Insert, Updates, Deletes¶

INSERT, UPDATE and DELETE statements build on a hierarchy starting with UpdateBase. The Insert and Update constructs build on the intermediary ValuesBase.

Object Name	Description
delete(table[, whereclause, bind, returning, ...], **dialect_kw)	Construct `Delete` object.
Delete	Represent a DELETE construct.
insert(table[, values, inline, bind, ...], **dialect_kw)	Construct an `Insert` object.
Insert	Represent an INSERT construct.
update(table[, whereclause, values, inline, ...], **dialect_kw)	Construct an `Update` object.
Update	Represent an Update construct.
UpdateBase	Form the base for `INSERT`, `UPDATE`, and `DELETE` statements.
ValuesBase	Supplies support for `ValuesBase.values()` to INSERT and UPDATE constructs.

function sqlalchemy.sql.expression.delete(table, whereclause=None, bind=None, returning=None, prefixes=None, **dialect_kw)¶

Construct Delete object.

Similar functionality is available via the TableClause.delete() method on Table.

Parameters:

table – The table to delete rows from.
whereclause –

A ClauseElement describing the WHERE
condition of the DELETE statement. Note that the Delete.where() generative method may be used instead.

The WHERE clause can refer to multiple tables. For databases which support this, a DELETE..USING or similar clause will be generated. The statement will fail on databases that don’t have support for multi-table delete statements. A SQL-standard method of referring to additional tables in the WHERE clause is to use a correlated subquery:
```
users.delete().where(
        users.c.name==select([addresses.c.email_address]).                                where(addresses.c.user_id==users.c.id).                                as_scalar()
        )
```
Changed in version 1.2.0: The WHERE clause of DELETE can refer to multiple tables.

See also

Deletes - SQL Expression Tutorial

function sqlalchemy.sql.expression.insert(table, values=None, inline=False, bind=None, prefixes=None, returning=None, return_defaults=False, **dialect_kw)¶

Construct an Insert object.

Similar functionality is available via the TableClause.insert() method on Table.

Parameters:

table – TableClause which is the subject of the insert.
values – collection of values to be inserted; see Insert.values() for a description of allowed formats here. Can be omitted entirely; a Insert construct will also dynamically render the VALUES clause at execution time based on the parameters passed to Connection.execute().
inline – if True, no attempt will be made to retrieve the SQL-generated default values to be provided within the statement; in particular, this allows SQL expressions to be rendered ‘inline’ within the statement without the need to pre-execute them beforehand; for backends that support “returning”, this turns off the “implicit returning” feature for the statement.

If both values and compile-time bind parameters are present, the compile-time bind parameters override the information specified within values on a per-key basis.

The keys within values can be either Column objects or their string identifiers. Each key may reference one of:

a literal data value (i.e. string, number, etc.);
a Column object;
a SELECT statement.

If a SELECT statement is specified which references this INSERT statement’s table, the statement will be correlated against the INSERT statement.

See also

Insert Expressions - SQL Expression Tutorial

Inserts, Updates and Deletes - SQL Expression Tutorial

function sqlalchemy.sql.expression.update(table, whereclause=None, values=None, inline=False, bind=None, prefixes=None, returning=None, return_defaults=False, preserve_parameter_order=False, **dialect_kw)¶

Construct an Update object.

E.g.:

from sqlalchemy import update

stmt = update(users).where(users.c.id==5).\
        values(name='user #5')

Similar functionality is available via the TableClause.update() method on Table:

stmt = users.update().\
            where(users.c.id==5).\
            values(name='user #5')

Parameters:

table – A Table object representing the database table to be updated.
whereclause –
Optional SQL expression describing the WHERE condition of the UPDATE statement. Modern applications may prefer to use the generative Update.where() method to specify the WHERE clause.

The WHERE clause can refer to multiple tables. For databases which support this, an UPDATE FROM clause will be generated, or on MySQL, a multi-table update. The statement will fail on databases that don’t have support for multi-table update statements. A SQL-standard method of referring to additional tables in the WHERE clause is to use a correlated subquery:
```
users.update().values(name='ed').where(
        users.c.name==select([addresses.c.email_address]).\
                    where(addresses.c.user_id==users.c.id).\
                    as_scalar()
        )
```
values –
Optional dictionary which specifies the SET conditions of the UPDATE. If left as None, the SET conditions are determined from those parameters passed to the statement during the execution and/or compilation of the statement. When compiled standalone without any parameters, the SET clause generates for all columns.

Modern applications may prefer to use the generative Update.values() method to set the values of the UPDATE statement.
inline – if True, SQL defaults present on Column objects via the default keyword will be compiled ‘inline’ into the statement and not pre-executed. This means that their values will not be available in the dictionary returned from ResultProxy.last_updated_params().
preserve_parameter_order –
if True, the update statement is expected to receive parameters only via the Update.values() method, and they must be passed as a Python list of 2-tuples. The rendered UPDATE statement will emit the SET clause for each referenced column maintaining this order.

New in version 1.0.10.

See also

Parameter-Ordered Updates - full example of the update.preserve_parameter_order flag

If both values and compile-time bind parameters are present, the compile-time bind parameters override the information specified within values on a per-key basis.

The keys within values can be either Column objects or their string identifiers (specifically the “key” of the Column, normally but not necessarily equivalent to its “name”). Normally, the Column objects used here are expected to be part of the target Table that is the table to be updated. However when using MySQL, a multiple-table UPDATE statement can refer to columns from any of the tables referred to in the WHERE clause.

The values referred to in values are typically:

a literal data value (i.e. string, number, etc.)
a SQL expression, such as a related Column, a scalar-returning select() construct, etc.

When combining select() constructs within the values clause of an update() construct, the subquery represented by the select() should be correlated to the parent table, that is, providing criterion which links the table inside the subquery to the outer table being updated:

users.update().values(
        name=select([addresses.c.email_address]).\
                where(addresses.c.user_id==users.c.id).\
                as_scalar()
    )

See also

Inserts, Updates and Deletes - SQL Expression Language Tutorial

class sqlalchemy.sql.expression.Delete(table, whereclause=None, bind=None, returning=None, prefixes=None, **dialect_kw)¶

Represent a DELETE construct.

The Delete object is created using the delete() function.

Class signature

class sqlalchemy.sql.expression.Delete (sqlalchemy.sql.expression.UpdateBase)

method sqlalchemy.sql.expression.Delete.__init__(table, whereclause=None, bind=None, returning=None, prefixes=None, **dialect_kw)¶

Construct a new Delete object.

This constructor is mirrored as a public API function; see delete() for a full usage and argument description.

classmethod sqlalchemy.sql.expression.Delete.argument_for(dialect_name, argument_name, default)¶

inherited from the DialectKWArgs.argument_for() method of DialectKWArgs

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

E.g.:

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

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

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

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

Parameters:

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

New in version 0.9.4.

attribute sqlalchemy.sql.expression.Delete.bind¶: inherited from the UpdateBase.bind attribute of UpdateBase

Return a ‘bind’ linked to this UpdateBase or a Table associated with it.

method sqlalchemy.sql.expression.Delete.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.Delete.compile(default, 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.
inline – Used for INSERT statements, for a dialect which does not support inline retrieval of newly generated primary key columns, will force the expression used to create the new primary key value to be rendered inline within the INSERT statement’s VALUES clause. This typically refers to Sequence execution but may also refer to any server-side default generation function associated with a primary key Column.
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.

method sqlalchemy.sql.expression.Delete.cte(name=None, recursive=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.

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.

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

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.

The following examples include two from PostgreSQL’s documentation at http://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)

See also

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

attribute sqlalchemy.sql.expression.Delete.dialect_kwargs¶

inherited from the DialectKWArgs.dialect_kwargs attribute of DialectKWArgs

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

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

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

New in version 0.9.2.

Changed in version 0.9.4: The DialectKWArgs.dialect_kwargs collection is now writable.

See also

DialectKWArgs.dialect_options - nested dictionary form

attribute sqlalchemy.sql.expression.Delete.dialect_options¶

inherited from the DialectKWArgs.dialect_options attribute of DialectKWArgs

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

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

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

New in version 0.9.2.

See also

DialectKWArgs.dialect_kwargs - flat dictionary form

method sqlalchemy.sql.expression.Delete.execute(*multiparams, **params)¶: inherited from the Executable.execute() method of Executable

Compile and execute this Executable.

method sqlalchemy.sql.expression.Delete.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()

method sqlalchemy.sql.expression.Delete.get_children(**kwargs)¶

Return immediate child elements of this ClauseElement.

This is used for visit traversal.

**kwargs 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.Delete.kwargs¶: inherited from the DialectKWArgs.kwargs attribute of DialectKWArgs

A synonym for DialectKWArgs.dialect_kwargs.

method sqlalchemy.sql.expression.Delete.params(*arg, **kw)¶

inherited from the UpdateBase.params() method of UpdateBase

Set the parameters for the statement.

This method raises NotImplementedError on the base class, and is overridden by ValuesBase to provide the SET/VALUES clause of UPDATE and INSERT.

method sqlalchemy.sql.expression.Delete.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")

Multiple prefixes can be specified by multiple calls to 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.Delete.returning(*cols)¶

inherited from the UpdateBase.returning() method of UpdateBase

Add a RETURNING or equivalent clause to this statement.

e.g.:

stmt = table.update().\
          where(table.c.data == 'value').\
          values(status='X').\
          returning(table.c.server_flag,
                    table.c.updated_timestamp)

for server_flag, updated_timestamp in connection.execute(stmt):
    print(server_flag, updated_timestamp)

The given collection of column expressions should be derived from the table that is the target of the INSERT, UPDATE, or DELETE. While Column objects are typical, the elements can also be expressions:

stmt = table.insert().returning(
    (table.c.first_name + " " + table.c.last_name).
    label('fullname'))

Upon compilation, a RETURNING clause, or database equivalent, will be rendered within the statement. For INSERT and UPDATE, the values are the newly inserted/updated values. For DELETE, the values are those of the rows which were deleted.

Upon execution, the values of the columns to be returned are made available via the result set and can be iterated using ResultProxy.fetchone() and similar. For DBAPIs which do not natively support returning values (i.e. cx_oracle), SQLAlchemy will approximate this behavior at the result level so that a reasonable amount of behavioral neutrality is provided.

Note that not all databases/DBAPIs support RETURNING. For those backends with no support, an exception is raised upon compilation and/or execution. For those who do support it, the functionality across backends varies greatly, including restrictions on executemany() and other statements which return multiple rows. Please read the documentation notes for the database in use in order to determine the availability of RETURNING.

See also

ValuesBase.return_defaults() - an alternative method tailored towards efficient fetching of server-side defaults and triggers for single-row INSERTs or UPDATEs.

method sqlalchemy.sql.expression.Delete.scalar(*multiparams, **params)¶: inherited from the Executable.scalar() method of Executable

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

method sqlalchemy.sql.expression.Delete.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.Delete.unique_params(*optionaldict, **kwargs)¶

inherited from the ClauseElement.unique_params() method of ClauseElement

Return a copy with bindparam() elements replaced.

Same functionality as params(), except adds unique=True to affected bind parameters so that multiple statements can be used.

method sqlalchemy.sql.expression.Delete.where(whereclause)¶: Add the given WHERE clause to a newly returned delete construct.

method sqlalchemy.sql.expression.Delete.with_hint(text, selectable=None, dialect_name='*')¶

inherited from the UpdateBase.with_hint() method of UpdateBase

Add a table hint for a single table to this INSERT/UPDATE/DELETE statement.

Note

UpdateBase.with_hint() currently applies only to Microsoft SQL Server. For MySQL INSERT/UPDATE/DELETE hints, use UpdateBase.prefix_with().

The text of the hint is rendered in the appropriate location for the database backend in use, relative to the Table that is the subject of this statement, or optionally to that of the given Table passed as the selectable argument.

The dialect_name option will limit the rendering of a particular hint to a particular backend. Such as, to add a hint that only takes effect for SQL Server:

mytable.insert().with_hint("WITH (PAGLOCK)", dialect_name="mssql")

Parameters:

text – Text of the hint.
selectable – optional Table that specifies an element of the FROM clause within an UPDATE or DELETE to be the subject of the hint - applies only to certain backends.
dialect_name – defaults to *, if specified as the name of a particular dialect, will apply these hints only when that dialect is in use.

class sqlalchemy.sql.expression.Insert(table, values=None, inline=False, bind=None, prefixes=None, returning=None, return_defaults=False, **dialect_kw)¶

Represent an INSERT construct.

The Insert object is created using the insert() function.

See also

Insert Expressions

Class signature

class sqlalchemy.sql.expression.Insert (sqlalchemy.sql.expression.ValuesBase)

method sqlalchemy.sql.expression.Insert.__init__(table, values=None, inline=False, bind=None, prefixes=None, returning=None, return_defaults=False, **dialect_kw)¶

Construct a new Insert object.

This constructor is mirrored as a public API function; see insert() for a full usage and argument description.

classmethod sqlalchemy.sql.expression.Insert.argument_for(dialect_name, argument_name, default)¶

inherited from the DialectKWArgs.argument_for() method of DialectKWArgs

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

E.g.:

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

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

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

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

Parameters:

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

New in version 0.9.4.

attribute sqlalchemy.sql.expression.Insert.bind¶: inherited from the UpdateBase.bind attribute of UpdateBase

Return a ‘bind’ linked to this UpdateBase or a Table associated with it.

method sqlalchemy.sql.expression.Insert.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.Insert.compile(default, 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.
inline – Used for INSERT statements, for a dialect which does not support inline retrieval of newly generated primary key columns, will force the expression used to create the new primary key value to be rendered inline within the INSERT statement’s VALUES clause. This typically refers to Sequence execution but may also refer to any server-side default generation function associated with a primary key Column.
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.

method sqlalchemy.sql.expression.Insert.cte(name=None, recursive=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.

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.

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

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.

The following examples include two from PostgreSQL’s documentation at http://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)

See also

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

attribute sqlalchemy.sql.expression.Insert.dialect_kwargs¶

inherited from the DialectKWArgs.dialect_kwargs attribute of DialectKWArgs

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

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

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

New in version 0.9.2.

Changed in version 0.9.4: The DialectKWArgs.dialect_kwargs collection is now writable.

See also

DialectKWArgs.dialect_options - nested dictionary form

attribute sqlalchemy.sql.expression.Insert.dialect_options¶

inherited from the DialectKWArgs.dialect_options attribute of DialectKWArgs

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

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

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

New in version 0.9.2.

See also

DialectKWArgs.dialect_kwargs - flat dictionary form

method sqlalchemy.sql.expression.Insert.execute(*multiparams, **params)¶: inherited from the Executable.execute() method of Executable

Compile and execute this Executable.

method sqlalchemy.sql.expression.Insert.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()

method sqlalchemy.sql.expression.Insert.from_select(names, select, include_defaults=True)¶

Return a new Insert construct which represents an INSERT...FROM SELECT statement.

e.g.:

sel = select([table1.c.a, table1.c.b]).where(table1.c.c > 5)
ins = table2.insert().from_select(['a', 'b'], sel)

Parameters:

names – a sequence of string column names or Column objects representing the target columns.
select – a select() construct, FromClause or other construct which resolves into a FromClause, such as an ORM Query object, etc. The order of columns returned from this FROM clause should correspond to the order of columns sent as the names parameter; while this is not checked before passing along to the database, the database would normally raise an exception if these column lists don’t correspond.
include_defaults –
if True, non-server default values and SQL expressions as specified on Column objects (as documented in Column Insert/Update Defaults) not otherwise specified in the list of names will be rendered into the INSERT and SELECT statements, so that these values are also included in the data to be inserted.

Note

A Python-side default that uses a Python callable function will only be invoked once for the whole statement, and not per row.

New in version 1.0.0: - Insert.from_select() now renders Python-side and SQL expression column defaults into the SELECT statement for columns otherwise not included in the list of column names.

Changed in version 1.0.0: an INSERT that uses FROM SELECT implies that the insert.inline flag is set to True, indicating that the statement will not attempt to fetch the “last inserted primary key” or other defaults. The statement deals with an arbitrary number of rows, so the ResultProxy.inserted_primary_key accessor does not apply.

method sqlalchemy.sql.expression.Insert.get_children(**kwargs)¶

Return immediate child elements of this ClauseElement.

This is used for visit traversal.

**kwargs 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.Insert.kwargs¶: inherited from the DialectKWArgs.kwargs attribute of DialectKWArgs

A synonym for DialectKWArgs.dialect_kwargs.

method sqlalchemy.sql.expression.Insert.params(*arg, **kw)¶

inherited from the UpdateBase.params() method of UpdateBase

Set the parameters for the statement.

This method raises NotImplementedError on the base class, and is overridden by ValuesBase to provide the SET/VALUES clause of UPDATE and INSERT.

method sqlalchemy.sql.expression.Insert.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")

Multiple prefixes can be specified by multiple calls to 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.Insert.return_defaults(*cols)¶

inherited from the ValuesBase.return_defaults() method of ValuesBase

Make use of a RETURNING clause for the purpose of fetching server-side expressions and defaults.

E.g.:

stmt = table.insert().values(data='newdata').return_defaults()

result = connection.execute(stmt)

server_created_at = result.returned_defaults['created_at']

When used against a backend that supports RETURNING, all column values generated by SQL expression or server-side-default will be added to any existing RETURNING clause, provided that UpdateBase.returning() is not used simultaneously. The column values will then be available on the result using the ResultProxy.returned_defaults accessor as a dictionary, referring to values keyed to the Column object as well as its .key.

This method differs from UpdateBase.returning() in these ways:

ValuesBase.return_defaults() is only intended for use with an INSERT or an UPDATE statement that matches exactly one row. While the RETURNING construct in the general sense supports multiple rows for a multi-row UPDATE or DELETE statement, or for special cases of INSERT that return multiple rows (e.g. INSERT from SELECT, multi-valued VALUES clause), ValuesBase.return_defaults() is intended only for an “ORM-style” single-row INSERT/UPDATE statement. The row returned by the statement is also consumed implicitly when ValuesBase.return_defaults() is used. By contrast, UpdateBase.returning() leaves the RETURNING result-set intact with a collection of any number of rows.
It is compatible with the existing logic to fetch auto-generated primary key values, also known as “implicit returning”. Backends that support RETURNING will automatically make use of RETURNING in order to fetch the value of newly generated primary keys; while the UpdateBase.returning() method circumvents this behavior, ValuesBase.return_defaults() leaves it intact.
It can be called against any backend. Backends that don’t support RETURNING will skip the usage of the feature, rather than raising an exception. The return value of ResultProxy.returned_defaults will be None

ValuesBase.return_defaults() is used by the ORM to provide an efficient implementation for the eager_defaults feature of mapper().

Parameters:: cols – optional list of column key names or Column objects. If omitted, all column expressions evaluated on the server are added to the returning list.

New in version 0.9.0.

See also

UpdateBase.returning()

ResultProxy.returned_defaults

method sqlalchemy.sql.expression.Insert.returning(*cols)¶

inherited from the UpdateBase.returning() method of UpdateBase

Add a RETURNING or equivalent clause to this statement.

e.g.:

stmt = table.update().\
          where(table.c.data == 'value').\
          values(status='X').\
          returning(table.c.server_flag,
                    table.c.updated_timestamp)

for server_flag, updated_timestamp in connection.execute(stmt):
    print(server_flag, updated_timestamp)

The given collection of column expressions should be derived from the table that is the target of the INSERT, UPDATE, or DELETE. While Column objects are typical, the elements can also be expressions:

stmt = table.insert().returning(
    (table.c.first_name + " " + table.c.last_name).
    label('fullname'))

Upon compilation, a RETURNING clause, or database equivalent, will be rendered within the statement. For INSERT and UPDATE, the values are the newly inserted/updated values. For DELETE, the values are those of the rows which were deleted.

Upon execution, the values of the columns to be returned are made available via the result set and can be iterated using ResultProxy.fetchone() and similar. For DBAPIs which do not natively support returning values (i.e. cx_oracle), SQLAlchemy will approximate this behavior at the result level so that a reasonable amount of behavioral neutrality is provided.

Note that not all databases/DBAPIs support RETURNING. For those backends with no support, an exception is raised upon compilation and/or execution. For those who do support it, the functionality across backends varies greatly, including restrictions on executemany() and other statements which return multiple rows. Please read the documentation notes for the database in use in order to determine the availability of RETURNING.

See also

ValuesBase.return_defaults() - an alternative method tailored towards efficient fetching of server-side defaults and triggers for single-row INSERTs or UPDATEs.

method sqlalchemy.sql.expression.Insert.scalar(*multiparams, **params)¶: inherited from the Executable.scalar() method of Executable

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

method sqlalchemy.sql.expression.Insert.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.Insert.unique_params(*optionaldict, **kwargs)¶

inherited from the ClauseElement.unique_params() method of ClauseElement

Return a copy with bindparam() elements replaced.

Same functionality as params(), except adds unique=True to affected bind parameters so that multiple statements can be used.

method sqlalchemy.sql.expression.Insert.values(*args, **kwargs)¶

inherited from the ValuesBase.values() method of ValuesBase

specify a fixed VALUES clause for an INSERT statement, or the SET clause for an UPDATE.

Note that the Insert and Update constructs support per-execution time formatting of the VALUES and/or SET clauses, based on the arguments passed to Connection.execute(). However, the ValuesBase.values() method can be used to “fix” a particular set of parameters into the statement.

Multiple calls to ValuesBase.values() will produce a new construct, each one with the parameter list modified to include the new parameters sent. In the typical case of a single dictionary of parameters, the newly passed keys will replace the same keys in the previous construct. In the case of a list-based “multiple values” construct, each new list of values is extended onto the existing list of values.

Parameters:

**kwargs –
key value pairs representing the string key of a Column mapped to the value to be rendered into the VALUES or SET clause:
```
users.insert().values(name="some name")

users.update().where(users.c.id==5).values(name="some name")
```
*args –
As an alternative to passing key/value parameters, a dictionary, tuple, or list of dictionaries or tuples can be passed as a single positional argument in order to form the VALUES or SET clause of the statement. The forms that are accepted vary based on whether this is an Insert or an Update construct.

For either an Insert or Update construct, a single dictionary can be passed, which works the same as that of the kwargs form:
```
users.insert().values({"name": "some name"})

users.update().values({"name": "some new name"})
```
Also for either form but more typically for the Insert construct, a tuple that contains an entry for every column in the table is also accepted:
```
users.insert().values((5, "some name"))
```
The Insert construct also supports being passed a list of dictionaries or full-table-tuples, which on the server will render the less common SQL syntax of “multiple values” - this syntax is supported on backends such as SQLite, PostgreSQL, MySQL, but not necessarily others:
```
users.insert().values([
                    {"name": "some name"},
                    {"name": "some other name"},
                    {"name": "yet another name"},
                ])
```
The above form would render a multiple VALUES statement similar to:
```
INSERT INTO users (name) VALUES
                (:name_1),
                (:name_2),
                (:name_3)
```
It is essential to note that passing multiple values is NOT the same as using traditional executemany() form. The above syntax is a special syntax not typically used. To emit an INSERT statement against multiple rows, the normal method is to pass a multiple values list to the Connection.execute() method, which is supported by all database backends and is generally more efficient for a very large number of parameters.

See also

Executing Multiple Statements - an introduction to the traditional Core method of multiple parameter set invocation for INSERTs and other statements.

Changed in version 1.0.0: an INSERT that uses a multiple-VALUES clause, even a list of length one, implies that the Insert.inline flag is set to True, indicating that the statement will not attempt to fetch the “last inserted primary key” or other defaults. The statement deals with an arbitrary number of rows, so the ResultProxy.inserted_primary_key accessor does not apply.

Changed in version 1.0.0: A multiple-VALUES INSERT now supports columns with Python side default values and callables in the same way as that of an “executemany” style of invocation; the callable is invoked for each row. See Python-side defaults invoked for each row individually when using a multivalued insert for other details.

The Update construct supports a special form which is a list of 2-tuples, which when provided must be passed in conjunction with the update.preserve_parameter_order parameter. This form causes the UPDATE statement to render the SET clauses using the order of parameters given to Update.values(), rather than the ordering of columns given in the Table.

New in version 1.0.10: - added support for parameter-ordered UPDATE statements via the update.preserve_parameter_order flag.

See also

Parameter-Ordered Updates - full example of the update.preserve_parameter_order flag

See also

Inserts, Updates and Deletes - SQL Expression Language Tutorial

insert() - produce an INSERT statement

update() - produce an UPDATE statement

method sqlalchemy.sql.expression.Insert.with_hint(text, selectable=None, dialect_name='*')¶

inherited from the UpdateBase.with_hint() method of UpdateBase

Add a table hint for a single table to this INSERT/UPDATE/DELETE statement.

Note

UpdateBase.with_hint() currently applies only to Microsoft SQL Server. For MySQL INSERT/UPDATE/DELETE hints, use UpdateBase.prefix_with().

The text of the hint is rendered in the appropriate location for the database backend in use, relative to the Table that is the subject of this statement, or optionally to that of the given Table passed as the selectable argument.

The dialect_name option will limit the rendering of a particular hint to a particular backend. Such as, to add a hint that only takes effect for SQL Server:

mytable.insert().with_hint("WITH (PAGLOCK)", dialect_name="mssql")

Parameters:

text – Text of the hint.
selectable – optional Table that specifies an element of the FROM clause within an UPDATE or DELETE to be the subject of the hint - applies only to certain backends.
dialect_name – defaults to *, if specified as the name of a particular dialect, will apply these hints only when that dialect is in use.

class sqlalchemy.sql.expression.Update(table, whereclause=None, values=None, inline=False, bind=None, prefixes=None, returning=None, return_defaults=False, preserve_parameter_order=False, **dialect_kw)¶

Represent an Update construct.

The Update object is created using the update() function.

Class signature

class sqlalchemy.sql.expression.Update (sqlalchemy.sql.expression.ValuesBase)

method sqlalchemy.sql.expression.Update.__init__(table, whereclause=None, values=None, inline=False, bind=None, prefixes=None, returning=None, return_defaults=False, preserve_parameter_order=False, **dialect_kw)¶

Construct a new Update object.

This constructor is mirrored as a public API function; see update() for a full usage and argument description.

classmethod sqlalchemy.sql.expression.Update.argument_for(dialect_name, argument_name, default)¶

inherited from the DialectKWArgs.argument_for() method of DialectKWArgs

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

E.g.:

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

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

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

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

Parameters:

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

New in version 0.9.4.

attribute sqlalchemy.sql.expression.Update.bind¶: inherited from the UpdateBase.bind attribute of UpdateBase

Return a ‘bind’ linked to this UpdateBase or a Table associated with it.

method sqlalchemy.sql.expression.Update.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.Update.compile(default, 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.
inline – Used for INSERT statements, for a dialect which does not support inline retrieval of newly generated primary key columns, will force the expression used to create the new primary key value to be rendered inline within the INSERT statement’s VALUES clause. This typically refers to Sequence execution but may also refer to any server-side default generation function associated with a primary key Column.
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.

method sqlalchemy.sql.expression.Update.cte(name=None, recursive=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.

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.

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

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.

The following examples include two from PostgreSQL’s documentation at http://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)

See also

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

attribute sqlalchemy.sql.expression.Update.dialect_kwargs¶

inherited from the DialectKWArgs.dialect_kwargs attribute of DialectKWArgs

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

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

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

New in version 0.9.2.

Changed in version 0.9.4: The DialectKWArgs.dialect_kwargs collection is now writable.

See also

DialectKWArgs.dialect_options - nested dictionary form

attribute sqlalchemy.sql.expression.Update.dialect_options¶

inherited from the DialectKWArgs.dialect_options attribute of DialectKWArgs

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

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

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

New in version 0.9.2.

See also

DialectKWArgs.dialect_kwargs - flat dictionary form

method sqlalchemy.sql.expression.Update.execute(*multiparams, **params)¶: inherited from the Executable.execute() method of Executable

Compile and execute this Executable.

method sqlalchemy.sql.expression.Update.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()

method sqlalchemy.sql.expression.Update.get_children(**kwargs)¶

Return immediate child elements of this ClauseElement.

This is used for visit traversal.

**kwargs 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.Update.kwargs¶: inherited from the DialectKWArgs.kwargs attribute of DialectKWArgs

A synonym for DialectKWArgs.dialect_kwargs.

method sqlalchemy.sql.expression.Update.params(*arg, **kw)¶

inherited from the UpdateBase.params() method of UpdateBase

Set the parameters for the statement.

This method raises NotImplementedError on the base class, and is overridden by ValuesBase to provide the SET/VALUES clause of UPDATE and INSERT.

method sqlalchemy.sql.expression.Update.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")

Multiple prefixes can be specified by multiple calls to 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.Update.return_defaults(*cols)¶

inherited from the ValuesBase.return_defaults() method of ValuesBase

Make use of a RETURNING clause for the purpose of fetching server-side expressions and defaults.

E.g.:

stmt = table.insert().values(data='newdata').return_defaults()

result = connection.execute(stmt)

server_created_at = result.returned_defaults['created_at']

When used against a backend that supports RETURNING, all column values generated by SQL expression or server-side-default will be added to any existing RETURNING clause, provided that UpdateBase.returning() is not used simultaneously. The column values will then be available on the result using the ResultProxy.returned_defaults accessor as a dictionary, referring to values keyed to the Column object as well as its .key.

This method differs from UpdateBase.returning() in these ways:

ValuesBase.return_defaults() is only intended for use with an INSERT or an UPDATE statement that matches exactly one row. While the RETURNING construct in the general sense supports multiple rows for a multi-row UPDATE or DELETE statement, or for special cases of INSERT that return multiple rows (e.g. INSERT from SELECT, multi-valued VALUES clause), ValuesBase.return_defaults() is intended only for an “ORM-style” single-row INSERT/UPDATE statement. The row returned by the statement is also consumed implicitly when ValuesBase.return_defaults() is used. By contrast, UpdateBase.returning() leaves the RETURNING result-set intact with a collection of any number of rows.
It is compatible with the existing logic to fetch auto-generated primary key values, also known as “implicit returning”. Backends that support RETURNING will automatically make use of RETURNING in order to fetch the value of newly generated primary keys; while the UpdateBase.returning() method circumvents this behavior, ValuesBase.return_defaults() leaves it intact.
It can be called against any backend. Backends that don’t support RETURNING will skip the usage of the feature, rather than raising an exception. The return value of ResultProxy.returned_defaults will be None

ValuesBase.return_defaults() is used by the ORM to provide an efficient implementation for the eager_defaults feature of mapper().

Parameters:: cols – optional list of column key names or Column objects. If omitted, all column expressions evaluated on the server are added to the returning list.

New in version 0.9.0.

See also

UpdateBase.returning()

ResultProxy.returned_defaults

method sqlalchemy.sql.expression.Update.returning(*cols)¶

inherited from the UpdateBase.returning() method of UpdateBase

Add a RETURNING or equivalent clause to this statement.

e.g.:

stmt = table.update().\
          where(table.c.data == 'value').\
          values(status='X').\
          returning(table.c.server_flag,
                    table.c.updated_timestamp)

for server_flag, updated_timestamp in connection.execute(stmt):
    print(server_flag, updated_timestamp)

The given collection of column expressions should be derived from the table that is the target of the INSERT, UPDATE, or DELETE. While Column objects are typical, the elements can also be expressions:

stmt = table.insert().returning(
    (table.c.first_name + " " + table.c.last_name).
    label('fullname'))

Upon compilation, a RETURNING clause, or database equivalent, will be rendered within the statement. For INSERT and UPDATE, the values are the newly inserted/updated values. For DELETE, the values are those of the rows which were deleted.

Upon execution, the values of the columns to be returned are made available via the result set and can be iterated using ResultProxy.fetchone() and similar. For DBAPIs which do not natively support returning values (i.e. cx_oracle), SQLAlchemy will approximate this behavior at the result level so that a reasonable amount of behavioral neutrality is provided.

Note that not all databases/DBAPIs support RETURNING. For those backends with no support, an exception is raised upon compilation and/or execution. For those who do support it, the functionality across backends varies greatly, including restrictions on executemany() and other statements which return multiple rows. Please read the documentation notes for the database in use in order to determine the availability of RETURNING.

See also

ValuesBase.return_defaults() - an alternative method tailored towards efficient fetching of server-side defaults and triggers for single-row INSERTs or UPDATEs.

method sqlalchemy.sql.expression.Update.scalar(*multiparams, **params)¶: inherited from the Executable.scalar() method of Executable

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

method sqlalchemy.sql.expression.Update.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.Update.unique_params(*optionaldict, **kwargs)¶

inherited from the ClauseElement.unique_params() method of ClauseElement

Return a copy with bindparam() elements replaced.

Same functionality as params(), except adds unique=True to affected bind parameters so that multiple statements can be used.

method sqlalchemy.sql.expression.Update.values(*args, **kwargs)¶

inherited from the ValuesBase.values() method of ValuesBase

specify a fixed VALUES clause for an INSERT statement, or the SET clause for an UPDATE.

Note that the Insert and Update constructs support per-execution time formatting of the VALUES and/or SET clauses, based on the arguments passed to Connection.execute(). However, the ValuesBase.values() method can be used to “fix” a particular set of parameters into the statement.

Multiple calls to ValuesBase.values() will produce a new construct, each one with the parameter list modified to include the new parameters sent. In the typical case of a single dictionary of parameters, the newly passed keys will replace the same keys in the previous construct. In the case of a list-based “multiple values” construct, each new list of values is extended onto the existing list of values.

Parameters:

**kwargs –
key value pairs representing the string key of a Column mapped to the value to be rendered into the VALUES or SET clause:
```
users.insert().values(name="some name")

users.update().where(users.c.id==5).values(name="some name")
```
*args –
As an alternative to passing key/value parameters, a dictionary, tuple, or list of dictionaries or tuples can be passed as a single positional argument in order to form the VALUES or SET clause of the statement. The forms that are accepted vary based on whether this is an Insert or an Update construct.

For either an Insert or Update construct, a single dictionary can be passed, which works the same as that of the kwargs form:
```
users.insert().values({"name": "some name"})

users.update().values({"name": "some new name"})
```
Also for either form but more typically for the Insert construct, a tuple that contains an entry for every column in the table is also accepted:
```
users.insert().values((5, "some name"))
```
The Insert construct also supports being passed a list of dictionaries or full-table-tuples, which on the server will render the less common SQL syntax of “multiple values” - this syntax is supported on backends such as SQLite, PostgreSQL, MySQL, but not necessarily others:
```
users.insert().values([
                    {"name": "some name"},
                    {"name": "some other name"},
                    {"name": "yet another name"},
                ])
```
The above form would render a multiple VALUES statement similar to:
```
INSERT INTO users (name) VALUES
                (:name_1),
                (:name_2),
                (:name_3)
```
It is essential to note that passing multiple values is NOT the same as using traditional executemany() form. The above syntax is a special syntax not typically used. To emit an INSERT statement against multiple rows, the normal method is to pass a multiple values list to the Connection.execute() method, which is supported by all database backends and is generally more efficient for a very large number of parameters.

See also

Executing Multiple Statements - an introduction to the traditional Core method of multiple parameter set invocation for INSERTs and other statements.

Changed in version 1.0.0: an INSERT that uses a multiple-VALUES clause, even a list of length one, implies that the Insert.inline flag is set to True, indicating that the statement will not attempt to fetch the “last inserted primary key” or other defaults. The statement deals with an arbitrary number of rows, so the ResultProxy.inserted_primary_key accessor does not apply.

Changed in version 1.0.0: A multiple-VALUES INSERT now supports columns with Python side default values and callables in the same way as that of an “executemany” style of invocation; the callable is invoked for each row. See Python-side defaults invoked for each row individually when using a multivalued insert for other details.

The Update construct supports a special form which is a list of 2-tuples, which when provided must be passed in conjunction with the update.preserve_parameter_order parameter. This form causes the UPDATE statement to render the SET clauses using the order of parameters given to Update.values(), rather than the ordering of columns given in the Table.

New in version 1.0.10: - added support for parameter-ordered UPDATE statements via the update.preserve_parameter_order flag.

See also

Parameter-Ordered Updates - full example of the update.preserve_parameter_order flag

See also

Inserts, Updates and Deletes - SQL Expression Language Tutorial

insert() - produce an INSERT statement

update() - produce an UPDATE statement

method sqlalchemy.sql.expression.Update.where(whereclause)¶: return a new update() construct with the given expression added to its WHERE clause, joined to the existing clause via AND, if any.

method sqlalchemy.sql.expression.Update.with_hint(text, selectable=None, dialect_name='*')¶

inherited from the UpdateBase.with_hint() method of UpdateBase

Add a table hint for a single table to this INSERT/UPDATE/DELETE statement.

Note

UpdateBase.with_hint() currently applies only to Microsoft SQL Server. For MySQL INSERT/UPDATE/DELETE hints, use UpdateBase.prefix_with().

The text of the hint is rendered in the appropriate location for the database backend in use, relative to the Table that is the subject of this statement, or optionally to that of the given Table passed as the selectable argument.

The dialect_name option will limit the rendering of a particular hint to a particular backend. Such as, to add a hint that only takes effect for SQL Server:

mytable.insert().with_hint("WITH (PAGLOCK)", dialect_name="mssql")

Parameters:

text – Text of the hint.
selectable – optional Table that specifies an element of the FROM clause within an UPDATE or DELETE to be the subject of the hint - applies only to certain backends.
dialect_name – defaults to *, if specified as the name of a particular dialect, will apply these hints only when that dialect is in use.

class sqlalchemy.sql.expression.UpdateBase¶

Form the base for INSERT, UPDATE, and DELETE statements.

Members

argument_for(), bind, compare(), compile(), cte(), dialect_kwargs, dialect_options, execute(), execution_options(), get_children(), kwargs, params(), prefix_with(), returning(), scalar(), self_group(), unique_params(), with_hint()

Class signature

class sqlalchemy.sql.expression.UpdateBase (sqlalchemy.sql.expression.HasCTE, sqlalchemy.sql.base.DialectKWArgs, sqlalchemy.sql.expression.HasPrefixes, sqlalchemy.sql.expression.Executable, sqlalchemy.sql.expression.ClauseElement)

classmethod sqlalchemy.sql.expression.UpdateBase.argument_for(dialect_name, argument_name, default)¶

inherited from the DialectKWArgs.argument_for() method of DialectKWArgs

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

E.g.:

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

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

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

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

Parameters:

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

New in version 0.9.4.

attribute sqlalchemy.sql.expression.UpdateBase.bind¶: Return a ‘bind’ linked to this UpdateBase or a Table associated with it.

method sqlalchemy.sql.expression.UpdateBase.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.UpdateBase.compile(default, 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.
inline – Used for INSERT statements, for a dialect which does not support inline retrieval of newly generated primary key columns, will force the expression used to create the new primary key value to be rendered inline within the INSERT statement’s VALUES clause. This typically refers to Sequence execution but may also refer to any server-side default generation function associated with a primary key Column.
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.

method sqlalchemy.sql.expression.UpdateBase.cte(name=None, recursive=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.

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.

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

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.

The following examples include two from PostgreSQL’s documentation at http://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)

See also

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

attribute sqlalchemy.sql.expression.UpdateBase.dialect_kwargs¶

inherited from the DialectKWArgs.dialect_kwargs attribute of DialectKWArgs

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

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

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

New in version 0.9.2.

Changed in version 0.9.4: The DialectKWArgs.dialect_kwargs collection is now writable.

See also

DialectKWArgs.dialect_options - nested dictionary form

attribute sqlalchemy.sql.expression.UpdateBase.dialect_options¶

inherited from the DialectKWArgs.dialect_options attribute of DialectKWArgs

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

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

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

New in version 0.9.2.

See also

DialectKWArgs.dialect_kwargs - flat dictionary form

method sqlalchemy.sql.expression.UpdateBase.execute(*multiparams, **params)¶: inherited from the Executable.execute() method of Executable

Compile and execute this Executable.

method sqlalchemy.sql.expression.UpdateBase.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()

method sqlalchemy.sql.expression.UpdateBase.get_children(**kwargs)¶

inherited from the ClauseElement.get_children() method of ClauseElement

Return immediate child elements of this ClauseElement.

This is used for visit traversal.

**kwargs 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.UpdateBase.kwargs¶: inherited from the DialectKWArgs.kwargs attribute of DialectKWArgs

A synonym for DialectKWArgs.dialect_kwargs.

method sqlalchemy.sql.expression.UpdateBase.params(*arg, **kw)¶

Set the parameters for the statement.

This method raises NotImplementedError on the base class, and is overridden by ValuesBase to provide the SET/VALUES clause of UPDATE and INSERT.

method sqlalchemy.sql.expression.UpdateBase.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")

Multiple prefixes can be specified by multiple calls to 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.UpdateBase.returning(*cols)¶

Add a RETURNING or equivalent clause to this statement.

e.g.:

stmt = table.update().\
          where(table.c.data == 'value').\
          values(status='X').\
          returning(table.c.server_flag,
                    table.c.updated_timestamp)

for server_flag, updated_timestamp in connection.execute(stmt):
    print(server_flag, updated_timestamp)

The given collection of column expressions should be derived from the table that is the target of the INSERT, UPDATE, or DELETE. While Column objects are typical, the elements can also be expressions:

stmt = table.insert().returning(
    (table.c.first_name + " " + table.c.last_name).
    label('fullname'))

Upon compilation, a RETURNING clause, or database equivalent, will be rendered within the statement. For INSERT and UPDATE, the values are the newly inserted/updated values. For DELETE, the values are those of the rows which were deleted.

Upon execution, the values of the columns to be returned are made available via the result set and can be iterated using ResultProxy.fetchone() and similar. For DBAPIs which do not natively support returning values (i.e. cx_oracle), SQLAlchemy will approximate this behavior at the result level so that a reasonable amount of behavioral neutrality is provided.

Note that not all databases/DBAPIs support RETURNING. For those backends with no support, an exception is raised upon compilation and/or execution. For those who do support it, the functionality across backends varies greatly, including restrictions on executemany() and other statements which return multiple rows. Please read the documentation notes for the database in use in order to determine the availability of RETURNING.

See also

ValuesBase.return_defaults() - an alternative method tailored towards efficient fetching of server-side defaults and triggers for single-row INSERTs or UPDATEs.

method sqlalchemy.sql.expression.UpdateBase.scalar(*multiparams, **params)¶: inherited from the Executable.scalar() method of Executable

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

method sqlalchemy.sql.expression.UpdateBase.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.UpdateBase.unique_params(*optionaldict, **kwargs)¶

inherited from the ClauseElement.unique_params() method of ClauseElement

Return a copy with bindparam() elements replaced.

Same functionality as params(), except adds unique=True to affected bind parameters so that multiple statements can be used.

method sqlalchemy.sql.expression.UpdateBase.with_hint(text, selectable=None, dialect_name='*')¶

Add a table hint for a single table to this INSERT/UPDATE/DELETE statement.

Note

UpdateBase.with_hint() currently applies only to Microsoft SQL Server. For MySQL INSERT/UPDATE/DELETE hints, use UpdateBase.prefix_with().

The text of the hint is rendered in the appropriate location for the database backend in use, relative to the Table that is the subject of this statement, or optionally to that of the given Table passed as the selectable argument.

The dialect_name option will limit the rendering of a particular hint to a particular backend. Such as, to add a hint that only takes effect for SQL Server:

mytable.insert().with_hint("WITH (PAGLOCK)", dialect_name="mssql")

Parameters:

text – Text of the hint.
selectable – optional Table that specifies an element of the FROM clause within an UPDATE or DELETE to be the subject of the hint - applies only to certain backends.
dialect_name – defaults to *, if specified as the name of a particular dialect, will apply these hints only when that dialect is in use.

class sqlalchemy.sql.expression.ValuesBase(table, values, prefixes)¶

Supplies support for ValuesBase.values() to INSERT and UPDATE constructs.

Members

return_defaults(), values()

Class signature

class sqlalchemy.sql.expression.ValuesBase (sqlalchemy.sql.expression.UpdateBase)

method sqlalchemy.sql.expression.ValuesBase.return_defaults(*cols)¶

Make use of a RETURNING clause for the purpose of fetching server-side expressions and defaults.

E.g.:

stmt = table.insert().values(data='newdata').return_defaults()

result = connection.execute(stmt)

server_created_at = result.returned_defaults['created_at']

When used against a backend that supports RETURNING, all column values generated by SQL expression or server-side-default will be added to any existing RETURNING clause, provided that UpdateBase.returning() is not used simultaneously. The column values will then be available on the result using the ResultProxy.returned_defaults accessor as a dictionary, referring to values keyed to the Column object as well as its .key.

This method differs from UpdateBase.returning() in these ways:

ValuesBase.return_defaults() is only intended for use with an INSERT or an UPDATE statement that matches exactly one row. While the RETURNING construct in the general sense supports multiple rows for a multi-row UPDATE or DELETE statement, or for special cases of INSERT that return multiple rows (e.g. INSERT from SELECT, multi-valued VALUES clause), ValuesBase.return_defaults() is intended only for an “ORM-style” single-row INSERT/UPDATE statement. The row returned by the statement is also consumed implicitly when ValuesBase.return_defaults() is used. By contrast, UpdateBase.returning() leaves the RETURNING result-set intact with a collection of any number of rows.
It is compatible with the existing logic to fetch auto-generated primary key values, also known as “implicit returning”. Backends that support RETURNING will automatically make use of RETURNING in order to fetch the value of newly generated primary keys; while the UpdateBase.returning() method circumvents this behavior, ValuesBase.return_defaults() leaves it intact.
It can be called against any backend. Backends that don’t support RETURNING will skip the usage of the feature, rather than raising an exception. The return value of ResultProxy.returned_defaults will be None

ValuesBase.return_defaults() is used by the ORM to provide an efficient implementation for the eager_defaults feature of mapper().

Parameters:: cols – optional list of column key names or Column objects. If omitted, all column expressions evaluated on the server are added to the returning list.

New in version 0.9.0.

See also

UpdateBase.returning()

ResultProxy.returned_defaults

method sqlalchemy.sql.expression.ValuesBase.values(*args, **kwargs)¶

specify a fixed VALUES clause for an INSERT statement, or the SET clause for an UPDATE.

Note that the Insert and Update constructs support per-execution time formatting of the VALUES and/or SET clauses, based on the arguments passed to Connection.execute(). However, the ValuesBase.values() method can be used to “fix” a particular set of parameters into the statement.

Multiple calls to ValuesBase.values() will produce a new construct, each one with the parameter list modified to include the new parameters sent. In the typical case of a single dictionary of parameters, the newly passed keys will replace the same keys in the previous construct. In the case of a list-based “multiple values” construct, each new list of values is extended onto the existing list of values.

Parameters:

**kwargs –
key value pairs representing the string key of a Column mapped to the value to be rendered into the VALUES or SET clause:
```
users.insert().values(name="some name")

users.update().where(users.c.id==5).values(name="some name")
```
*args –
As an alternative to passing key/value parameters, a dictionary, tuple, or list of dictionaries or tuples can be passed as a single positional argument in order to form the VALUES or SET clause of the statement. The forms that are accepted vary based on whether this is an Insert or an Update construct.

For either an Insert or Update construct, a single dictionary can be passed, which works the same as that of the kwargs form:
```
users.insert().values({"name": "some name"})

users.update().values({"name": "some new name"})
```
Also for either form but more typically for the Insert construct, a tuple that contains an entry for every column in the table is also accepted:
```
users.insert().values((5, "some name"))
```
The Insert construct also supports being passed a list of dictionaries or full-table-tuples, which on the server will render the less common SQL syntax of “multiple values” - this syntax is supported on backends such as SQLite, PostgreSQL, MySQL, but not necessarily others:
```
users.insert().values([
                    {"name": "some name"},
                    {"name": "some other name"},
                    {"name": "yet another name"},
                ])
```
The above form would render a multiple VALUES statement similar to:
```
INSERT INTO users (name) VALUES
                (:name_1),
                (:name_2),
                (:name_3)
```
It is essential to note that passing multiple values is NOT the same as using traditional executemany() form. The above syntax is a special syntax not typically used. To emit an INSERT statement against multiple rows, the normal method is to pass a multiple values list to the Connection.execute() method, which is supported by all database backends and is generally more efficient for a very large number of parameters.

See also

Executing Multiple Statements - an introduction to the traditional Core method of multiple parameter set invocation for INSERTs and other statements.

Changed in version 1.0.0: an INSERT that uses a multiple-VALUES clause, even a list of length one, implies that the Insert.inline flag is set to True, indicating that the statement will not attempt to fetch the “last inserted primary key” or other defaults. The statement deals with an arbitrary number of rows, so the ResultProxy.inserted_primary_key accessor does not apply.

Changed in version 1.0.0: A multiple-VALUES INSERT now supports columns with Python side default values and callables in the same way as that of an “executemany” style of invocation; the callable is invoked for each row. See Python-side defaults invoked for each row individually when using a multivalued insert for other details.

The Update construct supports a special form which is a list of 2-tuples, which when provided must be passed in conjunction with the update.preserve_parameter_order parameter. This form causes the UPDATE statement to render the SET clauses using the order of parameters given to Update.values(), rather than the ordering of columns given in the Table.

New in version 1.0.10: - added support for parameter-ordered UPDATE statements via the update.preserve_parameter_order flag.

See also

Parameter-Ordered Updates - full example of the update.preserve_parameter_order flag

See also

Inserts, Updates and Deletes - SQL Expression Language Tutorial

insert() - produce an INSERT statement

update() - produce an UPDATE statement

SQLAlchemy 1.2 Documentation

SQLAlchemy 1.2 Documentation

SQLAlchemy Core

Insert, Updates, Deletes¶