Files
edx-platform/lms/djangoapps/instructor_analytics/tests/test_distributions.py
usamasadiq 3f1df8eb2a Ran pyupgrade on lms/djangoapps
Ran pyupgrade on lms/djangoapps/instructor_analytics
Ran pyugprade on lms/djangoapps/instructor_task
Ran pyupgrade on lms/djangoapps/learner_dashboard
2021-02-19 17:30:59 +05:00

118 lines
4.7 KiB
Python

""" Tests for analytics.distributions """
import pytest
from django.test import TestCase
from opaque_keys.edx.locator import CourseLocator
from common.djangoapps.student.models import CourseEnrollment
from common.djangoapps.student.tests.factories import UserFactory
from lms.djangoapps.instructor_analytics.distributions import AVAILABLE_PROFILE_FEATURES, profile_distribution
class TestAnalyticsDistributions(TestCase):
'''Test analytics distribution gathering.'''
def setUp(self):
super().setUp()
self.course_id = CourseLocator('robot', 'course', 'id')
self.users = [UserFactory(
profile__gender=['m', 'f', 'o'][i % 3],
profile__level_of_education=['a', 'hs', 'el'][i % 3],
profile__year_of_birth=i + 1930
) for i in range(30)]
self.ces = [CourseEnrollment.enroll(user, self.course_id)
for user in self.users]
def test_profile_distribution_bad_feature(self):
feature = 'robot-not-a-real-feature'
assert feature not in AVAILABLE_PROFILE_FEATURES
with pytest.raises(ValueError):
profile_distribution(self.course_id, feature)
def test_profile_distribution_easy_choice(self):
feature = 'gender'
assert feature in AVAILABLE_PROFILE_FEATURES
distribution = profile_distribution(self.course_id, feature)
assert distribution.type == 'EASY_CHOICE'
assert distribution.data['no_data'] == 0
assert distribution.data['m'] == (len(self.users) / 3)
assert distribution.choices_display_names['m'] == 'Male'
def test_profile_distribution_open_choice(self):
feature = 'year_of_birth'
assert feature in AVAILABLE_PROFILE_FEATURES
distribution = profile_distribution(self.course_id, feature)
print(distribution)
assert distribution.type == 'OPEN_CHOICE'
assert hasattr(distribution, 'choices_display_names')
assert distribution.choices_display_names is None
assert 'no_data' not in distribution.data
assert distribution.data[1930] == 1
def test_gender_count(self):
course_enrollments = CourseEnrollment.objects.filter(
course_id=self.course_id, user__profile__gender='m'
)
distribution = profile_distribution(self.course_id, "gender")
assert distribution.data['m'] == len(course_enrollments)
course_enrollments[0].deactivate()
distribution = profile_distribution(self.course_id, "gender")
assert distribution.data['m'] == (len(course_enrollments) - 1)
def test_level_of_education_count(self):
course_enrollments = CourseEnrollment.objects.filter(
course_id=self.course_id, user__profile__level_of_education='hs'
)
distribution = profile_distribution(self.course_id, "level_of_education")
assert distribution.data['hs'] == len(course_enrollments)
course_enrollments[0].deactivate()
distribution = profile_distribution(self.course_id, "level_of_education")
assert distribution.data['hs'] == (len(course_enrollments) - 1)
class TestAnalyticsDistributionsNoData(TestCase):
'''Test analytics distribution gathering.'''
def setUp(self):
super().setUp()
self.course_id = CourseLocator('robot', 'course', 'id')
self.users = [UserFactory(
profile__year_of_birth=i + 1930,
) for i in range(5)]
self.nodata_users = [UserFactory(
profile__year_of_birth=None,
profile__gender=[None, ''][i % 2]
) for i in range(4)]
self.users += self.nodata_users
self.ces = tuple(CourseEnrollment.enroll(user, self.course_id)
for user in self.users)
def test_profile_distribution_easy_choice_nodata(self):
feature = 'gender'
assert feature in AVAILABLE_PROFILE_FEATURES
distribution = profile_distribution(self.course_id, feature)
print(distribution)
assert distribution.type == 'EASY_CHOICE'
assert hasattr(distribution, 'choices_display_names')
assert distribution.choices_display_names is not None
assert 'no_data' in distribution.data
assert distribution.data['no_data'] == len(self.nodata_users)
def test_profile_distribution_open_choice_nodata(self):
feature = 'year_of_birth'
assert feature in AVAILABLE_PROFILE_FEATURES
distribution = profile_distribution(self.course_id, feature)
print(distribution)
assert distribution.type == 'OPEN_CHOICE'
assert hasattr(distribution, 'choices_display_names')
assert distribution.choices_display_names is None
assert 'no_data' in distribution.data
assert distribution.data['no_data'] == len(self.nodata_users)