SQLAlchemy 0.9 Documentation
Column Insert/Update Defaults¶
SQLAlchemy provides a very rich featureset regarding column level events which take place during INSERT and UPDATE statements. Options include:
- Scalar values used as defaults during INSERT and UPDATE operations
- Python functions which execute upon INSERT and UPDATE operations
- SQL expressions which are embedded in INSERT statements (or in some cases execute beforehand)
- SQL expressions which are embedded in UPDATE statements
- Server side default values used during INSERT
- Markers for server-side triggers used during UPDATE
The general rule for all insert/update defaults is that they only take effect
if no value for a particular column is passed as an
otherwise, the given value is used.
The simplest kind of default is a scalar value used as the default value of a column:
Table("mytable", meta, Column("somecolumn", Integer, default=12) )
Above, the value “12” will be bound as the column value during an INSERT if no other value is supplied.
A scalar value may also be associated with an UPDATE statement, though this is not very common (as UPDATE statements are usually looking for dynamic defaults):
Table("mytable", meta, Column("somecolumn", Integer, onupdate=25) )
onupdate keyword arguments also accept Python
functions. These functions are invoked at the time of insert or update if no
other value for that column is supplied, and the value returned is used for
the column’s value. Below illustrates a crude “sequence” that assigns an
incrementing counter to a primary key column:
# a function which counts upwards i = 0 def mydefault(): global i i += 1 return i t = Table("mytable", meta, Column('id', Integer, primary_key=True, default=mydefault), )
It should be noted that for real “incrementing sequence” behavior, the
built-in capabilities of the database should normally be used, which may
include sequence objects or other autoincrementing capabilities. For primary
key columns, SQLAlchemy will in most cases use these capabilities
automatically. See the API documentation for
Column including the
autoincrement flag, as
well as the section on
Sequence later in this
chapter for background on standard primary key generation techniques.
To illustrate onupdate, we assign the Python
import datetime t = Table("mytable", meta, Column('id', Integer, primary_key=True), # define 'last_updated' to be populated with datetime.now() Column('last_updated', DateTime, onupdate=datetime.datetime.now), )
When an update statement executes and no value is passed for
datetime.datetime.now() Python function is executed and its return
value used as the value for
last_updated. Notice that we provide
as the function itself without calling it (i.e. there are no parenthesis
following) - SQLAlchemy will execute the function at the time the statement
Context-Sensitive Default Functions¶
The Python functions used by
onupdate may also make use of
the current statement’s context in order to determine a value. The context
of a statement is an internal SQLAlchemy object which contains all information
about the statement being executed, including its source expression, the
parameters associated with it and the cursor. The typical use case for this
context with regards to default generation is to have access to the other
values being inserted or updated on the row. To access the context, provide a
function that accepts a single
def mydefault(context): return context.current_parameters['counter'] + 12 t = Table('mytable', meta, Column('counter', Integer), Column('counter_plus_twelve', Integer, default=mydefault, onupdate=mydefault) )
Above we illustrate a default function which will execute for all INSERT and
UPDATE statements where a value for
counter_plus_twelve was otherwise not
provided, and the value will be that of whatever value is present in the
execution for the
counter column, plus the number 12.
While the context object passed to the default function has many attributes,
current_parameters member is a special member provided only during the
execution of a default function for the purposes of deriving defaults from its
existing values. For a single statement that is executing many sets of bind
parameters, the user-defined function is called for each set of parameters,
current_parameters will be provided with each individual parameter set
for each execution.
The “default” and “onupdate” keywords may also be passed SQL expressions, including select statements or direct function calls:
t = Table("mytable", meta, Column('id', Integer, primary_key=True), # define 'create_date' to default to now() Column('create_date', DateTime, default=func.now()), # define 'key' to pull its default from the 'keyvalues' table Column('key', String(20), default=keyvalues.select(keyvalues.c.type='type1', limit=1)), # define 'last_modified' to use the current_timestamp SQL function on update Column('last_modified', DateTime, onupdate=func.utc_timestamp()) )
create_date column will be populated with the result of the
now() SQL function (which, depending on backend, compiles into
CURRENT_TIMESTAMP in most cases) during an INSERT statement, and the
key column with the result of a SELECT subquery from another table. The
last_modified column will be populated with the value of
UTC_TIMESTAMP(), a function specific to MySQL, when an UPDATE statement is
emitted for this table.
Note that when using
func functions, unlike when using Python datetime
functions we do call the function, i.e. with parenthesis “()” - this is
because what we want in this case is the return value of the function, which
is the SQL expression construct that will be rendered into the INSERT or
The above SQL functions are usually executed “inline” with the INSERT or UPDATE statement being executed, meaning, a single statement is executed which embeds the given expressions or subqueries within the VALUES or SET clause of the statement. Although in some cases, the function is “pre-executed” in a SELECT statement of its own beforehand. This happens when all of the following is true:
- the column is a primary key column
- the database dialect does not support a usable
cursor.lastrowidaccessor (or equivalent); this currently includes PostgreSQL, Oracle, and Firebird, as well as some MySQL dialects.
- the dialect does not support the “RETURNING” clause or similar, or the
implicit_returningflag is set to
Falsefor the dialect. Dialects which support RETURNING currently include Postgresql, Oracle, Firebird, and MS-SQL.
- the statement is a single execution, i.e. only supplies one set of parameters and doesn’t use “executemany” behavior
inline=Trueflag is not set on the
Update()construct, and the statement has not defined an explicit returning() clause.
Whether or not the default generation clause “pre-executes” is not something that normally needs to be considered, unless it is being addressed for performance reasons.
When the statement is executed with a single set of parameters (that is, it is
not an “executemany” style execution), the returned
ResultProxy will contain a collection
result.postfetch_cols() which contains a list of all
Column objects which had an inline-executed
default. Similarly, all parameters which were bound to the statement,
including all Python and SQL expressions which were pre-executed, are present
last_updated_params() collections on
collection contains a list of primary key values for the row inserted (a list
so that single-column and composite-column primary keys are represented in the
Server Side Defaults¶
A variant on the SQL expression default is the
server_default, which gets
placed in the CREATE TABLE statement during a
t = Table('test', meta, Column('abc', String(20), server_default='abc'), Column('created_at', DateTime, server_default=text("sysdate")) )
A create call for the above table will produce:
CREATE TABLE test ( abc varchar(20) default 'abc', created_at datetime default sysdate )
The behavior of
server_default is similar to that of a regular SQL
default; if it’s placed on a primary key column for a database which doesn’t
have a way to “postfetch” the ID, and the statement is not “inlined”, the SQL
expression is pre-executed; otherwise, SQLAlchemy lets the default fire off on
the database side normally.
Columns with values set by a database trigger or other external process may be
called out using
FetchedValue as a marker:
t = Table('test', meta, Column('abc', String(20), server_default=FetchedValue()), Column('def', String(20), server_onupdate=FetchedValue()) )
Changed in version 0.8.0b2,0.7.10: The
for_update argument on
FetchedValue is set automatically
when specified as the
server_onupdate argument. If using an older version,
specify the onupdate above as
These markers do not emit a “default” clause when the table is created,
however they do set the same internal flags as a static
clause, providing hints to higher-level tools that a “post-fetch” of these
rows should be performed after an insert or update.
It’s generally not appropriate to use
conjunction with a primary key column, particularly when using the
ORM or any other scenario where the
attribute is required. This is becaue the “post-fetch” operation requires
that the primary key value already be available, so that the
row can be selected on its primary key.
For a server-generated primary key value, all databases provide special
accessors or other techniques in order to acquire the “last inserted
primary key” column of a table. These mechanisms aren’t affected by the presence
FetchedValue. For special situations where triggers are
used to generate primary key values, and the database in use does not
RETURNING clause, it may be necessary to forego the usage
of the trigger and instead apply the SQL expression or function as a
“pre execute” expression:
t = Table('test', meta, Column('abc', MyType, default=func.generate_new_value(), primary_key=True) )
Where above, when
Table.insert() is used,
func.generate_new_value() expression will be pre-executed
in the context of a scalar
SELECT statement, and the new value will
be applied to the subsequent
INSERT, while at the same time being
made available to the
SQLAlchemy represents database sequences using the
Sequence object, which is considered to be a
special case of “column default”. It only has an effect on databases which
have explicit support for sequences, which currently includes Postgresql,
Oracle, and Firebird. The
Sequence object is
Sequence may be placed on any column as a
“default” generator to be used during INSERT operations, and can also be
configured to fire off during UPDATE operations if desired. It is most
commonly used in conjunction with a single integer primary key column:
table = Table("cartitems", meta, Column("cart_id", Integer, Sequence('cart_id_seq'), primary_key=True), Column("description", String(40)), Column("createdate", DateTime()) )
Where above, the table “cartitems” is associated with a sequence named “cart_id_seq”. When INSERT statements take place for “cartitems”, and no value is passed for the “cart_id” column, the “cart_id_seq” sequence will be used to generate a value.
Sequence is associated with a table,
CREATE and DROP statements issued for that table will also issue CREATE/DROP
for the sequence object as well, thus “bundling” the sequence object with its
Sequence object also implements special
functionality to accommodate Postgresql’s SERIAL datatype. The SERIAL type in
PG automatically generates a sequence that is used implicitly during inserts.
This means that if a
Table object defines a
Sequence on its primary key column so that it
works with Oracle and Firebird, the
get in the way of the “implicit” sequence that PG would normally use. For this
use case, add the flag
optional=True to the
Sequence object - this indicates that the
Sequence should only be used if the database
provides no other option for generating primary key identifiers.
Sequence object also has the ability to be
executed standalone like a SQL expression, which has the effect of calling its
“next value” function:
seq = Sequence('some_sequence') nextid = connection.execute(seq)
Associating a Sequence as the Server Side Default¶
When we associate a
Sequence with a
Column as above,
this association is an in-Python only association. The CREATE TABLE
that would be generated for our
Table would not refer to this
sequence. If we want the sequence to be used as a server-side default,
meaning it takes place even if we emit INSERT commands to the table from
the SQL commandline, we can use the
parameter in conjunction with the value-generation function of the
sequence, available from the
cart_id_seq = Sequence('cart_id_seq') table = Table("cartitems", meta, Column( "cart_id", Integer, cart_id_seq, server_default=cart_id_seq.next_value(), primary_key=True), Column("description", String(40)), Column("createdate", DateTime()) )
The above metadata will generate a CREATE TABLE statement on Postgresql as:
CREATE TABLE cartitems ( cart_id INTEGER DEFAULT nextval('cart_id_seq') NOT NULL, description VARCHAR(40), createdate TIMESTAMP WITHOUT TIME ZONE, PRIMARY KEY (cart_id) )
We place the
Sequence also as a Python-side default above, that
is, it is mentioned twice in the
Column definition. Depending
on the backend in use, this may not be strictly necessary, for example
on the Postgresql backend the Core will use
RETURNING to access the
newly generated primary key value in any case. However, for the best
Sequence was originally intended to be a Python-side
directive first and foremost so it’s probably a good idea to specify it
in this way as well.
Default Objects API¶
A plain default value on a column.
This could correspond to a constant, a callable function, or a SQL clause.
For example, the following:
Column('foo', Integer, default=50)
Is equivalent to:
Column('foo', Integer, ColumnDefault(50))
DefaultClause(arg, for_update=False, _reflected=False)¶
A DDL-specified DEFAULT column value.
For example, the following:
Column('foo', Integer, server_default="50")
Is equivalent to:
Column('foo', Integer, DefaultClause("50"))
Base class for column default values.
A marker for a transparent database-side default.
FetchedValuewhen the database is configured to provide some automatic default for a column.
Column('foo', Integer, FetchedValue())
Would indicate that some trigger or default generator will create a new value for the
foocolumn during an INSERT.
A DDL-specified DEFAULT column value.
Sequence(name, start=None, increment=None, schema=None, optional=False, quote=None, metadata=None, quote_schema=None, for_update=False)¶
Represents a named database sequence.
Sequenceobject represents the name and configurational parameters of a database sequence. It also represents a construct that can be “executed” by a SQLAlchemy
Connection, rendering the appropriate “next value” function for the target database and returning a result.
Sequenceis typically associated with a primary key column:
some_table = Table( 'some_table', metadata, Column('id', Integer, Sequence('some_table_seq'), primary_key=True) )
When CREATE TABLE is emitted for the above
Table, if the target platform supports sequences, a CREATE SEQUENCE statement will be emitted as well. For platforms that don’t support sequences, the
Sequenceconstruct is ignored.
__init__(name, start=None, increment=None, schema=None, optional=False, quote=None, metadata=None, quote_schema=None, for_update=False)¶
- name¶ – The name of the sequence.
- start¶ – the starting index of the sequence. This value is
used when the CREATE SEQUENCE command is emitted to the database
as the value of the “START WITH” clause. If
None, the clause is omitted, which on most platforms indicates a starting value of 1.
- increment¶ – the increment value of the sequence. This
value is used when the CREATE SEQUENCE command is emitted to
the database as the value of the “INCREMENT BY” clause. If
None, the clause is omitted, which on most platforms indicates an increment of 1.
- schema¶ – Optional schema name for the sequence, if located in a schema other than the default.
- optional¶ – boolean value, when
True, indicates that this
Sequenceobject only needs to be explicitly generated on backends that don’t provide another way to generate primary key identifiers. Currently, it essentially means, “don’t create this sequence on the Postgresql backend, where the SERIAL keyword creates a sequence for us automatically”.
- quote¶ – boolean value, when
False, explicitly forces quoting of the schema name on or off. When left at its default of
None, normal quoting rules based on casing and reserved words take place.
- quote_schema¶ – set the quoting preferences for the
- metadata¶ –
MetaDataobject which will be associated with this
Sequencethat is associated with a
MetaDatagains access to the
MetaData, meaning the
Sequence.drop()methods will make usage of that engine automatically.
Changed in version 0.7: Additionally, the appropriate CREATE SEQUENCE/ DROP SEQUENCE DDL commands will be emitted corresponding to this
Note that when a
Sequenceis applied to a
Sequenceis automatically associated with the
MetaDataobject of that column’s parent
Table, when that association is made. The
Sequencewill then be subject to automatic CREATE SEQUENCE/DROP SEQUENCE corresponding to when the
Tableobject itself is created or dropped, rather than that of the
- for_update¶ – Indicates this
Sequence, when associated with a
Column, should be invoked for UPDATE statements on that column’s table, rather than for INSERT statements, when no value is otherwise present for that column in the statement.
Creates this sequence in the database.
Drops this sequence from the database.