def test_cant_recommend(test_ctx):
ctx = install_mock_data(test_ctx)
r = CollaborativeRecommender(ctx)
# Test that we can't recommend if we have not enough client info.
assert not r.can_recommend({})
assert not r.can_recommend({"installed_addons": []})
def test_can_recommend_no_model(activate_error_responses):
r = CollaborativeRecommender()
# We should never be able to recommend if something went wrong with the model.
assert not r.can_recommend({})
assert not r.can_recommend({"installed_addons": []})
assert not r.can_recommend({"installed_addons": ["*****@*****.**"]})
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_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_can_recommend(activate_responses):
r = CollaborativeRecommender()
# Test that we can't recommend if we have not enough client info.
assert not r.can_recommend({})
assert not r.can_recommend({"installed_addons": []})
# Check that we can recommend if we the user has at least an addon.
assert r.can_recommend({"installed_addons": ["*****@*****.**"]})
def test_can_recommend(test_ctx):
with mock_install_mock_data(test_ctx):
r = CollaborativeRecommender(test_ctx)
# Check that we can recommend if the user has at least an addon.
assert r.can_recommend({
"installed_addons": ["*****@*****.**"],
"client_id": "test-client",
})
def test_can_recommend_no_model(test_ctx):
ctx = install_none_mock_data(test_ctx)
r = CollaborativeRecommender(ctx)
# We should never be able to recommend if something went wrong with the model.
assert not r.can_recommend({})
assert not r.can_recommend({"installed_addons": []})
assert not r.can_recommend(
{"installed_addons": ["*****@*****.**"]})
def test_can_recommend(test_ctx):
ctx = install_mock_data(test_ctx)
r = CollaborativeRecommender(ctx)
# For some reason, moto doesn't like to play nice with this call
# Check that we can recommend if we the user has at least an addon.
assert r.can_recommend({
"installed_addons": ["*****@*****.**"],
"client_id": "test-client"
})
def test_can_recommend():
ctx = get_mocked_ctx()
r = CollaborativeRecommender(ctx)
# Test that we can't recommend if we have not enough client info.
assert not r.can_recommend({})
assert not r.can_recommend({"installed_addons": []})
# Check that we can recommend if we the user has at least an addon.
assert r.can_recommend({"installed_addons": ["*****@*****.**"]})
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_recommender_str(activate_responses):
"""Tests that the string representation of the recommender is correct
"""
# TODO: this test is brittle and should be removed once it is safe
# to do so
r = CollaborativeRecommender()
assert str(r) == "CollaborativeRecommender"
def test_recommender_str():
"""Tests that the string representation of the recommender is correct
"""
# TODO: this test is brittle and should be removed once it is safe
# to do so
ctx = get_mocked_ctx()
r = CollaborativeRecommender(ctx)
assert str(r) == "CollaborativeRecommender"
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
def test_empty_recommendations(activate_responses):
# Tests that the empty recommender always recommends an empty list
# of addons if we have no addons
r = CollaborativeRecommender()
assert not r.can_recommend({})
def test_recommender_str(activate_responses):
# Tests that the string representation of the recommender is correct
r = CollaborativeRecommender()
assert str(r) == "CollaborativeRecommender"
def test_empty_recommendations():
# Tests that the empty recommender always recommends an empty list
# of addons if we have no addons
ctx = get_mocked_ctx()
r = CollaborativeRecommender(ctx)
assert not r.can_recommend({})
def test_empty_recommendations(test_ctx):
# Tests that the empty recommender always recommends an empty list
# of addons if we have no addons
ctx = install_none_mock_data(test_ctx)
r = CollaborativeRecommender(ctx)
assert not r.can_recommend({})
