.. _session_toplevel: ================= Using the Session ================= .. module:: sqlalchemy.orm.session The :func:`.orm.mapper` function and :mod:`~sqlalchemy.ext.declarative` extensions are the primary configurational interface for the ORM. Once mappings are configured, the primary usage interface for persistence operations is the :class:`.Session`. What does the Session do ? ========================== In the most general sense, the :class:`~.Session` establishes all conversations with the database and represents a "holding zone" for all the objects which you've loaded or associated with it during its lifespan. It provides the entrypoint to acquire a :class:`.Query` object, which sends queries to the database using the :class:`~.Session` object's current database connection, populating result rows into objects that are then stored in the :class:`.Session`, inside a structure called the `Identity Map `_ - a data structure that maintains unique copies of each object, where "unique" means "only one object with a particular primary key". The :class:`.Session` begins in an essentially stateless form. Once queries are issued or other objects are persisted with it, it requests a connection resource from an :class:`.Engine` that is associated either with the :class:`.Session` itself or with the mapped :class:`.Table` objects being operated upon. This connection represents an ongoing transaction, which remains in effect until the :class:`.Session` is instructed to commit or roll back its pending state. All changes to objects maintained by a :class:`.Session` are tracked - before the database is queried again or before the current transaction is committed, it **flushes** all pending changes to the database. This is known as the `Unit of Work `_ pattern. When using a :class:`.Session`, it's important to note that the objects which are associated with it are **proxy objects** to the transaction being held by the :class:`.Session` - there are a variety of events that will cause objects to re-access the database in order to keep synchronized. It is possible to "detach" objects from a :class:`.Session`, and to continue using them, though this practice has its caveats. It's intended that usually, you'd re-associate detached objects with another :class:`.Session` when you want to work with them again, so that they can resume their normal task of representing database state. .. _session_getting: Getting a Session ================= :class:`.Session` is a regular Python class which can be directly instantiated. However, to standardize how sessions are configured and acquired, the :class:`.sessionmaker` class is normally used to create a top level :class:`.Session` configuration which can then be used throughout an application without the need to repeat the configurational arguments. The usage of :class:`.sessionmaker` is illustrated below: .. sourcecode:: python+sql from sqlalchemy import create_engine from sqlalchemy.orm import sessionmaker # an Engine, which the Session will use for connection # resources some_engine = create_engine('postgresql://scott:tiger@localhost/') # create a configured "Session" class Session = sessionmaker(bind=some_engine) # create a Session session = Session() # work with sess myobject = MyObject('foo', 'bar') session.add(myobject) session.commit() Above, the :class:`.sessionmaker` call creates a factory for us, which we assign to the name ``Session``. This factory, when called, will create a new :class:`.Session` object using the configurational arguments we've given the factory. In this case, as is typical, we've configured the factory to specify a particular :class:`.Engine` for connection resources. A typical setup will associate the :class:`.sessionmaker` with an :class:`.Engine`, so that each :class:`.Session` generated will use this :class:`.Engine` to acquire connection resources. This association can be set up as in the example above, using the ``bind`` argument. When you write your application, place the :class:`.sessionmaker` factory at the global level. This factory can then be used by the rest of the applcation as the source of new :class:`.Session` instances, keeping the configuration for how :class:`.Session` objects are constructed in one place. The :class:`.sessionmaker` factory can also be used in conjunction with other helpers, which are passed a user-defined :class:`.sessionmaker` that is then maintained by the helper. Some of these helpers are discussed in the section :ref:`session_faq_whentocreate`. Adding Additional Configuration to an Existing sessionmaker() -------------------------------------------------------------- A common scenario is where the :class:`.sessionmaker` is invoked at module import time, however the generation of one or more :class:`.Engine` instances to be associated with the :class:`.sessionmaker` has not yet proceeded. For this use case, the :class:`.sessionmaker` construct offers the :meth:`.sessionmaker.configure` method, which will place additional configuration directives into an existing :class:`.sessionmaker` that will take place when the construct is invoked:: from sqlalchemy.orm import sessionmaker from sqlalchemy import create_engine # configure Session class with desired options Session = sessionmaker() # later, we create the engine engine = create_engine('postgresql://...') # associate it with our custom Session class Session.configure(bind=engine) # work with the session session = Session() Creating Ad-Hoc Session Objects with Alternate Arguments --------------------------------------------------------- For the use case where an application needs to create a new :class:`.Session` with special arguments that deviate from what is normally used throughout the application, such as a :class:`.Session` that binds to an alternate source of connectivity, or a :class:`.Session` that should have other arguments such as ``expire_on_commit`` established differently from what most of the application wants, specific arguments can be passed to the :class:`.sessionmaker` factory's :meth:`.sessionmaker.__call__` method. These arguments will override whatever configurations have already been placed, such as below, where a new :class:`.Session` is constructed against a specific :class:`.Connection`:: # at the module level, the global sessionmaker, # bound to a specific Engine Session = sessionmaker(bind=engine) # later, some unit of code wants to create a # Session that is bound to a specific Connection conn = engine.connect() session = Session(bind=conn) The typical rationale for the association of a :class:`.Session` with a specific :class:`.Connection` is that of a test fixture that maintains an external transaction - see :ref:`session_external_transaction` for an example of this. Using the Session ================== .. _session_object_states: Quickie Intro to Object States ------------------------------ It's helpful to know the states which an instance can have within a session: * **Transient** - an instance that's not in a session, and is not saved to the database; i.e. it has no database identity. The only relationship such an object has to the ORM is that its class has a ``mapper()`` associated with it. * **Pending** - when you :meth:`~.Session.add` a transient instance, it becomes pending. It still wasn't actually flushed to the database yet, but it will be when the next flush occurs. * **Persistent** - An instance which is present in the session and has a record in the database. You get persistent instances by either flushing so that the pending instances become persistent, or by querying the database for existing instances (or moving persistent instances from other sessions into your local session). * **Detached** - an instance which has a record in the database, but is not in any session. There's nothing wrong with this, and you can use objects normally when they're detached, **except** they will not be able to issue any SQL in order to load collections or attributes which are not yet loaded, or were marked as "expired". Knowing these states is important, since the :class:`.Session` tries to be strict about ambiguous operations (such as trying to save the same object to two different sessions at the same time). .. _session_faq: Session Frequently Asked Questions ----------------------------------- When do I make a :class:`.sessionmaker`? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Just one time, somewhere in your application's global scope. It should be looked upon as part of your application's configuration. If your application has three .py files in a package, you could, for example, place the :class:`.sessionmaker` line in your ``__init__.py`` file; from that point on your other modules say "from mypackage import Session". That way, everyone else just uses :class:`.Session()`, and the configuration of that session is controlled by that central point. If your application starts up, does imports, but does not know what database it's going to be connecting to, you can bind the :class:`.Session` at the "class" level to the engine later on, using :meth:`.sessionmaker.configure`. In the examples in this section, we will frequently show the :class:`.sessionmaker` being created right above the line where we actually invoke :class:`.Session`. But that's just for example's sake! In reality, the :class:`.sessionmaker` would be somewhere at the module level. The calls to instantiate :class:`.Session` would then be placed at the point in the application where database conversations begin. .. _session_faq_whentocreate: When do I construct a :class:`.Session`, when do I commit it, and when do I close it? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. topic:: tl;dr; As a general rule, keep the lifecycle of the session **separate and external** from functions and objects that access and/or manipulate database data. A :class:`.Session` is typically constructed at the beginning of a logical operation where database access is potentially anticipated. The :class:`.Session`, whenever it is used to talk to the database, begins a database transaction as soon as it starts communicating. Assuming the ``autocommit`` flag is left at its recommended default of ``False``, this transaction remains in progress until the :class:`.Session` is rolled back, committed, or closed. The :class:`.Session` will begin a new transaction if it is used again, subsequent to the previous transaction ending; from this it follows that the :class:`.Session` is capable of having a lifespan across many transactions, though only one at a time. We refer to these two concepts as **transaction scope** and **session scope**. The implication here is that the SQLAlchemy ORM is encouraging the developer to establish these two scopes in their application, including not only when the scopes begin and end, but also the expanse of those scopes, for example should a single :class:`.Session` instance be local to the execution flow within a function or method, should it be a global object used by the entire application, or somewhere in between these two. The burden placed on the developer to determine this scope is one area where the SQLAlchemy ORM necessarily has a strong opinion about how the database should be used. The :term:`unit of work` pattern is specifically one of accumulating changes over time and flushing them periodically, keeping in-memory state in sync with what's known to be present in a local transaction. This pattern is only effective when meaningful transaction scopes are in place. It's usually not very hard to determine the best points at which to begin and end the scope of a :class:`.Session`, though the wide variety of application architectures possible can introduce challenging situations. A common choice is to tear down the :class:`.Session` at the same time the transaction ends, meaning the transaction and session scopes are the same. This is a great choice to start out with as it removes the need to consider session scope as separate from transaction scope. While there's no one-size-fits-all recommendation for how transaction scope should be determined, there are common patterns. Especially if one is writing a web application, the choice is pretty much established. A web application is the easiest case because such an appication is already constructed around a single, consistent scope - this is the **request**, which represents an incoming request from a browser, the processing of that request to formulate a response, and finally the delivery of that response back to the client. Integrating web applications with the :class:`.Session` is then the straightforward task of linking the scope of the :class:`.Session` to that of the request. The :class:`.Session` can be established as the request begins, or using a :term:`lazy initialization` pattern which establishes one as soon as it is needed. The request then proceeds, with some system in place where application logic can access the current :class:`.Session` in a manner associated with how the actual request object is accessed. As the request ends, the :class:`.Session` is torn down as well, usually through the usage of event hooks provided by the web framework. The transaction used by the :class:`.Session` may also be committed at this point, or alternatively the application may opt for an explicit commit pattern, only committing for those requests where one is warranted, but still always tearing down the :class:`.Session` unconditionally at the end. Most web frameworks include infrastructure to establish a single :class:`.Session`, associated with the request, which is correctly constructed and torn down corresponding torn down at the end of a request. Such infrastructure pieces include products such as `Flask-SQLAlchemy `_, for usage in conjunction with the Flask web framework, and `Zope-SQLAlchemy `_, for usage in conjunction with the Pyramid and Zope frameworks. SQLAlchemy strongly recommends that these products be used as available. In those situations where integration libraries are not available, SQLAlchemy includes its own "helper" class known as :class:`.scoped_session`. A tutorial on the usage of this object is at :ref:`unitofwork_contextual`. It provides both a quick way to associate a :class:`.Session` with the current thread, as well as patterns to associate :class:`.Session` objects with other kinds of scopes. As mentioned before, for non-web applications there is no one clear pattern, as applications themselves don't have just one pattern of architecture. The best strategy is to attempt to demarcate "operations", points at which a particular thread begins to perform a series of operations for some period of time, which can be committed at the end. Some examples: * A background daemon which spawns off child forks would want to create a :class:`.Session` local to each child process, work with that :class:`.Session` through the life of the "job" that the fork is handling, then tear it down when the job is completed. * For a command-line script, the application would create a single, global :class:`.Session` that is established when the program begins to do its work, and commits it right as the program is completing its task. * For a GUI interface-driven application, the scope of the :class:`.Session` may best be within the scope of a user-generated event, such as a button push. Or, the scope may correspond to explicit user interaction, such as the user "opening" a series of records, then "saving" them. As a general rule, the application should manage the lifecycle of the session *externally* to functions that deal with specific data. This is a fundamental separation of concerns which keeps data-specific operations agnostic of the context in which they access and manipulate that data. E.g. **don't do this**:: ### this is the **wrong way to do it** ### class ThingOne(object): def go(self): session = Session() try: session.query(FooBar).update({"x": 5}) session.commit() except: session.rollback() raise class ThingTwo(object): def go(self): session = Session() try: session.query(Widget).update({"q": 18}) session.commit() except: session.rollback() raise def run_my_program(): ThingOne().go() ThingTwo().go() Keep the lifecycle of the session (and usually the transaction) **separate and external**:: ### this is a **better** (but not the only) way to do it ### class ThingOne(object): def go(self, session): session.query(FooBar).update({"x": 5}) class ThingTwo(object): def go(self, session): session.query(Widget).update({"q": 18}) def run_my_program(): session = Session() try: ThingOne().go(session) ThingTwo().go(session) session.commit() except: session.rollback() raise finally: session.close() The advanced developer will try to keep the details of session, transaction and exception management as far as possible from the details of the program doing its work. For example, we can further separate concerns using a `context manager `_:: ### another way (but again *not the only way*) to do it ### from contextlib import contextmanager @contextmanager def session_scope(): """Provide a transactional scope around a series of operations.""" session = Session() try: yield session session.commit() except: session.rollback() raise finally: session.close() def run_my_program(): with session_scope() as session: ThingOne().go(session) ThingTwo().go(session) Is the Session a cache? ~~~~~~~~~~~~~~~~~~~~~~~~~~~ Yeee...no. It's somewhat used as a cache, in that it implements the :term:`identity map` pattern, and stores objects keyed to their primary key. However, it doesn't do any kind of query caching. This means, if you say ``session.query(Foo).filter_by(name='bar')``, even if ``Foo(name='bar')`` is right there, in the identity map, the session has no idea about that. It has to issue SQL to the database, get the rows back, and then when it sees the primary key in the row, *then* it can look in the local identity map and see that the object is already there. It's only when you say ``query.get({some primary key})`` that the :class:`~sqlalchemy.orm.session.Session` doesn't have to issue a query. Additionally, the Session stores object instances using a weak reference by default. This also defeats the purpose of using the Session as a cache. The :class:`.Session` is not designed to be a global object from which everyone consults as a "registry" of objects. That's more the job of a **second level cache**. SQLAlchemy provides a pattern for implementing second level caching using `dogpile.cache `_, via the :ref:`examples_caching` example. How can I get the :class:`~sqlalchemy.orm.session.Session` for a certain object? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Use the :meth:`~.Session.object_session` classmethod available on :class:`~sqlalchemy.orm.session.Session`:: session = Session.object_session(someobject) The newer :ref:`core_inspection_toplevel` system can also be used:: from sqlalchemy import inspect session = inspect(someobject).session .. _session_faq_threadsafe: Is the session thread-safe? ~~~~~~~~~~~~~~~~~~~~~~~~~~~ The :class:`.Session` is very much intended to be used in a **non-concurrent** fashion, which usually means in only one thread at a time. The :class:`.Session` should be used in such a way that one instance exists for a single series of operations within a single transaction. One expedient way to get this effect is by associating a :class:`.Session` with the current thread (see :ref:`unitofwork_contextual` for background). Another is to use a pattern where the :class:`.Session` is passed between functions and is otherwise not shared with other threads. The bigger point is that you should not *want* to use the session with multiple concurrent threads. That would be like having everyone at a restaurant all eat from the same plate. The session is a local "workspace" that you use for a specific set of tasks; you don't want to, or need to, share that session with other threads who are doing some other task. Making sure the :class:`.Session` is only used in a single concurrent thread at a time is called a "share nothing" approach to concurrency. But actually, not sharing the :class:`.Session` implies a more significant pattern; it means not just the :class:`.Session` object itself, but also **all objects that are associated with that Session**, must be kept within the scope of a single concurrent thread. The set of mapped objects associated with a :class:`.Session` are essentially proxies for data within database rows accessed over a database connection, and so just like the :class:`.Session` itself, the whole set of objects is really just a large-scale proxy for a database connection (or connections). Ultimately, it's mostly the DBAPI connection itself that we're keeping away from concurrent access; but since the :class:`.Session` and all the objects associated with it are all proxies for that DBAPI connection, the entire graph is essentially not safe for concurrent access. If there are in fact multiple threads participating in the same task, then you may consider sharing the session and its objects between those threads; however, in this extremely unusual scenario the application would need to ensure that a proper locking scheme is implemented so that there isn't *concurrent* access to the :class:`.Session` or its state. A more common approach to this situation is to maintain a single :class:`.Session` per concurrent thread, but to instead *copy* objects from one :class:`.Session` to another, often using the :meth:`.Session.merge` method to copy the state of an object into a new object local to a different :class:`.Session`. Querying -------- The :meth:`~.Session.query` function takes one or more *entities* and returns a new :class:`~sqlalchemy.orm.query.Query` object which will issue mapper queries within the context of this Session. An entity is defined as a mapped class, a :class:`~sqlalchemy.orm.mapper.Mapper` object, an orm-enabled *descriptor*, or an ``AliasedClass`` object:: # query from a class session.query(User).filter_by(name='ed').all() # query with multiple classes, returns tuples session.query(User, Address).join('addresses').filter_by(name='ed').all() # query using orm-enabled descriptors session.query(User.name, User.fullname).all() # query from a mapper user_mapper = class_mapper(User) session.query(user_mapper) When :class:`~sqlalchemy.orm.query.Query` returns results, each object instantiated is stored within the identity map. When a row matches an object which is already present, the same object is returned. In the latter case, whether or not the row is populated onto an existing object depends upon whether the attributes of the instance have been *expired* or not. A default-configured :class:`~sqlalchemy.orm.session.Session` automatically expires all instances along transaction boundaries, so that with a normally isolated transaction, there shouldn't be any issue of instances representing data which is stale with regards to the current transaction. The :class:`.Query` object is introduced in great detail in :ref:`ormtutorial_toplevel`, and further documented in :ref:`query_api_toplevel`. Adding New or Existing Items ---------------------------- :meth:`~.Session.add` is used to place instances in the session. For *transient* (i.e. brand new) instances, this will have the effect of an INSERT taking place for those instances upon the next flush. For instances which are *persistent* (i.e. were loaded by this session), they are already present and do not need to be added. Instances which are *detached* (i.e. have been removed from a session) may be re-associated with a session using this method:: user1 = User(name='user1') user2 = User(name='user2') session.add(user1) session.add(user2) session.commit() # write changes to the database To add a list of items to the session at once, use :meth:`~.Session.add_all`:: session.add_all([item1, item2, item3]) The :meth:`~.Session.add` operation **cascades** along the ``save-update`` cascade. For more details see the section :ref:`unitofwork_cascades`. .. _unitofwork_merging: Merging ------- :meth:`~.Session.merge` transfers state from an outside object into a new or already existing instance within a session. It also reconciles the incoming data against the state of the database, producing a history stream which will be applied towards the next flush, or alternatively can be made to produce a simple "transfer" of state without producing change history or accessing the database. Usage is as follows:: merged_object = session.merge(existing_object) When given an instance, it follows these steps: * It examines the primary key of the instance. If it's present, it attempts to locate that instance in the local identity map. If the ``load=True`` flag is left at its default, it also checks the database for this primary key if not located locally. * If the given instance has no primary key, or if no instance can be found with the primary key given, a new instance is created. * The state of the given instance is then copied onto the located/newly created instance. For attributes which are present on the source instance, the value is transferred to the target instance. For mapped attributes which aren't present on the source, the attribute is expired on the target instance, discarding its existing value. If the ``load=True`` flag is left at its default, this copy process emits events and will load the target object's unloaded collections for each attribute present on the source object, so that the incoming state can be reconciled against what's present in the database. If ``load`` is passed as ``False``, the incoming data is "stamped" directly without producing any history. * The operation is cascaded to related objects and collections, as indicated by the ``merge`` cascade (see :ref:`unitofwork_cascades`). * The new instance is returned. With :meth:`~.Session.merge`, the given "source" instance is not modifed nor is it associated with the target :class:`.Session`, and remains available to be merged with any number of other :class:`.Session` objects. :meth:`~.Session.merge` is useful for taking the state of any kind of object structure without regard for its origins or current session associations and copying its state into a new session. Here's some examples: * An application which reads an object structure from a file and wishes to save it to the database might parse the file, build up the structure, and then use :meth:`~.Session.merge` to save it to the database, ensuring that the data within the file is used to formulate the primary key of each element of the structure. Later, when the file has changed, the same process can be re-run, producing a slightly different object structure, which can then be ``merged`` in again, and the :class:`~sqlalchemy.orm.session.Session` will automatically update the database to reflect those changes, loading each object from the database by primary key and then updating its state with the new state given. * An application is storing objects in an in-memory cache, shared by many :class:`.Session` objects simultaneously. :meth:`~.Session.merge` is used each time an object is retrieved from the cache to create a local copy of it in each :class:`.Session` which requests it. The cached object remains detached; only its state is moved into copies of itself that are local to individual :class:`~.Session` objects. In the caching use case, it's common that the ``load=False`` flag is used to remove the overhead of reconciling the object's state with the database. There's also a "bulk" version of :meth:`~.Session.merge` called :meth:`~.Query.merge_result` that was designed to work with cache-extended :class:`.Query` objects - see the section :ref:`examples_caching`. * An application wants to transfer the state of a series of objects into a :class:`.Session` maintained by a worker thread or other concurrent system. :meth:`~.Session.merge` makes a copy of each object to be placed into this new :class:`.Session`. At the end of the operation, the parent thread/process maintains the objects it started with, and the thread/worker can proceed with local copies of those objects. In the "transfer between threads/processes" use case, the application may want to use the ``load=False`` flag as well to avoid overhead and redundant SQL queries as the data is transferred. Merge Tips ~~~~~~~~~~ :meth:`~.Session.merge` is an extremely useful method for many purposes. However, it deals with the intricate border between objects that are transient/detached and those that are persistent, as well as the automated transferrence of state. The wide variety of scenarios that can present themselves here often require a more careful approach to the state of objects. Common problems with merge usually involve some unexpected state regarding the object being passed to :meth:`~.Session.merge`. Lets use the canonical example of the User and Address objects:: class User(Base): __tablename__ = 'user' id = Column(Integer, primary_key=True) name = Column(String(50), nullable=False) addresses = relationship("Address", backref="user") class Address(Base): __tablename__ = 'address' id = Column(Integer, primary_key=True) email_address = Column(String(50), nullable=False) user_id = Column(Integer, ForeignKey('user.id'), nullable=False) Assume a ``User`` object with one ``Address``, already persistent:: >>> u1 = User(name='ed', addresses=[Address(email_address='ed@ed.com')]) >>> session.add(u1) >>> session.commit() We now create ``a1``, an object outside the session, which we'd like to merge on top of the existing ``Address``:: >>> existing_a1 = u1.addresses[0] >>> a1 = Address(id=existing_a1.id) A surprise would occur if we said this:: >>> a1.user = u1 >>> a1 = session.merge(a1) >>> session.commit() sqlalchemy.orm.exc.FlushError: New instance
with identity key (, (1,)) conflicts with persistent instance
Why is that ? We weren't careful with our cascades. The assignment of ``a1.user`` to a persistent object cascaded to the backref of ``User.addresses`` and made our ``a1`` object pending, as though we had added it. Now we have *two* ``Address`` objects in the session:: >>> a1 = Address() >>> a1.user = u1 >>> a1 in session True >>> existing_a1 in session True >>> a1 is existing_a1 False Above, our ``a1`` is already pending in the session. The subsequent :meth:`~.Session.merge` operation essentially does nothing. Cascade can be configured via the ``cascade`` option on :func:`.relationship`, although in this case it would mean removing the ``save-update`` cascade from the ``User.addresses`` relationship - and usually, that behavior is extremely convenient. The solution here would usually be to not assign ``a1.user`` to an object already persistent in the target session. The ``cascade_backrefs=False`` option of :func:`.relationship` will also prevent the ``Address`` from being added to the session via the ``a1.user = u1`` assignment. Further detail on cascade operation is at :ref:`unitofwork_cascades`. Another example of unexpected state:: >>> a1 = Address(id=existing_a1.id, user_id=u1.id) >>> assert a1.user is None >>> True >>> a1 = session.merge(a1) >>> session.commit() sqlalchemy.exc.IntegrityError: (IntegrityError) address.user_id may not be NULL Here, we accessed a1.user, which returned its default value of ``None``, which as a result of this access, has been placed in the ``__dict__`` of our object ``a1``. Normally, this operation creates no change event, so the ``user_id`` attribute takes precedence during a flush. But when we merge the ``Address`` object into the session, the operation is equivalent to:: >>> existing_a1.id = existing_a1.id >>> existing_a1.user_id = u1.id >>> existing_a1.user = None Where above, both ``user_id`` and ``user`` are assigned to, and change events are emitted for both. The ``user`` association takes precedence, and None is applied to ``user_id``, causing a failure. Most :meth:`~.Session.merge` issues can be examined by first checking - is the object prematurely in the session ? .. sourcecode:: python+sql >>> a1 = Address(id=existing_a1, user_id=user.id) >>> assert a1 not in session >>> a1 = session.merge(a1) Or is there state on the object that we don't want ? Examining ``__dict__`` is a quick way to check:: >>> a1 = Address(id=existing_a1, user_id=user.id) >>> a1.user >>> a1.__dict__ {'_sa_instance_state': , 'user_id': 1, 'id': 1, 'user': None} >>> # we don't want user=None merged, remove it >>> del a1.user >>> a1 = session.merge(a1) >>> # success >>> session.commit() Deleting -------- The :meth:`~.Session.delete` method places an instance into the Session's list of objects to be marked as deleted:: # mark two objects to be deleted session.delete(obj1) session.delete(obj2) # commit (or flush) session.commit() .. _session_deleting_from_collections: Deleting from Collections ~~~~~~~~~~~~~~~~~~~~~~~~~~ A common confusion that arises regarding :meth:`~.Session.delete` is when objects which are members of a collection are being deleted. While the collection member is marked for deletion from the database, this does not impact the collection itself in memory until the collection is expired. Below, we illustrate that even after an ``Address`` object is marked for deletion, it's still present in the collection associated with the parent ``User``, even after a flush:: >>> address = user.addresses[1] >>> session.delete(address) >>> session.flush() >>> address in user.addresses True When the above session is committed, all attributes are expired. The next access of ``user.addresses`` will re-load the collection, revealing the desired state:: >>> session.commit() >>> address in user.addresses False The usual practice of deleting items within collections is to forego the usage of :meth:`~.Session.delete` directly, and instead use cascade behavior to automatically invoke the deletion as a result of removing the object from the parent collection. The ``delete-orphan`` cascade accomplishes this, as illustrated in the example below:: mapper(User, users_table, properties={ 'addresses':relationship(Address, cascade="all, delete, delete-orphan") }) del user.addresses[1] session.flush() Where above, upon removing the ``Address`` object from the ``User.addresses`` collection, the ``delete-orphan`` cascade has the effect of marking the ``Address`` object for deletion in the same way as passing it to :meth:`~.Session.delete`. See also :ref:`unitofwork_cascades` for detail on cascades. Deleting based on Filter Criterion ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The caveat with ``Session.delete()`` is that you need to have an object handy already in order to delete. The Query includes a :func:`~sqlalchemy.orm.query.Query.delete` method which deletes based on filtering criteria:: session.query(User).filter(User.id==7).delete() The ``Query.delete()`` method includes functionality to "expire" objects already in the session which match the criteria. However it does have some caveats, including that "delete" and "delete-orphan" cascades won't be fully expressed for collections which are already loaded. See the API docs for :meth:`~sqlalchemy.orm.query.Query.delete` for more details. .. _session_flushing: Flushing -------- When the :class:`~sqlalchemy.orm.session.Session` is used with its default configuration, the flush step is nearly always done transparently. Specifically, the flush occurs before any individual :class:`~sqlalchemy.orm.query.Query` is issued, as well as within the :meth:`~.Session.commit` call before the transaction is committed. It also occurs before a SAVEPOINT is issued when :meth:`~.Session.begin_nested` is used. Regardless of the autoflush setting, a flush can always be forced by issuing :meth:`~.Session.flush`:: session.flush() The "flush-on-Query" aspect of the behavior can be disabled by constructing :class:`.sessionmaker` with the flag ``autoflush=False``:: Session = sessionmaker(autoflush=False) Additionally, autoflush can be temporarily disabled by setting the ``autoflush`` flag at any time:: mysession = Session() mysession.autoflush = False Some autoflush-disable recipes are available at `DisableAutoFlush `_. The flush process *always* occurs within a transaction, even if the :class:`~sqlalchemy.orm.session.Session` has been configured with ``autocommit=True``, a setting that disables the session's persistent transactional state. If no transaction is present, :meth:`~.Session.flush` creates its own transaction and commits it. Any failures during flush will always result in a rollback of whatever transaction is present. If the Session is not in ``autocommit=True`` mode, an explicit call to :meth:`~.Session.rollback` is required after a flush fails, even though the underlying transaction will have been rolled back already - this is so that the overall nesting pattern of so-called "subtransactions" is consistently maintained. .. _session_committing: Committing ---------- :meth:`~.Session.commit` is used to commit the current transaction. It always issues :meth:`~.Session.flush` beforehand to flush any remaining state to the database; this is independent of the "autoflush" setting. If no transaction is present, it raises an error. Note that the default behavior of the :class:`~sqlalchemy.orm.session.Session` is that a "transaction" is always present; this behavior can be disabled by setting ``autocommit=True``. In autocommit mode, a transaction can be initiated by calling the :meth:`~.Session.begin` method. .. note:: The term "transaction" here refers to a transactional construct within the :class:`.Session` itself which may be maintaining zero or more actual database (DBAPI) transactions. An individual DBAPI connection begins participation in the "transaction" as it is first used to execute a SQL statement, then remains present until the session-level "transaction" is completed. See :ref:`unitofwork_transaction` for further detail. Another behavior of :meth:`~.Session.commit` is that by default it expires the state of all instances present after the commit is complete. This is so that when the instances are next accessed, either through attribute access or by them being present in a :class:`~sqlalchemy.orm.query.Query` result set, they receive the most recent state. To disable this behavior, configure :class:`.sessionmaker` with ``expire_on_commit=False``. Normally, instances loaded into the :class:`~sqlalchemy.orm.session.Session` are never changed by subsequent queries; the assumption is that the current transaction is isolated so the state most recently loaded is correct as long as the transaction continues. Setting ``autocommit=True`` works against this model to some degree since the :class:`~sqlalchemy.orm.session.Session` behaves in exactly the same way with regard to attribute state, except no transaction is present. .. _session_rollback: Rolling Back ------------ :meth:`~.Session.rollback` rolls back the current transaction. With a default configured session, the post-rollback state of the session is as follows: * All transactions are rolled back and all connections returned to the connection pool, unless the Session was bound directly to a Connection, in which case the connection is still maintained (but still rolled back). * Objects which were initially in the *pending* state when they were added to the :class:`~sqlalchemy.orm.session.Session` within the lifespan of the transaction are expunged, corresponding to their INSERT statement being rolled back. The state of their attributes remains unchanged. * Objects which were marked as *deleted* within the lifespan of the transaction are promoted back to the *persistent* state, corresponding to their DELETE statement being rolled back. Note that if those objects were first *pending* within the transaction, that operation takes precedence instead. * All objects not expunged are fully expired. With that state understood, the :class:`~sqlalchemy.orm.session.Session` may safely continue usage after a rollback occurs. When a :meth:`~.Session.flush` fails, typically for reasons like primary key, foreign key, or "not nullable" constraint violations, a :meth:`~.Session.rollback` is issued automatically (it's currently not possible for a flush to continue after a partial failure). However, the flush process always uses its own transactional demarcator called a *subtransaction*, which is described more fully in the docstrings for :class:`~sqlalchemy.orm.session.Session`. What it means here is that even though the database transaction has been rolled back, the end user must still issue :meth:`~.Session.rollback` to fully reset the state of the :class:`~sqlalchemy.orm.session.Session`. Expunging --------- Expunge removes an object from the Session, sending persistent instances to the detached state, and pending instances to the transient state: .. sourcecode:: python+sql session.expunge(obj1) To remove all items, call :meth:`~.Session.expunge_all` (this method was formerly known as ``clear()``). Closing ------- The :meth:`~.Session.close` method issues a :meth:`~.Session.expunge_all`, and :term:`releases` any transactional/connection resources. When connections are returned to the connection pool, transactional state is rolled back as well. .. _session_expire: Refreshing / Expiring --------------------- :term:`Expiring` means that the database-persisted data held inside a series of object attributes is erased, in such a way that when those attributes are next accessed, a SQL query is emitted which will refresh that data from the database. When we talk about expiration of data we are usually talking about an object that is in the :term:`persistent` state. For example, if we load an object as follows:: user = session.query(User).filter_by(name='user1').first() The above ``User`` object is persistent, and has a series of attributes present; if we were to look inside its ``__dict__``, we'd see that state loaded:: >>> user.__dict__ { 'id': 1, 'name': u'user1', '_sa_instance_state': <...>, } where ``id`` and ``name`` refer to those columns in the database. ``_sa_instance_state`` is a non-database-persisted value used by SQLAlchemy internally (it refers to the :class:`.InstanceState` for the instance. While not directly relevant to this section, if we want to get at it, we should use the :func:`.inspect` function to access it). At this point, the state in our ``User`` object matches that of the loaded database row. But upon expiring the object using a method such as :meth:`.Session.expire`, we see that the state is removed:: >>> session.expire(user) >>> user.__dict__ {'_sa_instance_state': <...>} We see that while the internal "state" still hangs around, the values which correspond to the ``id`` and ``name`` columns are gone. If we were to access one of these columns and are watching SQL, we'd see this: .. sourcecode:: python+sql >>> print(user.name) {opensql}SELECT user.id AS user_id, user.name AS user_name FROM user WHERE user.id = ? (1,) {stop}user1 Above, upon accessing the expired attribute ``user.name``, the ORM initiated a :term:`lazy load` to retrieve the most recent state from the database, by emitting a SELECT for the user row to which this user refers. Afterwards, the ``__dict__`` is again populated:: >>> user.__dict__ { 'id': 1, 'name': u'user1', '_sa_instance_state': <...>, } .. note:: While we are peeking inside of ``__dict__`` in order to see a bit of what SQLAlchemy does with object attributes, we **should not modify** the contents of ``__dict__`` directly, at least as far as those attributes which the SQLAlchemy ORM is maintaining (other attributes outside of SQLA's realm are fine). This is because SQLAlchemy uses :term:`descriptors` in order to track the changes we make to an object, and when we modify ``__dict__`` directly, the ORM won't be able to track that we changed something. Another key behavior of both :meth:`~.Session.expire` and :meth:`~.Session.refresh` is that all un-flushed changes on an object are discarded. That is, if we were to modify an attribute on our ``User``:: >>> user.name = 'user2' but then we call :meth:`~.Session.expire` without first calling :meth:`~.Session.flush`, our pending value of ``'user2'`` is discarded:: >>> session.expire(user) >>> user.name 'user1' The :meth:`~.Session.expire` method can be used to mark as "expired" all ORM-mapped attributes for an instance:: # expire all ORM-mapped attributes on obj1 session.expire(obj1) it can also be passed a list of string attribute names, referring to specific attributes to be marked as expired:: # expire only attributes obj1.attr1, obj1.attr2 session.expire(obj1, ['attr1', 'attr2']) The :meth:`~.Session.refresh` method has a similar interface, but instead of expiring, it emits an immediate SELECT for the object's row immediately:: # reload all attributes on obj1 session.refresh(obj1) :meth:`~.Session.refresh` also accepts a list of string attribute names, but unlike :meth:`~.Session.expire`, expects at least one name to be that of a column-mapped attribute:: # reload obj1.attr1, obj1.attr2 session.refresh(obj1, ['attr1', 'attr2']) The :meth:`.Session.expire_all` method allows us to essentially call :meth:`.Session.expire` on all objects contained within the :class:`.Session` at once:: session.expire_all() What Actually Loads ~~~~~~~~~~~~~~~~~~~ The SELECT statement that's emitted when an object marked with :meth:`~.Session.expire` or loaded with :meth:`~.Session.refresh` varies based on several factors, including: * The load of expired attributes is triggered from **column-mapped attributes only**. While any kind of attribute can be marked as expired, including a :func:`.relationship` - mapped attribute, accessing an expired :func:`.relationship` attribute will emit a load only for that attribute, using standard relationship-oriented lazy loading. Column-oriented attributes, even if expired, will not load as part of this operation, and instead will load when any column-oriented attribute is accessed. * :func:`.relationship`- mapped attributes will not load in response to expired column-based attributes being accessed. * Regarding relationships, :meth:`~.Session.refresh` is more restrictive than :meth:`~.Session.expire` with regards to attributes that aren't column-mapped. Calling :meth:`.refresh` and passing a list of names that only includes relationship-mapped attributes will actually raise an error. In any case, non-eager-loading :func:`.relationship` attributes will not be included in any refresh operation. * :func:`.relationship` attributes configured as "eager loading" via the :paramref:`~.relationship.lazy` parameter will load in the case of :meth:`~.Session.refresh`, if either no attribute names are specified, or if their names are inclued in the list of attributes to be refreshed. * Attributes that are configured as :func:`.deferred` will not normally load, during either the expired-attribute load or during a refresh. An unloaded attribute that's :func:`.deferred` instead loads on its own when directly accessed, or if part of a "group" of deferred attributes where an unloaded attribute in that group is accessed. * For expired attributes that are loaded on access, a joined-inheritance table mapping will emit a SELECT that typically only includes those tables for which unloaded attributes are present. The action here is sophisticated enough to load only the parent or child table, for example, if the subset of columns that were originally expired encompass only one or the other of those tables. * When :meth:`~.Session.refresh` is used on a joined-inheritance table mapping, the SELECT emitted will resemble that of when :meth:`.Session.query` is used on the target object's class. This is typically all those tables that are set up as part of the mapping. When to Expire or Refresh ~~~~~~~~~~~~~~~~~~~~~~~~~~ The :class:`.Session` uses the expiration feature automatically whenever the transaction referred to by the session ends. Meaning, whenever :meth:`.Session.commit` or :meth:`.Session.rollback` is called, all objects within the :class:`.Session` are expired, using a feature equivalent to that of the :meth:`.Session.expire_all` method. The rationale is that the end of a transaction is a demarcating point at which there is no more context available in order to know what the current state of the database is, as any number of other transactions may be affecting it. Only when a new transaction starts can we again have access to the current state of the database, at which point any number of changes may have occurred. .. sidebar:: Transaction Isolation Of course, most databases are capable of handling multiple transactions at once, even involving the same rows of data. When a relational database handles multiple transactions involving the same tables or rows, this is when the :term:`isolation` aspect of the database comes into play. The isolation behavior of different databases varies considerably and even on a single database can be configured to behave in different ways (via the so-called :term:`isolation level` setting). In that sense, the :class:`.Session` can't fully predict when the same SELECT statement, emitted a second time, will definitely return the data we already have, or will return new data. So as a best guess, it assumes that within the scope of a transaction, unless it is known that a SQL expression has been emitted to modify a particular row, there's no need to refresh a row unless explicitly told to do so. The :meth:`.Session.expire` and :meth:`.Session.refresh` methods are used in those cases when one wants to force an object to re-load its data from the database, in those cases when it is known that the current state of data is possibly stale. Reasons for this might include: * some SQL has been emitted within the transaction outside of the scope of the ORM's object handling, such as if a :meth:`.Table.update` construct were emitted using the :meth:`.Session.execute` method; * if the application is attempting to acquire data that is known to have been modified in a concurrent transaction, and it is also known that the isolation rules in effect allow this data to be visible. The second bullet has the important caveat that "it is also known that the isolation rules in effect allow this data to be visible." This means that it cannot be assumed that an UPDATE that happened on another database connection will yet be visible here locally; in many cases, it will not. This is why if one wishes to use :meth:`.expire` or :meth:`.refresh` in order to view data between ongoing transactions, an understanding of the isolation behavior in effect is essential. .. seealso:: :meth:`.Session.expire` :meth:`.Session.expire_all` :meth:`.Session.refresh` :term:`isolation` - glossary explanation of isolation which includes links to Wikipedia. `The SQLAlchemy Session In-Depth `_ - a video + slides with an in-depth discussion of the object lifecycle including the role of data expiration. Session Attributes ------------------ The :class:`~sqlalchemy.orm.session.Session` itself acts somewhat like a set-like collection. All items present may be accessed using the iterator interface:: for obj in session: print obj And presence may be tested for using regular "contains" semantics:: if obj in session: print "Object is present" The session is also keeping track of all newly created (i.e. pending) objects, all objects which have had changes since they were last loaded or saved (i.e. "dirty"), and everything that's been marked as deleted:: # pending objects recently added to the Session session.new # persistent objects which currently have changes detected # (this collection is now created on the fly each time the property is called) session.dirty # persistent objects that have been marked as deleted via session.delete(obj) session.deleted # dictionary of all persistent objects, keyed on their # identity key session.identity_map (Documentation: :attr:`.Session.new`, :attr:`.Session.dirty`, :attr:`.Session.deleted`, :attr:`.Session.identity_map`). Note that objects within the session are by default *weakly referenced*. This means that when they are dereferenced in the outside application, they fall out of scope from within the :class:`~sqlalchemy.orm.session.Session` as well and are subject to garbage collection by the Python interpreter. The exceptions to this include objects which are pending, objects which are marked as deleted, or persistent objects which have pending changes on them. After a full flush, these collections are all empty, and all objects are again weakly referenced. To disable the weak referencing behavior and force all objects within the session to remain until explicitly expunged, configure :class:`.sessionmaker` with the ``weak_identity_map=False`` setting. .. _unitofwork_cascades: Cascades ======== Mappers support the concept of configurable **cascade** behavior on :func:`~sqlalchemy.orm.relationship` constructs. This refers to how operations performed on a parent object relative to a particular :class:`.Session` should be propagated to items referred to by that relationship. The default cascade behavior is usually suitable for most situations, and the option is normally invoked explicitly in order to enable ``delete`` and ``delete-orphan`` cascades, which refer to how the relationship should be treated when the parent is marked for deletion as well as when a child is de-associated from its parent. Cascade behavior is configured by setting the ``cascade`` keyword argument on :func:`~sqlalchemy.orm.relationship`:: class Order(Base): __tablename__ = 'order' items = relationship("Item", cascade="all, delete-orphan") customer = relationship("User", secondary=user_orders_table, cascade="save-update") To set cascades on a backref, the same flag can be used with the :func:`~.sqlalchemy.orm.backref` function, which ultimately feeds its arguments back into :func:`~sqlalchemy.orm.relationship`:: class Item(Base): __tablename__ = 'item' order = relationship("Order", backref=backref("items", cascade="all, delete-orphan") ) The default value of ``cascade`` is ``save-update, merge``. The ``all`` symbol in the cascade options indicates that all cascade flags should be enabled, with the exception of ``delete-orphan``. Typically, cascade is usually left at its default, or configured as ``all, delete-orphan``, indicating the child objects should be treated as "owned" by the parent. The list of available values which can be specified in ``cascade`` are as follows: * ``save-update`` - Indicates that when an object is placed into a :class:`.Session` via :meth:`.Session.add`, all the objects associated with it via this :func:`~sqlalchemy.orm.relationship` should also be added to that same :class:`.Session`. Additionally, if this object is already present in a :class:`.Session`, child objects will be added to that session as they are associated with this parent, i.e. as they are appended to lists, added to sets, or otherwise associated with the parent. ``save-update`` cascade also cascades the *pending history* of the target attribute, meaning that objects which were removed from a scalar or collection attribute whose changes have not yet been flushed are also placed into the target session. This is because they may have foreign key attributes present which will need to be updated to no longer refer to the parent. The ``save-update`` cascade is on by default, and it's common to not even be aware of it. It's customary that only a single call to :meth:`.Session.add` against the lead object of a structure has the effect of placing the full structure of objects into the :class:`.Session` at once. However, it can be turned off, which would imply that objects associated with a parent would need to be placed individually using :meth:`.Session.add` calls for each one. Another default behavior of ``save-update`` cascade is that it will take effect in the reverse direction, that is, associating a child with a parent when a backref is present means both relationships are affected; the parent will be added to the child's session. To disable this somewhat indirect session addition, use the ``cascade_backrefs=False`` option described below in :ref:`backref_cascade`. * ``delete`` - This cascade indicates that when the parent object is marked for deletion, the related objects should also be marked for deletion. Without this cascade present, SQLAlchemy will set the foreign key on a one-to-many relationship to NULL when the parent object is deleted. When enabled, the row is instead deleted. ``delete`` cascade is often used in conjunction with ``delete-orphan`` cascade, as is appropriate for an object whose foreign key is not intended to be nullable. On some backends, it's also a good idea to set ``ON DELETE`` on the foreign key itself; see the section :ref:`passive_deletes` for more details. Note that for many-to-many relationships which make usage of the ``secondary`` argument to :func:`~.sqlalchemy.orm.relationship`, SQLAlchemy always emits a DELETE for the association row in between "parent" and "child", when the parent is deleted or whenever the linkage between a particular parent and child is broken. * ``delete-orphan`` - This cascade adds behavior to the ``delete`` cascade, such that a child object will be marked for deletion when it is de-associated from the parent, not just when the parent is marked for deletion. This is a common feature when dealing with a related object that is "owned" by its parent, with a NOT NULL foreign key, so that removal of the item from the parent collection results in its deletion. ``delete-orphan`` cascade implies that each child object can only have one parent at a time, so is configured in the vast majority of cases on a one-to-many relationship. Setting it on a many-to-one or many-to-many relationship is more awkward; for this use case, SQLAlchemy requires that the :func:`~sqlalchemy.orm.relationship` be configured with the :paramref:`~.relationship.single_parent` argument, establishes Python-side validation that ensures the object is associated with only one parent at a time. * ``merge`` - This cascade indicates that the :meth:`.Session.merge` operation should be propagated from a parent that's the subject of the :meth:`.Session.merge` call down to referred objects. This cascade is also on by default. * ``refresh-expire`` - A less common option, indicates that the :meth:`.Session.expire` operation should be propagated from a parent down to referred objects. When using :meth:`.Session.refresh`, the referred objects are expired only, but not actually refreshed. * ``expunge`` - Indicate that when the parent object is removed from the :class:`.Session` using :meth:`.Session.expunge`, the operation should be propagated down to referred objects. .. _backref_cascade: Controlling Cascade on Backrefs ------------------------------- The ``save-update`` cascade takes place on backrefs by default. This means that, given a mapping such as this:: mapper(Order, order_table, properties={ 'items' : relationship(Item, backref='order') }) If an ``Order`` is already in the session, and is assigned to the ``order`` attribute of an ``Item``, the backref appends the ``Order`` to the ``items`` collection of that ``Order``, resulting in the ``save-update`` cascade taking place:: >>> o1 = Order() >>> session.add(o1) >>> o1 in session True >>> i1 = Item() >>> i1.order = o1 >>> i1 in o1.items True >>> i1 in session True This behavior can be disabled using the :paramref:`~.relationship.cascade_backrefs` flag:: mapper(Order, order_table, properties={ 'items' : relationship(Item, backref='order', cascade_backrefs=False) }) So above, the assignment of ``i1.order = o1`` will append ``i1`` to the ``items`` collection of ``o1``, but will not add ``i1`` to the session. You can, of course, :meth:`~.Session.add` ``i1`` to the session at a later point. This option may be helpful for situations where an object needs to be kept out of a session until it's construction is completed, but still needs to be given associations to objects which are already persistent in the target session. .. _unitofwork_transaction: Managing Transactions ===================== A newly constructed :class:`.Session` may be said to be in the "begin" state. In this state, the :class:`.Session` has not established any connection or transactional state with any of the :class:`.Engine` objects that may be associated with it. The :class:`.Session` then receives requests to operate upon a database connection. Typically, this means it is called upon to execute SQL statements using a particular :class:`.Engine`, which may be via :meth:`.Session.query`, :meth:`.Session.execute`, or within a flush operation of pending data, which occurs when such state exists and :meth:`.Session.commit` or :meth:`.Session.flush` is called. As these requests are received, each new :class:`.Engine` encountered is associated with an ongoing transactional state maintained by the :class:`.Session`. When the first :class:`.Engine` is operated upon, the :class:`.Session` can be said to have left the "begin" state and entered "transactional" state. For each :class:`.Engine` encountered, a :class:`.Connection` is associated with it, which is acquired via the :meth:`.Engine.contextual_connect` method. If a :class:`.Connection` was directly associated with the :class:`.Session` (see :ref:`session_external_transaction` for an example of this), it is added to the transactional state directly. For each :class:`.Connection`, the :class:`.Session` also maintains a :class:`.Transaction` object, which is acquired by calling :meth:`.Connection.begin` on each :class:`.Connection`, or if the :class:`.Session` object has been established using the flag ``twophase=True``, a :class:`.TwoPhaseTransaction` object acquired via :meth:`.Connection.begin_twophase`. These transactions are all committed or rolled back corresponding to the invocation of the :meth:`.Session.commit` and :meth:`.Session.rollback` methods. A commit operation will also call the :meth:`.TwoPhaseTransaction.prepare` method on all transactions if applicable. When the transactional state is completed after a rollback or commit, the :class:`.Session` :term:`releases` all :class:`.Transaction` and :class:`.Connection` resources, and goes back to the "begin" state, which will again invoke new :class:`.Connection` and :class:`.Transaction` objects as new requests to emit SQL statements are received. The example below illustrates this lifecycle:: engine = create_engine("...") Session = sessionmaker(bind=engine) # new session. no connections are in use. session = Session() try: # first query. a Connection is acquired # from the Engine, and a Transaction # started. item1 = session.query(Item).get(1) # second query. the same Connection/Transaction # are used. item2 = session.query(Item).get(2) # pending changes are created. item1.foo = 'bar' item2.bar = 'foo' # commit. The pending changes above # are flushed via flush(), the Transaction # is committed, the Connection object closed # and discarded, the underlying DBAPI connection # returned to the connection pool. session.commit() except: # on rollback, the same closure of state # as that of commit proceeds. session.rollback() raise .. _session_begin_nested: Using SAVEPOINT --------------- SAVEPOINT transactions, if supported by the underlying engine, may be delineated using the :meth:`~.Session.begin_nested` method:: Session = sessionmaker() session = Session() session.add(u1) session.add(u2) session.begin_nested() # establish a savepoint session.add(u3) session.rollback() # rolls back u3, keeps u1 and u2 session.commit() # commits u1 and u2 :meth:`~.Session.begin_nested` may be called any number of times, which will issue a new SAVEPOINT with a unique identifier for each call. For each :meth:`~.Session.begin_nested` call, a corresponding :meth:`~.Session.rollback` or :meth:`~.Session.commit` must be issued. When :meth:`~.Session.begin_nested` is called, a :meth:`~.Session.flush` is unconditionally issued (regardless of the ``autoflush`` setting). This is so that when a :meth:`~.Session.rollback` occurs, the full state of the session is expired, thus causing all subsequent attribute/instance access to reference the full state of the :class:`~sqlalchemy.orm.session.Session` right before :meth:`~.Session.begin_nested` was called. :meth:`~.Session.begin_nested`, in the same manner as the less often used :meth:`~.Session.begin` method, returns a transactional object which also works as a context manager. It can be succinctly used around individual record inserts in order to catch things like unique constraint exceptions:: for record in records: try: with session.begin_nested(): session.merge(record) except: print "Skipped record %s" % record session.commit() .. _session_autocommit: Autocommit Mode --------------- The example of :class:`.Session` transaction lifecycle illustrated at the start of :ref:`unitofwork_transaction` applies to a :class:`.Session` configured in the default mode of ``autocommit=False``. Constructing a :class:`.Session` with ``autocommit=True`` produces a :class:`.Session` placed into "autocommit" mode, where each SQL statement invoked by a :meth:`.Session.query` or :meth:`.Session.execute` occurs using a new connection from the connection pool, discarding it after results have been iterated. The :meth:`.Session.flush` operation still occurs within the scope of a single transaction, though this transaction is closed out after the :meth:`.Session.flush` operation completes. .. warning:: "autocommit" mode should **not be considered for general use**. If used, it should always be combined with the usage of :meth:`.Session.begin` and :meth:`.Session.commit`, to ensure a transaction demarcation. Executing queries outside of a demarcated transaction is a legacy mode of usage, and can in some cases lead to concurrent connection checkouts. In the absense of a demarcated transaction, the :class:`.Session` cannot make appropriate decisions as to when autoflush should occur nor when auto-expiration should occur, so these features should be disabled with ``autoflush=False, expire_on_commit=False``. Modern usage of "autocommit" is for framework integrations that need to control specifically when the "begin" state occurs. A session which is configured with ``autocommit=True`` may be placed into the "begin" state using the :meth:`.Session.begin` method. After the cycle completes upon :meth:`.Session.commit` or :meth:`.Session.rollback`, connection and transaction resources are :term:`released` and the :class:`.Session` goes back into "autocommit" mode, until :meth:`.Session.begin` is called again:: Session = sessionmaker(bind=engine, autocommit=True) session = Session() session.begin() try: item1 = session.query(Item).get(1) item2 = session.query(Item).get(2) item1.foo = 'bar' item2.bar = 'foo' session.commit() except: session.rollback() raise The :meth:`.Session.begin` method also returns a transactional token which is compatible with the Python 2.6 ``with`` statement:: Session = sessionmaker(bind=engine, autocommit=True) session = Session() with session.begin(): item1 = session.query(Item).get(1) item2 = session.query(Item).get(2) item1.foo = 'bar' item2.bar = 'foo' .. _session_subtransactions: Using Subtransactions with Autocommit ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ A subtransaction indicates usage of the :meth:`.Session.begin` method in conjunction with the ``subtransactions=True`` flag. This produces a non-transactional, delimiting construct that allows nesting of calls to :meth:`~.Session.begin` and :meth:`~.Session.commit`. It's purpose is to allow the construction of code that can function within a transaction both independently of any external code that starts a transaction, as well as within a block that has already demarcated a transaction. ``subtransactions=True`` is generally only useful in conjunction with autocommit, and is equivalent to the pattern described at :ref:`connections_nested_transactions`, where any number of functions can call :meth:`.Connection.begin` and :meth:`.Transaction.commit` as though they are the initiator of the transaction, but in fact may be participating in an already ongoing transaction:: # method_a starts a transaction and calls method_b def method_a(session): session.begin(subtransactions=True) try: method_b(session) session.commit() # transaction is committed here except: session.rollback() # rolls back the transaction raise # method_b also starts a transaction, but when # called from method_a participates in the ongoing # transaction. def method_b(session): session.begin(subtransactions=True) try: session.add(SomeObject('bat', 'lala')) session.commit() # transaction is not committed yet except: session.rollback() # rolls back the transaction, in this case # the one that was initiated in method_a(). raise # create a Session and call method_a session = Session(autocommit=True) method_a(session) session.close() Subtransactions are used by the :meth:`.Session.flush` process to ensure that the flush operation takes place within a transaction, regardless of autocommit. When autocommit is disabled, it is still useful in that it forces the :class:`.Session` into a "pending rollback" state, as a failed flush cannot be resumed in mid-operation, where the end user still maintains the "scope" of the transaction overall. .. _session_twophase: Enabling Two-Phase Commit ------------------------- For backends which support two-phase operaration (currently MySQL and PostgreSQL), the session can be instructed to use two-phase commit semantics. This will coordinate the committing of transactions across databases so that the transaction is either committed or rolled back in all databases. You can also :meth:`~.Session.prepare` the session for interacting with transactions not managed by SQLAlchemy. To use two phase transactions set the flag ``twophase=True`` on the session:: engine1 = create_engine('postgresql://db1') engine2 = create_engine('postgresql://db2') Session = sessionmaker(twophase=True) # bind User operations to engine 1, Account operations to engine 2 Session.configure(binds={User:engine1, Account:engine2}) session = Session() # .... work with accounts and users # commit. session will issue a flush to all DBs, and a prepare step to all DBs, # before committing both transactions session.commit() Embedding SQL Insert/Update Expressions into a Flush ===================================================== This feature allows the value of a database column to be set to a SQL expression instead of a literal value. It's especially useful for atomic updates, calling stored procedures, etc. All you do is assign an expression to an attribute:: class SomeClass(object): pass mapper(SomeClass, some_table) someobject = session.query(SomeClass).get(5) # set 'value' attribute to a SQL expression adding one someobject.value = some_table.c.value + 1 # issues "UPDATE some_table SET value=value+1" session.commit() This technique works both for INSERT and UPDATE statements. After the flush/commit operation, the ``value`` attribute on ``someobject`` above is expired, so that when next accessed the newly generated value will be loaded from the database. .. _session_sql_expressions: Using SQL Expressions with Sessions ==================================== SQL expressions and strings can be executed via the :class:`~sqlalchemy.orm.session.Session` within its transactional context. This is most easily accomplished using the :meth:`~.Session.execute` method, which returns a :class:`~sqlalchemy.engine.ResultProxy` in the same manner as an :class:`~sqlalchemy.engine.Engine` or :class:`~sqlalchemy.engine.Connection`:: Session = sessionmaker(bind=engine) session = Session() # execute a string statement result = session.execute("select * from table where id=:id", {'id':7}) # execute a SQL expression construct result = session.execute(select([mytable]).where(mytable.c.id==7)) The current :class:`~sqlalchemy.engine.Connection` held by the :class:`~sqlalchemy.orm.session.Session` is accessible using the :meth:`~.Session.connection` method:: connection = session.connection() The examples above deal with a :class:`~sqlalchemy.orm.session.Session` that's bound to a single :class:`~sqlalchemy.engine.Engine` or :class:`~sqlalchemy.engine.Connection`. To execute statements using a :class:`~sqlalchemy.orm.session.Session` which is bound either to multiple engines, or none at all (i.e. relies upon bound metadata), both :meth:`~.Session.execute` and :meth:`~.Session.connection` accept a ``mapper`` keyword argument, which is passed a mapped class or :class:`~sqlalchemy.orm.mapper.Mapper` instance, which is used to locate the proper context for the desired engine:: Session = sessionmaker() session = Session() # need to specify mapper or class when executing result = session.execute("select * from table where id=:id", {'id':7}, mapper=MyMappedClass) result = session.execute(select([mytable], mytable.c.id==7), mapper=MyMappedClass) connection = session.connection(MyMappedClass) .. _session_external_transaction: Joining a Session into an External Transaction (such as for test suites) ======================================================================== If a :class:`.Connection` is being used which is already in a transactional state (i.e. has a :class:`.Transaction` established), a :class:`.Session` can be made to participate within that transaction by just binding the :class:`.Session` to that :class:`.Connection`. The usual rationale for this is a test suite that allows ORM code to work freely with a :class:`.Session`, including the ability to call :meth:`.Session.commit`, where afterwards the entire database interaction is rolled back:: from sqlalchemy.orm import sessionmaker from sqlalchemy import create_engine from unittest import TestCase # global application scope. create Session class, engine Session = sessionmaker() engine = create_engine('postgresql://...') class SomeTest(TestCase): def setUp(self): # connect to the database self.connection = engine.connect() # begin a non-ORM transaction self.trans = connection.begin() # bind an individual Session to the connection self.session = Session(bind=self.connection) def test_something(self): # use the session in tests. self.session.add(Foo()) self.session.commit() def tearDown(self): self.session.close() # rollback - everything that happened with the # Session above (including calls to commit()) # is rolled back. self.trans.rollback() # return connection to the Engine self.connection.close() Above, we issue :meth:`.Session.commit` as well as :meth:`.Transaction.rollback`. This is an example of where we take advantage of the :class:`.Connection` object's ability to maintain *subtransactions*, or nested begin/commit-or-rollback pairs where only the outermost begin/commit pair actually commits the transaction, or if the outermost block rolls back, everything is rolled back. .. topic:: Supporting Tests with Rollbacks The above recipe works well for any kind of database enabled test, except for a test that needs to actually invoke :meth:`.Session.rollback` within the scope of the test itself. The above recipe can be expanded, such that the :class:`.Session` always runs all operations within the scope of a SAVEPOINT, which is established at the start of each transaction, so that tests can also rollback the "transaction" as well while still remaining in the scope of a larger "transaction" that's never committed, using two extra events:: from sqlalchemy import event class SomeTest(TestCase): def setUp(self): # connect to the database self.connection = engine.connect() # begin a non-ORM transaction self.trans = connection.begin() # bind an individual Session to the connection self.session = Session(bind=self.connection) # start the session in a SAVEPOINT... self.session.begin_nested() # then each time that SAVEPOINT ends, reopen it @event.listens_for(self.session, "after_transaction_end") def restart_savepoint(session, transaction): if transaction.nested and not transaction._parent.nested: session.begin_nested() # ... the tearDown() method stays the same .. _unitofwork_contextual: Contextual/Thread-local Sessions ================================= Recall from the section :ref:`session_faq_whentocreate`, the concept of "session scopes" was introduced, with an emphasis on web applications and the practice of linking the scope of a :class:`.Session` with that of a web request. Most modern web frameworks include integration tools so that the scope of the :class:`.Session` can be managed automatically, and these tools should be used as they are available. SQLAlchemy includes its own helper object, which helps with the establishment of user-defined :class:`.Session` scopes. It is also used by third-party integration systems to help construct their integration schemes. The object is the :class:`.scoped_session` object, and it represents a **registry** of :class:`.Session` objects. If you're not familiar with the registry pattern, a good introduction can be found in `Patterns of Enterprise Architecture `_. .. note:: The :class:`.scoped_session` object is a very popular and useful object used by many SQLAlchemy applications. However, it is important to note that it presents **only one approach** to the issue of :class:`.Session` management. If you're new to SQLAlchemy, and especially if the term "thread-local variable" seems strange to you, we recommend that if possible you familiarize first with an off-the-shelf integration system such as `Flask-SQLAlchemy `_ or `zope.sqlalchemy `_. A :class:`.scoped_session` is constructed by calling it, passing it a **factory** which can create new :class:`.Session` objects. A factory is just something that produces a new object when called, and in the case of :class:`.Session`, the most common factory is the :class:`.sessionmaker`, introduced earlier in this section. Below we illustrate this usage:: >>> from sqlalchemy.orm import scoped_session >>> from sqlalchemy.orm import sessionmaker >>> session_factory = sessionmaker(bind=some_engine) >>> Session = scoped_session(session_factory) The :class:`.scoped_session` object we've created will now call upon the :class:`.sessionmaker` when we "call" the registry:: >>> some_session = Session() Above, ``some_session`` is an instance of :class:`.Session`, which we can now use to talk to the database. This same :class:`.Session` is also present within the :class:`.scoped_session` registry we've created. If we call upon the registry a second time, we get back the **same** :class:`.Session`:: >>> some_other_session = Session() >>> some_session is some_other_session True This pattern allows disparate sections of the application to call upon a global :class:`.scoped_session`, so that all those areas may share the same session without the need to pass it explicitly. The :class:`.Session` we've established in our registry will remain, until we explicitly tell our registry to dispose of it, by calling :meth:`.scoped_session.remove`:: >>> Session.remove() The :meth:`.scoped_session.remove` method first calls :meth:`.Session.close` on the current :class:`.Session`, which has the effect of releasing any connection/transactional resources owned by the :class:`.Session` first, then discarding the :class:`.Session` itself. "Releasing" here means that connections are returned to their connection pool and any transactional state is rolled back, ultimately using the ``rollback()`` method of the underlying DBAPI connection. At this point, the :class:`.scoped_session` object is "empty", and will create a **new** :class:`.Session` when called again. As illustrated below, this is not the same :class:`.Session` we had before:: >>> new_session = Session() >>> new_session is some_session False The above series of steps illustrates the idea of the "registry" pattern in a nutshell. With that basic idea in hand, we can discuss some of the details of how this pattern proceeds. Implicit Method Access ---------------------- The job of the :class:`.scoped_session` is simple; hold onto a :class:`.Session` for all who ask for it. As a means of producing more transparent access to this :class:`.Session`, the :class:`.scoped_session` also includes **proxy behavior**, meaning that the registry itself can be treated just like a :class:`.Session` directly; when methods are called on this object, they are **proxied** to the underlying :class:`.Session` being maintained by the registry:: Session = scoped_session(some_factory) # equivalent to: # # session = Session() # print session.query(MyClass).all() # print Session.query(MyClass).all() The above code accomplishes the same task as that of acquiring the current :class:`.Session` by calling upon the registry, then using that :class:`.Session`. Thread-Local Scope ------------------ Users who are familiar with multithreaded programming will note that representing anything as a global variable is usually a bad idea, as it implies that the global object will be accessed by many threads concurrently. The :class:`.Session` object is entirely designed to be used in a **non-concurrent** fashion, which in terms of multithreading means "only in one thread at a time". So our above example of :class:`.scoped_session` usage, where the same :class:`.Session` object is maintained across multiple calls, suggests that some process needs to be in place such that mutltiple calls across many threads don't actually get a handle to the same session. We call this notion **thread local storage**, which means, a special object is used that will maintain a distinct object per each application thread. Python provides this via the `threading.local() `_ construct. The :class:`.scoped_session` object by default uses this object as storage, so that a single :class:`.Session` is maintained for all who call upon the :class:`.scoped_session` registry, but only within the scope of a single thread. Callers who call upon the registry in a different thread get a :class:`.Session` instance that is local to that other thread. Using this technique, the :class:`.scoped_session` provides a quick and relatively simple (if one is familiar with thread-local storage) way of providing a single, global object in an application that is safe to be called upon from multiple threads. The :meth:`.scoped_session.remove` method, as always, removes the current :class:`.Session` associated with the thread, if any. However, one advantage of the ``threading.local()`` object is that if the application thread itself ends, the "storage" for that thread is also garbage collected. So it is in fact "safe" to use thread local scope with an application that spawns and tears down threads, without the need to call :meth:`.scoped_session.remove`. However, the scope of transactions themselves, i.e. ending them via :meth:`.Session.commit` or :meth:`.Session.rollback`, will usually still be something that must be explicitly arranged for at the appropriate time, unless the application actually ties the lifespan of a thread to the lifespan of a transaction. .. _session_lifespan: Using Thread-Local Scope with Web Applications ---------------------------------------------- As discussed in the section :ref:`session_faq_whentocreate`, a web application is architected around the concept of a **web request**, and integrating such an application with the :class:`.Session` usually implies that the :class:`.Session` will be associated with that request. As it turns out, most Python web frameworks, with notable exceptions such as the asynchronous frameworks Twisted and Tornado, use threads in a simple way, such that a particular web request is received, processed, and completed within the scope of a single *worker thread*. When the request ends, the worker thread is released to a pool of workers where it is available to handle another request. This simple correspondence of web request and thread means that to associate a :class:`.Session` with a thread implies it is also associated with the web request running within that thread, and vice versa, provided that the :class:`.Session` is created only after the web request begins and torn down just before the web request ends. So it is a common practice to use :class:`.scoped_session` as a quick way to integrate the :class:`.Session` with a web application. The sequence diagram below illustrates this flow:: Web Server Web Framework SQLAlchemy ORM Code -------------- -------------- ------------------------------ startup -> Web framework # Session registry is established initializes Session = scoped_session(sessionmaker()) incoming web request -> web request -> # The registry is *optionally* starts # called upon explicitly to create # a Session local to the thread and/or request Session() # the Session registry can otherwise # be used at any time, creating the # request-local Session() if not present, # or returning the existing one Session.query(MyClass) # ... Session.add(some_object) # ... # if data was modified, commit the # transaction Session.commit() web request ends -> # the registry is instructed to # remove the Session Session.remove() sends output <- outgoing web <- response Using the above flow, the process of integrating the :class:`.Session` with the web application has exactly two requirements: 1. Create a single :class:`.scoped_session` registry when the web application first starts, ensuring that this object is accessible by the rest of the application. 2. Ensure that :meth:`.scoped_session.remove` is called when the web request ends, usually by integrating with the web framework's event system to establish an "on request end" event. As noted earlier, the above pattern is **just one potential way** to integrate a :class:`.Session` with a web framework, one which in particular makes the significant assumption that the **web framework associates web requests with application threads**. It is however **strongly recommended that the integration tools provided with the web framework itself be used, if available**, instead of :class:`.scoped_session`. In particular, while using a thread local can be convenient, it is preferable that the :class:`.Session` be associated **directly with the request**, rather than with the current thread. The next section on custom scopes details a more advanced configuration which can combine the usage of :class:`.scoped_session` with direct request based scope, or any kind of scope. Using Custom Created Scopes --------------------------- The :class:`.scoped_session` object's default behavior of "thread local" scope is only one of many options on how to "scope" a :class:`.Session`. A custom scope can be defined based on any existing system of getting at "the current thing we are working with". Suppose a web framework defines a library function ``get_current_request()``. An application built using this framework can call this function at any time, and the result will be some kind of ``Request`` object that represents the current request being processed. If the ``Request`` object is hashable, then this function can be easily integrated with :class:`.scoped_session` to associate the :class:`.Session` with the request. Below we illustrate this in conjunction with a hypothetical event marker provided by the web framework ``on_request_end``, which allows code to be invoked whenever a request ends:: from my_web_framework import get_current_request, on_request_end from sqlalchemy.orm import scoped_session, sessionmaker Session = scoped_session(sessionmaker(bind=some_engine), scopefunc=get_current_request) @on_request_end def remove_session(req): Session.remove() Above, we instantiate :class:`.scoped_session` in the usual way, except that we pass our request-returning function as the "scopefunc". This instructs :class:`.scoped_session` to use this function to generate a dictionary key whenever the registry is called upon to return the current :class:`.Session`. In this case it is particularly important that we ensure a reliable "remove" system is implemented, as this dictionary is not otherwise self-managed. Contextual Session API ---------------------- .. autoclass:: sqlalchemy.orm.scoping.scoped_session :members: .. autoclass:: sqlalchemy.util.ScopedRegistry :members: .. autoclass:: sqlalchemy.util.ThreadLocalRegistry .. _session_partitioning: Partitioning Strategies ======================= Simple Vertical Partitioning ---------------------------- Vertical partitioning places different kinds of objects, or different tables, across multiple databases:: engine1 = create_engine('postgresql://db1') engine2 = create_engine('postgresql://db2') Session = sessionmaker(twophase=True) # bind User operations to engine 1, Account operations to engine 2 Session.configure(binds={User:engine1, Account:engine2}) session = Session() Above, operations against either class will make usage of the :class:`.Engine` linked to that class. Upon a flush operation, similar rules take place to ensure each class is written to the right database. The transactions among the multiple databases can optionally be coordinated via two phase commit, if the underlying backend supports it. See :ref:`session_twophase` for an example. Custom Vertical Partitioning ---------------------------- More comprehensive rule-based class-level partitioning can be built by overriding the :meth:`.Session.get_bind` method. Below we illustrate a custom :class:`.Session` which delivers the following rules: 1. Flush operations are delivered to the engine named ``master``. 2. Operations on objects that subclass ``MyOtherClass`` all occur on the ``other`` engine. 3. Read operations for all other classes occur on a random choice of the ``slave1`` or ``slave2`` database. :: engines = { 'master':create_engine("sqlite:///master.db"), 'other':create_engine("sqlite:///other.db"), 'slave1':create_engine("sqlite:///slave1.db"), 'slave2':create_engine("sqlite:///slave2.db"), } from sqlalchemy.orm import Session, sessionmaker import random class RoutingSession(Session): def get_bind(self, mapper=None, clause=None): if mapper and issubclass(mapper.class_, MyOtherClass): return engines['other'] elif self._flushing: return engines['master'] else: return engines[ random.choice(['slave1','slave2']) ] The above :class:`.Session` class is plugged in using the ``class_`` argument to :class:`.sessionmaker`:: Session = sessionmaker(class_=RoutingSession) This approach can be combined with multiple :class:`.MetaData` objects, using an approach such as that of using the declarative ``__abstract__`` keyword, described at :ref:`declarative_abstract`. Horizontal Partitioning ----------------------- Horizontal partitioning partitions the rows of a single table (or a set of tables) across multiple databases. See the "sharding" example: :ref:`examples_sharding`. Sessions API ============ Session and sessionmaker() --------------------------- .. autoclass:: sessionmaker :members: :inherited-members: .. autoclass:: sqlalchemy.orm.session.Session :members: :inherited-members: .. autoclass:: sqlalchemy.orm.session.SessionTransaction :members: Session Utilites ---------------- .. autofunction:: make_transient .. autofunction:: object_session .. autofunction:: sqlalchemy.orm.util.was_deleted Attribute and State Management Utilities ----------------------------------------- These functions are provided by the SQLAlchemy attribute instrumentation API to provide a detailed interface for dealing with instances, attribute values, and history. Some of them are useful when constructing event listener functions, such as those described in :doc:`/orm/events`. .. currentmodule:: sqlalchemy.orm.util .. autofunction:: object_state .. currentmodule:: sqlalchemy.orm.attributes .. autofunction:: del_attribute .. autofunction:: get_attribute .. autofunction:: get_history .. autofunction:: init_collection .. autofunction:: flag_modified .. function:: instance_state Return the :class:`.InstanceState` for a given mapped object. This function is the internal version of :func:`.object_state`. The :func:`.object_state` and/or the :func:`.inspect` function is preferred here as they each emit an informative exception if the given object is not mapped. .. autofunction:: sqlalchemy.orm.instrumentation.is_instrumented .. autofunction:: set_attribute .. autofunction:: set_committed_value .. autoclass:: History :members: