def test_recommendation_weights():
"""
Weights should be ordered greatest to lowest
"""
ctx = get_mocked_ctx()
r = CollaborativeRecommender(ctx)
# An non-empty set of addons should give a list of recommendations
fixture_client_data = {"installed_addons": ["addon4.id"],
"client_id": "test_client"}
assert r.can_recommend(fixture_client_data)
recommendations = r.recommend(fixture_client_data, 2)
assert isinstance(recommendations, list)
assert len(recommendations) == 2
# Verify that addon2 - the most heavy weighted addon was
# recommended
result = recommendations[0]
assert type(result) is tuple
assert len(result) == 2
assert result[0] == 'addon2.id'
assert type(result[1]) is numpy.float64
assert numpy.isclose(result[1], numpy.float64('0.3225'))
# Verify that addon2 - the most heavy weighted addon was
# recommended
result = recommendations[1]
assert type(result) is tuple
assert len(result) == 2
assert result[0] == 'addon5.id'
assert type(result[1]) is numpy.float64
assert numpy.isclose(result[1], numpy.float64('0.29'))
def test_best_recommendation(test_ctx):
# Make sure the structure of the recommendations is correct and that we
# recommended the the right addon.
ctx = install_mock_data(test_ctx)
r = CollaborativeRecommender(ctx)
# An non-empty set of addons should give a list of recommendations
fixture_client_data = {
"installed_addons": ["addon4.id"],
"client_id": "test_client"
}
assert r.can_recommend(fixture_client_data)
recommendations = r.recommend(fixture_client_data, 1)
assert isinstance(recommendations, list)
assert len(recommendations) == 1
# Verify that addon2 - the most heavy weighted addon was
# recommended
result = recommendations[0]
assert type(result) is tuple
assert len(result) == 2
assert result[0] == 'addon2.id'
assert type(result[1]) is numpy.float64
assert numpy.isclose(result[1], numpy.float64('0.3225'))
def test_recommendations(activate_responses):
# Tests that the empty recommender always recommends an empty list
# of addons.
r = CollaborativeRecommender()
recommendations = r.recommend({}, 1)
# Make sure the structure of the recommendations is correct and that we
# recommended the the right addon.
assert isinstance(recommendations, list)
assert len(recommendations) == 1
def test_recommendations(activate_responses):
# Tests that the empty recommender always recommends an empty list
# of addons.
r = CollaborativeRecommender()
recommendations = r.recommend({}, 1)
# Make sure the structure of the recommendations is correct and that we
# recommended the the right addon.
assert isinstance(recommendations, list)
assert len(recommendations) == 1
# We are not sure about what addon will be recommended in the test.
# Only make sure the reported id is among the expected ones and that
# it's a webextension.
ADDON_IDS = [
value['id'] for value in FAKE_MAPPING.values()
if value['isWebextension']
]
assert recommendations[0] in ADDON_IDS