Contextual/Thread-local Sessions

Recall from the section When do I construct a Session, when do I commit it, and when do I close it?, the concept of “session scopes” was introduced, with an emphasis on web applications and the practice of linking the scope of a Session with that of a web request. Most modern web frameworks include integration tools so that the scope of the 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 Session scopes. It is also used by third-party integration systems to help construct their integration schemes.

The object is the scoped_session object, and it represents a registry of Session objects. If you’re not familiar with the registry pattern, a good introduction can be found in Patterns of Enterprise Architecture.


The scoped_session registry by default uses a Python threading.local() in order to track Session instances. This is not necessarily compatible with all application servers, particularly those which make use of greenlets or other alternative forms of concurrency control, which may lead to race conditions (e.g. randomly occurring failures) when used in moderate to high concurrency scenarios. Please read Thread-Local Scope and Using Thread-Local Scope with Web Applications below to more fully understand the implications of using threading.local() to track Session objects and consider more explicit means of scoping when using application servers which are not based on traditional threads.


The 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 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 scoped_session is constructed by calling it, passing it a factory which can create new Session objects. A factory is just something that produces a new object when called, and in the case of Session, the most common factory is the 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 scoped_session object we’ve created will now call upon the sessionmaker when we “call” the registry:

>>> some_session = Session()

Above, some_session is an instance of Session, which we can now use to talk to the database. This same Session is also present within the scoped_session registry we’ve created. If we call upon the registry a second time, we get back the same Session:

>>> some_other_session = Session()
>>> some_session is some_other_session

This pattern allows disparate sections of the application to call upon a global scoped_session, so that all those areas may share the same session without the need to pass it explicitly. The Session we’ve established in our registry will remain, until we explicitly tell our registry to dispose of it, by calling scoped_session.remove():

>>> Session.remove()

The scoped_session.remove() method first calls Session.close() on the current Session, which has the effect of releasing any connection/transactional resources owned by the Session first, then discarding the 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 scoped_session object is “empty”, and will create a new Session when called again. As illustrated below, this is not the same Session we had before:

>>> new_session = Session()
>>> new_session is some_session

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 scoped_session is simple; hold onto a Session for all who ask for it. As a means of producing more transparent access to this Session, the scoped_session also includes proxy behavior, meaning that the registry itself can be treated just like a Session directly; when methods are called on this object, they are proxied to the underlying Session being maintained by the registry:

Session = scoped_session(some_factory)

# equivalent to:
# session = Session()
# print(session.query(MyClass).all())

The above code accomplishes the same task as that of acquiring the current Session by calling upon the registry, then using that 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 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 scoped_session usage, where the same Session object is maintained across multiple calls, suggests that some process needs to be in place such that multiple 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 scoped_session object by default uses this object as storage, so that a single Session is maintained for all who call upon the scoped_session registry, but only within the scope of a single thread. Callers who call upon the registry in a different thread get a Session instance that is local to that other thread.

Using this technique, the 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 scoped_session.remove() method, as always, removes the current 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 scoped_session.remove(). However, the scope of transactions themselves, i.e. ending them via Session.commit() or 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.

Using Thread-Local Scope with Web Applications

As discussed in the section When do I construct a Session, when do I commit it, and when do I close it?, a web application is architected around the concept of a web request, and integrating such an application with the Session usually implies that the 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 Session with a thread implies it is also associated with the web request running within that thread, and vice versa, provided that the 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 scoped_session as a quick way to integrate the 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())

web request    ->   web request     ->   # The registry is *optionally*
                    starts               # called upon explicitly to create
                                         # a Session local to the thread and/or request

                                         # 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

                    web request ends  -> # the registry is instructed to
                                         # remove the Session

                    sends output      <-
outgoing web    <-

Using the above flow, the process of integrating the Session with the web application has exactly two requirements:

  1. Create a single scoped_session registry when the web application first starts, ensuring that this object is accessible by the rest of the application.

  2. Ensure that 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 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 scoped_session.

In particular, while using a thread local can be convenient, it is preferable that the 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 scoped_session with direct request based scope, or any kind of scope.

Using Custom Created Scopes

The scoped_session object’s default behavior of “thread local” scope is only one of many options on how to “scope” a 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 scoped_session to associate the 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)

def remove_session(req):

Above, we instantiate scoped_session in the usual way, except that we pass our request-returning function as the “scopefunc”. This instructs scoped_session to use this function to generate a dictionary key whenever the registry is called upon to return the current 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

Object Name Description


Provides scoped management of Session objects.


A Registry that can store one or multiple instances of a single class on the basis of a “scope” function.


A ScopedRegistry that uses a threading.local() variable for storage.

class sqlalchemy.orm.scoping.scoped_session(session_factory, scopefunc=None)

Provides scoped management of Session objects.

See Contextual/Thread-local Sessions for a tutorial.

method sqlalchemy.orm.scoping.scoped_session.__call__(**kw)

Return the current Session, creating it using the scoped_session.session_factory if not present.


**kw – Keyword arguments will be passed to the scoped_session.session_factory callable, if an existing Session is not present. If the Session is present and keyword arguments have been passed, InvalidRequestError is raised.

method sqlalchemy.orm.scoping.scoped_session.__init__(session_factory, scopefunc=None)

Construct a new scoped_session.

  • session_factory – a factory to create new Session instances. This is usually, but not necessarily, an instance of sessionmaker.

  • scopefunc – optional function which defines the current scope. If not passed, the scoped_session object assumes “thread-local” scope, and will use a Python threading.local() in order to maintain the current Session. If passed, the function should return a hashable token; this token will be used as the key in a dictionary in order to store and retrieve the current Session.

method sqlalchemy.orm.scoping.scoped_session.configure(**kwargs)

reconfigure the sessionmaker used by this scoped_session.

See sessionmaker.configure().

method sqlalchemy.orm.scoping.scoped_session.query_property(query_cls=None)

return a class property which produces a Query object against the class and the current Session when called.


Session = scoped_session(sessionmaker())

class MyClass(object):
    query = Session.query_property()

# after mappers are defined
result = MyClass.query.filter('foo').all()

Produces instances of the session’s configured query class by default. To override and use a custom implementation, provide a query_cls callable. The callable will be invoked with the class’s mapper as a positional argument and a session keyword argument.

There is no limit to the number of query properties placed on a class.

method sqlalchemy.orm.scoping.scoped_session.remove()

Dispose of the current Session, if present.

This will first call Session.close() method on the current Session, which releases any existing transactional/connection resources still being held; transactions specifically are rolled back. The Session is then discarded. Upon next usage within the same scope, the scoped_session will produce a new Session object.

attribute sqlalchemy.orm.scoping.scoped_session.session_factory = None

The session_factory provided to __init__ is stored in this attribute and may be accessed at a later time. This can be useful when a new non-scoped Session or Connection to the database is needed.

class sqlalchemy.util.ScopedRegistry(createfunc, scopefunc)

A Registry that can store one or multiple instances of a single class on the basis of a “scope” function.

The object implements __call__ as the “getter”, so by calling myregistry() the contained object is returned for the current scope.

  • createfunc – a callable that returns a new object to be placed in the registry

  • scopefunc – a callable that will return a key to store/retrieve an object.

method sqlalchemy.util.ScopedRegistry.__init__(createfunc, scopefunc)

Construct a new ScopedRegistry.

  • createfunc – A creation function that will generate a new value for the current scope, if none is present.

  • scopefunc – A function that returns a hashable token representing the current scope (such as, current thread identifier).

method sqlalchemy.util.ScopedRegistry.clear()

Clear the current scope, if any.

method sqlalchemy.util.ScopedRegistry.has()

Return True if an object is present in the current scope.

method sqlalchemy.util.ScopedRegistry.set(obj)

Set the value for the current scope.

class sqlalchemy.util.ThreadLocalRegistry(createfunc)

A ScopedRegistry that uses a threading.local() variable for storage.