Filters for django
Project description
__What it is:__
A lightweight package for django which does the filtering of django querysets. The central object - a filter - is a callable that takes a queryset as a parameter and returns a queryset:
filtered_queryset = filtr(Model.objects.all())
Django itself has a similar object - Q-object (`django.db.models.Q`). Q-objects can be combined toghether (with `|`, `&` operations) or inverted (`~`) and then passed to `queryset.filter`.
With `qfilters`, what you get in the most common case, is just a wrapper around the Q-object. However there are __2 features__ that may be the reasons to use the package:
__1. Support for additional filter types.__
For example, there is `ValuesDictFilter`, that is constructed from a field list, that will be passed to `queryset.values` and retrieve a list of dictionaries, and a filtering function, which accepts that dict as a parameter.
This filters can be combined or inverted in the same way Q-objects do, so that using multiple filters would result in a single call to `queryset.values`.
This is what it looks like in practice (all examples are taken from the `qfilter` testsuite):
@ValuesDictFilter('@', fields_list=['traits__good_hunter'])
def nas_i_zdes_neploho_kormyat(obj):
return obj['traits__good_hunter'] is False # because it can be None
cats = nas_i_zdes_neploho_kormyat(self.CatsBreed.objects.all())
assert cats.exists()
There are also exotic variants (`qfilters.exotic_types`) like `QuerysetIterationHook`, which appends attributes to objects when queryset is iterated over. Another one is `PropertyBasedFilter`, which can access object's attributes and even properties like it were a regular django model object. The implementation is not very straightforward, still it passes the tests so far. Here is what it looks like:
class CatsBreed(models.Model):
# ...
traits = models.OneToOneField('Traits')
class Traits(models.Model):
#...
weight_min = models.FloatField(u'Вес от, кг', null=True)
weight_max = models.FloatField(u'Вес до, кг', null=True)
# if you can't specify min and max
weight = models.FloatField(u'Вес, кг', null=True)
@property
def kg(self):
return self.weight or self.weight_max
from qfilters import PropertyBasedFilter
@PropertyBasedFilter('@',
fields_list=['traits__weight', 'traits__weight_max'],
properties=['traits.kg'])
def light_cats(obj):
return not obj.traits.kg or obj.traits.kg < 3
assert light_cats(CatsBreed.objects.all()).exists()
__2. Using class as container: methods are filters__
It is convenient to have an object, which can hold some context (for example, the view itself),
and let the methods be filters, and be able to access this context. `qfilters.containers` provide this functionality, specifically, there is a `MethodFilter` class:
from qfilter import MethodFilter
class ManyFilters(MethodFilter):
def filter__q(self):
return Q(name__in=[u'Сиамская', u'Норвежская лесная'])
@make_filter(PropertyBasedFilter,
fields_list=['traits__weight', 'traits__weight_max'],
properties=['traits.kg'])
def filter__big(self, cat):
return cat.traits.kg and cat.traits.kg > 5
def filter__q_yet_another(self):
return Q(name__in=[u'Персидская', u'Норвежская лесная'])
filters = ManyFilters()
cat = filters(CatsBreed.objects.all())[0]
The idea was born from the experience of using the [django-rest-framework](http://www.django-rest-framework.org/). There is a notion of filter backend (a class) which every view knows about. First I implemented a simple method-based filter backend, the possible return values for the methods were eiher a Q-object or a queryset. But then I got difficulties with debugging since the return value doesn't even know which method it came from. Thus, I decided it will be a good idea to have this filter obbject.
P.S. `qfilters` does not provide a filter backend to use with django-rest-framework, but it's a piece of cake to write one.
A lightweight package for django which does the filtering of django querysets. The central object - a filter - is a callable that takes a queryset as a parameter and returns a queryset:
filtered_queryset = filtr(Model.objects.all())
Django itself has a similar object - Q-object (`django.db.models.Q`). Q-objects can be combined toghether (with `|`, `&` operations) or inverted (`~`) and then passed to `queryset.filter`.
With `qfilters`, what you get in the most common case, is just a wrapper around the Q-object. However there are __2 features__ that may be the reasons to use the package:
__1. Support for additional filter types.__
For example, there is `ValuesDictFilter`, that is constructed from a field list, that will be passed to `queryset.values` and retrieve a list of dictionaries, and a filtering function, which accepts that dict as a parameter.
This filters can be combined or inverted in the same way Q-objects do, so that using multiple filters would result in a single call to `queryset.values`.
This is what it looks like in practice (all examples are taken from the `qfilter` testsuite):
@ValuesDictFilter('@', fields_list=['traits__good_hunter'])
def nas_i_zdes_neploho_kormyat(obj):
return obj['traits__good_hunter'] is False # because it can be None
cats = nas_i_zdes_neploho_kormyat(self.CatsBreed.objects.all())
assert cats.exists()
There are also exotic variants (`qfilters.exotic_types`) like `QuerysetIterationHook`, which appends attributes to objects when queryset is iterated over. Another one is `PropertyBasedFilter`, which can access object's attributes and even properties like it were a regular django model object. The implementation is not very straightforward, still it passes the tests so far. Here is what it looks like:
class CatsBreed(models.Model):
# ...
traits = models.OneToOneField('Traits')
class Traits(models.Model):
#...
weight_min = models.FloatField(u'Вес от, кг', null=True)
weight_max = models.FloatField(u'Вес до, кг', null=True)
# if you can't specify min and max
weight = models.FloatField(u'Вес, кг', null=True)
@property
def kg(self):
return self.weight or self.weight_max
from qfilters import PropertyBasedFilter
@PropertyBasedFilter('@',
fields_list=['traits__weight', 'traits__weight_max'],
properties=['traits.kg'])
def light_cats(obj):
return not obj.traits.kg or obj.traits.kg < 3
assert light_cats(CatsBreed.objects.all()).exists()
__2. Using class as container: methods are filters__
It is convenient to have an object, which can hold some context (for example, the view itself),
and let the methods be filters, and be able to access this context. `qfilters.containers` provide this functionality, specifically, there is a `MethodFilter` class:
from qfilter import MethodFilter
class ManyFilters(MethodFilter):
def filter__q(self):
return Q(name__in=[u'Сиамская', u'Норвежская лесная'])
@make_filter(PropertyBasedFilter,
fields_list=['traits__weight', 'traits__weight_max'],
properties=['traits.kg'])
def filter__big(self, cat):
return cat.traits.kg and cat.traits.kg > 5
def filter__q_yet_another(self):
return Q(name__in=[u'Персидская', u'Норвежская лесная'])
filters = ManyFilters()
cat = filters(CatsBreed.objects.all())[0]
The idea was born from the experience of using the [django-rest-framework](http://www.django-rest-framework.org/). There is a notion of filter backend (a class) which every view knows about. First I implemented a simple method-based filter backend, the possible return values for the methods were eiher a Q-object or a queryset. But then I got difficulties with debugging since the return value doesn't even know which method it came from. Thus, I decided it will be a good idea to have this filter obbject.
P.S. `qfilters` does not provide a filter backend to use with django-rest-framework, but it's a piece of cake to write one.
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