Commit 2cb1d50b authored by Janez K's avatar Janez K

merge simpson

parents 2434257a 6fceec6b
......@@ -20,6 +20,8 @@ atlassian-ide-plugin.xml
# SQLite
\ No newline at end of file
......@@ -26,7 +26,7 @@ source bin/activate
Obtain the url to your git repository.
git clone
git clone mothra
### Install requirements ###
WSGIScriptAlias / /srv/django-projects/mothra/mothra/
WSGIScriptAlias / /srv/django-projects/mothra/apache/
<Directory /srv/django-projects/mothra/apache>
Order allow,deny
Allow from all
......@@ -15,4 +15,5 @@ Alias /media /srv/django-projects/mothra/mothra/public/media
<Directory /srv/django-projects/mothra/mothra/public/media>
Order allow,deny
Allow from all
\ No newline at end of file
WSGIApplicationGroup %{GLOBAL}
WSGI config for mothra project.
This module contains the WSGI application used by Django's development server
and any production WSGI deployments. It should expose a module-level variable
named ``application``. Django's ``runserver`` and ``runfcgi`` commands discover
this application via the ``WSGI_APPLICATION`` setting.
Usually you will have the standard Django WSGI application here, but it also
might make sense to replace the whole Django WSGI application with a custom one
that later delegates to the Django one. For example, you could introduce WSGI
middleware here, or combine a Django application with an application of another
import os
import sys
import site
project_path = '/srv/django-projects/mothra'
if project_path not in sys.path:
os.environ["DJANGO_SETTINGS_MODULE"] = "mothra.settings"
# This application object is used by any WSGI server configured to use this
# file. This includes Django's development server, if the WSGI_APPLICATION
# setting points here.
from django.core.wsgi import get_wsgi_application
application = get_wsgi_application()
# Apply WSGI middleware here.
# from helloworld.wsgi import HelloWorldApplication
# application = HelloWorldApplication(application)
from __future__ import with_statement
from fabric.api import *
from fabric.colors import *
from fabric.utils import puts, abort
env.use_ssh_config = True
apps_to_migrate = ('workflows',)
def live():
""" doloci live server kot aktivni """
env.os = 'ubuntu'
env.hosts = ['']
env.branch = 'master'
def deploy():
""" deploy na serverju
$ fab live deploy
with prefix('source /srv/django-envs/mothra/bin/activate'):
with cd('/srv/django-projects/mothra'):
puts(yellow("[Pulling from origin, on branch %s]" % (env.branch,)))
run('git pull origin %s' % (env.branch,))
run('git checkout %s' % (env.branch,))
puts(yellow("[Installing packages]"))
run('pip install -qr requirements.txt')
puts(yellow("[Migrating apps]"))
for app in apps_to_migrate:
puts("--> [Migrating %s]" % (app,))
run('python migrate %s --no-initial-data' % (app, ))
puts(yellow("[Collecting static files]"))
run("python collectstatic --noinput")
puts(yellow("[Auto importing packages]"))
run("python auto_import_packages")
#run('python compress')
def apache_restart():
"""restarta apache service
$ fab dev apache_restart
$ fab live apache_restart
if env.os == 'ubuntu':
sudo('service apache2 restart')
elif env.os == 'arch':
sudo('rc.d restart httpd')
abort('env.os ni definiran, kaj je zdej to')
This file is placed here by pip to indicate the source was put
here by pip.
Once this package is successfully installed this source code will be
deleted (unless you remove this file).
This diff is collapsed.
"""Pickle field implementation for Django."""
from picklefield.fields import PickledObjectField # reexport
"""Pickle field implementation for Django."""
from copy import deepcopy
from base64 import b64encode, b64decode
from zlib import compress, decompress
from cPickle import loads, dumps
except ImportError:
from pickle import loads, dumps
from django.db import models
from django.utils.encoding import force_unicode
from picklefield import DEFAULT_PROTOCOL
class PickledObject(str):
A subclass of string so it can be told whether a string is a pickled
object or not (if the object is an instance of this class then it must
[well, should] be a pickled one).
Only really useful for passing pre-encoded values to ``default``
with ``dbsafe_encode``, not that doing so is necessary. If you
remove PickledObject and its references, you won't be able to pass
in pre-encoded values anymore, but you can always just pass in the
python objects themselves.
class _ObjectWrapper(object):
A class used to wrap object that have properties that may clash with the
ORM internals.
For example, objects with the `prepare_database_save` property such as
`django.db.Model` subclasses won't work under certain conditions and the
same apply for trying to retrieve any `callable` object.
__slots__ = ('_obj',)
def __init__(self, obj):
self._obj = obj
def wrap_conflictual_object(obj):
if hasattr(obj, 'prepare_database_save') or callable(obj):
obj = _ObjectWrapper(obj)
return obj
def dbsafe_encode(value, compress_object=False, pickle_protocol=DEFAULT_PROTOCOL):
# We use deepcopy() here to avoid a problem with cPickle, where dumps
# can generate different character streams for same lookup value if
# they are referenced differently.
# The reason this is important is because we do all of our lookups as
# simple string matches, thus the character streams must be the same
# for the lookups to work properly. See for more information.
#import time
#print "bla enocde!!!\n"+str(time.time())
#import traceback
if not compress_object:
value = b64encode(dumps(deepcopy(value), pickle_protocol))
value = b64encode(compress(dumps(deepcopy(value), pickle_protocol)))
return PickledObject(value)
def dbsafe_decode(value, compress_object=False):
#import time
#print "bla decode!!!\n"+str(time.time())
#import traceback
if not compress_object:
value = loads(b64decode(value))
value = loads(decompress(b64decode(value)))
return value
class PickledObjectField(models.Field):
A field that will accept *any* python object and store it in the
database. PickledObjectField will optionally compress its values if
declared with the keyword argument ``compress=True``.
Does not actually encode and compress ``None`` objects (although you
can still do lookups using None). This way, it is still possible to
use the ``isnull`` lookup type correctly.
__metaclass__ = models.SubfieldBase
def __init__(self, *args, **kwargs):
self.compress = kwargs.pop('compress', False)
self.protocol = kwargs.pop('protocol', DEFAULT_PROTOCOL)
kwargs.setdefault('editable', False)
super(PickledObjectField, self).__init__(*args, **kwargs)
def get_default(self):
Returns the default value for this field.
The default implementation on models.Field calls force_unicode
on the default, which means you can't set arbitrary Python
objects as the default. To fix this, we just return the value
without calling force_unicode on it. Note that if you set a
callable as a default, the field will still call it. It will
*not* try to pickle and encode it.
if self.has_default():
if callable(self.default):
return self.default()
return self.default
# If the field doesn't have a default, then we punt to models.Field.
return super(PickledObjectField, self).get_default()
def to_python(self, value):
B64decode and unpickle the object, optionally decompressing it.
If an error is raised in de-pickling and we're sure the value is
a definite pickle, the error is allowed to propogate. If we
aren't sure if the value is a pickle or not, then we catch the
error and return the original value instead.
if value is not None:
value = dbsafe_decode(value, self.compress)
# If the value is a definite pickle; and an error is raised in
# de-pickling it should be allowed to propogate.
if isinstance(value, PickledObject):
if isinstance(value, _ObjectWrapper):
return value._obj
return value
def pre_save(self, model_instance, add):
value = super(PickledObjectField, self).pre_save(model_instance, add)
return wrap_conflictual_object(value)
def get_db_prep_value(self, value, connection=None, prepared=False):
Pickle and b64encode the object, optionally compressing it.
The pickling protocol is specified explicitly (by default 2),
rather than as -1 or HIGHEST_PROTOCOL, because we don't want the
protocol to change over time. If it did, ``exact`` and ``in``
lookups would likely fail, since pickle would now be generating
a different string.
if value is not None and not isinstance(value, PickledObject):
# We call force_unicode here explicitly, so that the encoded string
# isn't rejected by the postgresql_psycopg2 backend. Alternatively,
# we could have just registered PickledObject with the psycopg
# marshaller (telling it to store it like it would a string), but
# since both of these methods result in the same value being stored,
# doing things this way is much easier.
value = force_unicode(dbsafe_encode(value, self.compress, self.protocol))
return value
def value_to_string(self, obj):
value = self._get_val_from_obj(obj)
return self.get_db_prep_value(value)
def get_internal_type(self):
return 'TextField'
def get_db_prep_lookup(self, lookup_type, value, connection=None, prepared=False):
if lookup_type not in ['exact', 'in', 'isnull']:
raise TypeError('Lookup type %s is not supported.' % lookup_type)
# The Field model already calls get_db_prep_value before doing the
# actual lookup, so all we need to do is limit the lookup types.
return super(PickledObjectField, self).get_db_prep_lookup(
lookup_type, value, connection=connection, prepared=prepared)
except TypeError:
# Try not to break on older versions of Django, where the
# `connection` and `prepared` parameters are not available.
return super(PickledObjectField, self).get_db_prep_lookup(
lookup_type, value)
# South support; see
from south.modelsinspector import add_introspection_rules
except ImportError:
add_introspection_rules([], [r"^picklefield\.fields\.PickledObjectField"])
"""Unit tests for django-picklefield."""
from django.test import TestCase
from django.db import models
from django.core import serializers
from picklefield.fields import PickledObjectField, wrap_conflictual_object
class TestingModel(models.Model):
pickle_field = PickledObjectField()
compressed_pickle_field = PickledObjectField(compress=True)
default_pickle_field = PickledObjectField(default=({1: 1, 2: 4, 3: 6, 4: 8, 5: 10}, 'Hello World', (1, 2, 3, 4, 5), [1, 2, 3, 4, 5]))
class MinimalTestingModel(models.Model):
pickle_field = PickledObjectField()
class TestCustomDataType(str):
class PickledObjectFieldTests(TestCase):
def setUp(self):
self.testing_data = (
{1:2, 2:4, 3:6, 4:8, 5:10},
'Hello World',
(1, 2, 3, 4, 5),
[1, 2, 3, 4, 5],
TestCustomDataType('Hello World'),
return super(PickledObjectFieldTests, self).setUp()
def testDataIntegriry(self):
Tests that data remains the same when saved to and fetched from
the database, whether compression is enabled or not.
for value in self.testing_data:
model_test = TestingModel(pickle_field=value, compressed_pickle_field=value)
model_test = TestingModel.objects.get(
# Make sure that both the compressed and uncompressed fields return
# the same data, even thought it's stored differently in the DB.
self.assertEquals(value, model_test.pickle_field)
self.assertEquals(value, model_test.compressed_pickle_field)
# Make sure we can also retreive the model
# Make sure the default value for default_pickled_field gets stored
# correctly and that it isn't converted to a string.
model_test = TestingModel()
model_test = TestingModel.objects.get(
self.assertEquals(({1: 1, 2: 4, 3: 6, 4: 8, 5: 10}, 'Hello World', (1, 2, 3, 4, 5), [1, 2, 3, 4, 5]), model_test.default_pickle_field)
def testLookups(self):
Tests that lookups can be performed on data once stored in the
database, whether compression is enabled or not.
One problem with cPickle is that it will sometimes output
different streams for the same object, depending on how they are
referenced. It should be noted though, that this does not happen
for every object, but usually only with more complex ones.
>>> from pickle import dumps
>>> t = ({1: 1, 2: 4, 3: 6, 4: 8, 5: 10}, \
... 'Hello World', (1, 2, 3, 4, 5), [1, 2, 3, 4, 5])
>>> dumps(({1: 1, 2: 4, 3: 6, 4: 8, 5: 10}, \
... 'Hello World', (1, 2, 3, 4, 5), [1, 2, 3, 4, 5]))
"((dp0\nI1\nI1\nsI2\nI4\nsI3\nI6\nsI4\nI8\nsI5\nI10\nsS'Hello World'\np1\n(I1\nI2\nI3\nI4\nI5\ntp2\n(lp3\nI1\naI2\naI3\naI4\naI5\natp4\n."
>>> dumps(t)
"((dp0\nI1\nI1\nsI2\nI4\nsI3\nI6\nsI4\nI8\nsI5\nI10\nsS'Hello World'\np1\n(I1\nI2\nI3\nI4\nI5\ntp2\n(lp3\nI1\naI2\naI3\naI4\naI5\natp4\n."
>>> # Both dumps() are the same using pickle.
>>> from cPickle import dumps
>>> t = ({1: 1, 2: 4, 3: 6, 4: 8, 5: 10}, 'Hello World', (1, 2, 3, 4, 5), [1, 2, 3, 4, 5])
>>> dumps(({1: 1, 2: 4, 3: 6, 4: 8, 5: 10}, 'Hello World', (1, 2, 3, 4, 5), [1, 2, 3, 4, 5]))
"((dp1\nI1\nI1\nsI2\nI4\nsI3\nI6\nsI4\nI8\nsI5\nI10\nsS'Hello World'\np2\n(I1\nI2\nI3\nI4\nI5\ntp3\n(lp4\nI1\naI2\naI3\naI4\naI5\nat."
>>> dumps(t)
"((dp1\nI1\nI1\nsI2\nI4\nsI3\nI6\nsI4\nI8\nsI5\nI10\nsS'Hello World'\n(I1\nI2\nI3\nI4\nI5\nt(lp2\nI1\naI2\naI3\naI4\naI5\natp3\n."
>>> # But with cPickle the two dumps() are not the same!
>>> # Both will generate the same object when loads() is called though.
We can solve this by calling deepcopy() on the value before
pickling it, as this copies everything to a brand new data
>>> from cPickle import dumps
>>> from copy import deepcopy
>>> t = ({1: 1, 2: 4, 3: 6, 4: 8, 5: 10}, 'Hello World', (1, 2, 3, 4, 5), [1, 2, 3, 4, 5])
>>> dumps(deepcopy(({1: 1, 2: 4, 3: 6, 4: 8, 5: 10}, 'Hello World', (1, 2, 3, 4, 5), [1, 2, 3, 4, 5])))
"((dp1\nI1\nI1\nsI2\nI4\nsI3\nI6\nsI4\nI8\nsI5\nI10\nsS'Hello World'\np2\n(I1\nI2\nI3\nI4\nI5\ntp3\n(lp4\nI1\naI2\naI3\naI4\naI5\nat."
>>> dumps(deepcopy(t))
"((dp1\nI1\nI1\nsI2\nI4\nsI3\nI6\nsI4\nI8\nsI5\nI10\nsS'Hello World'\np2\n(I1\nI2\nI3\nI4\nI5\ntp3\n(lp4\nI1\naI2\naI3\naI4\naI5\nat."
>>> # Using deepcopy() beforehand means that now both dumps() are idential.
>>> # It may not be necessary, but deepcopy() ensures that lookups will always work.
Unfortunately calling copy() alone doesn't seem to fix the
problem as it lies primarily with complex data types.
>>> from cPickle import dumps
>>> from copy import copy
>>> t = ({1: 1, 2: 4, 3: 6, 4: 8, 5: 10}, 'Hello World', (1, 2, 3, 4, 5), [1, 2, 3, 4, 5])
>>> dumps(copy(({1: 1, 2: 4, 3: 6, 4: 8, 5: 10}, 'Hello World', (1, 2, 3, 4, 5), [1, 2, 3, 4, 5])))
"((dp1\nI1\nI1\nsI2\nI4\nsI3\nI6\nsI4\nI8\nsI5\nI10\nsS'Hello World'\np2\n(I1\nI2\nI3\nI4\nI5\ntp3\n(lp4\nI1\naI2\naI3\naI4\naI5\nat."
>>> dumps(copy(t))
"((dp1\nI1\nI1\nsI2\nI4\nsI3\nI6\nsI4\nI8\nsI5\nI10\nsS'Hello World'\n(I1\nI2\nI3\nI4\nI5\nt(lp2\nI1\naI2\naI3\naI4\naI5\natp3\n."
for value in self.testing_data:
model_test = TestingModel(pickle_field=value, compressed_pickle_field=value)
# Make sure that we can do an ``exact`` lookup by both the
# pickle_field and the compressed_pickle_field.
wrapped_value = wrap_conflictual_object(value)
model_test = TestingModel.objects.get(pickle_field__exact=wrapped_value,
self.assertEquals(value, model_test.pickle_field)
self.assertEquals(value, model_test.compressed_pickle_field)
# Make sure that ``in`` lookups also work correctly.
model_test = TestingModel.objects.get(pickle_field__in=[wrapped_value],