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Calculate correct avg_rating for JSON rep as well

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Kovid Goyal 2015-11-23 15:39:37 +05:30
parent 502193eb24
commit 68790624fe
1 changed files with 40 additions and 4 deletions
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44
src/calibre/srv/metadata.py
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@ -252,7 +252,7 @@ def collapse_first_letter(collapse_nodes, items, category_node, cl_list, idx, is
def process_category_node(
category_node, items, category_data, eval_formatter, field_metadata,
opts, tag_map, hierarchical_tags, node_to_tag_map, collapse_nodes,
intermediate_nodes):
intermediate_nodes, hierarchical_nodes):
category = items[category_node['id']]['category']
category_items = category_data[category]
cat_len = len(category_items)
@ -288,6 +288,8 @@ def process_category_node(
else:
node_id, node_data = node_data
node = {'id':node_id, 'children':[]}
if node_id not in hierarchical_nodes:
hierarchical_nodes[node_id] = node
parent['children'].append(node)
return node, node_data
@ -329,7 +331,10 @@ def process_category_node(
cm_key = component, tag.category
if cm_key in child_map:
node_parent = child_map[cm_key]
items[node_parent['id']]['is_hierarchical'] = 3 if tag.category == 'search' else 5
node_id = node_parent['id']
items[node_id]['is_hierarchical'] = 3 if tag.category == 'search' else 5
if node_id not in hierarchical_nodes:
hierarchical_nodes[node_id] = node_parent
hierarchical_tags.add(id(node_to_tag_map[node_parent['id']]))
else:
if i < len(components) - 1: # Non-leaf node
@ -368,7 +373,7 @@ def iternode_descendants(node):
def fillout_tree(root, items, node_id_map, category_nodes, category_data, field_metadata, opts):
eval_formatter = EvalFormatter()
tag_map, hierarchical_tags, node_to_tag_map = {}, set(), {}
first, later, collapse_nodes, intermediate_nodes = [], [], [], {}
first, later, collapse_nodes, intermediate_nodes, hierarchical_nodes = [], [], [], {}, {}
# User categories have to be processed after normal categories as they can
# reference hierarchical nodes that were created only during processing of
# normal categories
@ -382,7 +387,7 @@ def fillout_tree(root, items, node_id_map, category_nodes, category_data, field_
process_category_node(
cnode, items, category_data, eval_formatter, field_metadata,
opts, tag_map, hierarchical_tags, node_to_tag_map,
collapse_nodes, intermediate_nodes)
collapse_nodes, intermediate_nodes, hierarchical_nodes)
# Do not store id_set in the tag items as it is a lot of data, with not
# much use. Instead only update the counts based on id_set
@ -395,6 +400,37 @@ def fillout_tree(root, items, node_id_map, category_nodes, category_data, field_
item = items[node['id']]
item['count'] = sum(1 for _ in iternode_descendants(node))
# Calculate correct avg_rating for hierarchical category items
calculated = {}
def set_average_rating(item_id, children):
cr = calculated.get(item_id, None)
if cr is not None:
return cr
item = items[item_id]
if not item.get('is_hierarchical', False) or not children:
return item.get('avg_rating', 0)
total = num = 0
for child in children:
r = set_average_rating(child['id'], child['children'])
if r:
total += 1
num += r
sr = item.get('avg_rating', 0)
if sr:
total += 1
num += sr
try:
calculated[item_id] = item['avg_rating'] = ans = num/float(total)
except ZeroDivisionError:
calculated[item_id] = item['avg_rating'] = ans = 0
return ans
for item_id, node in hierarchical_nodes.iteritems():
item = items[item_id]
if item.get('is_hierarchical', False):
set_average_rating(item_id, node['children'])
def render_categories(field_metadata, opts, category_data):
items = {}
root, node_id_map, category_nodes, recount_nodes = create_toplevel_tree(category_data, items, field_metadata, opts)