 1.0.0: `table()` can now be imported from the plain `sqlalchemy` namespace like any other SQL element.

  Parameters:

    - name – Name of the table.

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

    - schema –

      The schema name for this table.

      New in version 1.3.18: `table()` can now accept a `schema` argument.

function sqlalchemy.sql.expression.union(*selects, **kwargs)

  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, **kwargs)

  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.

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

function sqlalchemy.sql.expression.values(*columns, **kw)

  Construct a `Values` construct.

  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

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

  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 an `Alias` object.
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, name=None, flat=False)

  Return an `Alias` object.

  An `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`.

  Similar functionality is available via the `FromClause.alias()` method available on all `FromClause` subclasses. In terms of a SELECT object as generated from the `select()` function, the `SelectBase.alias()` method returns an `Alias` or similar object which represents a named, parenthesized subquery.

  When an `Alias` is created from a `Table` object, this has the effect of the table being rendered as `tablename AS aliasname` in a SELECT statement.

  For `select()` objects, the effect is that of creating a named subquery, i.e. `(select ...) AS aliasname`.

  The `name` parameter is optional, and provides the name to use in the rendered SQL. If blank, an “anonymous” 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.

  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.

    - 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, name=None, recursive=False)

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

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

function sqlalchemy.sql.expression.join(left, right, onclause=None, isouter=False, full=False)

  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.

      New in version 1.1.

  See also

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

  `Join` - the type of object produced.

function sqlalchemy.sql.expression.lateral(selectable, name=None)

  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.

  New in version 1.1.

  See also

  LATERAL correlation - overview of usage.

function sqlalchemy.sql.expression.outerjoin(left, right, onclause=None, full=False)

  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, sampling, name=None, seed=None)

  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())

  New in version 1.1.

  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.
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.
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(*arg, **kw)

  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).

  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()`

  Members

  inherit_cache

  Class signature

  class `sqlalchemy.sql.expression.Alias` (`sqlalchemy.sql.roles.DMLTableRole`, `sqlalchemy.sql.expression.AliasedReturnsRows`)

  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(*arg, **kw)

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

  Members

  description, is_derived_from(), original

  Class signature

  class `sqlalchemy.sql.expression.AliasedReturnsRows` (`sqlalchemy.sql.expression.NoInit`, `sqlalchemy.sql.expression.FromClause`)

  attribute `sqlalchemy.sql.expression.AliasedReturnsRows.`description
  method `sqlalchemy.sql.expression.AliasedReturnsRows.`is_derived_from(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.

  attribute `sqlalchemy.sql.expression.AliasedReturnsRows.`original

    Legacy for dialects that are referring to Alias.original.

class sqlalchemy.sql.expression.CompoundSelect(keyword, *selects, **kwargs)

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

  See also

  `union()`

  `union_all()`

  `intersect()`

  `intersect_all()`

  `except()`

  `except_all()`

  Members

  add_cte(), alias(), append_group_by(), append_order_by(), apply_labels(), as_scalar(), bind, c, corresponding_column(), cte(), execute(), execution_options(), exists(), exported_columns, fetch(), get_execution_options(), get_label_style(), group_by(), label(), lateral(), limit(), offset(), options(), order_by(), replace_selectable(), scalar(), scalar_subquery(), select(), selected_columns, self_group(), set_label_style(), slice(), subquery(), with_for_update()

  Class signature

  class `sqlalchemy.sql.expression.CompoundSelect` (`sqlalchemy.sql.expression.HasCompileState`, `sqlalchemy.sql.expression.GenerativeSelect`)

  method `sqlalchemy.sql.expression.CompoundSelect.`add_cte(cte)

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

    Add a `CTE` to this statement object that will be independently rendered even if not referenced in the statement otherwise.

    This feature is useful for 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; while PostgreSQL is known to support this usage, it may not be supported by other backends.

    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 referred towards 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

    New in version 1.4.21.

  method `sqlalchemy.sql.expression.CompoundSelect.`alias(name=None, flat=False)

    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.CompoundSelect.`append_group_by(*clauses)

    inherited from the `DeprecatedSelectBaseGenerations.append_group_by()` method of `DeprecatedSelectBaseGenerations`

    Append the given GROUP BY criterion applied to this selectable.

    Deprecated since version 1.4: The `GenerativeSelect.append_group_by()` method is deprecated and will be removed in a future release. Use the generative method `GenerativeSelect.group_by()`.

    The criterion will be appended to any pre-existing GROUP BY criterion.

    This is an in-place mutation method; the `GenerativeSelect.group_by()` method is preferred, as it provides standard method chaining.

  method `sqlalchemy.sql.expression.CompoundSelect.`append_order_by(*clauses)

    inherited from the `DeprecatedSelectBaseGenerations.append_order_by()` method of `DeprecatedSelectBaseGenerations`

    Append the given ORDER BY criterion applied to this selectable.

    Deprecated since version 1.4: The `GenerativeSelect.append_order_by()` method is deprecated and will be removed in a future release. Use the generative method `GenerativeSelect.order_by()`.

    The criterion will be appended to any pre-existing ORDER BY criterion.

    This is an in-place mutation method; the `GenerativeSelect.order_by()` method is preferred, as it provides standard method chaining.

    See also

    `GenerativeSelect.order_by()`

  method `sqlalchemy.sql.expression.CompoundSelect.`apply_labels()

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

    Deprecated since version 1.4: The `GenerativeSelect.apply_labels()` method is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. Use set_label_style(LABEL_STYLE_TABLENAME_PLUS_COL) instead. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

  method `sqlalchemy.sql.expression.CompoundSelect.`as_scalar()

    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()`.

  attribute `sqlalchemy.sql.expression.CompoundSelect.`bind

    Returns the `Engine` or `Connection` to which this `Executable` is bound, or None if none found.

    Deprecated since version 1.4: The `Executable.bind` attribute is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. Bound metadata is being removed as of SQLAlchemy 2.0. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

  attribute `sqlalchemy.sql.expression.CompoundSelect.`c

    inherited from the `SelectBase.c` attribute of `SelectBase`

    Deprecated since version 1.4: The `SelectBase.c` and `SelectBase.columns` attributes are deprecated and will be removed in a future release; these attributes implicitly create a subquery that should be explicit. Please call `SelectBase.subquery()` first in order to create a subquery, which then contains this attribute. To access the columns that this SELECT object SELECTs from, use the `SelectBase.selected_columns` attribute.

  method `sqlalchemy.sql.expression.CompoundSelect.`corresponding_column(column, require_embedded=False)

    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=None, recursive=False, nesting=False)

    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.

    Changed in version 1.1: Added support for UPDATE/INSERT/DELETE as CTE, CTEs added to UPDATE/INSERT/DELETE.

    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.

    Changed in version 1.3.13: Added support for prefixes. In particular - MATERIALIZED and NOT MATERIALIZED.

    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 actual statement.

        New in version 1.4.24.

    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

    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.CompoundSelect.`execute(*multiparams, **params)

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

    Compile and execute this `Executable`.

    Deprecated since version 1.4: The `Executable.execute()` method is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. All statement execution in SQLAlchemy 2.0 is performed by the `Connection.execute()` method of `Connection`, or in the ORM by the `Session.execute()` method of `Session`. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

  method `sqlalchemy.sql.expression.CompoundSelect.`execution_options(**kw)

    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 on a per-statement or per `Connection` basis. Additionally, the `Engine` and ORM `Query` objects provide access to execution options which they in turn configure upon connections.

    The `execution_options()` method is generative. A new instance of this statement is returned that contains the options:

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

    Note that only a subset of possible execution options can be applied to a statement - these include “autocommit” and “stream_results”, but not “isolation_level” or “compiled_cache”. See `Connection.execution_options()` for a full list of possible options.

    See also

    `Connection.execution_options()`

    `Query.execution_options()`

    `Executable.get_execution_options()`

  method `sqlalchemy.sql.expression.CompoundSelect.`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.

    New in version 1.4.

  attribute `sqlalchemy.sql.expression.CompoundSelect.`exported_columns

    inherited from the `SelectBase.exported_columns` attribute of `SelectBase`

    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.

    New in version 1.4.

    See also

    `Select.exported_columns`

    `Selectable.exported_columns`

    `FromClause.exported_columns`

  method `sqlalchemy.sql.expression.CompoundSelect.`fetch(count, with_ties=False, percent=False)

    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, PostgreSQL, MSSQL.

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

    Note

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

    New 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`

    See also

    `GenerativeSelect.limit()`

    `GenerativeSelect.offset()`

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

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

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

    New in version 1.3.

    See also

    `Executable.execution_options()`

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

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

    Retrieve the current label style.

    New in version 1.4.

  method `sqlalchemy.sql.expression.CompoundSelect.`group_by(*clauses)

    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.

    See also

    Aggregate functions with GROUP BY / HAVING - in the SQLAlchemy 1.4 / 2.0 Tutorial

    Ordering or Grouping by a Label - in the SQLAlchemy 1.4 / 2.0 Tutorial

  method `sqlalchemy.sql.expression.CompoundSelect.`label(name)

    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.as_scalar()`.

  method `sqlalchemy.sql.expression.CompoundSelect.`lateral(name=None)

    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.

    New in version 1.1.

    See also

    LATERAL correlation - overview of usage.

  method `sqlalchemy.sql.expression.CompoundSelect.`limit(limit)

    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()`.

    Changed in version 1.0.0: - `Select.limit()` can now accept arbitrary SQL expressions as well as integer values.

    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.CompoundSelect.`offset(offset)

    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.

    Changed in version 1.0.0: - `Select.offset()` can now accept arbitrary SQL expressions as well as integer values.

    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)

    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 the SQL compiler for the statement. These options can be consumed by specific dialects or specific kinds of compilers.

    The most commonly known kind of option are the ORM level options that apply “eager load” and other loading behaviors to an ORM query. However, options can theoretically be used for many other purposes.

    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 `Generative.options()` to Core statement objects towards the goal of allowing unified Core / ORM querying capabilities.

    See also

    Deferred Column Loader Query 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(*clauses)

    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)

    All existing ORDER BY criteria may be cancelled by passing `None` by itself. New ORDER BY criteria may then be added by invoking `Select.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.

    See also

    ORDER BY - in the SQLAlchemy 1.4 / 2.0 Tutorial

    Ordering or Grouping by a Label - in the SQLAlchemy 1.4 / 2.0 Tutorial

  method `sqlalchemy.sql.expression.CompoundSelect.`replace_selectable(old, alias)

    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(*multiparams, **params)

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

    Compile and execute this `Executable`, returning the result’s scalar representation.

    Deprecated since version 1.4: The `Executable.scalar()` method is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. Scalar execution in SQLAlchemy 2.0 is performed by the `Connection.scalar()` method of `Connection`, or in the ORM by the `Session.scalar()` method of `Session`. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

  method `sqlalchemy.sql.expression.CompoundSelect.`scalar_subquery()

    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.

    See also

    Scalar and Correlated Subqueries - in the 2.0 tutorial

  method `sqlalchemy.sql.expression.CompoundSelect.`select(*arg, **kw)

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

    Deprecated since version 1.4: The `SelectBase.select()` method is deprecated and will be removed in a future release; this method implicitly creates a subquery that should be explicit. Please call `SelectBase.subquery()` first in order to create a subquery, which then can be selected.

  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`

    New in version 1.4.

  method `sqlalchemy.sql.expression.CompoundSelect.`self_group(against=None)

    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)

    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, `LABEL_STYLE_DISAMBIGUATE_ONLY`, `LABEL_STYLE_TABLENAME_PLUS_COL`, and `LABEL_STYLE_NONE`. The default style is `LABEL_STYLE_TABLENAME_PLUS_COL`.

    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.

    New 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

    `LABEL_STYLE_DISAMBIGUATE_ONLY`

    `LABEL_STYLE_TABLENAME_PLUS_COL`

    `LABEL_STYLE_NONE`

    `LABEL_STYLE_DEFAULT`

  method `sqlalchemy.sql.expression.CompoundSelect.`slice(start, stop)

    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()`.

    New 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=None)

    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.

    New in version 1.4.

  method `sqlalchemy.sql.expression.CompoundSelect.`with_for_update(nowait=False, read=False, of=None, skip_locked=False, key_share=False)

    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, 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 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) which will render into a `FOR UPDATE OF` clause; supported by PostgreSQL and Oracle. May render as a table or as a column depending on backend.

      - skip_locked – boolean, will render `FOR UPDATE SKIP LOCKED` on Oracle 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(*arg, **kw)

  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

  Members

  alias(), union(), union_all()

  Class signature

  class `sqlalchemy.sql.expression.CTE` (`sqlalchemy.sql.roles.DMLTableRole`, `sqlalchemy.sql.roles.IsCTERole`, `sqlalchemy.sql.expression.Generative`, `sqlalchemy.sql.expression.HasPrefixes`, `sqlalchemy.sql.expression.HasSuffixes`, `sqlalchemy.sql.expression.AliasedReturnsRows`)

  method `sqlalchemy.sql.expression.CTE.`alias(name=None, flat=False)

    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)

    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)

    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

  Mark a `ClauseElement` as supporting execution.

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

  Members

  bind, execute(), execution_options(), get_execution_options(), options(), scalar()

  Class signature

  class `sqlalchemy.sql.expression.Executable` (`sqlalchemy.sql.roles.StatementRole`, `sqlalchemy.sql.expression.Generative`)

  attribute `sqlalchemy.sql.expression.Executable.`bind

    Returns the `Engine` or `Connection` to which this `Executable` is bound, or None if none found.

    Deprecated since version 1.4: The `Executable.bind` attribute is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. Bound metadata is being removed as of SQLAlchemy 2.0. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

    This is a traversal which checks locally, then checks among the “from” clauses of associated objects until a bound engine or connection is found.

  method `sqlalchemy.sql.expression.Executable.`execute(*multiparams, **params)

    Compile and execute this `Executable`.

    Deprecated since version 1.4: The `Executable.execute()` method is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. All statement execution in SQLAlchemy 2.0 is performed by the `Connection.execute()` method of `Connection`, or in the ORM by the `Session.execute()` method of `Session`. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

  method `sqlalchemy.sql.expression.Executable.`execution_options(**kw)

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

    Execution options can be set on a per-statement or per `Connection` basis. Additionally, the `Engine` and ORM `Query` objects provide access to execution options which they in turn configure upon connections.

    The `execution_options()` method is generative. A new instance of this statement is returned that contains the options:

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

    Note that only a subset of possible execution options can be applied to a statement - these include “autocommit” and “stream_results”, but not “isolation_level” or “compiled_cache”. See `Connection.execution_options()` for a full list of possible options.

    See also

    `Connection.execution_options()`

    `Query.execution_options()`

    `Executable.get_execution_options()`

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

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

    New in version 1.3.

    See also

    `Executable.execution_options()`

  method `sqlalchemy.sql.expression.Executable.`options(*options)

    Apply options to this statement.

    In the general sense, options are any kind of Python object that can be interpreted by the SQL compiler for the statement. These options can be consumed by specific dialects or specific kinds of compilers.

    The most commonly known kind of option are the ORM level options that apply “eager load” and other loading behaviors to an ORM query. However, options can theoretically be used for many other purposes.

    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 `Generative.options()` to Core statement objects towards the goal of allowing unified Core / ORM querying capabilities.

    See also

    Deferred Column Loader Query 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.Executable.`scalar(*multiparams, **params)

    Compile and execute this `Executable`, returning the result’s scalar representation.

    Deprecated since version 1.4: The `Executable.scalar()` method is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. Scalar execution in SQLAlchemy 2.0 is performed by the `Connection.scalar()` method of `Connection`, or in the ORM by the `Session.scalar()` method of `Session`. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

class sqlalchemy.sql.expression.Exists(*args, **kwargs)

  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()`.

  Members

  __init__(), correlate(), correlate_except(), inherit_cache, select(), select_from(), where()

  Class signature

  class `sqlalchemy.sql.expression.Exists` (`sqlalchemy.sql.expression.UnaryExpression`)

  method `sqlalchemy.sql.expression.Exists.`__init__(*args, **kwargs)

    Construct a new `Exists` object.

    This constructor is mirrored as a public API function; see `sqlalchemy.sql.expression.exists()` for a full usage and argument description.

  method `sqlalchemy.sql.expression.Exists.`correlate(*fromclause)

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

    See also

    `ScalarSelect.correlate()`

  method `sqlalchemy.sql.expression.Exists.`correlate_except(*fromclause)

    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(whereclause=None, **kwargs)

    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

    Parameters:

      - whereclause –

        a WHERE clause, equivalent to calling the `Select.where()` method.

        Deprecated since version 1.4: The `Exists.select().whereclause` parameter is deprecated and will be removed in version 2.0. Please make use of the `Select.where()` method to add WHERE criteria to the SELECT statement.

      - **kwargs –

        additional keyword arguments are passed to the legacy constructor for `Select` described at `Select.create_legacy_select()`.

        Deprecated since version 1.4: The `Exists.select()` method will no longer accept keyword arguments in version 2.0. Please use generative methods from the `Select` construct in order to apply additional modifications.

    See also

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

  method `sqlalchemy.sql.expression.Exists.`select_from(*froms)

    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)

    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

  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()`.

  Members

  alias(), c, columns, description, entity_namespace, exported_columns, foreign_keys, is_derived_from(), join(), outerjoin(), primary_key, schema, select(), table_valued(), tablesample()

  Class signature

  class `sqlalchemy.sql.expression.FromClause` (`sqlalchemy.sql.roles.AnonymizedFromClauseRole`, `sqlalchemy.sql.expression.Selectable`)

  method `sqlalchemy.sql.expression.FromClause.`alias(name=None, flat=False)

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

    The `FromClause.c` attribute is an alias for the `FromClause.columns` attribute.

    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 `Selectable`.

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

    New 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)

    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, onclause=None, isouter=False, full=False)

    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`.

        New in version 1.1.

    See also

    `join()` - standalone function

    `Join` - the type of object produced

  method `sqlalchemy.sql.expression.FromClause.`outerjoin(right, onclause=None, full=False)

    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.

        New in version 1.1.

    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 = 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(whereclause=None, **kwargs)

    Return a SELECT of this `FromClause`.

    e.g.:

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

    Parameters:

      - whereclause –

        a WHERE clause, equivalent to calling the `Select.where()` method.

        Deprecated since version 1.4: The `FromClause.select().whereclause` parameter is deprecated and will be removed in version 2.0. Please make use of the `Select.where()` method to add WHERE criteria to the SELECT statement.

      - **kwargs – additional keyword arguments are passed to the legacy constructor for `Select` described at `Select.create_legacy_select()`.

    See also

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

  method `sqlalchemy.sql.expression.FromClause.`table_valued()

    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 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

    New in version 1.4.0b2.

    See also

    Working with SQL Functions - in the SQLAlchemy 1.4 / 2.0 Tutorial

  method `sqlalchemy.sql.expression.FromClause.`tablesample(sampling, name=None, seed=None)

    Return a TABLESAMPLE alias of this `FromClause`.

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

    New in version 1.1.

    See also

    `tablesample()` - usage guidelines and parameters

class sqlalchemy.sql.expression.GenerativeSelect(_label_style=symbol('LABEL_STYLE_DISAMBIGUATE_ONLY'), use_labels=False, limit=None, offset=None, order_by=None, group_by=None, bind=None)

  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.

  Members

  apply_labels(), fetch(), get_label_style(), group_by(), limit(), offset(), order_by(), set_label_style(), slice(), with_for_update()

  Class signature

  class `sqlalchemy.sql.expression.GenerativeSelect` (`sqlalchemy.sql.expression.DeprecatedSelectBaseGenerations`, `sqlalchemy.sql.expression.SelectBase`)

  method `sqlalchemy.sql.expression.GenerativeSelect.`apply_labels()

    Deprecated since version 1.4: The `GenerativeSelect.apply_labels()` method is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. Use set_label_style(LABEL_STYLE_TABLENAME_PLUS_COL) instead. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

  method `sqlalchemy.sql.expression.GenerativeSelect.`fetch(count, with_ties=False, percent=False)

    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, PostgreSQL, MSSQL.

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

    Note

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

    New 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`

    See also

    `GenerativeSelect.limit()`

    `GenerativeSelect.offset()`

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

    Retrieve the current label style.

    New in version 1.4.

  method `sqlalchemy.sql.expression.GenerativeSelect.`group_by(*clauses)

    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.

    See also

    Aggregate functions with GROUP BY / HAVING - in the SQLAlchemy 1.4 / 2.0 Tutorial

    Ordering or Grouping by a Label - in the SQLAlchemy 1.4 / 2.0 Tutorial

  method `sqlalchemy.sql.expression.GenerativeSelect.`limit(limit)

    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()`.

    Changed in version 1.0.0: - `Select.limit()` can now accept arbitrary SQL expressions as well as integer values.

    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)

    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.

    Changed in version 1.0.0: - `Select.offset()` can now accept arbitrary SQL expressions as well as integer values.

    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(*clauses)

    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)

    All existing ORDER BY criteria may be cancelled by passing `None` by itself. New ORDER BY criteria may then be added by invoking `Select.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.

    See also

    ORDER BY - in the SQLAlchemy 1.4 / 2.0 Tutorial

    Ordering or Grouping by a Label - in the SQLAlchemy 1.4 / 2.0 Tutorial

  method `sqlalchemy.sql.expression.GenerativeSelect.`set_label_style(style)

    Return a new selectable with the specified label style.

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

    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.

    New 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

    `LABEL_STYLE_DISAMBIGUATE_ONLY`

    `LABEL_STYLE_TABLENAME_PLUS_COL`

    `LABEL_STYLE_NONE`

    `LABEL_STYLE_DEFAULT`

  method `sqlalchemy.sql.expression.GenerativeSelect.`slice(start, stop)

    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()`.

    New 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=False, read=False, of=None, skip_locked=False, key_share=False)

    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, 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 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) which will render into a `FOR UPDATE OF` clause; supported by PostgreSQL and Oracle. May render as a table or as a column depending on backend.

      - skip_locked – boolean, will render `FOR UPDATE SKIP LOCKED` on Oracle 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

  Mixin that declares a class to include CTE support.

  New in version 1.1.

  Members

  add_cte(), cte()

  Class signature

  class `sqlalchemy.sql.expression.HasCTE` (`sqlalchemy.sql.roles.HasCTERole`)

  method `sqlalchemy.sql.expression.HasCTE.`add_cte(cte)

    Add a `CTE` to this statement object that will be independently rendered even if not referenced in the statement otherwise.

    This feature is useful for 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; while PostgreSQL is known to support this usage, it may not be supported by other backends.

    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 referred towards 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

    New in version 1.4.21.

  method `sqlalchemy.sql.expression.HasCTE.`cte(name=None, recursive=False, nesting=False)

    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.

    Changed in version 1.1: Added support for UPDATE/INSERT/DELETE as CTE, CTEs added to UPDATE/INSERT/DELETE.

    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.

    Changed in version 1.3.13: Added support for prefixes. In particular - MATERIALIZED and NOT MATERIALIZED.

    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 actual statement.

        New in version 1.4.24.

    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

    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()`.

class sqlalchemy.sql.expression.HasPrefixes

  Members

  prefix_with()

  method `sqlalchemy.sql.expression.HasPrefixes.`prefix_with(*expr, **kw)

    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:

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

      - **kw – A single keyword ‘dialect’ is accepted. This is an optional string dialect name which will limit rendering of this prefix to only that dialect.

class sqlalchemy.sql.expression.HasSuffixes

  Members

  suffix_with()

  method `sqlalchemy.sql.expression.HasSuffixes.`suffix_with(*expr, **kw)

    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:

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

      - **kw – A single keyword ‘dialect’ is accepted. This is an optional string dialect name which will limit rendering of this suffix to only that dialect.

class sqlalchemy.sql.expression.Join(left, right, onclause=None, isouter=False, full=False)

  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()`

  Members

  __init__(), alias(), bind, description, is_derived_from(), select(), self_group()

  Class signature

  class `sqlalchemy.sql.expression.Join` (`sqlalchemy.sql.roles.DMLTableRole`, `sqlalchemy.sql.expression.FromClause`)

  method `sqlalchemy.sql.expression.Join.`__init__(left, right, onclause=None, isouter=False, full=False)

    Construct a new `Join`.

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

  method `sqlalchemy.sql.expression.Join.`alias(name=None, flat=False)

    Return an alias of this `Join`.

    Deprecated since version 1.4: The `Join.alias()` method is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. Create a select + subquery, or alias the individual tables inside the join, instead. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

    The default behavior here is to first produce a SELECT construct from this `Join`, then to produce an `Alias` from that. So given a join of the form:

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

    The JOIN by itself would look like:

        table_a JOIN table_b ON table_a.id = table_b.a_id

    Whereas the alias of the above, `j.alias()`, would in a SELECT context look like:

        (SELECT table_a.id AS table_a_id, table_b.id AS table_b_id,
            table_b.a_id AS table_b_a_id
            FROM table_a
            JOIN table_b ON table_a.id = table_b.a_id) AS anon_1

    The equivalent long-hand form, given a `Join` object `j`, is:

        from sqlalchemy import select, alias
        j = alias(
            select(j.left, j.right).\
                select_from(j).\
                set_label_style(LABEL_STYLE_TABLENAME_PLUS_COL).\
                correlate(False),
            name=name
        )

    The selectable produced by `Join.alias()` features the same columns as that of the two individual selectables presented under a single name - the individual columns are “auto-labeled”, meaning the `.c.` collection of the resulting `Alias` represents the names of the individual columns using a `<tablename>_<columname>` scheme:

        j.c.table_a_id
        j.c.table_b_a_id

    `Join.alias()` also features an alternate option for aliasing joins which produces no enclosing SELECT and does not normally apply labels to the column names. The `flat=True` option will call `FromClause.alias()` against the left and right sides individually. Using this option, no new `SELECT` is produced; we instead, from a construct as below:

        j = table_a.join(table_b, table_a.c.id == table_b.c.a_id)
        j = j.alias(flat=True)

    we get a result like this:

        table_a AS table_a_1 JOIN table_b AS table_b_1 ON
        table_a_1.id = table_b_1.a_id

    The `flat=True` argument is also propagated to the contained selectables, so that a composite join such as:

        j = table_a.join(
                table_b.join(table_c,
                        table_b.c.id == table_c.c.b_id),
                table_b.c.a_id == table_a.c.id
            ).alias(flat=True)

    Will produce an expression like:

        table_a AS table_a_1 JOIN (
                table_b AS table_b_1 JOIN table_c AS table_c_1
                ON table_b_1.id = table_c_1.b_id
        ) ON table_a_1.id = table_b_1.a_id

    The standalone `alias()` function as well as the base `FromClause.alias()` method also support the `flat=True` argument as a no-op, so that the argument can be passed to the `alias()` method of any selectable.

    Parameters:

      - name – name given to the alias.

      - flat – if True, produce an alias of the left and right sides of this `Join` and return the join of those two selectables. This produces join expression that does not include an enclosing SELECT.

    See also

    Using Aliases and Subqueries

    `alias()`

  attribute `sqlalchemy.sql.expression.Join.`bind

    Return the bound engine associated with either the left or right side of this `Join`.

    Deprecated since version 1.4: The `Executable.bind` attribute is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. Bound metadata is being removed as of SQLAlchemy 2.0. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

  attribute `sqlalchemy.sql.expression.Join.`description
  method `sqlalchemy.sql.expression.Join.`is_derived_from(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.Join.`select(whereclause=None, **kwargs)

    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

    Parameters:

      - whereclause –

        WHERE criteria, same as calling `Select.where()` on the resulting statement

        Deprecated since version 1.4: The `Join.select().whereclause` parameter is deprecated and will be removed in version 2.0. Please make use of the `Select.where()` method to add WHERE criteria to the SELECT statement.

      - **kwargs – additional keyword arguments are passed to the legacy constructor for `Select` described at `Select.create_legacy_select()`.

  method `sqlalchemy.sql.expression.Join.`self_group(against=None)

    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(*arg, **kw)

  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.

  New in version 1.1.

  See also

  LATERAL correlation - overview of usage.

  Members

  inherit_cache

  Class signature

  class `sqlalchemy.sql.expression.Lateral` (`sqlalchemy.sql.expression.AliasedReturnsRows`)

  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

  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.

  New in version 1.4.

  Members

  exported_columns

  Class signature

  class `sqlalchemy.sql.expression.ReturnsRows` (`sqlalchemy.sql.roles.ReturnsRowsRole`, `sqlalchemy.sql.expression.ClauseElement`)

  attribute `sqlalchemy.sql.expression.ReturnsRows.`exported_columns

    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..

    New in version 1.4.

    See also

    `FromClause.exported_columns`

    `SelectBase.exported_columns`

class sqlalchemy.sql.expression.ScalarSelect(element)

  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

  Members

  correlate(), correlate_except(), inherit_cache, self_group(), where()

  Class signature

  class `sqlalchemy.sql.expression.ScalarSelect` (`sqlalchemy.sql.roles.InElementRole`, `sqlalchemy.sql.expression.Generative`, `sqlalchemy.sql.expression.Grouping`)

  method `sqlalchemy.sql.expression.ScalarSelect.`correlate(*fromclauses)

    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.

    New 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)

    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.

    New 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(**kwargs)

    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)

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

class sqlalchemy.sql.expression.Select

  Represents a `SELECT` statement.

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

  See also

  `select()`

  Selecting Rows with Core or ORM - in the 2.0 tutorial

  Members

  add_columns(), add_cte(), alias(), apply_labels(), as_scalar(), bind, c, column(), column_descriptions, columns_clause_froms, correlate(), correlate_except(), corresponding_column(), create_legacy_select(), cte(), distinct(), except_(), except_all(), execute(), execution_options(), exists(), exported_columns, fetch(), filter(), filter_by(), from_statement(), froms, get_children(), get_execution_options(), get_final_froms(), get_label_style(), group_by(), having(), inner_columns, intersect(), intersect_all(), join(), join_from(), label(), lateral(), limit(), offset(), options(), order_by(), outerjoin(), outerjoin_from(), prefix_with(), reduce_columns(), replace_selectable(), scalar(), scalar_subquery(), select(), select_from(), selected_columns, self_group(), set_label_style(), slice(), subquery(), suffix_with(), union(), union_all(), where(), whereclause, with_for_update(), with_hint(), with_only_columns(), with_statement_hint()

  Class signature

  class `sqlalchemy.sql.expression.Select` (`sqlalchemy.sql.expression.HasPrefixes`, `sqlalchemy.sql.expression.HasSuffixes`, `sqlalchemy.sql.expression.HasHints`, `sqlalchemy.sql.expression.HasCompileState`, `sqlalchemy.sql.expression.DeprecatedSelectGenerations`, `sqlalchemy.sql.expression._SelectFromElements`, `sqlalchemy.sql.expression.GenerativeSelect`)

  method `sqlalchemy.sql.expression.Select.`add_columns(*columns)

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

    E.g.:

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

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

  method `sqlalchemy.sql.expression.Select.`add_cte(cte)

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

    Add a `CTE` to this statement object that will be independently rendered even if not referenced in the statement otherwise.

    This feature is useful for 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; while PostgreSQL is known to support this usage, it may not be supported by other backends.

    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 referred towards 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

    New in version 1.4.21.

  method `sqlalchemy.sql.expression.Select.`alias(name=None, flat=False)

    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_labels()

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

    Deprecated since version 1.4: The `GenerativeSelect.apply_labels()` method is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. Use set_label_style(LABEL_STYLE_TABLENAME_PLUS_COL) instead. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

  method `sqlalchemy.sql.expression.Select.`as_scalar()

    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()`.

  attribute `sqlalchemy.sql.expression.Select.`bind

    Returns the `Engine` or `Connection` to which this `Executable` is bound, or None if none found.

    Deprecated since version 1.4: The `Executable.bind` attribute is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. Bound metadata is being removed as of SQLAlchemy 2.0. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

  attribute `sqlalchemy.sql.expression.Select.`c

    inherited from the `SelectBase.c` attribute of `SelectBase`

    Deprecated since version 1.4: The `SelectBase.c` and `SelectBase.columns` attributes are deprecated and will be removed in a future release; these attributes implicitly create a subquery that should be explicit. Please call `SelectBase.subquery()` first in order to create a subquery, which then contains this attribute. To access the columns that this SELECT object SELECTs from, use the `SelectBase.selected_columns` attribute.

  method `sqlalchemy.sql.expression.Select.`column(column)

    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.

  attribute `sqlalchemy.sql.expression.Select.`column_descriptions

    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

  attribute `sqlalchemy.sql.expression.Select.`columns_clause_froms

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

    New 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.`correlate(*fromclauses)

    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 – 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

    `Select.correlate_except()`

    Scalar and Correlated Subqueries

  method `sqlalchemy.sql.expression.Select.`correlate_except(*fromclauses)

    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, 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, require_embedded=False)

    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.

  classmethod `sqlalchemy.sql.expression.Select.`create_legacy_select(columns=None, whereclause=None, from_obj=None, distinct=False, having=None, correlate=True, prefixes=None, suffixes=None, **kwargs)

    Construct a new `Select` using the 1.x style API.

    Deprecated since version 1.4: The legacy calling style of `select()` is deprecated and will be removed in SQLAlchemy 2.0. Please use the new calling style described at `select()`. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

    This method is called implicitly when the `select()` construct is used and the first argument is a Python list or other plain sequence object, which is taken to refer to the columns collection.

    Changed in version 1.4: Added the `Select.create_legacy_select()` constructor which documents the calling style in use when the `select()` construct is invoked using 1.x-style arguments.

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

    All arguments which accept `ClauseElement` arguments also accept string arguments, which will be converted as appropriate into either `text()` or `literal_column()` constructs.

    See also

    Selecting Rows with Core or ORM - in the SQLAlchemy 1.4 / 2.0 Tutorial

    Parameters:

      - columns –

        A list of `ColumnElement` 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.

        Note

        The `select.columns` parameter is not available in the method form of `select()`, e.g. `FromClause.select()`.

        See also

        `Select.column()`

        `Select.with_only_columns()`

      - whereclause –

        A `ClauseElement` expression which will be used to form the `WHERE` clause. It is typically preferable to add WHERE criterion to an existing `Select` using method chaining with `Select.where()`.

        See also

        `Select.where()`

      - from_obj –

        A list of `ClauseElement` objects which will be added to the `FROM` clause of the resulting statement. This is equivalent to calling `Select.select_from()` using method chaining on an existing `Select` object.

        See also

        `Select.select_from()` - full description of explicit FROM clause specification.

      - bind=None – an `Engine` or `Connection` instance to which the resulting `Select` object will be bound. The `Select` object will otherwise automatically bind to whatever `Connectable` instances can be located within its contained `ClauseElement` members.

      - correlate=True –

        indicates that this `Select` object should have its contained `FromClause` elements “correlated” to an enclosing `Select` object. It is typically preferable to specify correlations on an existing `Select` construct using `Select.correlate()`.

        See also

        `Select.correlate()` - full description of correlation.

      - distinct=False –

        when `True`, applies a `DISTINCT` qualifier to the columns clause of the resulting statement.

        The boolean argument may also be a column expression or list of column expressions - this is a special calling form which is understood by the PostgreSQL dialect to render the `DISTINCT ON (<columns>)` syntax.

        `distinct` is also available on an existing `Select` object via the `Select.distinct()` method.

        See also

        `Select.distinct()`

      - group_by –

        a list of `ClauseElement` objects which will comprise the `GROUP BY` clause of the resulting select. This parameter is typically specified more naturally using the `Select.group_by()` method on an existing `Select`.

        See also

        `Select.group_by()`

      - having –

        a `ClauseElement` that will comprise the `HAVING` clause of the resulting select when `GROUP BY` is used. This parameter is typically specified more naturally using the `Select.having()` method on an existing `Select`.

        See also

        `Select.having()`

      - limit=None –

        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. This parameter is typically specified more naturally using the `Select.limit()` method on an existing `Select`.

        See also

        `Select.limit()`

      - offset=None –

        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. This parameter is typically specified more naturally using the `Select.offset()` method on an existing `Select`.

        See also

        `Select.offset()`

      - order_by –

        a scalar or list of `ClauseElement` objects which will comprise the `ORDER BY` clause of the resulting select. This parameter is typically specified more naturally using the `Select.order_by()` method on an existing `Select`.

        See also

        `Select.order_by()`

      - use_labels=False –

        when `True`, the statement will be generated using labels for each column in the columns clause, which qualify each column with its parent table’s (or aliases) name so that name conflicts between columns in different tables don’t occur. The format of the label is `<tablename>_<column>`. The “c” collection of a `Subquery` created against this `Select` object, as well as the `Select.selected_columns` collection of the `Select` itself, will use these names for targeting column members.

        This parameter can also be specified on an existing `Select` object using the `Select.set_label_style()` method.

        See also

        `Select.set_label_style()`

  method `sqlalchemy.sql.expression.Select.`cte(name=None, recursive=False, nesting=False)

    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.

    Changed in version 1.1: Added support for UPDATE/INSERT/DELETE as CTE, CTEs added to UPDATE/INSERT/DELETE.

    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.

    Changed in version 1.3.13: Added support for prefixes. In particular - MATERIALIZED and NOT MATERIALIZED.

    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 actual statement.

        New in version 1.4.24.

    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

    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.Select.`distinct(*expr)

    Return a new `select()` construct which will apply DISTINCT to its columns clause.

    Parameters:

      *expr –

      optional column expressions. When present, the PostgreSQL dialect will render a `DISTINCT ON (<expressions>>)` construct.

      Deprecated since version 1.4: Using *expr in other dialects is deprecated and will raise `CompileError` in a future version.

  method `sqlalchemy.sql.expression.Select.`except_(*other, **kwargs)

    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.

      - **kwargs – keyword arguments are forwarded to the constructor for the newly created `CompoundSelect` object.

  method `sqlalchemy.sql.expression.Select.`except_all(*other, **kwargs)

    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.

      - **kwargs – keyword arguments are forwarded to the constructor for the newly created `CompoundSelect` object.

  method `sqlalchemy.sql.expression.Select.`execute(*multiparams, **params)

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

    Compile and execute this `Executable`.

    Deprecated since version 1.4: The `Executable.execute()` method is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. All statement execution in SQLAlchemy 2.0 is performed by the `Connection.execute()` method of `Connection`, or in the ORM by the `Session.execute()` method of `Session`. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

  method `sqlalchemy.sql.expression.Select.`execution_options(**kw)

    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 on a per-statement or per `Connection` basis. Additionally, the `Engine` and ORM `Query` objects provide access to execution options which they in turn configure upon connections.

    The `execution_options()` method is generative. A new instance of this statement is returned that contains the options:

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

    Note that only a subset of possible execution options can be applied to a statement - these include “autocommit” and “stream_results”, but not “isolation_level” or “compiled_cache”. See `Connection.execution_options()` for a full list of possible options.

    See also

    `Connection.execution_options()`

    `Query.execution_options()`

    `Executable.get_execution_options()`

  method `sqlalchemy.sql.expression.Select.`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.

    New in version 1.4.

  attribute `sqlalchemy.sql.expression.Select.`exported_columns

    inherited from the `SelectBase.exported_columns` attribute of `SelectBase`

    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.

    New in version 1.4.

    See also

    `Select.exported_columns`

    `Selectable.exported_columns`

    `FromClause.exported_columns`

  method `sqlalchemy.sql.expression.Select.`fetch(count, with_ties=False, percent=False)

    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, PostgreSQL, MSSQL.

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

    Note

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

    New 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`

    See also

    `GenerativeSelect.limit()`

    `GenerativeSelect.offset()`

  method `sqlalchemy.sql.expression.Select.`filter(*criteria)

    A synonym for the `Select.where()` method.

  method `sqlalchemy.sql.expression.Select.`filter_by(**kwargs)

    apply the given filtering criterion as a WHERE clause to this select.

  method `sqlalchemy.sql.expression.Select.`from_statement(statement)

    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 and Core Statements - usage examples in the ORM Querying Guide

  attribute `sqlalchemy.sql.expression.Select.`froms

    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(**kwargs)

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

    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()

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

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

    New in version 1.3.

    See also

    `Executable.execution_options()`

  method `sqlalchemy.sql.expression.Select.`get_final_froms()

    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.

    New 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()

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

    Retrieve the current label style.

    New in version 1.4.

  method `sqlalchemy.sql.expression.Select.`group_by(*clauses)

    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.

    See also

    Aggregate functions with GROUP BY / HAVING - in the SQLAlchemy 1.4 / 2.0 Tutorial

    Ordering or Grouping by a Label - in the SQLAlchemy 1.4 / 2.0 Tutorial

  method `sqlalchemy.sql.expression.Select.`having(having)

    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.`inner_columns

    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, **kwargs)

    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, **kwargs)

    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.`join(target, onclause=None, isouter=False, full=False)

    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 1.4 / 2.0 Tutorial

    Joins - in the ORM Querying Guide

    `Select.join_from()`

    `Select.outerjoin()`

  method `sqlalchemy.sql.expression.Select.`join_from(from_, target, onclause=None, isouter=False, full=False)

    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

    New 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 1.4 / 2.0 Tutorial

    Joins - in the ORM Querying Guide

    `Select.join()`

  method `sqlalchemy.sql.expression.Select.`label(name)

    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.as_scalar()`.

  method `sqlalchemy.sql.expression.Select.`lateral(name=None)

    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.

    New in version 1.1.

    See also

    LATERAL correlation - overview of usage.

  method `sqlalchemy.sql.expression.Select.`limit(limit)

    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()`.

    Changed in version 1.0.0: - `Select.limit()` can now accept arbitrary SQL expressions as well as integer values.

    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.Select.`offset(offset)

    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.

    Changed in version 1.0.0: - `Select.offset()` can now accept arbitrary SQL expressions as well as integer values.

    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)

    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 the SQL compiler for the statement. These options can be consumed by specific dialects or specific kinds of compilers.

    The most commonly known kind of option are the ORM level options that apply “eager load” and other loading behaviors to an ORM query. However, options can theoretically be used for many other purposes.

    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 `Generative.options()` to Core statement objects towards the goal of allowing unified Core / ORM querying capabilities.

    See also

    Deferred Column Loader Query 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(*clauses)

    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)

    All existing ORDER BY criteria may be cancelled by passing `None` by itself. New ORDER BY criteria may then be added by invoking `Select.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.

    See also

    ORDER BY - in the SQLAlchemy 1.4 / 2.0 Tutorial

    Ordering or Grouping by a Label - in the SQLAlchemy 1.4 / 2.0 Tutorial

  method `sqlalchemy.sql.expression.Select.`outerjoin(target, onclause=None, full=False)

    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 1.4 / 2.0 Tutorial

    Joins - in the ORM Querying Guide

    `Select.join()`

  method `sqlalchemy.sql.expression.Select.`outerjoin_from(from_, target, onclause=None, full=False)

    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.`prefix_with(*expr, **kw)

    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:

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

      - **kw – A single keyword ‘dialect’ is accepted. This is an optional string dialect name which will limit rendering of this prefix to only that dialect.

  method `sqlalchemy.sql.expression.Select.`reduce_columns(only_synonyms=True)

    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, alias)

    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(*multiparams, **params)

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

    Compile and execute this `Executable`, returning the result’s scalar representation.

    Deprecated since version 1.4: The `Executable.scalar()` method is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. Scalar execution in SQLAlchemy 2.0 is performed by the `Connection.scalar()` method of `Connection`, or in the ORM by the `Session.scalar()` method of `Session`. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

  method `sqlalchemy.sql.expression.Select.`scalar_subquery()

    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.

    See also

    Scalar and Correlated Subqueries - in the 2.0 tutorial

  method `sqlalchemy.sql.expression.Select.`select(*arg, **kw)

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

    Deprecated since version 1.4: The `SelectBase.select()` method is deprecated and will be removed in a future release; this method implicitly creates a subquery that should be explicit. Please call `SelectBase.subquery()` first in order to create a subquery, which then can be selected.

  method `sqlalchemy.sql.expression.Select.`select_from(*froms)

    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.

    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.

    New in version 1.4.

  method `sqlalchemy.sql.expression.Select.`self_group(against=None)

    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)

    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, `LABEL_STYLE_DISAMBIGUATE_ONLY`, `LABEL_STYLE_TABLENAME_PLUS_COL`, and `LABEL_STYLE_NONE`. The default style is `LABEL_STYLE_TABLENAME_PLUS_COL`.

    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.

    New 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

    `LABEL_STYLE_DISAMBIGUATE_ONLY`

    `LABEL_STYLE_TABLENAME_PLUS_COL`

    `LABEL_STYLE_NONE`

    `LABEL_STYLE_DEFAULT`

  method `sqlalchemy.sql.expression.Select.`slice(start, stop)

    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()`.

    New 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=None)

    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.

    New in version 1.4.

  method `sqlalchemy.sql.expression.Select.`suffix_with(*expr, **kw)

    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:

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

      - **kw – A single keyword ‘dialect’ is accepted. This is an optional string dialect name which will limit rendering of this suffix to only that dialect.

  method `sqlalchemy.sql.expression.Select.`union(*other, **kwargs)

    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, **kwargs)

    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)

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

  attribute `sqlalchemy.sql.expression.Select.`whereclause

    Return the completed WHERE clause for this `Select` statement.

    This assembles the current collection of WHERE criteria into a single `BooleanClauseList` construct.

    New in version 1.4.

  method `sqlalchemy.sql.expression.Select.`with_for_update(nowait=False, read=False, of=None, skip_locked=False, key_share=False)

    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, 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 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) which will render into a `FOR UPDATE OF` clause; supported by PostgreSQL and Oracle. May render as a table or as a column depending on backend.

      - skip_locked – boolean, will render `FOR UPDATE SKIP LOCKED` on Oracle 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, text, dialect_name='*')

    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.

    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, 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 and Sybase simultaneously:

        select(mytable).\
            with_hint(mytable, "index(%(name)s ix_mytable)", 'oracle').\
            with_hint(mytable, "WITH INDEX ix_mytable", 'sybase')

    See also

    `Select.with_statement_hint()`

  method `sqlalchemy.sql.expression.Select.`with_only_columns(*columns, **kw)

    Return a new `select()` construct with its columns clause replaced with the given columns.

    By default, this method is exactly equivalent to as if the original `select()` had been called with the given columns clause. 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:

      - *columns –

        column expressions to be used.

        Changed in version 1.4: the `Select.with_only_columns()` method accepts the list of column expressions positionally; passing the expressions as a list is deprecated.

      - 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.

        New in version 1.4.23.

  method `sqlalchemy.sql.expression.Select.`with_statement_hint(text, dialect_name='*')

    inherited from the `HasHints.with_statement_hint()` method of `HasHints`

    Add a statement hint to this `Select` or other selectable object.

    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.

    New in version 1.0.0.

    See also

    `Select.with_hint()`

    `Select.prefix_with()` - generic SELECT prefixing which also can suit some database-specific HINT syntaxes such as MySQL optimizer hints

class sqlalchemy.sql.expression.Selectable

  Mark a class as being selectable.

  Members

  corresponding_column(), exported_columns, lateral(), replace_selectable()

  Class signature

  class `sqlalchemy.sql.expression.Selectable` (`sqlalchemy.sql.expression.ReturnsRows`)

  method `sqlalchemy.sql.expression.Selectable.`corresponding_column(column, require_embedded=False)

    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.

  attribute `sqlalchemy.sql.expression.Selectable.`exported_columns

    inherited from the `ReturnsRows.exported_columns` attribute of `ReturnsRows`

    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..

    New in version 1.4.

    See also

    `FromClause.exported_columns`

    `SelectBase.exported_columns`

  method `sqlalchemy.sql.expression.Selectable.`lateral(name=None)

    Return a LATERAL alias of this `Selectable`.

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

    New in version 1.1.

    See also

    LATERAL correlation - overview of usage.

  method `sqlalchemy.sql.expression.Selectable.`replace_selectable(old, alias)

    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

  Base class for SELECT statements.

  This includes `Select`, `CompoundSelect` and `TextualSelect`.

  Members

  add_cte(), alias(), as_scalar(), bind, c, corresponding_column(), cte(), execute(), execution_options(), exists(), exported_columns, get_execution_options(), label(), lateral(), options(), replace_selectable(), scalar(), scalar_subquery(), select(), selected_columns, subquery()

  Class signature

  class `sqlalchemy.sql.expression.SelectBase` (`sqlalchemy.sql.roles.SelectStatementRole`, `sqlalchemy.sql.roles.DMLSelectRole`, `sqlalchemy.sql.roles.CompoundElementRole`, `sqlalchemy.sql.roles.InElementRole`, `sqlalchemy.sql.expression.HasCTE`, `sqlalchemy.sql.expression.Executable`, `sqlalchemy.sql.annotation.SupportsCloneAnnotations`, `sqlalchemy.sql.expression.Selectable`)

  method `sqlalchemy.sql.expression.SelectBase.`add_cte(cte)

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

    Add a `CTE` to this statement object that will be independently rendered even if not referenced in the statement otherwise.

    This feature is useful for 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; while PostgreSQL is known to support this usage, it may not be supported by other backends.

    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 referred towards 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

    New in version 1.4.21.

  method `sqlalchemy.sql.expression.SelectBase.`alias(name=None, flat=False)

    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()

    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()`.

  attribute `sqlalchemy.sql.expression.SelectBase.`bind

    inherited from the `Executable.bind` attribute of `Executable`

    Returns the `Engine` or `Connection` to which this `Executable` is bound, or None if none found.

    Deprecated since version 1.4: The `Executable.bind` attribute is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. Bound metadata is being removed as of SQLAlchemy 2.0. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

    This is a traversal which checks locally, then checks among the “from” clauses of associated objects until a bound engine or connection is found.

  attribute `sqlalchemy.sql.expression.SelectBase.`c

    Deprecated since version 1.4: The `SelectBase.c` and `SelectBase.columns` attributes are deprecated and will be removed in a future release; these attributes implicitly create a subquery that should be explicit. Please call `SelectBase.subquery()` first in order to create a subquery, which then contains this attribute. To access the columns that this SELECT object SELECTs from, use the `SelectBase.selected_columns` attribute.

  method `sqlalchemy.sql.expression.SelectBase.`corresponding_column(column, require_embedded=False)

    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=None, recursive=False, nesting=False)

    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.

    Changed in version 1.1: Added support for UPDATE/INSERT/DELETE as CTE, CTEs added to UPDATE/INSERT/DELETE.

    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.

    Changed in version 1.3.13: Added support for prefixes. In particular - MATERIALIZED and NOT MATERIALIZED.

    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 actual statement.

        New in version 1.4.24.

    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

    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.`execute(*multiparams, **params)

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

    Compile and execute this `Executable`.

    Deprecated since version 1.4: The `Executable.execute()` method is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. All statement execution in SQLAlchemy 2.0 is performed by the `Connection.execute()` method of `Connection`, or in the ORM by the `Session.execute()` method of `Session`. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

  method `sqlalchemy.sql.expression.SelectBase.`execution_options(**kw)

    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 on a per-statement or per `Connection` basis. Additionally, the `Engine` and ORM `Query` objects provide access to execution options which they in turn configure upon connections.

    The `execution_options()` method is generative. A new instance of this statement is returned that contains the options:

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

    Note that only a subset of possible execution options can be applied to a statement - these include “autocommit” and “stream_results”, but not “isolation_level” or “compiled_cache”. See `Connection.execution_options()` for a full list of possible options.

    See also

    `Connection.execution_options()`

    `Query.execution_options()`

    `Executable.get_execution_options()`

  method `sqlalchemy.sql.expression.SelectBase.`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.

    New in version 1.4.

  attribute `sqlalchemy.sql.expression.SelectBase.`exported_columns

    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.

    New in version 1.4.

    See also

    `Select.exported_columns`

    `Selectable.exported_columns`

    `FromClause.exported_columns`

  method `sqlalchemy.sql.expression.SelectBase.`get_execution_options()

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

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

    New in version 1.3.

    See also

    `Executable.execution_options()`

  method `sqlalchemy.sql.expression.SelectBase.`label(name)

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

    See also

    `SelectBase.as_scalar()`.

  method `sqlalchemy.sql.expression.SelectBase.`lateral(name=None)

    Return a LATERAL alias of this `Selectable`.

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

    New in version 1.1.

    See also

    LATERAL correlation - overview of usage.

  method `sqlalchemy.sql.expression.SelectBase.`options(*options)

    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 the SQL compiler for the statement. These options can be consumed by specific dialects or specific kinds of compilers.

    The most commonly known kind of option are the ORM level options that apply “eager load” and other loading behaviors to an ORM query. However, options can theoretically be used for many other purposes.

    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 `Generative.options()` to Core statement objects towards the goal of allowing unified Core / ORM querying capabilities.

    See also

    Deferred Column Loader Query 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.SelectBase.`replace_selectable(old, alias)

    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(*multiparams, **params)

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

    Compile and execute this `Executable`, returning the result’s scalar representation.

    Deprecated since version 1.4: The `Executable.scalar()` method is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. Scalar execution in SQLAlchemy 2.0 is performed by the `Connection.scalar()` method of `Connection`, or in the ORM by the `Session.scalar()` method of `Session`. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

  method `sqlalchemy.sql.expression.SelectBase.`scalar_subquery()

    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.

    See also

    Scalar and Correlated Subqueries - in the 2.0 tutorial

  method `sqlalchemy.sql.expression.SelectBase.`select(*arg, **kw)

    Deprecated since version 1.4: The `SelectBase.select()` method is deprecated and will be removed in a future release; this method implicitly creates a subquery that should be explicit. Please call `SelectBase.subquery()` first in order to create a subquery, which then can be selected.

  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`

    New in version 1.4.

  method `sqlalchemy.sql.expression.SelectBase.`subquery(name=None)

    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.

    New in version 1.4.

class sqlalchemy.sql.expression.Subquery(*arg, **kw)

  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.

  New in version 1.4: The `Subquery` class was added which now serves the purpose of providing an aliased version of a SELECT statement.

  Members

  as_scalar(), inherit_cache

  Class signature

  class `sqlalchemy.sql.expression.Subquery` (`sqlalchemy.sql.expression.AliasedReturnsRows`)

  method `sqlalchemy.sql.expression.Subquery.`as_scalar()

    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(name, *columns, **kw)

  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.

  Members

  __init__(), alias(), c, columns, compare(), compile(), corresponding_column(), delete(), description, entity_namespace, exported_columns, foreign_keys, get_children(), implicit_returning, inherit_cache, insert(), is_derived_from(), join(), lateral(), memoized_instancemethod(), outerjoin(), params(), primary_key, replace_selectable(), schema, select(), self_group(), table_valued(), tablesample(), unique_params(), update()

  Class signature

  class `sqlalchemy.sql.expression.TableClause` (`sqlalchemy.sql.roles.DMLTableRole`, `sqlalchemy.sql.expression.Immutable`, `sqlalchemy.sql.expression.FromClause`)

  method `sqlalchemy.sql.expression.TableClause.`__init__(name, *columns, **kw)

    Construct a new `TableClause` object.

    This constructor is mirrored as a public API function; see `sqlalchemy.sql.expression.table()` for a full usage and argument description.

  method `sqlalchemy.sql.expression.TableClause.`alias(name=None, flat=False)

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

    The `FromClause.c` attribute is an alias for the `FromClause.columns` attribute.

    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, **kw)

    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=None, dialect=None, **kw)

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

    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 `Engine` or `Connection` from which a `Compiled` will be acquired. This argument takes precedence over this `ClauseElement`’s bound engine, if any.

      - 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 from which a `Compiled` will be acquired. This argument takes precedence over the bind argument as well as this `ClauseElement` ‘s bound engine, if any.

      - 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}))

        New in version 0.9.0.

    See also

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

  method `sqlalchemy.sql.expression.TableClause.`corresponding_column(column, require_embedded=False)

    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(whereclause=None, **kwargs)

    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 `Selectable`.

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

    New 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=(), **kw)

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

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

    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(values=None, inline=False, **kwargs)

    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)

    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, onclause=None, isouter=False, full=False)

    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`.

        New in version 1.1.

    See also

    `join()` - standalone function

    `Join` - the type of object produced

  method `sqlalchemy.sql.expression.TableClause.`lateral(name=None)

    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.

    New in version 1.1.

    See also

    LATERAL correlation - overview of usage.

  classmethod `sqlalchemy.sql.expression.TableClause.`memoized_instancemethod(fn)

    inherited from the `HasMemoized.memoized_instancemethod()` method of `HasMemoized`

    Decorate a method memoize its return value.

  method `sqlalchemy.sql.expression.TableClause.`outerjoin(right, onclause=None, full=False)

    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.

        New in version 1.1.

    See also

    `FromClause.join()`

    `Join`

  method `sqlalchemy.sql.expression.TableClause.`params(*optionaldict, **kwargs)

    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, alias)

    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(whereclause=None, **kwargs)

    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)

    Parameters:

      - whereclause –

        a WHERE clause, equivalent to calling the `Select.where()` method.

        Deprecated since version 1.4: The `FromClause.select().whereclause` parameter is deprecated and will be removed in version 2.0. Please make use of the `Select.where()` method to add WHERE criteria to the SELECT statement.

      - **kwargs – additional keyword arguments are passed to the legacy constructor for `Select` described at `Select.create_legacy_select()`.

    See also

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

  method `sqlalchemy.sql.expression.TableClause.`self_group(against=None)

    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()

    inherited from the `FromClause.table_valued()` method of `FromClause`

    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 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

    New in version 1.4.0b2.

    See also

    Working with SQL Functions - in the SQLAlchemy 1.4 / 2.0 Tutorial

  method `sqlalchemy.sql.expression.TableClause.`tablesample(sampling, name=None, seed=None)

    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.

    New in version 1.1.

    See also

    `tablesample()` - usage guidelines and parameters

  method `sqlalchemy.sql.expression.TableClause.`unique_params(*optionaldict, **kwargs)

    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(whereclause=None, values=None, inline=False, **kwargs)

    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(*arg, **kw)

  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.

  New in version 1.1.

  See also

  `tablesample()`

  Class signature

  class `sqlalchemy.sql.expression.TableSample` (`sqlalchemy.sql.expression.AliasedReturnsRows`)

class sqlalchemy.sql.expression.TableValuedAlias(*arg, **kw)

  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

  New in version 1.4.0b2.

  See also

  Table-Valued Functions - in the SQLAlchemy 1.4 / 2.0 Tutorial

  Members

  alias(), column, lateral(), render_derived()

  Class signature

  class `sqlalchemy.sql.expression.TableValuedAlias` (`sqlalchemy.sql.expression.Alias`)

  method `sqlalchemy.sql.expression.TableValuedAlias.`alias(name=None)

    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=None)

    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=None, with_types=False)

    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(text, columns, positional=False)

  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.

  Members

  add_cte(), alias(), as_scalar(), bind, c, compare(), compile(), corresponding_column(), cte(), execute(), execution_options(), exists(), exported_columns, get_children(), get_execution_options(), inherit_cache, label(), lateral(), memoized_instancemethod(), options(), params(), replace_selectable(), scalar(), scalar_subquery(), select(), selected_columns, self_group(), subquery(), unique_params()

  Class signature

  class `sqlalchemy.sql.expression.TextualSelect` (`sqlalchemy.sql.expression.SelectBase`)

  method `sqlalchemy.sql.expression.TextualSelect.`add_cte(cte)

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

    Add a `CTE` to this statement object that will be independently rendered even if not referenced in the statement otherwise.

    This feature is useful for 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; while PostgreSQL is known to support this usage, it may not be supported by other backends.

    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 referred towards 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

    New in version 1.4.21.

  method `sqlalchemy.sql.expression.TextualSelect.`alias(name=None, flat=False)

    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()

    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()`.

  attribute `sqlalchemy.sql.expression.TextualSelect.`bind

    inherited from the `Executable.bind` attribute of `Executable`

    Returns the `Engine` or `Connection` to which this `Executable` is bound, or None if none found.

    Deprecated since version 1.4: The `Executable.bind` attribute is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. Bound metadata is being removed as of SQLAlchemy 2.0. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

    This is a traversal which checks locally, then checks among the “from” clauses of associated objects until a bound engine or connection is found.

  attribute `sqlalchemy.sql.expression.TextualSelect.`c

    inherited from the `SelectBase.c` attribute of `SelectBase`

    Deprecated since version 1.4: The `SelectBase.c` and `SelectBase.columns` attributes are deprecated and will be removed in a future release; these attributes implicitly create a subquery that should be explicit. Please call `SelectBase.subquery()` first in order to create a subquery, which then contains this attribute. To access the columns that this SELECT object SELECTs from, use the `SelectBase.selected_columns` attribute.

  method `sqlalchemy.sql.expression.TextualSelect.`compare(other, **kw)

    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=None, dialect=None, **kw)

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

    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 `Engine` or `Connection` from which a `Compiled` will be acquired. This argument takes precedence over this `ClauseElement`’s bound engine, if any.

      - 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 from which a `Compiled` will be acquired. This argument takes precedence over the bind argument as well as this `ClauseElement` ‘s bound engine, if any.

      - 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}))

        New in version 0.9.0.

    See also

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

  method `sqlalchemy.sql.expression.TextualSelect.`corresponding_column(column, require_embedded=False)

    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=None, recursive=False, nesting=False)

    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.

    Changed in version 1.1: Added support for UPDATE/INSERT/DELETE as CTE, CTEs added to UPDATE/INSERT/DELETE.

    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.

    Changed in version 1.3.13: Added support for prefixes. In particular - MATERIALIZED and NOT MATERIALIZED.

    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 actual statement.

        New in version 1.4.24.

    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

    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.`execute(*multiparams, **params)

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

    Compile and execute this `Executable`.

    Deprecated since version 1.4: The `Executable.execute()` method is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. All statement execution in SQLAlchemy 2.0 is performed by the `Connection.execute()` method of `Connection`, or in the ORM by the `Session.execute()` method of `Session`. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

  method `sqlalchemy.sql.expression.TextualSelect.`execution_options(**kw)

    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 on a per-statement or per `Connection` basis. Additionally, the `Engine` and ORM `Query` objects provide access to execution options which they in turn configure upon connections.

    The `execution_options()` method is generative. A new instance of this statement is returned that contains the options:

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

    Note that only a subset of possible execution options can be applied to a statement - these include “autocommit” and “stream_results”, but not “isolation_level” or “compiled_cache”. See `Connection.execution_options()` for a full list of possible options.

    See also

    `Connection.execution_options()`

    `Query.execution_options()`

    `Executable.get_execution_options()`

  method `sqlalchemy.sql.expression.TextualSelect.`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.

    New in version 1.4.

  attribute `sqlalchemy.sql.expression.TextualSelect.`exported_columns

    inherited from the `SelectBase.exported_columns` attribute of `SelectBase`

    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.

    New in version 1.4.

    See also

    `Select.exported_columns`

    `Selectable.exported_columns`

    `FromClause.exported_columns`

  method `sqlalchemy.sql.expression.TextualSelect.`get_children(omit_attrs=(), **kw)

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

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

    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()

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

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

    New in version 1.3.

    See also

    `Executable.execution_options()`

  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.`label(name)

    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.as_scalar()`.

  method `sqlalchemy.sql.expression.TextualSelect.`lateral(name=None)

    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.

    New in version 1.1.

    See also

    LATERAL correlation - overview of usage.

  classmethod `sqlalchemy.sql.expression.TextualSelect.`memoized_instancemethod(fn)

    inherited from the `HasMemoized.memoized_instancemethod()` method of `HasMemoized`

    Decorate a method memoize its return value.

  method `sqlalchemy.sql.expression.TextualSelect.`options(*options)

    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 the SQL compiler for the statement. These options can be consumed by specific dialects or specific kinds of compilers.

    The most commonly known kind of option are the ORM level options that apply “eager load” and other loading behaviors to an ORM query. However, options can theoretically be used for many other purposes.

    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 `Generative.options()` to Core statement objects towards the goal of allowing unified Core / ORM querying capabilities.

    See also

    Deferred Column Loader Query 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(*optionaldict, **kwargs)

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

    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}

  method `sqlalchemy.sql.expression.TextualSelect.`replace_selectable(old, alias)

    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(*multiparams, **params)

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

    Compile and execute this `Executable`, returning the result’s scalar representation.

    Deprecated since version 1.4: The `Executable.scalar()` method is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. Scalar execution in SQLAlchemy 2.0 is performed by the `Connection.scalar()` method of `Connection`, or in the ORM by the `Session.scalar()` method of `Session`. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)

  method `sqlalchemy.sql.expression.TextualSelect.`scalar_subquery()

    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.

    See also

    Scalar and Correlated Subqueries - in the 2.0 tutorial

  method `sqlalchemy.sql.expression.TextualSelect.`select(*arg, **kw)

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

    Deprecated since version 1.4: The `SelectBase.select()` method is deprecated and will be removed in a future release; this method implicitly creates a subquery that should be explicit. Please call `SelectBase.subquery()` first in order to create a subquery, which then can be selected.

  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.

    New in version 1.4.

  method `sqlalchemy.sql.expression.TextualSelect.`self_group(against=None)

    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.`subquery(name=None)

    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.

    New in version 1.4.

  method `sqlalchemy.sql.expression.TextualSelect.`unique_params(*optionaldict, **kwargs)

    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(*columns, **kw)

  Represent a `VALUES` construct that can be used as a FROM element in a statement.

  The `Values` object is created from the `values()` function.

  New in version 1.4.

  Members

  __init__(), alias(), data(), lateral()

  Class signature

  class `sqlalchemy.sql.expression.Values` (`sqlalchemy.sql.expression.Generative`, `sqlalchemy.sql.expression.FromClause`)

  method `sqlalchemy.sql.expression.Values.`__init__(*columns, **kw)

    Construct a new `Values` object.

    This constructor is mirrored as a public API function; see `sqlalchemy.sql.expression.values()` for a full usage and argument description.

  method `sqlalchemy.sql.expression.Values.`alias(name, **kw)

    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.`data(values)

    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.

  method `sqlalchemy.sql.expression.Values.`lateral(name=None)

    Return a new `Values` with the lateral flag set, so that it renders as LATERAL.

    See also

    `lateral()`

## Label Style Constants

Constants used with the `GenerativeSelect.set_label_style()` method.

Object 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.

sqlalchemy.sql.expression.LABEL_STYLE_DISAMBIGUATE_ONLY = symbol('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.

  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.

  New in version 1.4.

sqlalchemy.sql.expression.LABEL_STYLE_NONE = symbol('LABEL_STYLE_NONE')

  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.

  New in version 1.4.

sqlalchemy.sql.expression.LABEL_STYLE_TABLENAME_PLUS_COL = symbol('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.

  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.

  New in version 1.4.

sqlalchemy.sql.expression.LABEL_STYLE_DEFAULT

  The default label style, refers to `LABEL_STYLE_DISAMBIGUATE_ONLY`.

  New in version 1.4.

  See also

  `Select.set_label_style()`

  `Select.get_label_style()`