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feat: [VAN-986] Add amplitude API (#30675)

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* feat: [VAN-986] Add amplitude API

* feat: add suggestion

* feat: add spinner

Co-authored-by: Zainab Amir <zainab.amir@arbisoft.com>
This commit is contained in:
Attiya Ishaque
2022-07-05 16:23:38 +05:00
committed by GitHub
parent 4d6df67a02
commit 9d1f31603e
8 changed files with 211 additions and 72 deletions
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22
common/djangoapps/student/models.py
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@@ -19,7 +19,7 @@ from collections import defaultdict, namedtuple # lint-amnesty, pylint: disable
from datetime import date, datetime, timedelta # lint-amnesty, pylint: disable=wrong-import-order
from functools import total_ordering # lint-amnesty, pylint: disable=wrong-import-order
from importlib import import_module # lint-amnesty, pylint: disable=wrong-import-order
from urllib.parse import urlencode, urljoin
from urllib.parse import unquote, urlencode, urljoin
import crum
from config_models.models import ConfigurationModel
@@ -438,6 +438,21 @@ def get_potentially_retired_user_by_username_and_hash(username, hashed_username)
return User.objects.get(username__in=locally_hashed_usernames)
def is_personalized_recommendation_for_user(course_id):
"""
Returns the personalized recommendation value from the cookie.
"""
request = crum.get_current_request()
recommended_courses = \
request.COOKIES.get(settings.PERSONALIZED_RECOMMENDATION_COOKIE_NAME, None) if request else None
if recommended_courses:
recommended_courses = json.loads(unquote(recommended_courses))
if course_id in recommended_courses['course_keys']:
return recommended_courses['is_personalized_recommendation']
return None
class UserStanding(models.Model):
"""
This table contains a student's account's status.
@@ -1557,6 +1572,11 @@ class CourseEnrollment(models.Model):
self.course_id)
segment_properties['course_start'] = self.course.start
segment_properties['course_pacing'] = self.course.pacing
is_personalized_recommendation = is_personalized_recommendation_for_user(str(self.course_id))
if is_personalized_recommendation is not None:
segment_properties['is_personalized_recommendation'] = is_personalized_recommendation
with tracker.get_tracker().context(event_name, context):
tracker.emit(event_name, data)
segment.track(self.user_id, event_name, segment_properties, traits=segment_traits)