sqlite3 back end DB for django - weird error - django

Question

So for a project I am querying a bunch of Google Analytics data and storing it into a Sqlit3 database. Right now I am working on a script that retrieves historical data for each day over the course of several months. The Script runs without error for around a month and then throws this weird error that I couldn't find much information on. Can anyone help me figure out why it's throwing this. Is it some sort of memory error?
here is the traceback:
Traceback (most recent call last):
File "manage.py", line 10, in <module>
execute_from_command_line(sys.argv)
File "C:\Python27\lib\site-packages\django\core\management\__init__.py", line
399, in execute_from_command_line
utility.execute()
File "C:\Python27\lib\site-packages\django\core\management\__init__.py", line
392, in execute
self.fetch_command(subcommand).run_from_argv(self.argv)
File "C:\Python27\lib\site-packages\django\core\management\__init__.py", line
272, in fetch_command
klass = load_command_class(app_name, subcommand)
File "C:\Python27\lib\site-packages\django\core\management\__init__.py", line
75, in load_command_class
module = import_module('%s.management.commands.%s' % (app_name, name))
File "C:\Python27\lib\site-packages\django\utils\importlib.py", line 40, in im
port_module
__import__(name)
File "C:\Users\root.BrandonYates-PC\Documents\GitHub\Weblife-Repo\bipol_django
_site\ga\management\commands\backlog.py", line 10, in <module>
class backLog():
File "C:\Users\root.BrandonYates-PC\Documents\GitHub\Weblife-Repo\bipol_django
_site\ga\management\commands\backlog.py", line 42, in backLog
p = Populate(str(date.fromordinal(i)), str(date.fromordinal(i)))
File "C:\Users\root.BrandonYates-PC\Documents\GitHub\Weblife-Repo\bipol_django
_site\ga\management\commands\fillTest.py", line 126, in __init__
PageTrackingData())
File "C:\Users\root.BrandonYates-PC\Documents\GitHub\Weblife-Repo\bipol_django
_site\ga\management\commands\fillTest.py", line 56, in fill
element.save()
File "C:\Python27\lib\site-packages\django\db\models\base.py", line 545, in sa
ve
force_update=force_update, update_fields=update_fields)
File "C:\Python27\lib\site-packages\django\db\models\base.py", line 573, in sa
ve_base
updated = self._save_table(raw, cls, force_insert, force_update, using, upda
te_fields)
File "C:\Python27\lib\site-packages\django\db\transaction.py", line 319, in __
exit__
connection.rollback()
File "C:\Python27\lib\site-packages\django\db\backends\__init__.py", line 180,
in rollback
self._rollback()
File "C:\Python27\lib\site-packages\django\db\backends\__init__.py", line 144,
in _rollback
return self.connection.rollback()
File "C:\Python27\lib\site-packages\django\db\utils.py", line 99, in __exit__
six.reraise(dj_exc_type, dj_exc_value, traceback)
File "C:\Python27\lib\site-packages\django\db\backends\__init__.py", line 144,
in _rollback
return self.connection.rollback()
django.db.utils.OperationalError: cannot rollback - no transaction is active
Relevant Code sections:
for i in range(d1, d2):
print "Date Range: " + str(date.fromordinal(i))
p = Populate(str(date.fromordinal(i)), str(date.fromordinal(i)))
#inside populate
self.fill(ecommerce, EcommerceData())
self.fill(self.query.get_data(qsf.getPageTrackingMetrics(),
qsf.getPageTrackingDimensions()),
PageTrackingData())
self.fill(self.query.get_data(qsf.getTrafficSourceMetrics(),
qsf.getTrafficSourceDimensions()),
TrafficData())
self.fill(self.query.get_data(qsf.getAdwordsMetrics(),
qsf.getAdwordsDimensions()), AdwordsData())
def fill(self, data, object):
"""
Create an object list
Iterate through the row data, create and append each object to the list
Add the analytics data key to the user data, insert the row by saving
"""
rows = []
for row in data:
#print row
rows.append( object.create( row ) )
for element in rows:
element.analytics = self.analytic
#print element
element.save()

Answer 1

Ok so it seems to be some sort of memory related error. If you are receiving this error you may be running too many variables through ram. In short you need to make your code more efficient for the data you are handling or slice up the data into more manageable chunks.