Commit session error

I’m re-loading data with my Session but it isn’t seeing changes that I committed elsewhere¶

The main issue regarding this behavior is that the session acts as though
the transaction is in the serializable isolation state, even if it’s not
(and it usually is not). In practical terms, this means that the session
does not alter any data that it’s already read within the scope of a transaction.

If the term “isolation level” is unfamiliar, then you first need to read this link:

Isolation Level

In short, serializable isolation level generally means
that once you SELECT a series of rows in a transaction, you will get
the identical data back each time you re-emit that SELECT. If you are in
the next-lower isolation level, “repeatable read”, you’ll
see newly added rows (and no longer see deleted rows), but for rows that
you’ve already loaded, you won’t see any change. Only if you are in a
lower isolation level, e.g. “read committed”, does it become possible to
see a row of data change its value.

For information on controlling the isolation level when using the
SQLAlchemy ORM, see Setting Transaction Isolation Levels / DBAPI AUTOCOMMIT.

To simplify things dramatically, the Session itself works in
terms of a completely isolated transaction, and doesn’t overwrite any mapped attributes
it’s already read unless you tell it to. The use case of trying to re-read
data you’ve already loaded in an ongoing transaction is an uncommon use
case that in many cases has no effect, so this is considered to be the
exception, not the norm; to work within this exception, several methods
are provided to allow specific data to be reloaded within the context
of an ongoing transaction.

To understand what we mean by “the transaction” when we talk about the
Session, your Session is intended to only work within
a transaction. An overview of this is at Managing Transactions.

Once we’ve figured out what our isolation level is, and we think that
our isolation level is set at a low enough level so that if we re-SELECT a row,
we should see new data in our Session, how do we see it?

Three ways, from most common to least:

1. We simply end our transaction and start a new one on next access
   with our Session by calling Session.commit() (note
   that if the Session is in the lesser-used “autocommit”
   mode, there would be a call to Session.begin() as well). The
   vast majority of applications and use cases do not have any issues
   with not being able to “see” data in other transactions because
   they stick to this pattern, which is at the core of the best practice of
   short lived transactions.
   See When do I construct a Session, when do I commit it, and when do I close it? for some thoughts on this.

2. We tell our Session to re-read rows that it has already read,
   either when we next query for them using Session.expire_all()
   or Session.expire(), or immediately on an object using
   refresh. See Refreshing / Expiring for detail on this.

3. We can run whole queries while setting them to definitely overwrite
   already-loaded objects as they read rows by using “populate existing”.
   This is an execution option described at
   Populate Existing.

But remember, the ORM cannot see changes in rows if our isolation
level is repeatable read or higher, unless we start a new transaction.

“This Session’s transaction has been rolled back due to a previous exception during flush.” (or similar)¶

This is an error that occurs when a Session.flush() raises an exception, rolls back
the transaction, but further commands upon the Session are called without an
explicit call to Session.rollback() or Session.close().

It usually corresponds to an application that catches an exception
upon Session.flush() or Session.commit() and
does not properly handle the exception. For example:

from sqlalchemy import create_engine, Column, Integer
from sqlalchemy.orm import sessionmaker
from sqlalchemy.ext.declarative import declarative_base

Base = declarative_base(create_engine("sqlite://"))


class Foo(Base):
    __tablename__ = "foo"
    id = Column(Integer, primary_key=True)


Base.metadata.create_all()

session = sessionmaker()()

# constraint violation
session.add_all([Foo(id=1), Foo(id=1)])

try:
    session.commit()
except:
    # ignore error
    pass

# continue using session without rolling back
session.commit()

The usage of the Session should fit within a structure similar to this:

try:
    # <use session>
    session.commit()
except:
    session.rollback()
    raise
finally:
    session.close()  # optional, depends on use case

Many things can cause a failure within the try/except besides flushes.
Applications should ensure some system of “framing” is applied to ORM-oriented
processes so that connection and transaction resources have a definitive
boundary, and so that transactions can be explicitly rolled back if any
failure conditions occur.

This does not mean there should be try/except blocks throughout an application,
which would not be a scalable architecture. Instead, a typical approach is
that when ORM-oriented methods and functions are first called, the process
that’s calling the functions from the very top would be within a block that
commits transactions at the successful completion of a series of operations,
as well as rolls transactions back if operations fail for any reason,
including failed flushes. There are also approaches using function decorators or
context managers to achieve similar results. The kind of approach taken
depends very much on the kind of application being written.

For a detailed discussion on how to organize usage of the Session,
please see When do I construct a Session, when do I commit it, and when do I close it?.

test=> create table foo(id integer primary key);
NOTICE:  CREATE TABLE / PRIMARY KEY will create implicit index "foo_pkey" for table "foo"
CREATE TABLE
test=> begin;
BEGIN
test=> insert into foo values(1);
INSERT 0 1
test=> commit;
COMMIT
test=> begin;
BEGIN
test=> insert into foo values(1);
ERROR:  duplicate key value violates unique constraint "foo_pkey"
test=> insert into foo values(2);
ERROR:  current transaction is aborted, commands ignored until end of transaction block

sess = Session()  # begins a logical transaction
try:
    sess.flush()

    sess.commit()
except:
    sess.rollback()

How do I make a Query that always adds a certain filter to every query?¶

See the recipe at FilteredQuery.

My Query does not return the same number of objects as query.count() tells me — why?¶

The Query object, when asked to return a list of ORM-mapped objects,
will deduplicate the objects based on primary key. That is, if we
for example use the User mapping described at Using ORM Declarative Forms to Define Table Metadata,
and we had a SQL query like the following:

q = session.query(User).outerjoin(User.addresses).filter(User.name == "jack")

Above, the sample data used in the tutorial has two rows in the addresses
table for the users row with the name 'jack', primary key value 5.
If we ask the above query for a Query.count(), we will get the answer
2:

However, if we run Query.all() or iterate over the query, we get back
one element:

>>> q.all()
[User(id=5, name='jack', ...)]

This is because when the Query object returns full entities, they
are deduplicated. This does not occur if we instead request individual
columns back:

>>> session.query(User.id, User.name).outerjoin(User.addresses).filter(
...     User.name == "jack"
... ).all()
[(5, 'jack'), (5, 'jack')]

There are two main reasons the Query will deduplicate:

• To allow joined eager loading to work correctly — Joined Eager Loading
  works by querying rows using joins against related tables, where it then routes
  rows from those joins into collections upon the lead objects. In order to do this,
  it has to fetch rows where the lead object primary key is repeated for each
  sub-entry. This pattern can then continue into further sub-collections such
  that a multiple of rows may be processed for a single lead object, such as
  User(id=5). The dedpulication allows us to receive objects in the way they
  were queried, e.g. all the User() objects whose name is 'jack' which
  for us is one object, with
  the User.addresses collection eagerly loaded as was indicated either
  by lazy='joined' on the relationship() or via the joinedload()
  option. For consistency, the deduplication is still applied whether or not
  the joinedload is established, as the key philosophy behind eager loading
  is that these options never affect the result.

• To eliminate confusion regarding the identity map — this is admittedly
  the less critical reason. As the Session
  makes use of an identity map, even though our SQL result set has two
  rows with primary key 5, there is only one User(id=5) object inside the Session
  which must be maintained uniquely on its identity, that is, its primary key /
  class combination. It doesn’t actually make much sense, if one is querying for
  User() objects, to get the same object multiple times in the list. An
  ordered set would potentially be a better representation of what Query
  seeks to return when it returns full objects.

The issue of Query deduplication remains problematic, mostly for the
single reason that the Query.count() method is inconsistent, and the
current status is that joined eager loading has in recent releases been
superseded first by the “subquery eager loading” strategy and more recently the
“select IN eager loading” strategy, both of which are generally more
appropriate for collection eager loading. As this evolution continues,
SQLAlchemy may alter this behavior on Query, which may also involve
new APIs in order to more directly control this behavior, and may also alter
the behavior of joined eager loading in order to create a more consistent usage
pattern.

I’ve created a mapping against an Outer Join, and while the query returns rows, no objects are returned. Why not?¶

Rows returned by an outer join may contain NULL for part of the primary key,
as the primary key is the composite of both tables. The Query object ignores incoming rows
that don’t have an acceptable primary key. Based on the setting of the allow_partial_pks
flag on Mapper, a primary key is accepted if the value has at least one non-NULL
value, or alternatively if the value has no NULL values. See allow_partial_pks
at Mapper.

I’m using joinedload() or lazy=False to create a JOIN/OUTER JOIN and SQLAlchemy is not constructing the correct query when I try to add a WHERE, ORDER BY, LIMIT, etc. (which relies upon the (OUTER) JOIN)¶

The joins generated by joined eager loading are only used to fully load related
collections, and are designed to have no impact on the primary results of the query.
Since they are anonymously aliased, they cannot be referenced directly.

For detail on this behavior, see The Zen of Joined Eager Loading.

Query has no __len__(), why not?¶

The Python __len__() magic method applied to an object allows the len()
builtin to be used to determine the length of the collection. It’s intuitive
that a SQL query object would link __len__() to the Query.count()
method, which emits a SELECT COUNT. The reason this is not possible is
because evaluating the query as a list would incur two SQL calls instead of
one:

class Iterates:
    def __len__(self):
        print("LEN!")
        return 5

    def __iter__(self):
        print("ITER!")
        return iter([1, 2, 3, 4, 5])


list(Iterates())

output:

How Do I use Textual SQL with ORM Queries?¶

See:

• Getting ORM Results from Textual Statements — Ad-hoc textual blocks with Query

• Using SQL Expressions with Sessions — Using Session with textual SQL directly.

I’m calling Session.delete(myobject) and it isn’t removed from the parent collection!¶

See Notes on Delete — Deleting Objects Referenced from Collections and Scalar Relationships for a description of this behavior.

why isn’t my __init__() called when I load objects?¶

See Constructors and Object Initialization for a description of this behavior.

how do I use ON DELETE CASCADE with SA’s ORM?¶

SQLAlchemy will always issue UPDATE or DELETE statements for dependent
rows which are currently loaded in the Session. For rows which
are not loaded, it will by default issue SELECT statements to load
those rows and update/delete those as well; in other words it assumes
there is no ON DELETE CASCADE configured.
To configure SQLAlchemy to cooperate with ON DELETE CASCADE, see
Using foreign key ON DELETE cascade with ORM relationships.

I set the “foo_id” attribute on my instance to “7”, but the “foo” attribute is still None — shouldn’t it have loaded Foo with id #7?¶

The ORM is not constructed in such a way as to support
immediate population of relationships driven from foreign
key attribute changes — instead, it is designed to work the
other way around — foreign key attributes are handled by the
ORM behind the scenes, the end user sets up object
relationships naturally. Therefore, the recommended way to
set o.foo is to do just that — set it!:

foo = session.get(Foo, 7)
o.foo = foo
Session.commit()

Manipulation of foreign key attributes is of course entirely legal. However,
setting a foreign-key attribute to a new value currently does not trigger
an “expire” event of the relationship() in which it’s involved. This means
that for the following sequence:

o = session.scalars(select(SomeClass).limit(1)).first()

# assume the existing o.foo_id value is None;
# accessing o.foo will reconcile this as ``None``, but will effectively
# "load" the value of None
assert o.foo is None

# now set foo_id to something.  o.foo will not be immediately affected
o.foo_id = 7

o.foo is loaded with its effective database value of None when it
is first accessed. Setting
o.foo_id = 7 will have the value of “7” as a pending change, but no flush
has occurred — so o.foo is still None:

# attribute is already "loaded" as None, has not been
# reconciled with o.foo_id = 7 yet
assert o.foo is None

For o.foo to load based on the foreign key mutation is usually achieved
naturally after the commit, which both flushes the new foreign key value
and expires all state:

session.commit()  # expires all attributes

foo_7 = session.get(Foo, 7)

# o.foo will lazyload again, this time getting the new object
assert o.foo is foo_7

A more minimal operation is to expire the attribute individually — this can
be performed for any persistent object using Session.expire():

o = session.scalars(select(SomeClass).limit(1)).first()
o.foo_id = 7
Session.expire(o, ["foo"])  # object must be persistent for this

foo_7 = session.get(Foo, 7)

assert o.foo is foo_7  # o.foo lazyloads on access

Note that if the object is not persistent but present in the Session,
it’s known as pending. This means the row for the object has not been
INSERTed into the database yet. For such an object, setting foo_id does not
have meaning until the row is inserted; otherwise there is no row yet:

new_obj = SomeClass()
new_obj.foo_id = 7

Session.add(new_obj)

# returns None but this is not a "lazyload", as the object is not
# persistent in the DB yet, and the None value is not part of the
# object's state
assert new_obj.foo is None

Session.flush()  # emits INSERT

assert new_obj.foo is foo_7  # now it loads

The recipe ExpireRelationshipOnFKChange features an example using SQLAlchemy events
in order to coordinate the setting of foreign key attributes with many-to-one
relationships.

Is there a way to automagically have only unique keywords (or other kinds of objects) without doing a query for the keyword and getting a reference to the row containing that keyword?¶

When people read the many-to-many example in the docs, they get hit with the
fact that if you create the same Keyword twice, it gets put in the DB twice.
Which is somewhat inconvenient.

This UniqueObject recipe was created to address this issue.

Why does post_update emit UPDATE in addition to the first UPDATE?¶

The post_update feature, documented at Rows that point to themselves / Mutually Dependent Rows, involves that an
UPDATE statement is emitted in response to changes to a particular
relationship-bound foreign key, in addition to the INSERT/UPDATE/DELETE that
would normally be emitted for the target row. While the primary purpose of this
UPDATE statement is that it pairs up with an INSERT or DELETE of that row, so
that it can post-set or pre-unset a foreign key reference in order to break a
cycle with a mutually dependent foreign key, it currently is also bundled as a
second UPDATE that emits when the target row itself is subject to an UPDATE.
In this case, the UPDATE emitted by post_update is usually unnecessary
and will often appear wasteful.

However, some research into trying to remove this “UPDATE / UPDATE” behavior
reveals that major changes to the unit of work process would need to occur not
just throughout the post_update implementation, but also in areas that aren’t
related to post_update for this to work, in that the order of operations would
need to be reversed on the non-post_update side in some cases, which in turn
can impact other cases, such as correctly handling an UPDATE of a referenced
primary key value (see #1063 for a proof of concept).

The answer is that “post_update” is used to break a cycle between two
mutually dependent foreign keys, and to have this cycle breaking be limited
to just INSERT/DELETE of the target table implies that the ordering of UPDATE
statements elsewhere would need to be liberalized, leading to breakage
in other edge cases.