samples/searchforshopping/histograms.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright 2014 Google Inc. All Rights Reserved.

"""Query with ranked results against the shopping search API"""
from __future__ import print_function

from googleapiclient.discovery import build


SHOPPING_API_VERSION = "v1"
DEVELOPER_KEY = "<YOUR DEVELOPER KEY>"


def main():
    """Get and print a histogram of the top 15 brand distribution for a search
    query.

    Histograms are created by using the "Facets" functionality of the API. A
    Facet is a view of a certain property of products, containing a number of
    buckets, one for each value of that property. Or concretely, for a parameter
    such as "brand" of a product, the facets would include a facet for brand,
    which would contain a number of buckets, one for each brand returned in the
    result.

    A bucket contains either a value and a count, or a value and a range. In the
    simple case of a value and a count for our example of the "brand" property,
    the value would be the brand name, eg "sony" and the count would be the
    number of results in the search.
    """
    client = build("shopping", SHOPPING_API_VERSION, developerKey=DEVELOPER_KEY)
    resource = client.products()
    request = resource.list(
        source="public",
        country="US",
        q="digital camera",
        facets_include="brand:15",
        facets_enabled=True,
    )
    response = request.execute()

    # Pick the first and only facet for this query
    facet = response["facets"][0]

    print('\n\tHistogram for "%s":\n' % facet["property"])

    labels = []
    values = []

    for bucket in facet["buckets"]:
        labels.append(bucket["value"].rjust(20))
        values.append(bucket["count"])

    weighting = 50.0 / max(values)

    for label, value in zip(labels, values):
        print(label, "#" * int(weighting * value), "(%s)" % value)

    print()


if __name__ == "__main__":
    main()