Using INSERT Statements ¶

When using Core as well as when using the ORM for bulk operations, a SQL INSERT statement is generated directly using the insert() function - this function generates a new instance of Insert which represents an INSERT statement in SQL, that adds new data into a table.

ORM Readers -

This section details the Core means of generating an individual SQL INSERT statement in order to add new rows to a table. When using the ORM, we normally use another tool that rides on top of this called the unit of work , which will automate the production of many INSERT statements at once. However, understanding how the Core handles data creation and manipulation is very useful even when the ORM is running it for us. Additionally, the ORM supports direct use of INSERT using a feature called Bulk / Multi Row INSERT, upsert, UPDATE and DELETE .

To skip directly to how to INSERT rows with the ORM using normal unit of work patterns, see Inserting Rows using the ORM Unit of Work pattern .

The insert() SQL Expression Construct ¶

A simple example of Insert illustrating the target table and the VALUES clause at once:

>>> from sqlalchemy import insert
>>> stmt = insert(user_table).values(name="spongebob", fullname="Spongebob Squarepants")

The above stmt variable is an instance of Insert . Most SQL expressions can be stringified in place as a means to see the general form of what’s being produced:

>>> print(stmt)
INSERT INTO user_account (name, fullname) VALUES (:name, :fullname)
The stringified form is created by producing a Compiled form
of the object which includes a database-specific string SQL representation of
the statement; we can acquire this object directly using the
ClauseElement.compile() method:
>>> compiled = stmt.compile()
Our Insert construct is an example of a “parameterized”
construct, illustrated previously at Sending Parameters; to
view the name and fullname bound parameters, these are
available from the Compiled construct as well:
>>> compiled.params
{'name': 'spongebob', 'fullname': 'Spongebob Squarepants'}
Executing the Statement¶
Invoking the statement we can INSERT a row into user_table.
The INSERT SQL as well as the bundled parameters can be seen in the
SQL logging:
>>> with engine.connect() as conn:
...     result = conn.execute(stmt)
...     conn.commit()
BEGIN (implicit)
INSERT INTO user_account (name, fullname) VALUES (?, ?)
[...] ('spongebob', 'Spongebob Squarepants')
COMMIT
In its simple form above, the INSERT statement does not return any rows, and if
only a single row is inserted, it will usually include the ability to return
information about column-level default values that were generated during the
INSERT of that row, most commonly an integer primary key value.  In the above
case the first row in a SQLite database will normally return 1 for the
first integer primary key value, which we can acquire using the
CursorResult.inserted_primary_key accessor:
>>> result.inserted_primary_key
CursorResult.inserted_primary_key returns a tuple
because a primary key may contain multiple columns.  This is known as
a composite primary key.  The CursorResult.inserted_primary_key
is intended to always contain the complete primary key of the record just
inserted, not just a “cursor.lastrowid” kind of value, and is also intended
to be populated regardless of whether or not “autoincrement” were used, hence
to express a complete primary key it’s a tuple.
Changed in version 1.4.8: the tuple returned by
CursorResult.inserted_primary_key is now a named tuple
fulfilled by returning it as a Row object.
INSERT usually generates the “values” clause automatically¶
The example above made use of the Insert.values() method to
explicitly create the VALUES clause of the SQL INSERT statement.   If
we don’t actually use Insert.values() and just print out an “empty”
statement, we get an INSERT for every column in the table:
>>> print(insert(user_table))
INSERT INTO user_account (id, name, fullname) VALUES (:id, :name, :fullname)
If we take an Insert construct that has not had
Insert.values() called upon it and execute it
rather than print it, the statement will be compiled to a string based
on the parameters that we passed to the Connection.execute()
method, and only include columns relevant to the parameters that were
passed.   This is actually the usual way that
Insert is used to insert rows without having to type out
an explicit VALUES clause.   The example below illustrates a two-column
INSERT statement being executed with a list of parameters at once:




    

>>> with engine.connect() as conn:
...     result = conn.execute(
...         insert(user_table),
...         [
...             {"name": "sandy", "fullname": "Sandy Cheeks"},
...             {"name": "patrick", "fullname": "Patrick Star"},
...         ],
...     )
...     conn.commit()
BEGIN (implicit)
INSERT INTO user_account (name, fullname) VALUES (?, ?)
[...] [('sandy', 'Sandy Cheeks'), ('patrick', 'Patrick Star')]
COMMIT
The execution above features “executemany” form first illustrated at
Sending Multiple Parameters, however unlike when using the
text() construct, we didn’t have to spell out any SQL.
By passing a dictionary or list of dictionaries to the Connection.execute()
method in conjunction with the Insert construct, the
Connection ensures that the column names which are passed
will be expressed in the VALUES clause of the Insert
construct automatically.
Deep Alchemy
Hi, welcome to the first edition of Deep Alchemy.   The person on the
left is known as The Alchemist, and you’ll note they are not a wizard,
as the pointy hat is not sticking upwards.   The Alchemist comes around to
describe things that are generally more advanced and/or tricky and
additionally not usually needed, but for whatever reason they feel you
should know about this thing that SQLAlchemy can do.
In this edition, towards the goal of having some interesting data in the
address_table as well, below is a more advanced example illustrating
how the Insert.values() method may be used explicitly while at
the same time including for additional VALUES generated from the
parameters.    A scalar subquery is constructed, making use of the
select() construct introduced in the next section, and the
parameters used in the subquery are set up using an explicit bound
parameter name, established using the bindparam() construct.
This is some slightly deeper alchemy just so that we can add related
rows without fetching the primary key identifiers from the user_table
operation into the application.   Most Alchemists will simply use the ORM
which takes care of things like this for us.
>>> from sqlalchemy import select, bindparam
>>> scalar_subq = (
...     select(user_table.c.id)
...     .where(user_table.c.name == bindparam("username"))
...     .scalar_subquery()
... )
>>> with engine.connect() as conn:
...     result = conn.execute(
...         insert(address_table).values(user_id=scalar_subq),
...         [
...             {
...                 "username": "spongebob",
...                 "email_address": "[email protected]",
...             },
...             {"username": "sandy", "email_address": "[email protected]"},
...             {"username": "sandy", "email_address": "[email protected]"},
...         ],
...     )
...     conn.commit()
BEGIN (implicit)
INSERT INTO address (user_id, email_address) VALUES ((SELECT user_account.id
FROM user_account
WHERE user_account.name = ?), ?)
[...] [('spongebob', '[email protected]'), ('sandy', '[email protected]'),
('sandy', '[email protected]')]
COMMIT
With that, we have some more interesting data in our tables that we will
make use of in the upcoming sections.
A true “empty” INSERT that inserts only the “defaults” for a table
without including any explicit values at all is generated if we indicate
Insert.values() with no arguments; not every database backend
supports this, but here’s what SQLite produces:
>>> print(insert(user_table).values().compile(engine))
INSERT INTO user_account DEFAULT VALUES
INSERT…RETURNING¶
The RETURNING clause for supported backends is used
automatically in order to retrieve the last inserted primary key value
as well as the values for server defaults.   However the RETURNING clause
may also be specified explicitly using the Insert.returning()
method; in this case, the Result
object that’s returned when the statement is executed has rows which
can be fetched:
>>> insert_stmt = insert(address_table).returning(
...     address_table.c.id, address_table.c.email_address
... )
>>> print(insert_stmt)
INSERT INTO address (id, user_id, email_address)
VALUES (:id, :user_id, :email_address)
RETURNING address.id, address.email_address
It can also be combined with Insert.from_select(),
as in the example below that builds upon the example stated in
INSERT…FROM SELECT:
>>> select_stmt = select(user_table.c.id, user_table.c.name + "@aol.com")
>>> insert_stmt = insert(address_table).from_select(
...     ["user_id", "email_address"], select_stmt
... )
>>> print(insert_stmt.returning(address_table.c.id, address_table.c.email_address))
INSERT INTO address (user_id, email_address)
SELECT user_account.id, user_account.name || :name_1 AS anon_1
FROM user_account RETURNING address.id, address.email_address
The RETURNING feature is also supported by UPDATE and DELETE statements,
which will be introduced later in this tutorial.
For INSERT statements, the RETURNING feature may be used
both for single-row statements as well as for statements that INSERT
multiple rows at once.  Support for multiple-row INSERT with RETURNING
is dialect specific, however is supported for all the dialects
that are included in SQLAlchemy which support RETURNING.  See the section
“Insert Many Values” Behavior for INSERT statements for background on this feature.
See also
Bulk INSERT with or without RETURNING is also supported by the ORM.  See
ORM Bulk INSERT Statements for reference documentation.
INSERT…FROM SELECT¶
A less used feature of Insert, but here for completeness, the
Insert construct can compose an INSERT that gets rows directly
from a SELECT using the Insert.from_select() method.
This method accepts a select() construct, which is discussed in the
next section, along with a list of column names to be targeted in the
actual INSERT.  In the example below, rows are added to the address
table which are derived from rows in the user_account table, giving each
user a free email address at aol.com:
>>> select_stmt = select(user_table.c.id, user_table.c.name + "@aol.com")
>>> insert_stmt = insert(address_table).from_select(
...     ["user_id", "email_address"], select_stmt
... )
>>> print(insert_stmt)
INSERT INTO address (user_id, email_address)
SELECT user_account.id, user_account.name || :name_1 AS anon_1
FROM user_account
This construct is used when one wants to copy data from
some other part of the database directly into a new set of rows, without
actually fetching and re-sending the data from the client.
See also
Insert - in the SQL Expression API documentation
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