Also: I'm using [Python 2.6.5] and [SQLAlchemy 0.5.8]
Previously I was just shallow copying my dictionaries, and there were no issues then with my simulations. My dictionaries contain objects such that my students dictionary is basically: students[stud_id] = Student(stud_id, name, preferences,...) Student is mapped to an SQLAlchemy table. This is similar for many of my objects. I was trying to run some code to optimise my allocations and there was no "real" involvement with SQLAlchemy -- in that I wasn't actually dealing with any SQLAlchemy code. I understand that the shallow copy in Python just copies the references whereas deepcopy copies the entire object. Does that mean the deepcopied object is "outside" the session or something? Some help would be much appreciated. I have a feeling that the answer lies somewhere within the way deepcopy and session work but my head just can't put two-and-two together right now :( On Jun 3, 6:24 am, Az <azfarul.is...@gmail.com> wrote: > In my code, I am currently adding to the "session" in various modules > (this is the same session since I'm importing it from my most > prominent module). > > Some sample code would be: > > ###### BEGIN CODE 1 ####### > > Session = sessionmaker(bind=engine) > session = Session() > > def addToTable(): > """Very simple SQLAlchemy function that populates the Student, > Project > and Supervisor tables.""" > > for student in students.itervalues(): > session.add(student) > session.flush() > > for project in projects.itervalues(): > session.add(project) > session.flush() > > for supervisor in supervisors.itervalues(): > session.add(supervisor) > session.flush() > > session.commit() > > And then again in a function in the same module: > > def monteCarloBasic(trials): > """The Monte-Carlo simulation will generate allocations for the > list of students by randomly arranging the order for each trial. > > In the case of a student having more than one project for a given > rank, > the algorithm with randomly select one of them since it is given that > all such projects are equally desireable to the student.""" > > session_id = 1 > ident = 1 > for trial in xrange(trials): > > for id in randomiseStudentKeys(True): > stud_id = id > student = students[id] > > if student.preferences: > temp_alloc = SimAllocation(ident, session_id, > stud_id) > > ranks = sorted(student.preferences.keys()) > > for rank in ranks: > # Now we begin to try giving him/her a project > proj = > random.choice(list(student.preferences[rank])) > > if not (proj.allocated or > proj.blocked or proj.own_project): > > student.allocated_project = > proj > student.allocated_proj_ref = > proj.proj_id > student.allocated_rank = rank > allocSuccessActions(proj) > > temp_alloc.alloc_proj = > proj.proj_id # ... we can set the > allocated project details > temp_alloc.alloc_proj_rank = > rank > > session.add(temp_alloc) > > break > > ident += 1 # Increment the primary key > session.add(temp_alloc) > > session.flush() > session_id += 1 > > resetData() # Resets all data > > session.commit() > > ####### END CODE 1 ####### > > Later on I'm using this session to run some calculations on my data. > For example: > > ####### BEGIN CODE 2 ######## > > sid = 4545 > project_id_list = list(students[sid].preferences) > for project_id in project_id_list > gotcha = > session.query(SimAllocation).filter(SimAllocation.student_id == > sid).filter(PP.SimAllocation.alloc_proj == project_id).count() > > ###### END CODE 2 ####### > > Simply, this line counts how many times a certain student was > allocated each project from his list when using the Monte-Carlo > simulation from ### CODE 1 ### above. > > +++ Questions +++ > > 1. Is this the correct way to use sessions or am I sort of abusing > them? > 2. When should I close a session? > 3. I got the following error after trying to use copy.deepcopy() on > one of my dictionaries. > > File "Main.py", line 106, in <module> > OPTM.preoptAlloc(some_best) > File "XXXXXXXX/Optimisation.py", line 48, in preoptAlloc > sid = projs_preopt[sim.alloc_proj_ref].proj_sup > File "/opt/local/Library/Frameworks/Python.framework/Versions/2.6/ > lib/python2.6/site-packages/SQLAlchemy-0.5.8-py2.6.egg/sqlalchemy/orm/ > attributes.py", line 158, in __get__ > return self.impl.get(instance_state(instance), > instance_dict(instance)) > File "/opt/local/Library/Frameworks/Python.framework/Versions/2.6/ > lib/python2.6/site-packages/SQLAlchemy-0.5.8-py2.6.egg/sqlalchemy/orm/ > attributes.py", line 377, in get > value = callable_() > File "/opt/local/Library/Frameworks/Python.framework/Versions/2.6/ > lib/python2.6/site-packages/SQLAlchemy-0.5.8-py2.6.egg/sqlalchemy/orm/ > state.py", line 185, in __call__ > attr.impl.key in unmodified > File "/opt/local/Library/Frameworks/Python.framework/Versions/2.6/ > lib/python2.6/site-packages/SQLAlchemy-0.5.8-py2.6.egg/sqlalchemy/orm/ > mapper.py", line 1864, in _load_scalar_attributes > "attribute refresh operation cannot proceed" % (state_str(state))) > sqlalchemy.exc.UnboundExecutionError: Instance <Project at 0x24c5c50> > is not bound to a Session; attribute refresh operation cannot proceed > > Is this something to do with the way I've been using the sessions? > > --- > > Thanks, > > Az -- You received this message because you are subscribed to the Google Groups "sqlalchemy" group. 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