1 #!/usr/bin/env python 2 # -*- coding: utf-8 -*- 3 # 4 # Copyright 2014 Google Inc. All Rights Reserved. 5 6 """Query with ranked results against the shopping search API""" 7 from __future__ import print_function 8 9 from googleapiclient.discovery import build 10 11 12 SHOPPING_API_VERSION = 'v1' 13 DEVELOPER_KEY = 'AIzaSyACZJW4JwcWwz5taR2gjIMNQrtgDLfILPc' 14 15 16 def main(): 17 """Get and print a histogram of the top 15 brand distribution for a search 18 query. 19 20 Histograms are created by using the "Facets" functionality of the API. A 21 Facet is a view of a certain property of products, containing a number of 22 buckets, one for each value of that property. Or concretely, for a parameter 23 such as "brand" of a product, the facets would include a facet for brand, 24 which would contain a number of buckets, one for each brand returned in the 25 result. 26 27 A bucket contains either a value and a count, or a value and a range. In the 28 simple case of a value and a count for our example of the "brand" property, 29 the value would be the brand name, eg "sony" and the count would be the 30 number of results in the search. 31 """ 32 client = build('shopping', SHOPPING_API_VERSION, developerKey=DEVELOPER_KEY) 33 resource = client.products() 34 request = resource.list(source='public', country='US', q=u'digital camera', 35 facets_include='brand:15', facets_enabled=True) 36 response = request.execute() 37 38 # Pick the first and only facet for this query 39 facet = response['facets'][0] 40 41 print('\n\tHistogram for "%s":\n' % facet['property']) 42 43 labels = [] 44 values = [] 45 46 for bucket in facet['buckets']: 47 labels.append(bucket['value'].rjust(20)) 48 values.append(bucket['count']) 49 50 weighting = 50.0 / max(values) 51 52 for label, value in zip(labels, values): 53 print(label, '#' * int(weighting * value), '(%s)' % value) 54 55 print() 56 57 58 if __name__ == '__main__': 59 main() 60
