def get_values_counts(self, qs):
# It is easiest to base queries around the intermediate table, in order
# to get counts.
through = self.field_obj.rel.through
rel_model = self.rel_model
assert rel_model != self.model, "Can't cope with this yet..."
fkey_this = [
f for f in through._meta.fields
if f.rel is not None and f.rel.to is self.model
][0]
fkey_other = [
f for f in through._meta.fields
if f.rel is not None and f.rel.to is rel_model
][0]
# We need to limit items by what is in the main QuerySet (which might
# already be filtered).
m2m_objs = through.objects.filter(**{fkey_this.name + '__in': qs})
# We need to exclude items in other table that we have already filtered
# on, because they are not interesting.
m2m_objs = m2m_objs.exclude(**{fkey_other.name + '__in': self.chosen})
# Now get counts:
field_name = fkey_other.name
return value_counts(m2m_objs, field_name)
def get_values_counts(self, qs):
"""
Returns a SortedDict dictionary of {value: count}.
The order is the underlying order produced by sorting ascending on the
DB field.
"""
return value_counts(qs, self.field)
def get_values_counts(self, qs):
"""
Returns a SortedDict dictionary of {value: count}.
The order is the underlying order produced by sorting ascending on the
DB field.
"""
return value_counts(qs, self.field)
def get_choices_add(self, qs):
chosen = list(self.chosen)
range_type = None
if not self.drilldown and len(chosen) > 0:
return []
all_vals = qs.values_list(self.field).distinct()
num = all_vals.count()
choices = []
if num <= self.max_links:
val_counts = value_counts(qs, self.field)
for v, count in val_counts.items():
choice = self.choice_type([RangeEnd(v, True)])
choices.append(FilterChoice(self.render_choice_object(choice),
count,
self.build_params(add=choice),
FILTER_ADD))
else:
if self.ranges is None:
val_range = qs.aggregate(lower=models.Min(self.field),
upper=models.Max(self.field))
ranges = auto_ranges(val_range['lower'], val_range['upper'], self.max_links)
else:
ranges = self.ranges
val_counts = numeric_range_counts(qs, self.field, ranges)
for i, (vals, count) in enumerate(val_counts.items()):
# For the lower bound, we make it inclusive only if it the first
# choice. The upper bound is always inclusive. This gives
# filters that behave sensibly e.g. with 10-20, 20-30, 30-40,
# the first will include 10 and 20, the second will exlude 20.
choice = self.choice_type([RangeEnd(vals[0], i == 0),
RangeEnd(vals[1], True)])
choices.append(FilterChoice(self.render_choice_object(choice),
count,
self.build_params(add=choice),
FILTER_ADD))
return choices
def get_choices_add(self, qs):
chosen = list(self.chosen)
if not self.drilldown and len(chosen) > 0:
return []
all_vals = qs.values_list(self.field).distinct()
num = all_vals.count()
choices = []
if num <= self.max_links:
val_counts = value_counts(qs, self.field)
for v, count in val_counts.items():
choice = self.choice_type([RangeEnd(v, True)])
choices.append(
FilterChoice(self.render_choice_object(choice), count,
self.build_params(add=choice), FILTER_ADD))
else:
if self.ranges is None:
val_range = qs.aggregate(lower=models.Min(self.field),
upper=models.Max(self.field))
ranges = auto_ranges(val_range['lower'], val_range['upper'],
self.max_links)
else:
ranges = self.ranges
val_counts = numeric_range_counts(qs, self.field, ranges)
for i, (vals, count) in enumerate(val_counts.items()):
# For the lower bound, we make it inclusive only if it the first
# choice. The upper bound is always inclusive. This gives
# filters that behave sensibly e.g. with 10-20, 20-30, 30-40,
# the first will include 10 and 20, the second will exlude 20.
choice = self.choice_type(
[RangeEnd(vals[0], i == 0),
RangeEnd(vals[1], True)])
choices.append(
FilterChoice(self.render_choice_object(choice), count,
self.build_params(add=choice), FILTER_ADD))
return choices
def get_values_counts(self, qs):
# It is easiest to base queries around the intermediate table, in order
# to get counts.
through = self.field_obj.rel.through
rel_model = self.rel_model
assert rel_model != self.model, "Can't cope with this yet..."
fkey_this = [f for f in through._meta.fields
if f.rel is not None and f.rel.to is self.model][0]
fkey_other = [f for f in through._meta.fields
if f.rel is not None and f.rel.to is rel_model][0]
# We need to limit items by what is in the main QuerySet (which might
# already be filtered).
m2m_objs = through.objects.filter(**{fkey_this.name + '__in': qs})
# We need to exclude items in other table that we have already filtered
# on, because they are not interesting.
m2m_objs = m2m_objs.exclude(**{fkey_other.name + '__in': self.chosen})
# Now get counts:
field_name = fkey_other.name
return value_counts(m2m_objs, field_name)
