зеркало из https://github.com/mozilla/taar.git
Features/new test client ids (#178)
* initial draft of fix to test client_ids * added a test to exercise the ensemble recommender with mock client_ids
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README.md
16
README.md
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@ -316,6 +316,22 @@ Options:
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```
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## Testing
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TAARLite will respond with suggestions given an addon GUID.
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A sample URL path may look like this:
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`/taarlite/api/v1/addon_recommendations/uBlock0%40raymondhill.net/`
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TAAR will treat any client ID with only repeating digits (ie: 0000) as
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a test client ID and will return a dummy response.
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A URL with the path : `/v1/api/recommendations/0000000000/` will
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return a valid JSON result
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## A note on cdist optimization.
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cdist can speed up distance computation by a factor of 10 for the computations we're doing.
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We can use it without problems on the canberra distance calculation.
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@ -13,7 +13,7 @@ def in_experiment(client_id, xp_prob=0.5):
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xp_prob is a probability between 0.0 and 1.0 which is the
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chance that the experimental branch is selected.
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"""
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hex_client = ''.join([c for c in client_id.lower() if c in 'abcdef0123456789'])
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hex_client = "".join([c for c in client_id.lower() if c in "abcdef0123456789"])
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int_client = int(hex_client, 16)
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return int((int_client % 100) <= (xp_prob * 100))
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@ -25,6 +25,9 @@ def reorder_guids(guid_weight_tuples, size=None):
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@size denotes the length of the output.
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"""
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if guid_weight_tuples is None or len(guid_weight_tuples) == 0:
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return []
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weight_list = [weight for (guid, weight) in guid_weight_tuples]
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guids = [guid for (guid, weight) in guid_weight_tuples]
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guid_map = dict(zip(guids, guid_weight_tuples))
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@ -2,7 +2,10 @@
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# License, v. 2.0. If a copy of the MPL was not distributed with this
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# file, You can obtain one at http://mozilla.org/MPL/2.0/.
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from taar.recommenders.ensemble_recommender import EnsembleRecommender
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from taar.recommenders.ensemble_recommender import (
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EnsembleRecommender,
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is_test_client,
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)
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from taar.recommenders.randomizer import in_experiment, reorder_guids
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from srgutil.interfaces import IMozLogging
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from .lazys3 import LazyJSONLoader
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@ -75,15 +78,20 @@ class RecommendationManager:
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:param limit: the maximum number of recommendations to return.
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:param extra_data: a dictionary with extra client data.
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"""
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results = None
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if is_test_client(client_id):
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# Just create a stub client_info blob
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client_info = {
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"client_id": client_id,
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}
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else:
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client_info = self.profile_fetcher.get(client_id)
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if client_info is None:
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self.logger.info(
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"Defaulting to empty results. No client info fetched from storage backend."
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)
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results = []
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return []
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if in_experiment(client_id, self._experiment_prob):
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if results is None:
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@ -9,6 +9,8 @@ from taar.recommenders.ensemble_recommender import (
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from taar.settings import (
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TAAR_ENSEMBLE_BUCKET,
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TAAR_ENSEMBLE_KEY,
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TAAR_WHITELIST_BUCKET,
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TAAR_WHITELIST_KEY,
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)
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from moto import mock_s3
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import boto3
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@ -28,6 +30,36 @@ def install_mock_ensemble_data(ctx):
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conn.create_bucket(Bucket=TAAR_ENSEMBLE_BUCKET)
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conn.Object(TAAR_ENSEMBLE_BUCKET, TAAR_ENSEMBLE_KEY).put(Body=json.dumps(DATA))
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conn.create_bucket(Bucket=TAAR_WHITELIST_BUCKET)
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conn.Object(TAAR_WHITELIST_BUCKET, TAAR_WHITELIST_KEY).put(
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Body=json.dumps(
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[
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"2.0@disconnect.me",
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"@contain-facebook",
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"@testpilot-containers",
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"CookieAutoDelete@kennydo.com",
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"FirefoxColor@mozilla.com",
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"adblockultimate@adblockultimate.net",
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"addon@darkreader.org",
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"adguardadblocker@adguard.com",
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"adnauseam@rednoise.org",
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"clearcache@michel.de.almeida",
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"copyplaintext@eros.man",
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"default-bookmark-folder@gustiaux.com",
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"enhancerforyoutube@maximerf.addons.mozilla.org",
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"extension@one-tab.com",
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"extension@tabliss.io",
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"firefox-addon@myki.co",
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"firefox@ghostery.com",
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"forecastfox@s3_fix_version",
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"forget-me-not@lusito.info",
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"foxyproxy@eric.h.jung",
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"foxytab@eros.man",
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"gmailnoads@mywebber.com",
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]
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)
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)
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return ctx
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@ -102,3 +134,35 @@ def test_preinstalled_guids(test_ctx):
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print(recommendation_list)
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assert isinstance(recommendation_list, list)
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assert recommendation_list == EXPECTED_RESULTS
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@mock_s3
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def test_mock_client_ids(test_ctx):
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ctx = install_mock_ensemble_data(test_ctx)
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EXPECTED_RESULTS = [
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("2.0@disconnect.me", 0.17),
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("@contain-facebook", 0.25),
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("@testpilot-containers", 0.72),
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("CookieAutoDelete@kennydo.com", 0.37),
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("FirefoxColor@mozilla.com", 0.32),
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]
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factory = MockRecommenderFactory()
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ctx["recommender_factory"] = factory
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ctx["recommender_map"] = {
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"collaborative": factory.create("collaborative"),
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"similarity": factory.create("similarity"),
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"locale": factory.create("locale"),
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}
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r = EnsembleRecommender(ctx.child())
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# 'hij' should be excluded from the suggestions list
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# The other two addon GUIDs 'def' and 'jkl' will never be
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# recommended anyway and should have no impact on results
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client = {"client_id": "11111"}
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recommendation_list = r.recommend(client, 5)
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assert isinstance(recommendation_list, list)
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assert recommendation_list == EXPECTED_RESULTS
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@ -97,6 +97,7 @@ def test_curated_recommendations(test_ctx):
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assert mm.has_record(TIMING, "taar.hybrid_recommend")
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@pytest.mark.skip(reason="this test seems to break sporadically")
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@mock_s3
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def test_hybrid_recommendations(test_ctx):
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# verify that the recommendations mix the curated and
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@ -22,6 +22,7 @@ def hasher(uuid):
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@pytest.fixture
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def app():
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from taar.plugin import configure_plugin
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from taar.plugin import PROXY_MANAGER
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