Overview of Vittoriosa Stars
Vittoriosa Stars is a renowned football team based in the Maltese region, competing in the Premier League. Founded in 1925, the team is currently managed by Coach Giovanni Scicluna. Known for their dynamic play and passionate fanbase, Vittoriosa Stars have established themselves as a formidable force in the league.
Team History and Achievements
Throughout their storied history, Vittoriosa Stars have claimed numerous titles, including multiple league championships and cup victories. Notable seasons include their 1985 championship win and consistent top-five finishes over the past decade. The team has also set several records, such as the longest unbeaten streak in a single season.
Current Squad and Key Players
The current squad boasts talented players like striker Marco Borg, midfielder Alessio Farrugia, and goalkeeper Daniel Zammit. Marco Borg is particularly noteworthy for his scoring prowess, having netted over 20 goals this season. Alessio Farrugia’s playmaking abilities make him a crucial asset in midfield.
Team Playing Style and Tactics
Vittoriosa Stars typically employ a 4-3-3 formation, emphasizing high pressing and quick transitions. Their strengths lie in their attacking flair and defensive solidity. However, they occasionally struggle against teams with strong aerial presence due to their relatively shorter average player height.
Interesting Facts and Unique Traits
The team is affectionately nicknamed “The Luminaries” due to their bright performances on the field. They boast a dedicated fanbase known as “The Star Supporters.” Rivalries with teams like Sliema Wanderers add an extra layer of excitement to their matches. Traditions include pre-match rituals that involve singing the club anthem.
Lists & Rankings of Players, Stats, or Performance Metrics
- Top Scorer: Marco Borg ✅
- Most Assists: Alessio Farrugia 💡
- Pick of the Season: Daniel Zammit 🎰
- Average Goals per Match: 1.8 ❌
Comparisons with Other Teams in the League
Vittoriosa Stars are often compared to rivals like Senglea Athletic due to their similar playing styles and competitive nature. While both teams excel in attacking play, Vittoriosa Stars have a slight edge in defensive consistency.
Case Studies or Notable Matches
A memorable match was their 2019 cup final victory against Floriana FC, where they overturned a deficit with two late goals. This game showcased their resilience and tactical acumen under pressure.
Tables Summarizing Team Stats, Recent Form, Head-to-Head Records, or Odds
| Statistic | Vittoriosa Stars | Average League Statistic |
|---|---|---|
| Last 10 Matches Form | W-W-D-L-W-W-W-D-L-W | N/A |
| Average Goals Scored per Match | 1.8 | 1.5 |
| Average Goals Conceded per Match | 0.9 | 1.0 |
| Last 5 Head-to-Head vs Senglea Athletic: W-D-L-W-L (Vittoriosa Wins) |
Tips & Recommendations for Analyzing the Team or Betting Insights
To maximize betting success on Vittoriosa Stars, consider focusing on matches against lower-ranked teams where they have historically performed well. Analyze player form and recent injuries before placing bets to ensure informed decisions.
Frequently Asked Questions (FAQ)
What is Vittoriosa Stars’ current league position?
Vittoriosa Stars are currently positioned third in the Premier League standings.
Who are some key players to watch?
Straightforwardly look out for Marco Borg’s goal-scoring ability and Alessio Farrugia’s playmaking skills.
What are some upcoming matches for Vittoriosa Stars?
Their next fixtures include games against Valletta FC and Rabat Ajax FC.
Bet on Vittoriosa Stars now at Betwhale!
Detailed Analysis: Pros & Cons of Current Form or Performance
- Pros:
- Rigorous defensive structure 🎰✅
- Potent attacking options 💡
- Cons:
- <ul
- Sometimes struggles with aerial duels ❌
- Suggested How-To Guide: Analyzing Team Tactics for Better Betting Decisions
- Identify key players’ roles within formations.
- Analyze recent match footage to understand tactical shifts.
- Monitor injury reports for potential impact on performance.
</o[0]: import logging
[1]: from django.contrib.auth.models import User
[2]: from django.core.management.base import BaseCommand
[3]: from django.db.models import Q
[4]: from dimagi.utils.couch.cache.cache_core import clear_caches
[5]: from corehq.apps.accounting.models import LedgerTransaction
[6]: from corehq.apps.hqwebapp.templatetags.hq_shared_tags import get_language_list_for_site
[7]: from corehq.apps.sms.models import SQLMobileWorker
[8]: from corehq.util.quickcache import quickcache
[9]: logger = logging.getLogger(__name__)
[10]: class Command(BaseCommand):
[11]: help = 'Removes users who were deleted via CommCareHQ but not via HQ.'
[12]: def handle(self, *args, **options):
[13]: self.remove_deleted_users()
[14]: self.remove_deleted_mobile_workers()
[15]: self.remove_orphan_ledger_transactions()
[16]: @quickcache(['site'])
[17]: def get_languages_for_site(self):
[18]: return get_language_list_for_site(None)
[19]: def remove_deleted_users(self):
[20]: logger.info('Removing deleted users')
[21]: deleted_user_ids = set()
[22]: # Get all deleted users that exist only because they're referenced by other models.
[23]: # Deleted mobile workers
user_id = m.user_id
deleted_user_ids.add(user_id)
user_id = m.user_id
deleted_user_ids.add(user_id)
if m.domain not in self.get_languages_for_site():
continue
user_id = m.user_id
deleted_user_ids.add(user_id)
if m.domain not in self.get_languages_for_site():
continue
user_id = m.user_id
deleted_user_ids.add(user_id)
user_queryset = User.objects.filter(
Q(is_active=False) &
~Q(id__in=deleted_user_ids) &
Q(id__isnull=False) &
Q(username__isnull=False) &
Q(first_name__isnull=False) &
Q(last_name__isnull=False)
)
count = user_queryset.count()
logger.info('Deleting {} inactive users'.format(count))
user_queryset.delete()
dimagi/commcare-hq<|file_sep/datatables/tests/test_datatables.py
from datetime import datetime
from django.test.client import RequestFactory
from mock.mock import MagicMock
from nose.tools import eq_, ok_
from dimagi.utils.parsing.couch_datetime import json_format_datetime_to_datetime
from dimagi.utils.decorators.memoized import memoized
from corehq.apps.app_manager.dbaccessors.app_dbaccessors import get_app_configs_by_domain
from corehq.apps.app_manager.tests.util.fixtures_utils import create_app_fixture
from corehq.apps.reports.datatables.base_data_table_class import DataTablesHeaderInfo
from corehq.apps.reports.datatables.django_datatable_view_base
import DjangoDataTableViewBaseMixin,
DataTablesQuerySetMixin,
DataTablesHeaderInfoMixin,
_get_request_params,
_build_query_dict_from_request_params,
_get_column_info_from_request_params,
_get_sorting_and_limit_info_from_request_params,
_get_filter_info_from_request_params,
_get_pagination_info_from_request_params,
_add_default_sorting_if_necessary
class TestDjangoDataTableViewBaseMixin(object):
def setUp(self):
super(TestDjangoDataTableViewBaseMixin,self).setUp()
self.request_factory=RequestFactory()
def test_get_initial_columns(self):
class TestClass(DjangoDataTableViewBaseMixin):
initial_columns=['a','b']
instance=TestClass()
eq_(instance.get_initial_columns(),['a','b'])
instance.initial_columns=['c']
eq_(instance.get_initial_columns(),['c'])
del instance.initial_columns
eq_(instance.get_initial_columns(),[])
instance._initial_columns=['d']
eq_(instance.get_initial_columns(),['d'])
class TestDataTablesQuerySetMixin(object):
class TestClass(DataTablesQuerySetMixin):
queryset=None
class TestClass(TestClass):pass
class TestClass(TestClass):
initial_query_set=None
class TestClass(TestClass):pass
class TestClass(TestClass):
initial_queryset=None
class TestClass(TestClass):pass
def test_get_query_set_uses_initial_queryset_if_provided(self):
request=self.request_factory.post('/',data={'draw':'123'})
instance=TestClass(request=request)
instance.initial_query_set=[MagicMock()]
query_set=instance._get_query_set()
eq_(query_set,[MagicMock()])
request=self.request_factory.post('/',data={'draw':'123'})
instance=TestClass(request=request)
instance.initial_query_set=[MagicMock()]
query_set=instance._get_query_set()
ok_(query_set!=instance.initial_query_set)
def test_get_query_set_uses_queryset_if_provided(self):
request=self.request_factory.post('/',data={'draw':'123'})
instance=TestClass(request=request)
instance.queryset=[MagicMock()]
query_set=instance._get_query_set()
eq_(query_set,[MagicMock()])
ok_(query_set!=instance.queryset)
ok_(query_set!=instance.initial_query_set)
request=self.request_factory.post('/',data={'draw':'123'})
instance=TestClass(request=request)
instance.queryset=[MagicMock()]
query_set=instance._get_query_set()
ok_(query_set==None)
raise ValueError("Can't use both queryset & initial_queryset")
request=self.request_factory.post('/',data={'draw':'123'})
instance=TestClass(request=request)
instance.queryset=[MagicMock()]
@classmethod
def get_initial_queryset(cls,request,*args,**kwargs):
return [MagicMock()]
queryset=cls._get_query_set(*args,**kwargs)
eq_(queryset,[MagicMock()])
ok_(queryset!=cls.queryset)
ok_(queryset!=cls.initial_query_set)
request=self.request_factory.post('/',data={'draw':'123'})
instance=TestClass(request=request)
instance.queryset=[MagicMock()]
@classmethod
def get_initial_queryset(cls,request,*args,**kwargs):
return [MagicMock()]
@classmethod
def construct_lookup(cls,request,*args,**kwargs):
return {}
queryset=cls._get_query_set(*args,**kwargs)
ok_(queryset==None)
raise ValueError("Can't use both queryset & initial_queryset")
request=self.request_factory.post('/',data={'draw':'123'})
data_tables_headers=[
DataTablesHeaderInfo(column_name='id',model_attr='id'),
DataTablesHeaderInfo(column_name='first_name',model_attr='first_name'),
DataTablesHeaderInfo(column_name='last_name',model_attr='last_name'),
]
class Model(MagicMock()):
pass
class QuerySet(MagicMock()):
def __iter__(self):
return iter([Model(id=i*100+10,i=i*100+20,j=i*100+30,k=i*100+40,l=i*100+50,m=i*100+60,n=i*100+70,o=i*100+80,p=i*100+90,q=i*100+110,r=i*100+120,s=i*100+130,t=i*100+140,u=i*100+150,v=i*100+160,w=i*100+i**i,x=(datetime.now()-datetime(1970,i%12,(i%28)+10)).total_seconds()) for i in range(500)])
def filter(**kwargs):
filtered_items=[]
for item_index,item_value in enumerate(iter(QuerySet())):
item_matches_all_criteria=True;
for key,value in kwargs.iteritems():
if isinstance(value,(list,tuple)):
if not hasattr(item_value,key):
item_matches_all_criteria=False;
break;
elif value:
if getattr(item_value,key)==value:
continue;
else:
item_matches_all_criteria=False;
break;
else:
item_matches_all_criteria=False;
break;
else:
if getattr(item_value,key)!=value:
item_matches_all_criteria=False;
break;
if item_matches_all_criteria:
filtered_items.append(item_value);
return QuerySet(filtered_items);
def exclude(**kwargs):
excluded_items=[]
for item_index,item_value in enumerate(iter(QuerySet())):
item_matches_any_exclusion_criteria=False;
for key,value in kwargs.iteritems():
if isinstance(value,(list,tuple)):
if not hasattr(item_value,key):
item_matches_any_exclusion_criteria=True;
break;
elif value:
if getattr(item_value,key)==value:
continue;
else:
item_matches_any_exclusion_criteria=True;
break;
else:
item_matches_any_exclusion_criteria=True;
break;
else:
if getattr(item_value,key)!=value:
item_matches_any_exclusion_criteria=True;
break;
if not item_matches_any_exclusion_criteria:
excluded_items.append(item_value);
return QuerySet(excluded_items);
def order_by(*ordering_fields):
items=list(iter(QuerySet()));
sorted_items=[];
ordering_field_index=-len(ordering_fields);
while ordering_field_index<len(ordering_fields)-1 or len(sorted_items)=start if index<=end if slice_step==None else index%slice_step==0);
sliced_list=list(sliced_iterable)[:end-start];
return QuerySet(sliced_list);
def count():
counted_length=len(list(iter(QuerySet())));
return counted_length;
class ClassUnderTest(DataTablesQuerySetMixin,data_tables_headers=data_tables_headers,class_of_model_under_test=Model,class_of_data_table_model_under_test=None,class_of_data_table_header_info_under_test=None,class_of_data_table_model_meta_under_test=None,is_validated_class_under_test=True,is_using_single_object_returned_as_dictionary_under_test=False,is_using_single_object_returned_as_instance_under_test=True,is_using_multiple_objects_returned_as_dictionary_under_test=True,is_using_multiple_objects_returned_as_instances_under_test=True,is_using_single_object_returned_as_pks_only_under_test=False,is_using_multiple_objects_returned_as_pks_only_under_test=False,single_object_pk_attribute_is_not_nullable_in_the_database_under_test=False,default_sort_when_no_sort_is_specified_in_the_request_is_a_string_under_test=True,default_sort_when_no_sort_is_specified_in_the_request_is_a_tuple_with_a_string_and_an_int_under_test=True,default_sort_when_no_sort_is_specified_in_the_request_is_a_list_with_strings_and_integers_under_test=True,default_limit_when_no_limit_is_specified_in_the_request_is_an_integer_greater_than_zero_under_test=True,default_limit_when_no_limit_is_specified_in_the_request_is_a_negative_integer_less_than_zero_under_test=True,default_offset_when_no_offset_is_specified_in_the_request_is_an_integer_greater_than_or_equal_to_zero_true_true_false_false_true_true_true_true_false_false_false,False,False,False,False,True,True,True,True,False,False,False,False,True,True,True,True,False,False,False,False,None,None,None,None,None,None,None,None,request=request));
query_dict=_build_query_dict_from_request_params(instance,request,'id');
column_names=get_column_names(instance,'id');
query_parameters=get_lookup_parameters(query_dict,column_names,'id');
expected_parameters={
'id__gt':4,
'first_name__in':['foo','bar'],
'last_name__in':[],
'i__lt':250,
'j__gt':250,
'k__lt':250,
'l__gt':250,
'm__lt':250,
'n__gt':250,
'o__lt':250,
'p__gt':250,
'q':None,
'r':None,
's':[500],
u't':u'u00f6',
u'u':[u'u00f6'],
u'v':[u'u00f6'],
u'w':[u'u00f6'],
u'x':{'gte':json_format_datetime_to_datetime(datetime.now())}
};
eq_(expected_parameters,get_expected_lookup_parameters(query_dict,column_names));
query_sets=get_filtered_and_ordered_data(query_parameters,request,'id');
expected_queries=[
{
'filter_args':{'id':{'gt':4},'first_name':{'in':['foo','bar']}},
'exclude_args':{'last_name':{'in':['']},'i':{'lt':[250]}},
'order_by':['j','k','l','m','n','o','p']},
{
'filter_args':{'r':{'eq':[500]}},
'exclude_args:{'t':{'eq':['xf6']}},
'order_by':['v']}
];
eq_([list(q)[0].i,list(q)[0].j,list(q)[0].k,list(q)[0].l,list(q)[0].m,list(q)[0].n,list(q)[0].o,list(q)[0].p] for q in query_sets,[200,-200,-200,-200,-200,-200,-200,-200],[300,-300,-300,-300,-300,-300,-300,-300]);
eq_([list(q)[0].r,list(q)[0].t] for q in query_sets,[500,'xf6'],[])
def test_get_filtered_and_ordered_data_fails_on_invalid_filter_keys(self):
request=self.request_factory.post('/',data={'draw':'123'})
data_tables_headers=[
DataTablesHeaderInfo(column_name='id',model_attr='id'),
DataTablesHeaderInfo(column_name='first_name',model_attr='first_name'),
DataTablesHeaderInfo(column_name='last_name',model_attr='last_name'),
]
class Model(MagicMock()):
pass
class QuerySet(MagicMock()):
def __iter__(self):
return iter([Model(id=i*100+10,i=i*100+20,j=i*100+30,k=i*100+40,l=i*100+50,m=i*100+60,n=i*100+70,o=i*100+80,p=i*100+90,q=i*100+110,r=i*100+120,s=(datetime.now()-datetime(1970,i%12,(i%28)+10)).total_seconds()) for i in range(500)])
raise NotImplementedError("This method should be implemented by subclasses.")
raise NotImplementedError("This method should be implemented by subclasses.")
raise NotImplementedError("This method should be implemented by subclasses.")
raise NotImplementedError("This method should be implemented by subclasses.")
raise NotImplementedError("This method should be implemented by subclasses.")
raise NotImplementedError("This method should be implemented by subclasses.")
raise NotImplementedError("This method should be implemented by subclasses.")
raise NotImplementedError("This method should be implemented by subclasses.")
raise NotImplementedError("This method should be implemented by subclasses.")
raise NotImplementedError("This method should be implemented by subclasses.")
class ClassUnderTest(DataTablesQuerySetMixin,data_tables_headers=data_tables_headers,class_of_model_under_test=None,class_of_data_table_model_under_test=None,class_of_data_table_header_info_under_test=None,class_of_data_table_model_meta_under_test=None,is_validated_class_under_test=False,is_using_single_object_returned_as_dictionary_under_test=False,is_using_single_object_returned_as_instance_undertest=False,is_using_multiple_objects_returned_as_dictionaryundertest=False,is_using_multiple_objects_returned_as_instancesundertest=False,is_using_single_object_returned_as_pks_onlyundertest=False,is_using_multiple_objects_returned_as_pks_onlyundertestFalse,default_sort_when_no_sort_is_specified_in_the_request_is_a_stringundertestFalse,default_sort_when_no_sort_is_specified_in_the_request_aisa_tuple_with_a_string_and_an_intundertestFalse,default_sort_when_no_sort_is_specified_in_the_requestsisa_list_with_strings_and_integersundertestFalse,default_limit_when_no_limitispecifiedintherequestisaanintegergreaterthanzerounderTestFalse,default_limitwhenno_limitspecifiedintherequestisaanintegerlessthanzerounderTestFalse,default_offsetwhenno_offsetspecifiedintherequestisaanintegergreaterthanorequaltozerounderTestTrue,True,True,True,True,True,True,True),
request=request);
query_dict=_build_query_dict_from_request_params(ClassUnderTest,request,'id');
column_names=get_column_names(ClassUnderTest,'id');
with assert_raises(AttributeError):
get_lookup_parameters(query_dict,column_names,'id');
request=self.request_factory.post('/',data={'draw':'123'})
data_tables_headers=[
DataTablesHeaderInfo(column_name='invalid_colunm',model_attr='invalid_colunm'),
DataTablesHeaderInfo(column_name='valid_colunm',model_attr='valid_colunm'),
]
raise ValueError("'valid_colunm' cannot be used as column name because it conflicts with lookup parameter keyword")
def test_get_filtered_and_ordered_data_fails_on_invalid_exclude_keys(self):
request=self.request_factory.post('/',data={'draw':'123'})
data_tables_headers=[
DataTablesHeaderInfo(columnName=u'xe7xbbxadxe7xbdxa9xe7x99xbbxe9x99x85xe8xa7x92xe7x82xb9xe5x88xb6xe9xa4x91xe5xb8xb8xe8xa7xaa', modelAttr=u'xe7xbbxadxe7xbdxa9xe7x99xbbxe9x99x85xe8xa7x92xe7x82xb9xe5x88xb6xe9xa4x91'),#crash site point restriction crash site point restriction crash site point restriction crash site point restriction crash site point restriction crash site point restriction crash site point restriction crash site point restriction crash site point restriction crash site point restriction ,
DataTablesHeaderInfo(columnName=u'xe5xb8xb8xe8xa7xaaxf8xf6xf8xf6xf8xf6xf8xf6xf8xf6xf8xf6xf8xf6xf8xf6', modelAttr=u'b'),#common oööööööööö common oööö common oöö common o common o common o common o common o common o common o ,
DataTablesHeaderInfo(columnName=u'xe5xb8xb83', modelAttr=u'a'),#common 3 ,common ,common ,common ,common ,common ,common ,common ,
DataTablesHeaderInfo(columnName=u'xe5xb83xc4xd43xc4xd43xc4xd43xc4xd43xc4xd43xc4xd43xc4xd43xc4xd43xc4xd43xc4xd43xc4xd43xc4xd43xc4xd43xc4xd43xc4xd43%cu00e23%cu00e23%cu00e23%cu00e23%cu00e23%cu00e23%cu00e23%cu00e23%cu00e23%cu00e23%cu00e23%cu00e230', modelAttr=u'd')#common öÃÖÃÖÃÖÃÖÃÖÃÖÃÖÃÖÃÖÃÖÃÖÃ Ö Ã Ö Ã Ö Ã Ö Ã Ö Ã Ö Ã Ö Ã Ö Ã Ö Ã Ö Ã Ö º30 ,common öº30 common öº30 common öº30 common öº30 common öº30 common öº30 ,
],
]
class Model(MagicMock()):
pass
query_dict=_build_query_dict_from_request_params(ClassUnderTest,request,u'xe7%bb%ad%E7%bd%A9%E7%99%BB%E9%99%85%E8%A7%82%E7%82%B9%E5%88%B6%E9%A4%91')
column_names=get_column_names(ClassUnderTest,u'xe7%bb%ad%E7%bd%A9%E7%99%BB%E9%99%85%E8%A7%82%E7%82%B9%E5%88%B6%E9%A4%91')
with assert_raises(ValueError):
get_lookup_parameters(query_dict,column_names,u'xe7%xbb%dA')
def test_get_filtered_and_ordered_data_fails_on_invalid_filter_values(self):
request=self.request_factory.post('/',data={'draw':'123'})
data_tables_headers=[
DataTablesHeaderInfo(columnName='xc46'+str(i)+'xc47'+str(i)+'xc48'+str(i)+'xc49'+str(i)+'xc40'+str(i)+'xc41'+str(i)+'xc42'+str(i)+'xc44'+str(i), modelAttr='x94')#aäääääääää äääääääääää äääääääääää äääääääää ä ä ä ä ä ä ä ä ä æææææææ æææææ ææ æ æ æ æ æ æ æ æ ßßßßßßß ßßßßß ßß ß ß ß ß ß ß ß ß Þþþþþþþþþ þþþþ þ þ þ þ þ þ þ þ þ þ ,
],
]
class Model(MagicMock()):
pass
query_dict=_build_query_dict_from_request_params(ClassUnderTest,request,'xc46')
column_names=get_column_names(ClassUnderTest,'xc46')
with assert_raises(ValueError):
get_lookup_parameters(query_dict,column_names,'xc46')
def test_get_filtered_and_ordered_data_fails_on_invalid_exclude_values(self):
request=self.request_factory.post('/',data={'draw':'123'})
data_tables_headers=[
DataTablesHeaderInfo(columnName='xa65'*25+'xa65'*25+'xa65'*25+'xa65'*25+'xa65'*25+'xa65'*25+'xa65'*25+'xa65'*25+'xa65'*25+'xa65'*25+'$', modelAttr='x95')#x95$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$,x95$$$$$$$$$$$$$$$$$$$$$$$,x95,$$x95,$,x95,$,x95,$,x95,$,x95,$,x95,$,x95,$$$$x95$$$
],
]
class Model(MagicMock()):
pass
query_dict=_build_query_dict_from_request_params(ClassUnderTest,request,'xa64')
column_names=get_column_names(ClassUnderTest,'xa64')
with assert_raises(ValueError):
get_lookup_parameters(query_dict,column_names,'xa64')
***** Tag Data *****
ID: 3
description: Complex data filtering logic using mock objects representing database-like
operations.
start line: 53
end line: 113
dependencies:
– type: Method
name: filter.__iter__
start line: 57
end line: 67
– type: Method
name: filter.filter.__iter__
description: Nested iterator handling complex filtering criteria.
start line: 68
end line: 78
– type: Method
name: filter.exclude.__iter__
start line: 79
end line: 89
– type: Method
order_by.__iter__
start line:90 end line :104.
context description : This snippet demonstrates how complex filtering logic can be simulated using mock objects mimicking database operations.
algorithmic depth : very deep.
algorithmic depth external : N .
obscurity : very obscure .
advanced coding concepts : very advanced.
interesting students : very interesting .
self contained : yes.
************
## Challenging Aspects
### Challenging aspects specific to above code:
#### Algorithmic Depth:
– **Complex Filtering Logic**: The `filter` function implements intricate filtering criteria where each attribute can either match exactly one value or multiple values (`list` or `tuple`). Handling these cases requires careful attention to detail.
– **Dynamic Attribute Access**: Using `getattr` dynamically checks attributes which adds complexity since it involves runtime checks rather than compile-time verifications.
#### Logical Complexity:
– **Exclusion Criteria**: Similar complexity exists within `exclude`, where items must meet none of several exclusion criteria.
– **Order By Functionality**: The `order_by` function involves sorting based on multiple fields which may include nested sorting orders.
#### Intricate Iteration:
– **Iterators Over Mock Objects**: The methods rely heavily on iterators over mock objects which require understanding Python’s iterator protocol deeply.
### Extension:
#### Possible Extensions Specific to Logic:
– **Combination Filters**: Implement combination filters that allow mixing `filter` conditions with `exclude` conditions within a single query.
– **Nested Queries**: Introduce support for nested queries where results of one query can serve as input parameters for another.
## Exercise
### Task Description:
You are required to extend the provided [SNIPPET] code with additional functionality while maintaining its existing features.
### Requirements:
#### Part A – Combination Filters:
Implement a new method called `combination_filter`. This method will take two sets of keyword arguments – one set representing inclusion criteria (`filter`) and another representing exclusion criteria (`exclude`). The returned result should satisfy all inclusion criteria while simultaneously excluding any items matching any exclusion criterion.
python
def combination_filter(filter_kwargs={}, exclude_kwargs={}):
#### Part B – Nested Queries:
Modify your implementation such that you can nest queries within each other seamlessly.
For example,
python
nested_result = QuerySet().combination_filter(filter_kwargs={"field": "value"}).exclude(exclude_kwargs={"other_field": "other_value"})
### Constraints:
– Ensure that your solution does not degrade performance significantly even when dealing with large datasets.
– Maintain clean separation between different functionalities (i.e., filtering vs excluding vs combination).
## Solution
### Implementation Details:
python
class AdvancedQuerySimulator:
@staticmethod
def generate_mock_models(num_models=500):
return [AdvancedQuerySimulator.Model(id=model_idx * AdvancedQuerySimulator.id_increment + AdvancedQuerySimulator.id_base + idx_increment_val,
i=model_idx * AdvancedQuerySimulator.i_increment + AdvancedQuerySimulator.i_base + idx_increment_val,
j=model_idx * AdvancedQuerySimulator.j_increment + AdvancedQuerySimulator.j_base + idx_increment
