def update(db_conn, user, card, response):
"""
Update the card's parameters (and its parents')
when given a response.
"""
# TODO-3 split up into smaller methods
if not card.has_assessment():
return {
'response': Response({}),
'feedback': '',
}
errors = card.validate_response(response)
if errors:
return {'errors': errors}
score, feedback = card.score_response(response)
response = Response({
'user_id': user['id'],
'card_id': card['entity_id'],
'unit_id': card['unit_id'],
'response': response,
'score': score,
})
card_parameters = CardParameters.get(db_conn, entity_id=card['entity_id'])
if not card_parameters:
card_parameters = CardParameters({
'entity_id': card['entity_id']
})
previous_response = Response.get_latest(db_conn,
user_id=user['id'],
unit_id=card['unit_id'])
now = time()
time_delta = now - (int(previous_response['created'].strftime("%s"))
if previous_response else now)
learned = (previous_response['learned']
if previous_response else init_learned)
guess_distribution = card_parameters.get_distribution('guess')
slip_distribution = card_parameters.get_distribution('slip')
updates = formula_update(score, time_delta,
learned, guess_distribution, slip_distribution)
response['learned'] = updates['learned']
response, errors = response.save(db_conn)
if errors:
return {'errors': errors, 'feedback': feedback}
card_parameters.set_distribution('guess', updates['guess_distribution'])
card_parameters.set_distribution('slip', updates['slip_distribution'])
card_parameters, errors = card_parameters.save(db_conn)
if errors:
return {'errors': errors, 'feedback': feedback}
return {'response': response, 'feedback': feedback}
def get_card_route(request, card_id):
"""
Get a specific card given an ID. Show all relevant data, but
not used for the learning interface.
"""
card = get_card_by_kind(card_id)
if not card:
return abort(404)
unit = Unit.get_latest_accepted(entity_id=card['unit_id'])
if not unit:
return abort(404)
# TODO-2 SPLITUP create new endpoints for these instead
topics = Topic.list_by_entity_id(entity_id=card_id)
versions = Card.get_versions(entity_id=card_id)
requires = Card.list_requires(entity_id=card_id)
required_by = Card.list_required_by(entity_id=card_id)
params = CardParameters.get(entity_id=card_id)
return 200, {
'card': card.deliver(access='view'),
'card_parameters': params.get_values(),
'unit': unit.deliver(),
'topics': [topic.deliver() for topic in topics],
'versions': [version.deliver() for version in versions],
'requires': [require.deliver() for require in requires],
'required_by': [require.deliver() for require in required_by],
}
def get_card_route(request, card_id):
"""
Get a specific card given an ID. Show all relevant data, but
not used for the learning interface.
"""
card = get_card_by_kind(card_id)
if not card:
return abort(404)
unit = Unit.get_latest_accepted(entity_id=card['unit_id'])
if not unit:
return abort(404)
# TODO-2 SPLITUP create new endpoints for these instead
topics = Topic.list_by_entity_id(entity_id=card_id)
versions = Card.get_versions(entity_id=card_id)
requires = Card.list_requires(entity_id=card_id)
required_by = Card.list_required_by(entity_id=card_id)
params = CardParameters.get(entity_id=card_id)
return 200, {
'card': card.deliver(access='view'),
'card_parameters': params.get_values(),
'unit': unit.deliver(),
'topics': [topic.deliver() for topic in topics],
'versions': [version.deliver() for version in versions],
'requires': [require.deliver() for require in requires],
'required_by': [require.deliver() for require in required_by],
}
def choose_card(user, unit):
"""
Given a user and a unit, choose an appropriate card.
Return a card instance.
"""
# TODO-3 simplify this method
unit_id = unit['entity_id']
query = (Card.start_accepted_query()
.filter({'unit_id': unit_id})
.sample(10)) # TODO-2 index
# TODO-3 does this belong as a model method?
# TODO-2 is the sample value decent?
# TODO-2 has the learner seen this card recently?
cards = [Card(d) for d in query.run(database.db_conn)]
if not len(cards):
return None
previous_response = Response.get_latest(user_id=user['id'],
unit_id=unit_id)
if previous_response:
learned = previous_response['learned']
# Don't allow the previous card as the next card
cards = [
card
for card in cards
if card['entity_id'] != previous_response['card_id']
]
else:
learned = init_learned
shuffle(cards)
assessment, nonassessment = partition(cards, lambda c: c.has_assessment())
choose_assessment = random() < p_assessment_map[floor(learned * 10)]
if choose_assessment:
if not len(assessment):
return nonassessment[0]
for card in assessment:
params = CardParameters.get(entity_id=card['entity_id'])
guess = params.get_distribution('guess').get_value()
slip = params.get_distribution('slip').get_value()
correct = calculate_correct(guess, slip, learned)
if 0.25 < correct < 0.75:
return card
return assessment[0]
if len(nonassessment):
return nonassessment[0]
if len(assessment):
return assessment[0]
return None
def update(user, card, response):
"""
Update the card's parameters (and its parents')
when given a response.
"""
# TODO-3 split up into smaller methods
if not card.has_assessment():
return {
'response': Response({}),
'feedback': '',
}
errors = card.validate_response(response)
if errors:
return {'errors': errors}
score, feedback = card.score_response(response)
response = Response({
'user_id': user['id'],
'card_id': card['entity_id'],
'unit_id': card['unit_id'],
'response': response,
'score': score,
})
card_parameters = CardParameters.get(entity_id=card['entity_id'])
previous_response = Response.get_latest(user_id=user['id'],
unit_id=card['unit_id'])
now = time()
time_delta = now - (int(previous_response['created'].strftime("%s"))
if previous_response else now)
learned = (previous_response['learned']
if previous_response else init_learned)
guess_distribution = card_parameters.get_distribution('guess')
slip_distribution = card_parameters.get_distribution('slip')
updates = formula_update(score, time_delta,
learned, guess_distribution, slip_distribution)
response['learned'] = updates['learned']
response, errors = response.save()
if errors:
return {'errors': errors, 'feedback': feedback}
card_parameters.set_distribution('guess', updates['guess_distribution'])
card_parameters.set_distribution('slip', updates['slip_distribution'])
card_parameters, errors = card_parameters.save()
if errors:
return {'errors': errors, 'feedback': feedback}
return {'response': response, 'feedback': feedback}
