def _load_objects(request, object_class):
objs = object_class.objects
if hasattr(objs, 'prepare_related'):
objs = objs.prepare_related()
if 'filter_column' in request.GET and 'filter_value' in request.GET:
column = request.GET['filter_column']
value = request.GET['filter_value']
if value.isdigit():
value = int(value)
objs = objs.filter(**{column: value})
else:
objs = objs.all()
if object_class == FlashcardAnswer:
user_id = get_user_id(request, allow_override=True)
item_filter = get_filter(request)
if len(item_filter) != 0:
item_ids = Item.objects.filter_all_reachable_leaves(
item_filter, get_language(request))
objs = objs.filter(item_asked__in=item_ids)
objs = objs.filter(user_id=user_id).order_by('-time')
if object_class == Flashcard or object_class == settings.PROSO_FLASHCARDS.get("term_extension", Term) or \
object_class == settings.PROSO_FLASHCARDS.get("context_extension", Context) or object_class == Category:
language = get_language(request)
objs = objs.filter(lang=language)
return objs
def schedule_email_with_discount_code(user,
discount_percentage=50,
dry=False,
output_dir=None):
discount_code = DiscountCode.objects.filter(
identifier='email_user_discount_code_{}'.format(user.id)).first()
if discount_code is None:
discount_code = DiscountCode.objects.create(
identifier='email_user_discount_code_{}'.format(user.id),
usage_limit=1,
code=DiscountCode.objects.generate_code(),
discount_percentage=discount_percentage)
request = get_current_request(force=False)
if request is not None:
language = get_language(request)
else:
last_answer = Answer.objects.filter(user=user).order_by('-id').first()
language = last_answer.lang if last_answer is not None else 'en'
language = canonize_language_for_email(language)
ScheduledEmail.objects.schedule_more(
'*****@*****.**',
'Anatom: Děkujeme, že sis vybral(a) nás'
if language == 'cs' else 'Practice Anatomy: Thank you chose us',
os.path.join(settings.BASE_DIR, 'anatomy', 'templates', 'email',
'thanks_discount_code_{}.html'.format(language)),
users=[user],
template_kwargs={'discount_code': discount_code},
dry=dry,
output_dir=output_dir)
def schedule_welcome_email(sender, instance, created=False, **kwargs):
if not created:
return
if instance.user.email is None or instance.user.email == '':
return
request = get_current_request(force=False)
if request is None:
return
language = get_language(request)
language = canonize_language_for_email(language)
ScheduledEmail.objects.schedule_more(
'*****@*****.**',
'Anatom: Vítej' if language == 'cs' else 'Practice Anatomy: Welcome',
os.path.join(settings.BASE_DIR, 'anatomy', 'templates', 'email',
'welcome_{}.html'.format(language)),
users=[instance.user])
# reminder e-mails
templates = glob.glob(
os.path.join(settings.BASE_DIR, 'anatomy', 'templates', 'email',
'relation_question_{}_*.html'.format(language)))
random.shuffle(templates)
shifts = [1, 3, 7]
last_datetime = datetime.datetime.now()
for i, template in enumerate(templates):
shift = shifts[min(i, len(shifts) - 1)]
last_datetime = last_datetime + datetime.timedelta(days=shift)
ScheduledEmail.objects.schedule_more(
'*****@*****.**',
'Anatom: Otázka dne'
if language == 'cs' else 'Practice Anatomy: Today\'s question',
template,
users=[instance.user],
scheduled=last_datetime)
def _load_objects(request, object_class):
objs = object_class.objects
if hasattr(objs, 'prepare_related'):
objs = objs.prepare_related().filter(active=True)
db_filter = proso_common.views.get_db_filter(request)
objs = objs.filter(lang=get_language(request)) if db_filter is None else objs.filter(**db_filter)
return objs
def _load_objects(request, object_class):
objs = object_class.objects.prepare_related()
db_filter = proso_common.views.get_db_filter(request)
objs = objs.all() if db_filter is None else objs.filter(**db_filter)
if object_class == Concept:
objs = objs.filter(active=True, lang=get_language(request))
return objs
def user_stats(request):
"""
JSON of user stats of the user
GET parameters:
html (bool):
turn on the HTML version of the API, defaults to false
user (int):
identifier of the user, defaults to logged user
concepts (list):
list of identifiers of concepts, defaults to all concepts
lang (str):
language of requested concepts, defaults to language from django
"""
user = get_user_id(request)
language = get_language(request)
concepts = None # meaning all concept
if "concepts" in request.GET:
concepts = Concept.objects.filter(lang=language,
active=True,
identifier__in=load_query_json(
request.GET, "concepts"))
data = UserStat.objects.get_user_stats(user, language, concepts)
return render_json(request,
data,
template='concepts_json.html',
help_text=user_stats.__doc__)
def user_stats_bulk(request):
"""
Get statistics for selected users and concepts
since:
time as timestamp - get stats changed since
users:
list of identifiers of users
concepts (Optional):
list of identifiers of concepts
language:
language of concepts
"""
language = get_language(request)
users = load_query_json(request.GET, "users")
since = None
if 'since' in request.GET:
since = datetime.datetime.fromtimestamp(int(request.GET['since']))
concepts = None
if "concepts" in request.GET:
concepts = Concept.objects.filter(lang=language, active=True,
identifier__in=load_query_json(request.GET, "concepts"))
stats = UserStat.objects.get_user_stats(users, language, concepts=concepts, since=since)
data = {"users": []}
for user, s in stats.items():
data["users"].append({
"user_id": user,
"concepts": s,
})
return render_json(request, data, template='concepts_json.html', help_text=user_stats_bulk.__doc__)
def practice_image(request):
user_id = get_user_id(request)
limit = min(int(request.GET.get('limit', 10)), 100)
item_ids = Item.objects.filter_all_reachable_leaves(get_filter(request), get_language(request))
answers = Answer.objects.filter(user_id=user_id).filter(item_asked_id__in=item_ids).order_by('-id')[:limit]
predictive_model = get_predictive_model()
environment = get_environment()
predictions = predictive_model.predict_more_items(environment, user=-1, items=item_ids, time=datetime.datetime.now())
items_in_order = list(zip(*sorted(zip(predictions, item_ids), reverse=True)))[1] if len(item_ids) > 1 else []
item_prediction = dict(list(zip(item_ids, predictions)))
item_position = dict(list(zip(items_in_order, list(range(len(item_ids))))))
svg = proso.svg.Printer()
answers = sorted(list(answers), key=lambda a: a.id)
SQUARE_SIZE = 10
OFFSET_X = SQUARE_SIZE
OFFSET_Y = SQUARE_SIZE * 3
for i, item in enumerate(items_in_order):
svg.print_square(OFFSET_X + SQUARE_SIZE * i, OFFSET_Y - SQUARE_SIZE, SQUARE_SIZE, int(255 * item_prediction[item]))
for i, answer in enumerate(answers):
for j in range(len(items_in_order)):
svg.print_square(OFFSET_X + SQUARE_SIZE * j, OFFSET_Y + SQUARE_SIZE * i, SQUARE_SIZE, 255, border_color=200)
color = 'green' if answer.item_asked_id == answer.item_answered_id else 'red'
svg.print_square(
OFFSET_X + SQUARE_SIZE * item_position[answer.item_asked_id],
OFFSET_Y + SQUARE_SIZE * i, SQUARE_SIZE, color, border_color=0)
svg.print_text(OFFSET_X + SQUARE_SIZE * (len(items_in_order) + 1), OFFSET_Y + SQUARE_SIZE * i + 0.8 * SQUARE_SIZE, answer.time.strftime('%H:%M:%S %Y-%m-%d'), font_size=10)
return HttpResponse(str(svg), content_type="image/svg+xml")
def _load_objects(request, object_class):
objs = object_class.objects.prepare_related()
db_filter = proso_common.views.get_db_filter(request)
objs = objs.all() if db_filter is None else objs.filter(**db_filter)
if object_class == Concept:
objs = objs.filter(active=True, lang=get_language(request))
return objs
def item2object(request, json_list, nested):
if any([x.get('object_type', '') != 'item' for x in json_list]):
raise Exception('Only items can be translated to objects!')
item_ids = [x['id'] for x in json_list]
translated = models.Item.objects.translate_item_ids(item_ids, get_language(request), is_nested=nested)
for object_json in json_list:
for key, value in translated[object_json['id']].items():
object_json[key] = value
def to_practice(request):
practice_filter = get_filter(request)
item_ids = Item.objects.filter_all_reachable_leaves(practice_filter, get_language(request))
if len(item_ids) == 0:
return render_json(request, {
'error': _('There is no item for the given filter to practice.'),
'error_type': 'empty_practice'
}, status=404, template='models_json.html')
result = [Item.objects.item_id_to_json(item_id) for item_id in item_ids]
return render_json(request, result, template='models_json.html', help_text=to_practice.__doc__)
def plans(request):
lang = get_language(request)
discount_code = get_discount_code(request)
if discount_code is not None:
discount_code.is_valid(request.user, throw_exception=True)
return render_json(request, [
p.to_json(lang=lang, discount_code=discount_code)
for p in SubscriptionPlan.objects.prepare_related().filter(active=True)
],
template='subscription_json.html')
def plans(request):
lang = get_language(request)
discount_code = get_discount_code(request)
if discount_code is not None:
discount_code.is_valid(request.user, throw_exception=True)
return render_json(
request,
[p.to_json(lang=lang, discount_code=discount_code) for p in SubscriptionPlan.objects.prepare_related().filter(active=True)],
template='subscription_json.html'
)
def _load_objects(request, object_class):
objs = object_class.objects
if hasattr(objs, 'prepare_related'):
objs = objs.prepare_related()
db_filter = proso_common.views.get_db_filter(request)
objs = objs.all() if db_filter is None else objs.filter(**db_filter)
if object_class == FlashcardAnswer:
user_id = get_user_id(request, allow_override=True)
item_filter = get_filter(request)
if len(item_filter) != 0:
item_ids = Item.objects.filter_all_reachable_leaves(item_filter, get_language(request))
objs = objs.filter(item_asked__in=item_ids)
objs = objs.filter(user_id=user_id).order_by('-time')
if object_class == Flashcard or object_class == settings.PROSO_FLASHCARDS.get("term_extension", Term) or \
object_class == settings.PROSO_FLASHCARDS.get("context_extension", Context) or object_class == Category:
language = get_language(request)
objs = objs.filter(lang=language)
if object_class in [Flashcard, Category, Context]:
objs = objs.filter(active=True)
return objs
def answers(request):
limit = min(int(request.GET.get('limit', 10)), 1000)
user_id = get_user_id(request)
item_ids = Item.objects.filter_all_reachable_leaves(
get_filter(request), get_language(request))
found_answers = Answer.objects.answers(
Answer.objects.filter(item_asked_id__in=item_ids,
user_id=user_id).order_by('-id').values_list(
'id', flat=True)[:limit])
return render_json(request,
found_answers,
template='models_json.html',
help_text=answers.__doc__)
def _load_objects(request, object_class):
objs = object_class.objects.prepare_related()
if 'filter_column' in request.GET and 'filter_value' in request.GET:
column = request.GET['filter_column']
value = request.GET['filter_value']
if value.isdigit():
value = int(value)
objs = objs.filter(**{column: value})
else:
objs = objs.all()
if object_class == Concept:
objs = objs.filter(active=True, lang=get_language(request))
return objs
def _load_objects(request, object_class):
objs = object_class.objects.prepare_related()
if 'filter_column' in request.GET and 'filter_value' in request.GET:
column = request.GET['filter_column']
value = request.GET['filter_value']
if value.isdigit():
value = int(value)
objs = objs.filter(**{column: value})
else:
objs = objs.all()
if object_class == Concept:
objs = objs.filter(active=True, lang=get_language(request))
return objs
def user_stats_bulk(request):
"""
Get statistics for selected users and concepts
since:
time as timestamp - get stats changed since
users:
list of identifiers of users
concepts (Optional):
list of identifiers of concepts
language:
language of concepts
"""
language = get_language(request)
users = load_query_json(request.GET, "users")
if request.user.is_staff:
if not hasattr(request.user, 'userprofile') or User.objects.filter(
pk__in=users, userprofile__classes__owner=request.user.
userprofile).count() < len(users):
return render_json(
request, {
'error':
_('Some requested users are not in owned classes'),
'error_type': 'permission_denied'
},
template='concepts_json.html',
status=401)
since = None
if 'since' in request.GET:
since = datetime.datetime.fromtimestamp(int(request.GET['since']))
concepts = None
if "concepts" in request.GET:
concepts = Concept.objects.filter(lang=language,
active=True,
identifier__in=load_query_json(
request.GET, "concepts"))
stats = UserStat.objects.get_user_stats(users,
language,
concepts=concepts,
since=since)
data = {"users": []}
for user, s in stats.items():
data["users"].append({
"user_id": user,
"concepts": s,
})
return render_json(request,
data,
template='concepts_json.html',
help_text=user_stats_bulk.__doc__)
def number_of_correct_answers(request, json_list, nested):
if 'stats' not in request.GET:
return
object_item_ids = [x['item_id'] for x in json_list]
user = get_user_id(request)
leaves = models.Item.objects.get_leaves(object_item_ids, language=get_language(request))
all_leaves = set(flatten(leaves.values()))
number_of_correct_answers = _environment(request).number_of_correct_answers_more_items(
user=user, items=all_leaves)
for object_json in json_list:
num = sum([number_of_correct_answers[leave] for leave in leaves[object_json['item_id']]])
object_json['number_of_correct_answers'] = num
object_json['practiced_correctly'] = num > 0
return json_list
def tag_values(request):
"""
Get tags types and values with localized names
language:
language of tags
"""
data = defaultdict(lambda: {"values": {}})
for tag in Tag.objects.filter(lang=get_language(request)):
data[tag.type]["name"] = tag.type_name
data[tag.type]["values"][tag.value] = tag.value_name
return render_json(request, data, template='concepts_json.html', help_text=tag_values.__doc__)
def _load_objects(request, object_class):
objs = object_class.objects
if hasattr(objs, 'prepare_related'):
objs = objs.prepare_related()
if 'filter_column' in request.GET and 'filter_value' in request.GET:
column = request.GET['filter_column']
value = request.GET['filter_value']
if value.isdigit():
value = int(value)
objs = objs.filter(**{column: value})
else:
objs = objs.all()
if object_class == FlashcardAnswer:
user_id = get_user_id(request, allow_override=True)
item_filter = get_filter(request)
if len(item_filter) != 0:
item_ids = Item.objects.filter_all_reachable_leaves(item_filter, get_language(request))
objs = objs.filter(item_asked__in=item_ids)
objs = objs.filter(user_id=user_id).order_by('-time')
if object_class == Flashcard or object_class == settings.PROSO_FLASHCARDS.get("term_extension", Term) or \
object_class == settings.PROSO_FLASHCARDS.get("context_extension", Context) or object_class == Category:
language = get_language(request)
objs = objs.filter(lang=language)
return objs
def practice_image(request):
user_id = get_user_id(request)
limit = min(int(request.GET.get('limit', 10)), 100)
item_ids = Item.objects.filter_all_reachable_leaves(
get_filter(request), get_language(request))
answers = Answer.objects.filter(user_id=user_id).filter(
item_asked_id__in=item_ids).order_by('-id')[:limit]
predictive_model = get_predictive_model()
environment = get_environment()
predictions = predictive_model.predict_more_items(
environment,
user=-1,
items=item_ids,
time=get_time_for_knowledge_overview(request))
items_in_order = list(
zip(*sorted(zip(predictions, item_ids),
reverse=True)))[1] if len(item_ids) > 1 else []
item_prediction = dict(list(zip(item_ids, predictions)))
item_position = dict(list(zip(items_in_order, list(range(len(item_ids))))))
svg = proso.svg.Printer()
answers = sorted(list(answers), key=lambda a: a.id)
SQUARE_SIZE = 10
OFFSET_X = SQUARE_SIZE
OFFSET_Y = SQUARE_SIZE * 3
for i, item in enumerate(items_in_order):
svg.print_square(OFFSET_X + SQUARE_SIZE * i, OFFSET_Y - SQUARE_SIZE,
SQUARE_SIZE, int(255 * item_prediction[item]))
for i, answer in enumerate(answers):
for j in range(len(items_in_order)):
svg.print_square(OFFSET_X + SQUARE_SIZE * j,
OFFSET_Y + SQUARE_SIZE * i,
SQUARE_SIZE,
255,
border_color=200)
color = 'green' if answer.item_asked_id == answer.item_answered_id else 'red'
svg.print_square(OFFSET_X +
SQUARE_SIZE * item_position[answer.item_asked_id],
OFFSET_Y + SQUARE_SIZE * i,
SQUARE_SIZE,
color,
border_color=0)
svg.print_text(OFFSET_X + SQUARE_SIZE * (len(items_in_order) + 1),
OFFSET_Y + SQUARE_SIZE * i + 0.8 * SQUARE_SIZE,
answer.time.strftime('%H:%M:%S %Y-%m-%d'),
font_size=10)
return HttpResponse(str(svg), content_type="image/svg+xml")
def tag_values(request):
"""
Get tags types and values with localized names
language:
language of tags
"""
data = defaultdict(lambda: {"values": {}})
for tag in Tag.objects.filter(lang=get_language(request)):
data[tag.type]["name"] = tag.type_name
data[tag.type]["values"][tag.value] = tag.value_name
return render_json(request,
data,
template='concepts_json.html',
help_text=tag_values.__doc__)
def to_practice(request):
practice_filter = get_filter(request)
item_ids = Item.objects.filter_all_reachable_leaves(
practice_filter, get_language(request))
if len(item_ids) == 0:
return render_json(
request, {
'error':
_('There is no item for the given filter to practice.'),
'error_type': 'empty_practice'
},
status=404,
template='models_json.html')
result = [Item.objects.item_id_to_json(item_id) for item_id in item_ids]
return render_json(request,
result,
template='models_json.html',
help_text=to_practice.__doc__)
def to_practice_counts(request):
"""
Get number of items available to practice.
filters: -- use this or body
json as in BODY
language:
language of the items
BODY
json in following format:
{
"#identifier": [] -- custom identifier (str) and filter
...
}
"""
data = None
if request.method == "POST":
data = json.loads(request.body.decode("utf-8"))["filters"]
if "filters" in request.GET:
data = load_query_json(request.GET, "filters")
if data is None or len(data) == 0:
return render_json(request, {},
template='models_json.html',
help_text=to_practice_counts.__doc__)
language = get_language(request)
timer('to_practice_counts')
filter_names, filter_filters = list(zip(*sorted(data.items())))
reachable_leaves = Item.objects.filter_all_reachable_leaves_many(
filter_filters, language)
response = {
group_id: {
'filter': data[group_id],
'number_of_items': len(items),
}
for group_id, items in zip(filter_names, reachable_leaves)
}
LOGGER.debug(
"to_practice_counts - getting items in groups took %s seconds",
(timer('to_practice_counts')))
return render_json(request,
response,
template='models_json.html',
help_text=to_practice_counts.__doc__)
def avg_prediction(request, json_list, nested):
if 'stats' not in request.GET:
return
object_item_ids = [x['item_id'] for x in json_list]
leaves = models.Item.objects.get_leaves(object_item_ids, language=get_language(request))
all_leaves = list(set(flatten(leaves.values())))
user = get_user_id(request)
time = models.get_time_for_knowledge_overview(request)
predictions = dict(list(zip(all_leaves, _predictive_model().predict_more_items(
_environment(request),
user,
all_leaves,
time
))))
mastery_threshold = get_mastery_trashold()
for object_json in json_list:
leaf_predictions = [predictions[leave] for leave in leaves[object_json['item_id']]]
object_json['avg_predicton'] = numpy.mean(leaf_predictions)
object_json['mastered'] = sum([p > mastery_threshold for p in leaf_predictions])
def audit(request, key):
if 'user' in request.GET:
user = get_user_id(request)
else:
user = None
limit = 100
if request.user.is_staff:
limit = request.GET.get('limit', limit)
item_identifier = request.GET['item'] if 'item' in request.GET else None
item_secondary_identifier = request.GET[
'item_secondary'] if 'item_secondary' in request.GET else None
translated = Item.objects.translate_identifiers([
i
for i in [item_identifier, item_secondary_identifier] if i is not None
], get_language(request))
item = translated.get(item_identifier)
item_secondary = translated.get(item_secondary_identifier)
time = get_time(request)
environment = get_environment()
if is_time_overridden(request):
environment.shift_time(time)
values = environment.audit(key,
user=user,
item=item,
item_secondary=item_secondary,
limit=limit)
def _to_json_audit(audit):
(time, value) = audit
return {
'object_type': 'value',
'key': key,
'item_primary_id': item,
'item_secondary_id': item_secondary,
'user_id': user,
'value': value,
'time': time.strftime('%Y-%m-%d %H:%M:%S')
}
return render_json(request,
list(map(_to_json_audit, values)),
template='models_json.html')
def user_stats_bulk(request):
"""
Get statistics for selected users and concepts
since:
time as timestamp - get stats changed since
users:
list of identifiers of users
concepts (Optional):
list of identifiers of concepts
language:
language of concepts
"""
language = get_language(request)
users = load_query_json(request.GET, "users")
since = None
if 'since' in request.GET:
since = datetime.datetime.fromtimestamp(int(request.GET['since']))
concepts = None
if "concepts" in request.GET:
concepts = Concept.objects.filter(lang=language,
active=True,
identifier__in=load_query_json(
request.GET, "concepts"))
stats = UserStat.objects.get_user_stats(users,
language,
concepts=concepts,
since=since)
data = {"users": []}
for user, s in stats.items():
data["users"].append({
"user_id": user,
"concepts": s,
})
return render_json(request,
data,
template='concepts_json.html',
help_text=user_stats_bulk.__doc__)
def user_stats_bulk(request):
"""
Get statistics for selected users and concepts
since:
time as timestamp - get stats changed since
users:
list of identifiers of users
concepts (Optional):
list of identifiers of concepts
language:
language of concepts
"""
language = get_language(request)
users = load_query_json(request.GET, "users")
if request.user.is_staff:
if not hasattr(request.user, 'userprofile') or User.objects.filter(pk__in=users,
userprofile__classes__owner=request.user.userprofile).count() < len(users):
return render_json(request, {
'error': _('Some requested users are not in owned classes'),
'error_type': 'permission_denied'
}, template='concepts_json.html', status=401)
since = None
if 'since' in request.GET:
since = datetime.datetime.fromtimestamp(int(request.GET['since']))
concepts = None
if "concepts" in request.GET:
concepts = Concept.objects.filter(lang=language, active=True,
identifier__in=load_query_json(request.GET, "concepts"))
stats = UserStat.objects.get_user_stats(users, language, concepts=concepts, since=since)
data = {"users": []}
for user, s in stats.items():
data["users"].append({
"user_id": user,
"concepts": s,
})
return render_json(request, data, template='concepts_json.html', help_text=user_stats_bulk.__doc__)
def user_stats(request):
"""
JSON of user stats of the user
GET parameters:
html (bool):
turn on the HTML version of the API, defaults to false
user (int):
identifier of the user, defaults to logged user
concepts (list):
list of identifiers of concepts, defaults to all concepts
lang (str):
language of requested concepts, defaults to language from django
"""
user = get_user_id(request)
language = get_language(request)
concepts = None # meaning all concept
if "concepts" in request.GET:
concepts = Concept.objects.filter(lang=language, active=True,
identifier__in=load_query_json(request.GET, "concepts"))
data = UserStat.objects.get_user_stats(user, language, concepts)
return render_json(request, data, template='concepts_json.html', help_text=user_stats.__doc__)
def to_practice_counts(request):
"""
Get number of items available to practice.
filters: -- use this or body
json as in BODY
language:
language of the items
BODY
json in following format:
{
"#identifier": [] -- custom identifier (str) and filter
...
}
"""
data = None
if request.method == "POST":
data = json.loads(request.body.decode("utf-8"))["filters"]
if "filters" in request.GET:
data = load_query_json(request.GET, "filters")
if data is None:
return render_json(request, {}, template='models_json.html', help_text=to_practice_counts.__doc__)
language = get_language(request)
timer('to_practice_counts')
filter_names, filter_filters = list(zip(*sorted(data.items())))
reachable_leaves = Item.objects.filter_all_reachable_leaves_many(filter_filters, language)
response = {
group_id: {
'filter': data[group_id],
'number_of_items': len(items),
}
for group_id, items in zip(filter_names, reachable_leaves)
}
LOGGER.debug("flashcard_counts - getting flashcards in groups took %s seconds", (timer('to_practice_counts')))
return render_json(request, response, template='models_json.html', help_text=to_practice_counts.__doc__)
def practice(request):
"""
Return the given number of questions to practice adaptively. In case of
POST request, try to save the answer(s).
GET parameters:
filter:
list of lists of identifiers (may be prefixed by minus sign to
mark complement)
language:
language (str) of flashcards
avoid:
list of item ids to avoid
limit:
number of returned questions (default 10, maximum 100)
time:
time in format '%Y-%m-%d_%H:%M:%S' used for practicing
user:
identifier for the practicing user (only for stuff users)
stats:
turn on the enrichment of the objects by some statistics
html:
turn on the HTML version of the API
BODY:
see answer resource
"""
if request.user.id is None: # Google Bot
return render_json(request, {
'error': _('There is no user available for the practice.'),
'error_type': 'user_undefined'
}, status=400, template='models_json.html')
limit = min(int(request.GET.get('limit', 10)), 100)
# prepare
user = get_user_id(request)
time = get_time(request)
avoid = load_query_json(request.GET, "avoid", "[]")
practice_filter = get_filter(request)
practice_context = PracticeContext.objects.from_content(practice_filter)
environment = get_environment()
item_selector = get_item_selector()
if is_time_overridden(request):
environment.shift_time(time)
# save answers
if request.method == 'POST':
_save_answers(request, practice_context)
if len(practice_filter) > 0:
item_ids = Item.objects.filter_all_reachable_leaves(practice_filter, get_language(request))
else:
item_ids = Item.objects.get_all_available_leaves()
item_ids = list(set(item_ids) - set(avoid))
if len(item_ids) == 0:
return render_json(request, {
'error': _('There is no item for the given filter to practice.'),
'error_type': 'empty_practice'
}, status=404, template='models_json.html')
selected_items, meta = item_selector.select(environment, user, item_ids, time, practice_context.id, limit, items_in_queue=len(avoid))
result = []
for item, item_meta in zip(selected_items, meta):
question = {
'object_type': 'question',
'payload': Item.objects.item_id_to_json(item),
}
if item_meta is not None:
question['meta'] = item_meta
result.append(question)
return render_json(request, result, template='models_json.html', help_text=practice.__doc__)
def user_stats(request):
"""
Get user statistics for selected groups of items
time:
time in format '%Y-%m-%d_%H:%M:%S' used for practicing
user:
identifier of the user (only for stuff users)
username:
username of user (only for users with public profile)
filters: -- use this or body
json as in BODY
mastered:
use model to compute number of mastered items - can be slowed
language:
language of the items
BODY
json in following format:
{
"#identifier": [] -- custom identifier (str) and filter
...
}
"""
timer('user_stats')
response = {}
data = None
if request.method == "POST":
data = json.loads(request.body.decode("utf-8"))["filters"]
if "filters" in request.GET:
data = load_query_json(request.GET, "filters")
if data is None:
return render_json(request, {}, template='models_user_stats.html', help_text=user_stats.__doc__)
environment = get_environment()
if is_time_overridden(request):
environment.shift_time(get_time(request))
user_id = get_user_id(request)
language = get_language(request)
filter_names, filter_filters = list(zip(*sorted(data.items())))
reachable_leaves = Item.objects.filter_all_reachable_leaves_many(filter_filters, language)
all_leaves = flatten(reachable_leaves)
answers = dict(list(zip(all_leaves, environment.number_of_answers_more_items(all_leaves, user_id))))
correct_answers = dict(list(zip(all_leaves, environment.number_of_correct_answers_more_items(all_leaves, user_id))))
if request.GET.get("mastered"):
timer('user_stats_mastered')
mastery_threshold = get_mastery_trashold()
predictions = get_predictive_model().predict_more_items(environment, user_id, all_leaves, get_time(request))
mastered = dict(list(zip(all_leaves, [p >= mastery_threshold for p in predictions])))
LOGGER.debug("user_stats - getting predictions for flashcards took %s seconds", (timer('user_stats_mastered')))
for identifier, items in zip(filter_names, reachable_leaves):
if len(items) == 0:
response[identifier] = {
"filter": data[identifier],
"number_of_flashcards": 0,
}
else:
response[identifier] = {
"filter": data[identifier],
"number_of_flashcards": len(items),
"number_of_practiced_flashcards": sum(answers[i] > 0 for i in items),
"number_of_answers": sum(answers[i] for i in items),
"number_of_correct_answers": sum(correct_answers[i] for i in items),
}
if request.GET.get("mastered"):
response[identifier]["number_of_mastered_flashcards"]= sum(mastered[i] for i in items)
return render_json(request, response, template='models_user_stats.html', help_text=user_stats.__doc__)
def answers_per_month(request):
try:
from pylab import rcParams
import matplotlib.pyplot as plt
import pandas
import seaborn as sns
except ImportError:
return HttpResponse('Can not import python packages for analysis.',
status=503)
categories = load_query_json(request.GET, "categories", "[]")
translated = Item.objects.translate_identifiers(categories,
get_language(request))
translated_inverted = {item: name for name, item in translated.items()}
children = pandas.DataFrame([{
'item': item,
'category': translated_inverted[category]
} for category, items in Item.objects.get_reachable_children(
list(translated.values()), get_language(request)).items()
for item in items])
with connection.cursor() as cursor:
cursor.execute('''
SELECT item_id, date_part('month', time), COUNT(1)
FROM proso_models_answer
GROUP BY 1, 2
''')
data = []
for item, month, answers in cursor:
data.append({
'item': item,
'month': month,
'answers': answers,
})
data = pandas.DataFrame(data)
if len(children) == 0:
data['category'] = data['item'].apply(lambda i: 'category/all')
else:
data = pandas.merge(data, children, on='item', how='inner')
if 'percentage' in request.GET:
def _percentage(group):
total = group['answers'].sum()
return group.groupby('category').apply(lambda g: 100 * g[
'answers'].sum() / total).reset_index().rename(
columns={0: 'answers'})
data = data.groupby('month').apply(_percentage).reset_index()
def _apply(group):
group['answers_cumsum'] = group['answers'].cumsum()
return group
data = data.sort_values(by=['category'],
ascending=False).groupby('month').apply(_apply)
data['month'] = data['month'].astype(int)
sns.set(style='white')
rcParams['figure.figsize'] = 15, 10
palette = sns.color_palette("hls", max(5, len(categories)))
fig = plt.figure()
for i, category in enumerate(sorted(data['category'].unique())):
item_data = data[data['category'] == category]
sns.barplot(x='month',
y='answers_cumsum',
data=item_data,
label=category.split('/')[1],
color=palette[i % len(palette)],
ci=None)
plt.ylabel('Answers' + (' (%)' if 'percentage' in request.GET else ''))
plt.xlabel('Month')
plt.title('Answers per Month')
if 'percentage' in request.GET:
plt.ylim(0, 100)
plt.legend(loc='center left', bbox_to_anchor=(1, 0.5))
response = HttpResponse(content_type='image/png')
canvas = FigureCanvas(fig)
canvas.print_png(response)
return response
def answers_per_month(request):
try:
from pylab import rcParams
import matplotlib.pyplot as plt
import pandas
import seaborn as sns
except ImportError:
return HttpResponse('Can not import python packages for analysis.', status=503)
categories = load_query_json(request.GET, "categories", "[]")
translated = Item.objects.translate_identifiers(categories, get_language(request))
translated_inverted = {item: name for name, item in translated.items()}
children = pandas.DataFrame([
{'item': item, 'category': translated_inverted[category]}
for category, items in Item.objects.get_reachable_children(
list(translated.values()), get_language(request)
).items()
for item in items
])
with connection.cursor() as cursor:
cursor.execute(
'''
SELECT item_id, date_part('month', time), COUNT(1)
FROM proso_models_answer
GROUP BY 1, 2
'''
)
data = []
for item, month, answers in cursor:
data.append({
'item': item,
'month': month,
'answers': answers,
})
data = pandas.DataFrame(data)
if len(children) == 0:
data['category'] = data['item'].apply(lambda i: 'category/all')
else:
data = pandas.merge(data, children, on='item', how='inner')
if 'percentage' in request.GET:
def _percentage(group):
total = group['answers'].sum()
return group.groupby('category').apply(lambda g: 100 * g['answers'].sum() / total).reset_index().rename(columns={0: 'answers'})
data = data.groupby('month').apply(_percentage).reset_index()
def _apply(group):
group['answers_cumsum'] = group['answers'].cumsum()
return group
data = data.sort_values(by=['category'], ascending=False).groupby('month').apply(_apply)
data['month'] = data['month'].astype(int)
sns.set(style='white')
rcParams['figure.figsize'] = 15, 10
palette = sns.color_palette("hls", max(5, len(categories)))
fig = plt.figure()
for i, category in enumerate(sorted(data['category'].unique())):
item_data = data[data['category'] == category]
sns.barplot(
x='month',
y='answers_cumsum',
data=item_data,
label=category.split('/')[1],
color=palette[i % len(palette)],
ci=None
)
plt.ylabel('Answers' + (' (%)' if 'percentage' in request.GET else ''))
plt.xlabel('Month')
plt.title('Answers per Month')
if 'percentage' in request.GET:
plt.ylim(0, 100)
plt.legend(loc='center left', bbox_to_anchor=(1, 0.5))
response = HttpResponse(content_type='image/png')
canvas = FigureCanvas(fig)
canvas.print_png(response)
return response
def questions_to_ask(request):
language = get_language(request)
user_id = get_user_id(request)
questions = UserQuestion.objects.questions_to_ask(user_id, language)
return render_json(request, list(questions), template='user_json.html')
def questions_to_ask(request):
language = get_language(request)
user_id = get_user_id(request)
questions = UserQuestion.objects.questions_to_ask(user_id, language)
return render_json(request, list(questions), template='user_json.html')
def answers(request):
limit = min(int(request.GET.get('limit', 10)), 1000)
user_id = get_user_id(request)
item_ids = Item.objects.filter_all_reachable_leaves(get_filter(request), get_language(request))
found_answers = Answer.objects.answers(Answer.objects.filter(item_asked_id__in=item_ids, user_id=user_id).order_by('-id').values_list('id', flat=True)[:limit])
return render_json(request, found_answers, template='models_json.html', help_text=answers.__doc__)
def user_stats(request):
"""
Get user statistics for selected groups of items
time:
time in format '%Y-%m-%d_%H:%M:%S' used for practicing
user:
identifier of the user (only for stuff users)
username:
username of user (only for users with public profile)
filters: -- use this or body
json as in BODY
mastered:
use model to compute number of mastered items - can be slowed
language:
language of the items
BODY
json in following format:
{
"#identifier": [] -- custom identifier (str) and filter
...
}
"""
timer('user_stats')
response = {}
data = None
if request.method == "POST":
data = json.loads(request.body.decode("utf-8"))["filters"]
if "filters" in request.GET:
data = load_query_json(request.GET, "filters")
if data is None:
return render_json(request, {},
template='models_user_stats.html',
help_text=user_stats.__doc__)
environment = get_environment()
if is_time_overridden(request):
environment.shift_time(get_time(request))
user_id = get_user_id(request)
language = get_language(request)
filter_names, filter_filters = list(zip(*sorted(data.items())))
reachable_leaves = Item.objects.filter_all_reachable_leaves_many(
filter_filters, language)
all_leaves = sorted(list(set(flatten(reachable_leaves))))
answers = environment.number_of_answers_more_items(all_leaves, user_id)
correct_answers = environment.number_of_correct_answers_more_items(
all_leaves, user_id)
if request.GET.get("mastered"):
timer('user_stats_mastered')
mastery_threshold = get_mastery_trashold()
predictions = Item.objects.predict_for_overview(
environment, user_id, all_leaves)
mastered = dict(
list(zip(all_leaves,
[p >= mastery_threshold for p in predictions])))
LOGGER.debug(
"user_stats - getting predictions for items took %s seconds",
(timer('user_stats_mastered')))
for identifier, items in zip(filter_names, reachable_leaves):
if len(items) == 0:
response[identifier] = {
"filter": data[identifier],
"number_of_items": 0,
}
else:
response[identifier] = {
"filter":
data[identifier],
"number_of_items":
len(items),
"number_of_practiced_items":
sum(answers[i] > 0 for i in items),
"number_of_answers":
sum(answers[i] for i in items),
"number_of_correct_answers":
sum(correct_answers[i] for i in items),
}
if request.GET.get("mastered"):
response[identifier]["number_of_mastered_items"] = sum(
mastered[i] for i in items)
return render_json(request,
response,
template='models_user_stats.html',
help_text=user_stats.__doc__)
def practice(request):
"""
Return the given number of questions to practice adaptively. In case of
POST request, try to save the answer(s).
GET parameters:
filter:
list of lists of identifiers (may be prefixed by minus sign to
mark complement)
language:
language (str) of items
avoid:
list of item ids to avoid
limit:
number of returned questions (default 10, maximum 100)
time:
time in format '%Y-%m-%d_%H:%M:%S' used for practicing
user:
identifier for the practicing user (only for stuff users)
stats:
turn on the enrichment of the objects by some statistics
html:
turn on the HTML version of the API
BODY:
see answer resource
"""
if request.user.id is None: # Google Bot
return render_json(
request, {
'error': _('There is no user available for the practice.'),
'error_type': 'user_undefined'
},
status=400,
template='models_json.html')
limit = min(int(request.GET.get('limit', 10)), 100)
# prepare
user = get_user_id(request)
time = get_time(request)
avoid = load_query_json(request.GET, "avoid", "[]")
practice_filter = get_filter(request)
practice_context = PracticeContext.objects.from_content(practice_filter)
environment = get_environment()
item_selector = get_item_selector()
if is_time_overridden(request):
environment.shift_time(time)
# save answers
if request.method == 'POST':
_save_answers(request, practice_context, False)
elif request.method == 'GET':
PracticeSet.objects.filter(answer__user_id=request.user.id).update(
finished=True)
if limit > 0:
item_ids = Item.objects.filter_all_reachable_leaves(
practice_filter, get_language(request))
item_ids = list(set(item_ids) - set(avoid))
limit_size = get_config('proso_models',
'practice.limit_item_set_size_to_select_from',
default=None)
if limit_size is not None and limit_size < len(item_ids):
item_ids = sample(item_ids, limit_size)
if len(item_ids) == 0:
return render_json(request, {
'error':
_('There is no item for the given filter to practice.'),
'error_type':
'empty_practice'
},
status=404,
template='models_json.html')
selected_items, meta = item_selector.select(environment,
user,
item_ids,
time,
practice_context.id,
limit,
items_in_queue=len(avoid))
result = []
for item, item_meta in zip(selected_items, meta):
question = {
'object_type': 'question',
'payload': Item.objects.item_id_to_json(item),
}
if item_meta is not None:
question['meta'] = item_meta
result.append(question)
else:
result = []
return render_json(request,
result,
template='models_json.html',
help_text=practice.__doc__)
