def test_is_learned_based_on_exercise_outcomes(self):
random_bookmarks = [BookmarkRule(self.user).bookmark for _ in range(0, 4)]
# Empty exercise_log should lead to a False return
learned = is_learned_based_on_exercise_outcomes(
SortedExerciseLog(random_bookmarks[0])
)
assert not learned
# An exercise with Outcome equal to TOO EASY results in True, and time of last exercise
random_exercise = ExerciseRule().exercise
random_exercise.outcome = OutcomeRule().too_easy
random_bookmarks[1].add_new_exercise(random_exercise)
learned = is_learned_based_on_exercise_outcomes(
SortedExerciseLog(random_bookmarks[1])
)
result_time = SortedExerciseLog(random_bookmarks[1]).last_exercise_time()
assert learned and result_time == random_exercise.time
# Same test as above, but without a second return value
learned = is_learned_based_on_exercise_outcomes(
SortedExerciseLog(random_bookmarks[1])
)
assert learned
# A bookmark with CORRECTS_IN_A_ROW_FOR_LEARNED correct exercises in a row
# returns true and the time of the last exercise
correct_bookmark = random_bookmarks[2]
exercises = 0
distinct_dates = set()
while not (
exercises >= CORRECTS_IN_A_ROW_FOR_LEARNED
and len(distinct_dates) >= CORRECTS_IN_DISTINCT_DAYS_FOR_LEARNED
):
correct_exercise = ExerciseRule().exercise
correct_exercise.outcome = OutcomeRule().correct
correct_bookmark.add_new_exercise(correct_exercise)
exercises += 1
distinct_dates.add(correct_exercise.time.date())
correct_bookmark.update_learned_status(self.db.session)
log = SortedExerciseLog(correct_bookmark)
learned = is_learned_based_on_exercise_outcomes(log)
result_time = log.last_exercise_time()
assert learned
log = SortedExerciseLog(correct_bookmark)
learned_time_from_log = log.last_exercise_time()
assert result_time == learned_time_from_log
# A bookmark with no TOO EASY outcome or less than 5 correct exercises in a row returns False, None
wrong_exercise = ExerciseRule().exercise
wrong_exercise.outcome = OutcomeRule().wrong
random_bookmarks[3].add_new_exercise(wrong_exercise)
log = SortedExerciseLog(random_bookmarks[3])
learned = is_learned_based_on_exercise_outcomes(log)
assert not learned
def test_check_if_learned_based_on_exercise_outcomes(self):
random_bookmarks = [
BookmarkRule(self.user).bookmark for _ in range(0, 4)
]
# Empty exercise_log should lead to a False return
assert not random_bookmarks[
0].check_if_learned_based_on_exercise_outcomes()
# An exercise with Outcome equal to TOO EASY results in True, and time of last exercise
random_exercise = ExerciseRule().exercise
random_exercise.outcome = OutcomeRule().too_easy
random_bookmarks[1].add_new_exercise(random_exercise)
result_bool, result_time = random_bookmarks[
1].check_if_learned_based_on_exercise_outcomes(
add_to_result_time=True)
assert result_bool and result_time == random_exercise.time
# Same test as above, but without a second return value
assert random_bookmarks[1].check_if_learned_based_on_exercise_outcomes(
)
# A bookmark with 5 correct exercises in a row returns true and the time of the last exercise
for i in range(0, 5):
correct_exercise = ExerciseRule().exercise
correct_exercise.outcome = OutcomeRule().correct
random_bookmarks[2].add_new_exercise(correct_exercise)
result_bool, result_time = random_bookmarks[
2].check_if_learned_based_on_exercise_outcomes()
assert result_bool and result_time == random_bookmarks[2].exercise_log[
-1].time
random_bookmarks[2].update_learned_status(self.db.session)
# A bookmark with no TOO EASY outcome or less than 5 correct exercises in a row returns False, None
wrong_exercise = ExerciseRule().exercise
wrong_exercise.outcome = OutcomeRule().wrong
random_bookmarks[3].add_new_exercise(wrong_exercise)
result_bool, result_None = random_bookmarks[
3].check_if_learned_based_on_exercise_outcomes(
add_to_result_time=True)
assert not result_bool and result_None is None
# Same as before, but without a second return value
assert not random_bookmarks[
3].check_if_learned_based_on_exercise_outcomes()
def test_add_new_exercise_result(self):
random_bookmark = BookmarkRule(self.user).bookmark
exercise_count_before = len(random_bookmark.exercise_log)
random_bookmark.add_new_exercise_result(SourceRule().random, OutcomeRule().random, random.randint(100, 1000))
exercise_count_after = len(random_bookmark.exercise_log)
assert exercise_count_after > exercise_count_before
def test_fit_for_study(self):
random_bookmarks = [BookmarkRule(self.user).bookmark for _ in range(0, 2)]
random_exercise = ExerciseRule().exercise
random_exercise.outcome = OutcomeRule().wrong
random_bookmarks[0].starred = True
random_bookmarks[1].starred = True
random_bookmarks[1].add_new_exercise(random_exercise)
for b in random_bookmarks:
assert b.fit_for_study
def _create_model_object(self):
random_outcome = OutcomeRule().random
random_source = SourceRule().random
random_speed = random.randint(500, 5000)
random_time = self.faker.date_time_this_month()
new_exercise = Exercise(random_outcome, random_source, random_speed,
random_time)
if self._exists_in_db(new_exercise):
return self._create_model_object()
return new_exercise
def test_has_been_learned(self):
random_bookmarks = [
BookmarkRule(self.user).bookmark for _ in range(0, 2)
]
random_exercise = ExerciseRule().exercise
random_exercise.outcome = OutcomeRule().too_easy
random_bookmarks[0].add_new_exercise(random_exercise)
result_bool, result_time = random_bookmarks[0].has_been_learned(
also_return_time=True)
assert result_bool and result_time == random_bookmarks[0].exercise_log[
-1].time
result_bool, result_None = random_bookmarks[1].has_been_learned(
also_return_time=True)
assert not result_bool and result_None is None
def test_just_finished_bookmark_has_not_the_highest_priority(self):
# GIVEN
ABTesting._algorithms = [ABTesting._algorithms[random.randint(0, len(ABTesting._algorithms) - 1)]]
arts.update_bookmark_priority(zeeguu_core.db, self.user)
first_bookmark_to_study = self.__get_bookmark_with_highest_priority()
# WHEN
# Add an exercise
exercise_rule = ExerciseRule()
exercise_rule.exercise.time = datetime.now()
exercise_rule.exercise.solving_speed = 100
exercise_rule.exercise.outcome = OutcomeRule().correct
first_bookmark_to_study.add_new_exercise(exercise_rule.exercise)
arts.update_bookmark_priority(zeeguu_core.db, self.user)
# THEN
bookmark = self.__get_bookmark_with_highest_priority()
assert first_bookmark_to_study != bookmark