Skip to content

E
edx-platform
Commit b6ea3f4e by John Orr Committed by jorr
Options

Factor the core Capa problem logic into a mixin. 

This mixin can be used by either the current XModule, or by an XBlock. Leave
the XModule-specific code in capa_module and move the shared code to capa_base.
Plan to move caba_base into the capa package in the future.
parent 157f734b
Showing with 1094 additions and 1073 deletions
common/lib/xmodule/xmodule/capa_base.py 0 → 100644
"""Implements basics of Capa, including class CapaModule."""
import cgi
import datetime
import hashlib
import json
import logging
import os
import traceback
import struct
import sys
from pkg_resources import resource_string
from capa.capa_problem import LoncapaProblem
from capa.responsetypes import StudentInputError, \
ResponseError, LoncapaProblemError
from capa.util import convert_files_to_filenames
from .progress import Progress
from xmodule.exceptions import NotFoundError, ProcessingError
from xblock.fields import Scope, String, Boolean, Dict, Integer, Float
from .fields import Timedelta, Date
from django.utils.timezone import UTC
from .util.duedate import get_extended_due_date
log = logging.getLogger("edx.courseware")
# Generate this many different variants of problems with rerandomize=per_student
NUM_RANDOMIZATION_BINS = 20
# Never produce more than this many different seeds, no matter what.
MAX_RANDOMIZATION_BINS = 1000
def randomization_bin(seed, problem_id):
"""
Pick a randomization bin for the problem given the user's seed and a problem id.
We do this because we only want e.g. 20 randomizations of a problem to make analytics
interesting. To avoid having sets of students that always get the same problems,
we'll combine the system's per-student seed with the problem id in picking the bin.
"""
r_hash = hashlib.sha1()
r_hash.update(str(seed))
r_hash.update(str(problem_id))
# get the first few digits of the hash, convert to an int, then mod.
return int(r_hash.hexdigest()[:7], 16) % NUM_RANDOMIZATION_BINS
class Randomization(String):
"""
Define a field to store how to randomize a problem.
"""
def from_json(self, value):
if value in ("", "true"):
return "always"
elif value == "false":
return "per_student"
return value
to_json = from_json
class ComplexEncoder(json.JSONEncoder):
"""
Extend the JSON encoder to correctly handle complex numbers
"""
def default(self, obj):
"""
Print a nicely formatted complex number, or default to the JSON encoder
"""
if isinstance(obj, complex):
return u"{real:.7g}{imag:+.7g}*j".format(real=obj.real, imag=obj.imag)
return json.JSONEncoder.default(self, obj)
class CapaFields(object):
"""
Define the possible fields for a Capa problem
"""
display_name = String(
display_name="Display Name",
help="This name appears in the horizontal navigation at the top of the page.",
scope=Scope.settings,
# it'd be nice to have a useful default but it screws up other things; so,
# use display_name_with_default for those
default="Blank Advanced Problem"
)
attempts = Integer(help="Number of attempts taken by the student on this problem",
default=0, scope=Scope.user_state)
max_attempts = Integer(
display_name="Maximum Attempts",
help=("Defines the number of times a student can try to answer this problem. "
"If the value is not set, infinite attempts are allowed."),
values={"min": 0}, scope=Scope.settings
)
due = Date(help="Date that this problem is due by", scope=Scope.settings)
extended_due = Date(
help="Date that this problem is due by for a particular student. This "
"can be set by an instructor, and will override the global due "
"date if it is set to a date that is later than the global due "
"date.",
default=None,
scope=Scope.user_state,
)
graceperiod = Timedelta(
help="Amount of time after the due date that submissions will be accepted",
scope=Scope.settings
)
showanswer = String(
display_name="Show Answer",
help=("Defines when to show the answer to the problem. "
"A default value can be set in Advanced Settings."),
scope=Scope.settings,
default="finished",
values=[
{"display_name": "Always", "value": "always"},
{"display_name": "Answered", "value": "answered"},
{"display_name": "Attempted", "value": "attempted"},
{"display_name": "Closed", "value": "closed"},
{"display_name": "Finished", "value": "finished"},
{"display_name": "Past Due", "value": "past_due"},
{"display_name": "Never", "value": "never"}]
)
force_save_button = Boolean(
help="Whether to force the save button to appear on the page",
scope=Scope.settings,
default=False
)
rerandomize = Randomization(
display_name="Randomization",
help="Defines how often inputs are randomized when a student loads the problem. "
"This setting only applies to problems that can have randomly generated numeric values. "
"A default value can be set in Advanced Settings.",
default="never",
scope=Scope.settings,
values=[
{"display_name": "Always", "value": "always"},
{"display_name": "On Reset", "value": "onreset"},
{"display_name": "Never", "value": "never"},
{"display_name": "Per Student", "value": "per_student"}
]
)
data = String(help="XML data for the problem", scope=Scope.content, default="<problem></problem>")
correct_map = Dict(help="Dictionary with the correctness of current student answers",
scope=Scope.user_state, default={})
input_state = Dict(help="Dictionary for maintaining the state of inputtypes", scope=Scope.user_state)
student_answers = Dict(help="Dictionary with the current student responses", scope=Scope.user_state)
done = Boolean(help="Whether the student has answered the problem", scope=Scope.user_state)
seed = Integer(help="Random seed for this student", scope=Scope.user_state)
weight = Float(
display_name="Problem Weight",
help=("Defines the number of points each problem is worth. "
"If the value is not set, each response field in the problem is worth one point."),
values={"min": 0, "step": .1},
scope=Scope.settings
)
markdown = String(help="Markdown source of this module", default=None, scope=Scope.settings)
source_code = String(
help="Source code for LaTeX and Word problems. This feature is not well-supported.",
scope=Scope.settings
)
text_customization = Dict(
help="String customization substitutions for particular locations",
scope=Scope.settings
# TODO: someday it should be possible to not duplicate this definition here
# and in inheritance.py
)
use_latex_compiler = Boolean(
help="Enable LaTeX templates?",
default=False,
scope=Scope.settings
)
class CapaMixin(CapaFields):
"""
Core logic for Capa Problem, which can be used by XModules or XBlocks.
"""
def __init__(self, *args, **kwargs):
super(CapaMixin, self).__init__(*args, **kwargs)
due_date = get_extended_due_date(self)
if self.graceperiod is not None and due_date:
self.close_date = due_date + self.graceperiod
else:
self.close_date = due_date
if self.seed is None:
self.choose_new_seed()
# Need the problem location in openendedresponse to send out. Adding
# it to the system here seems like the least clunky way to get it
# there.
self.runtime.set('location', self.location.url())
try:
# TODO (vshnayder): move as much as possible of this work and error
# checking to descriptor load time
self.lcp = self.new_lcp(self.get_state_for_lcp())
# At this point, we need to persist the randomization seed
# so that when the problem is re-loaded (to check/view/save)
# it stays the same.
# However, we do not want to write to the database
# every time the module is loaded.
# So we set the seed ONLY when there is not one set already
if self.seed is None:
self.seed = self.lcp.seed
except Exception as err: # pylint: disable=broad-except
msg = u'cannot create LoncapaProblem {loc}: {err}'.format(
loc=self.location.url(), err=err)
# TODO (vshnayder): do modules need error handlers too?
# We shouldn't be switching on DEBUG.
if self.runtime.DEBUG:
log.warning(msg)
# TODO (vshnayder): This logic should be general, not here--and may
# want to preserve the data instead of replacing it.
# e.g. in the CMS
msg = u'<p>{msg}</p>'.format(msg=cgi.escape(msg))
msg += u'<p><pre>{tb}</pre></p>'.format(
tb=cgi.escape(traceback.format_exc()))
# create a dummy problem with error message instead of failing
problem_text = (u'<problem><text><span class="inline-error">'
u'Problem {url} has an error:</span>{msg}</text></problem>'.format(
url=self.location.url(),
msg=msg)
)
self.lcp = self.new_lcp(self.get_state_for_lcp(), text=problem_text)
else:
# add extra info and raise
raise Exception(msg), None, sys.exc_info()[2]
self.set_state_from_lcp()
assert self.seed is not None
def choose_new_seed(self):
"""
Choose a new seed.
"""
if self.rerandomize == 'never':
self.seed = 1
elif self.rerandomize == "per_student" and hasattr(self.runtime, 'seed'):
# see comment on randomization_bin
self.seed = randomization_bin(self.runtime.seed, self.location.url)
else:
self.seed = struct.unpack('i', os.urandom(4))[0]
# So that sandboxed code execution can be cached, but still have an interesting
# number of possibilities, cap the number of different random seeds.
self.seed %= MAX_RANDOMIZATION_BINS
def new_lcp(self, state, text=None):
"""
Generate a new Loncapa Problem
"""
if text is None:
text = self.data
return LoncapaProblem(
problem_text=text,
id=self.location.html_id(),
state=state,
seed=self.seed,
system=self.runtime,
)
def get_state_for_lcp(self):
"""
Give a dictionary holding the state of the module
"""
return {
'done': self.done,
'correct_map': self.correct_map,
'student_answers': self.student_answers,
'input_state': self.input_state,
'seed': self.seed,
}
def set_state_from_lcp(self):
"""
Set the module's state from the settings in `self.lcp`
"""
lcp_state = self.lcp.get_state()
self.done = lcp_state['done']
self.correct_map = lcp_state['correct_map']
self.input_state = lcp_state['input_state']
self.student_answers = lcp_state['student_answers']
self.seed = lcp_state['seed']
def get_score(self):
"""
Access the problem's score
"""
return self.lcp.get_score()
def max_score(self):
"""
Access the problem's max score
"""
return self.lcp.get_max_score()
def get_progress(self):
"""
For now, just return score / max_score
"""
score_dict = self.get_score()
score = score_dict['score']
total = score_dict['total']
if total > 0:
if self.weight is not None:
# scale score and total by weight/total:
score = score * self.weight / total
total = self.weight
try:
return Progress(score, total)
except (TypeError, ValueError):
log.exception("Got bad progress")
return None
return None
def get_html(self):
"""
Return some html with data about the module
"""
progress = self.get_progress()
return self.runtime.render_template('problem_ajax.html', {
'element_id': self.location.html_id(),
'id': self.id,
'ajax_url': self.runtime.ajax_url,
'progress_status': Progress.to_js_status_str(progress),
'progress_detail': Progress.to_js_detail_str(progress),
})
def check_button_name(self):
"""
Determine the name for the "check" button.
Usually it is just "Check", but if this is the student's
final attempt, change the name to "Final Check".
The text can be customized by the text_customization setting.
"""
# The logic flow is a little odd so that _('xxx') strings can be found for
# translation while also running _() just once for each string.
_ = self.runtime.service(self, "i18n").ugettext
check = _('Check')
final_check = _('Final Check')
# Apply customizations if present
if 'custom_check' in self.text_customization:
check = _(self.text_customization.get('custom_check'))
if 'custom_final_check' in self.text_customization:
final_check = _(self.text_customization.get('custom_final_check'))
# TODO: need a way to get the customized words into the list of
# words to be translated
if self.max_attempts is not None and self.attempts >= self.max_attempts - 1:
return final_check
else:
return check
def should_show_check_button(self):
"""
Return True/False to indicate whether to show the "Check" button.
"""
submitted_without_reset = (self.is_submitted() and self.rerandomize == "always")
# If the problem is closed (past due / too many attempts)
# then we do NOT show the "check" button
# Also, do not show the "check" button if we're waiting
# for the user to reset a randomized problem
if self.closed() or submitted_without_reset:
return False
else:
return True
def should_show_reset_button(self):
"""
Return True/False to indicate whether to show the "Reset" button.
"""
is_survey_question = (self.max_attempts == 0)
if self.rerandomize in ["always", "onreset"]:
# If the problem is closed (and not a survey question with max_attempts==0),
# then do NOT show the reset button.
# If the problem hasn't been submitted yet, then do NOT show
# the reset button.
if (self.closed() and not is_survey_question) or not self.is_submitted():
return False
else:
return True
# Only randomized problems need a "reset" button
else:
return False
def should_show_save_button(self):
"""
Return True/False to indicate whether to show the "Save" button.
"""
# If the user has forced the save button to display,
# then show it as long as the problem is not closed
# (past due / too many attempts)
if self.force_save_button:
return not self.closed()
else:
is_survey_question = (self.max_attempts == 0)
needs_reset = self.is_submitted() and self.rerandomize == "always"
# If the student has unlimited attempts, and their answers
# are not randomized, then we do not need a save button
# because they can use the "Check" button without consequences.
#
# The consequences we want to avoid are:
# * Using up an attempt (if max_attempts is set)
# * Changing the current problem, and no longer being
# able to view it (if rerandomize is "always")
#
# In those cases. the if statement below is false,
# and the save button can still be displayed.
#
if self.max_attempts is None and self.rerandomize != "always":
return False
# If the problem is closed (and not a survey question with max_attempts==0),
# then do NOT show the save button
# If we're waiting for the user to reset a randomized problem
# then do NOT show the save button
elif (self.closed() and not is_survey_question) or needs_reset:
return False
else:
return True
def handle_problem_html_error(self, err):
"""
Create a dummy problem to represent any errors.
Change our problem to a dummy problem containing a warning message to
display to users. Returns the HTML to show to users
`err` is the Exception encountered while rendering the problem HTML.
"""
log.exception(err.message)
# TODO (vshnayder): another switch on DEBUG.
if self.runtime.DEBUG:
msg = (
u'[courseware.capa.capa_module] <font size="+1" color="red">'
u'Failed to generate HTML for problem {url}</font>'.format(
url=cgi.escape(self.location.url()))
)
msg += u'<p>Error:</p><p><pre>{msg}</pre></p>'.format(msg=cgi.escape(err.message))
msg += u'<p><pre>{tb}</pre></p>'.format(tb=cgi.escape(traceback.format_exc()))
html = msg
else:
# We're in non-debug mode, and possibly even in production. We want
# to avoid bricking of problem as much as possible
# Presumably, student submission has corrupted LoncapaProblem HTML.
# First, pull down all student answers
student_answers = self.lcp.student_answers
answer_ids = student_answers.keys()
# Some inputtypes, such as dynamath, have additional "hidden" state that
# is not exposed to the student. Keep those hidden
# TODO: Use regex, e.g. 'dynamath' is suffix at end of answer_id
hidden_state_keywords = ['dynamath']
for answer_id in answer_ids:
for hidden_state_keyword in hidden_state_keywords:
if answer_id.find(hidden_state_keyword) >= 0:
student_answers.pop(answer_id)
# Next, generate a fresh LoncapaProblem
self.lcp = self.new_lcp(None)
self.set_state_from_lcp()
# Prepend a scary warning to the student
warning = '<div class="capa_reset">'\
'<h2>Warning: The problem has been reset to its initial state!</h2>'\
'The problem\'s state was corrupted by an invalid submission. ' \
'The submission consisted of:'\
'<ul>'
for student_answer in student_answers.values():
if student_answer != '':
warning += '<li>' + cgi.escape(student_answer) + '</li>'
warning += '</ul>'\
'If this error persists, please contact the course staff.'\
'</div>'
html = warning
try:
html += self.lcp.get_html()
except Exception: # Couldn't do it. Give up
log.exception("Unable to generate html from LoncapaProblem")
raise
return html
def get_problem_html(self, encapsulate=True):
"""
Return html for the problem.
Adds check, reset, save buttons as necessary based on the problem config and state.
"""
try:
html = self.lcp.get_html()
# If we cannot construct the problem HTML,
# then generate an error message instead.
except Exception as err: # pylint: disable=broad-except
html = self.handle_problem_html_error(err)
# The convention is to pass the name of the check button
# if we want to show a check button, and False otherwise
# This works because non-empty strings evaluate to True
if self.should_show_check_button():
check_button = self.check_button_name()
else:
check_button = False
content = {'name': self.display_name_with_default,
'html': html,
'weight': self.weight,
}
context = {'problem': content,
'id': self.id,
'check_button': check_button,
'reset_button': self.should_show_reset_button(),
'save_button': self.should_show_save_button(),
'answer_available': self.answer_available(),
'attempts_used': self.attempts,
'attempts_allowed': self.max_attempts,
}
html = self.runtime.render_template('problem.html', context)
if encapsulate:
html = u'<div id="problem_{id}" class="problem" data-url="{ajax_url}">'.format(
id=self.location.html_id(), ajax_url=self.runtime.ajax_url
) + html + "</div>"
# now do all the substitutions which the LMS module_render normally does, but
# we need to do here explicitly since we can get called for our HTML via AJAX
html = self.runtime.replace_urls(html)
if self.runtime.replace_course_urls:
html = self.runtime.replace_course_urls(html)
if self.runtime.replace_jump_to_id_urls:
html = self.runtime.replace_jump_to_id_urls(html)
return html
def is_past_due(self):
"""
Is it now past this problem's due date, including grace period?
"""
return (self.close_date is not None and
datetime.datetime.now(UTC()) > self.close_date)
def closed(self):
"""
Is the student still allowed to submit answers?
"""
if self.max_attempts is not None and self.attempts >= self.max_attempts:
return True
if self.is_past_due():
return True
return False
def is_submitted(self):
"""
Used to decide to show or hide RESET or CHECK buttons.
Means that student submitted problem and nothing more.
Problem can be completely wrong.
Pressing RESET button makes this function to return False.
"""
# used by conditional module
return self.lcp.done
def is_attempted(self):
"""
Has the problem been attempted?
used by conditional module
"""
return self.attempts > 0
def is_correct(self):
"""
True iff full points
"""
score_dict = self.get_score()
return score_dict['score'] == score_dict['total']
def answer_available(self):
"""
Is the user allowed to see an answer?
"""
if self.showanswer == '':
return False
elif self.showanswer == "never":
return False
elif self.runtime.user_is_staff:
# This is after the 'never' check because admins can see the answer
# unless the problem explicitly prevents it
return True
elif self.showanswer == 'attempted':
return self.attempts > 0
elif self.showanswer == 'answered':
# NOTE: this is slightly different from 'attempted' -- resetting the problems
# makes lcp.done False, but leaves attempts unchanged.
return self.lcp.done
elif self.showanswer == 'closed':
return self.closed()
elif self.showanswer == 'finished':
return self.closed() or self.is_correct()
elif self.showanswer == 'past_due':
return self.is_past_due()
elif self.showanswer == 'always':
return True
return False
def update_score(self, data):
"""
Delivers grading response (e.g. from asynchronous code checking) to
the capa problem, so its score can be updated
'data' must have a key 'response' which is a string that contains the
grader's response
No ajax return is needed. Return empty dict.
"""
queuekey = data['queuekey']
score_msg = data['xqueue_body']
self.lcp.update_score(score_msg, queuekey)
self.set_state_from_lcp()
self.publish_grade()
return dict() # No AJAX return is needed
def handle_ungraded_response(self, data):
"""
Delivers a response from the XQueue to the capa problem
The score of the problem will not be updated
Args:
- data (dict) must contain keys:
queuekey - a key specific to this response
xqueue_body - the body of the response
Returns:
empty dictionary
No ajax return is needed, so an empty dict is returned
"""
queuekey = data['queuekey']
score_msg = data['xqueue_body']
# pass along the xqueue message to the problem
self.lcp.ungraded_response(score_msg, queuekey)
self.set_state_from_lcp()
return dict()
def handle_input_ajax(self, data):
"""
Handle ajax calls meant for a particular input in the problem
Args:
- data (dict) - data that should be passed to the input
Returns:
- dict containing the response from the input
"""
response = self.lcp.handle_input_ajax(data)
# save any state changes that may occur
self.set_state_from_lcp()
return response
def get_answer(self, _data):
"""
For the "show answer" button.
Returns the answers: {'answers' : answers}
"""
event_info = dict()
event_info['problem_id'] = self.location.url()
self.runtime.track_function('showanswer', event_info)
if not self.answer_available():
raise NotFoundError('Answer is not available')
else:
answers = self.lcp.get_question_answers()
self.set_state_from_lcp()
# answers (eg <solution>) may have embedded images
# but be careful, some problems are using non-string answer dicts
new_answers = dict()
for answer_id in answers:
try:
new_answer = {answer_id: self.runtime.replace_urls(answers[answer_id])}
except TypeError:
log.debug(u'Unable to perform URL substitution on answers[%s]: %s',
answer_id, answers[answer_id])
new_answer = {answer_id: answers[answer_id]}
new_answers.update(new_answer)
return {'answers': new_answers}
# Figure out if we should move these to capa_problem?
def get_problem(self, _data):
"""
Return results of get_problem_html, as a simple dict for json-ing.
{ 'html': <the-html> }
Used if we want to reconfirm we have the right thing e.g. after
several AJAX calls.
"""
return {'html': self.get_problem_html(encapsulate=False)}
@staticmethod
def make_dict_of_responses(data):
"""
Make dictionary of student responses (aka "answers")
`data` is POST dictionary (webob.multidict.MultiDict).
The `data` dict has keys of the form 'x_y', which are mapped
to key 'y' in the returned dict. For example,
'input_1_2_3' would be mapped to '1_2_3' in the returned dict.
Some inputs always expect a list in the returned dict
(e.g. checkbox inputs). The convention is that
keys in the `data` dict that end with '[]' will always
have list values in the returned dict.
For example, if the `data` dict contains {'input_1[]': 'test' }
then the output dict would contain {'1': ['test'] }
(the value is a list).
Some other inputs such as ChoiceTextInput expect a dict of values in the returned
dict If the key ends with '{}' then we will assume that the value is a json
encoded dict and deserialize it.
For example, if the `data` dict contains {'input_1{}': '{"1_2_1": 1}'}
then the output dict would contain {'1': {"1_2_1": 1} }
(the value is a dictionary)
Raises an exception if:
-A key in the `data` dictionary does not contain at least one underscore
(e.g. "input" is invalid, but "input_1" is valid)
-Two keys end up with the same name in the returned dict.
(e.g. 'input_1' and 'input_1[]', which both get mapped to 'input_1'
in the returned dict)
"""
answers = dict()
# webob.multidict.MultiDict is a view of a list of tuples,
# so it will return a multi-value key once for each value.
# We only want to consider each key a single time, so we use set(data.keys())
for key in set(data.keys()):
# e.g. input_resistor_1 ==> resistor_1
_, _, name = key.partition('_') # pylint: disable=redefined-outer-name
# If key has no underscores, then partition
# will return (key, '', '')
# We detect this and raise an error
if not name:
raise ValueError(u"{key} must contain at least one underscore".format(key=key))
else:
# This allows for answers which require more than one value for
# the same form input (e.g. checkbox inputs). The convention is that
# if the name ends with '[]' (which looks like an array), then the
# answer will be an array.
# if the name ends with '{}' (Which looks like a dict),
# then the answer will be a dict
is_list_key = name.endswith('[]')
is_dict_key = name.endswith('{}')
name = name[:-2] if is_list_key or is_dict_key else name
if is_list_key:
val = data.getall(key)
elif is_dict_key:
try:
val = json.loads(data[key])
# If the submission wasn't deserializable, raise an error.
except(KeyError, ValueError):
raise ValueError(
u"Invalid submission: {val} for {key}".format(val=data[key], key=key)
)
else:
val = data[key]
# If the name already exists, then we don't want
# to override it. Raise an error instead
if name in answers:
raise ValueError(u"Key {name} already exists in answers dict".format(name=name))
else:
answers[name] = val
return answers
def publish_grade(self):
"""
Publishes the student's current grade to the system as an event
"""
score = self.lcp.get_score()
self.runtime.publish({
'event_name': 'grade',
'value': score['score'],
'max_value': score['total'],
})
return {'grade': score['score'], 'max_grade': score['total']}
def check_problem(self, data):
"""
Checks whether answers to a problem are correct
Returns a map of correct/incorrect answers:
{'success' : 'correct' | 'incorrect' | AJAX alert msg string,
'contents' : html}
"""
event_info = dict()
event_info['state'] = self.lcp.get_state()
event_info['problem_id'] = self.location.url()
answers = self.make_dict_of_responses(data)
event_info['answers'] = convert_files_to_filenames(answers)
# Too late. Cannot submit
if self.closed():
event_info['failure'] = 'closed'
self.runtime.track_function('problem_check_fail', event_info)
raise NotFoundError('Problem is closed')
# Problem submitted. Student should reset before checking again
if self.done and self.rerandomize == "always":
event_info['failure'] = 'unreset'
self.runtime.track_function('problem_check_fail', event_info)
raise NotFoundError('Problem must be reset before it can be checked again')
# Problem queued. Students must wait a specified waittime before they are allowed to submit
if self.lcp.is_queued():
current_time = datetime.datetime.now(UTC())
prev_submit_time = self.lcp.get_recentmost_queuetime()
waittime_between_requests = self.runtime.xqueue['waittime']
if (current_time - prev_submit_time).total_seconds() < waittime_between_requests:
msg = u'You must wait at least {wait} seconds between submissions'.format(
wait=waittime_between_requests)
return {'success': msg, 'html': ''} # Prompts a modal dialog in ajax callback
try:
correct_map = self.lcp.grade_answers(answers)
self.attempts = self.attempts + 1
self.lcp.done = True
self.set_state_from_lcp()
except (StudentInputError, ResponseError, LoncapaProblemError) as inst:
log.warning("StudentInputError in capa_module:problem_check",
exc_info=True)
# Save the user's state before failing
self.set_state_from_lcp()
# If the user is a staff member, include
# the full exception, including traceback,
# in the response
if self.runtime.user_is_staff:
msg = u"Staff debug info: {tb}".format(tb=cgi.escape(traceback.format_exc()))
# Otherwise, display just an error message,
# without a stack trace
else:
msg = u"Error: {msg}".format(msg=inst.message)
return {'success': msg}
except Exception as err:
# Save the user's state before failing
self.set_state_from_lcp()
if self.runtime.DEBUG:
msg = u"Error checking problem: {}".format(err.message)
msg += u'\nTraceback:\n{}'.format(traceback.format_exc())
return {'success': msg}
raise
published_grade = self.publish_grade()
# success = correct if ALL questions in this problem are correct
success = 'correct'
for answer_id in correct_map:
if not correct_map.is_correct(answer_id):
success = 'incorrect'
# NOTE: We are logging both full grading and queued-grading submissions. In the latter,
# 'success' will always be incorrect
event_info['grade'] = published_grade['grade']
event_info['max_grade'] = published_grade['max_grade']
event_info['correct_map'] = correct_map.get_dict()
event_info['success'] = success
event_info['attempts'] = self.attempts
self.runtime.track_function('problem_check', event_info)
if hasattr(self.runtime, 'psychometrics_handler'): # update PsychometricsData using callback
self.runtime.psychometrics_handler(self.get_state_for_lcp())
# render problem into HTML
html = self.get_problem_html(encapsulate=False)
return {'success': success,
'contents': html,
}
def rescore_problem(self):
"""
Checks whether the existing answers to a problem are correct.
This is called when the correct answer to a problem has been changed,
and the grade should be re-evaluated.
Returns a dict with one key:
{'success' : 'correct' | 'incorrect' | AJAX alert msg string }
Raises NotFoundError if called on a problem that has not yet been
answered, or NotImplementedError if it's a problem that cannot be rescored.
Returns the error messages for exceptions occurring while performing
the rescoring, rather than throwing them.
"""
event_info = {'state': self.lcp.get_state(), 'problem_id': self.location.url()}
if not self.lcp.supports_rescoring():
event_info['failure'] = 'unsupported'
self.runtime.track_function('problem_rescore_fail', event_info)
raise NotImplementedError("Problem's definition does not support rescoring")
if not self.done:
event_info['failure'] = 'unanswered'
self.runtime.track_function('problem_rescore_fail', event_info)
raise NotFoundError('Problem must be answered before it can be graded again')
# get old score, for comparison:
orig_score = self.lcp.get_score()
event_info['orig_score'] = orig_score['score']
event_info['orig_total'] = orig_score['total']
try:
correct_map = self.lcp.rescore_existing_answers()
except (StudentInputError, ResponseError, LoncapaProblemError) as inst:
log.warning("Input error in capa_module:problem_rescore", exc_info=True)
event_info['failure'] = 'input_error'
self.runtime.track_function('problem_rescore_fail', event_info)
return {'success': u"Error: {0}".format(inst.message)}
except Exception as err:
event_info['failure'] = 'unexpected'
self.runtime.track_function('problem_rescore_fail', event_info)
if self.runtime.DEBUG:
msg = u"Error checking problem: {0}".format(err.message)
msg += u'\nTraceback:\n' + traceback.format_exc()
return {'success': msg}
raise
# rescoring should have no effect on attempts, so don't
# need to increment here, or mark done. Just save.
self.set_state_from_lcp()
self.publish_grade()
new_score = self.lcp.get_score()
event_info['new_score'] = new_score['score']
event_info['new_total'] = new_score['total']
# success = correct if ALL questions in this problem are correct
success = 'correct'
for answer_id in correct_map:
if not correct_map.is_correct(answer_id):
success = 'incorrect'
# NOTE: We are logging both full grading and queued-grading submissions. In the latter,
# 'success' will always be incorrect
event_info['correct_map'] = correct_map.get_dict()
event_info['success'] = success
event_info['attempts'] = self.attempts
self.runtime.track_function('problem_rescore', event_info)
# psychometrics should be called on rescoring requests in the same way as check-problem
if hasattr(self.runtime, 'psychometrics_handler'): # update PsychometricsData using callback
self.runtime.psychometrics_handler(self.get_state_for_lcp())
return {'success': success}
def save_problem(self, data):
"""
Save the passed in answers.
Returns a dict { 'success' : bool, 'msg' : message }
The message is informative on success, and an error message on failure.
"""
event_info = dict()
event_info['state'] = self.lcp.get_state()
event_info['problem_id'] = self.location.url()
answers = self.make_dict_of_responses(data)
event_info['answers'] = answers
# Too late. Cannot submit
if self.closed() and not self.max_attempts == 0:
event_info['failure'] = 'closed'
self.runtime.track_function('save_problem_fail', event_info)
return {'success': False,
'msg': "Problem is closed"}
# Problem submitted. Student should reset before saving
# again.
if self.done and self.rerandomize == "always":
event_info['failure'] = 'done'
self.runtime.track_function('save_problem_fail', event_info)
return {'success': False,
'msg': "Problem needs to be reset prior to save"}
self.lcp.student_answers = answers
self.set_state_from_lcp()
self.runtime.track_function('save_problem_success', event_info)
msg = "Your answers have been saved"
if not self.max_attempts == 0:
msg += " but not graded. Hit 'Check' to grade them."
return {'success': True,
'msg': msg}
def reset_problem(self, _data):
"""
Changes problem state to unfinished -- removes student answers,
and causes problem to rerender itself.
Returns a dictionary of the form:
{'success': True/False,
'html': Problem HTML string }
If an error occurs, the dictionary will also have an
`error` key containing an error message.
"""
event_info = dict()
event_info['old_state'] = self.lcp.get_state()
event_info['problem_id'] = self.location.url()
if self.closed():
event_info['failure'] = 'closed'
self.runtime.track_function('reset_problem_fail', event_info)
return {'success': False,
'error': "Problem is closed"}
if not self.done:
event_info['failure'] = 'not_done'
self.runtime.track_function('reset_problem_fail', event_info)
return {'success': False,
'error': "Refresh the page and make an attempt before resetting."}
if self.rerandomize in ["always", "onreset"]:
# Reset random number generator seed.
self.choose_new_seed()
# Generate a new problem with either the previous seed or a new seed
self.lcp = self.new_lcp(None)
# Pull in the new problem seed
self.set_state_from_lcp()
event_info['new_state'] = self.lcp.get_state()
self.runtime.track_function('reset_problem', event_info)
return {'success': True,
'html': self.get_problem_html(encapsulate=False)}
common/lib/xmodule/xmodule/capa_module.py
"""Implements basics of Capa, including class CapaModule."""
import cgi
import datetime
import hashlib
import json
import logging
import os
import traceback
import struct
import sys
from pkg_resources import resource_string
from capa.capa_problem import LoncapaProblem
from capa.responsetypes import StudentInputError, \
ResponseError, LoncapaProblemError
from capa.util import convert_files_to_filenames
from .capa_base import CapaMixin, CapaFields, ComplexEncoder
from .progress import Progress
from xmodule.x_module import XModule, module_attr
from xmodule.raw_module import RawDescriptor
from xmodule.exceptions import NotFoundError, ProcessingError
from xblock.fields import Scope, String, Boolean, Dict, Integer, Float
from .fields import Timedelta, Date
from django.utils.timezone import UTC
from .util.duedate import get_extended_due_date
log = logging.getLogger("edx.courseware")
# Generate this many different variants of problems with rerandomize=per_student
NUM_RANDOMIZATION_BINS = 20
# Never produce more than this many different seeds, no matter what.
MAX_RANDOMIZATION_BINS = 1000
def randomization_bin(seed, problem_id):
"""
Pick a randomization bin for the problem given the user's seed and a problem id.
We do this because we only want e.g. 20 randomizations of a problem to make analytics
interesting. To avoid having sets of students that always get the same problems,
we'll combine the system's per-student seed with the problem id in picking the bin.
"""
r_hash = hashlib.sha1()
r_hash.update(str(seed))
r_hash.update(str(problem_id))
# get the first few digits of the hash, convert to an int, then mod.
return int(r_hash.hexdigest()[:7], 16) % NUM_RANDOMIZATION_BINS
class Randomization(String):
"""
Define a field to store how to randomize a problem.
"""
def from_json(self, value):
if value in ("", "true"):
return "always"
elif value == "false":
return "per_student"
return value
to_json = from_json
class ComplexEncoder(json.JSONEncoder):
"""
Extend the JSON encoder to correctly handle complex numbers
"""
def default(self, obj):
"""
Print a nicely formatted complex number, or default to the JSON encoder
"""
if isinstance(obj, complex):
return u"{real:.7g}{imag:+.7g}*j".format(real=obj.real, imag=obj.imag)
return json.JSONEncoder.default(self, obj)
class CapaFields(object):
"""
Define the possible fields for a Capa problem
"""
display_name = String(
display_name="Display Name",
help="This name appears in the horizontal navigation at the top of the page.",
scope=Scope.settings,
# it'd be nice to have a useful default but it screws up other things; so,
# use display_name_with_default for those
default="Blank Advanced Problem"
)
attempts = Integer(help="Number of attempts taken by the student on this problem",
default=0, scope=Scope.user_state)
max_attempts = Integer(
display_name="Maximum Attempts",
help=("Defines the number of times a student can try to answer this problem. "
"If the value is not set, infinite attempts are allowed."),
values={"min": 0}, scope=Scope.settings
)
due = Date(help="Date that this problem is due by", scope=Scope.settings)
extended_due = Date(
help="Date that this problem is due by for a particular student. This "
"can be set by an instructor, and will override the global due "
"date if it is set to a date that is later than the global due "
"date.",
default=None,
scope=Scope.user_state,
)
graceperiod = Timedelta(
help="Amount of time after the due date that submissions will be accepted",
scope=Scope.settings
)
showanswer = String(
display_name="Show Answer",
help=("Defines when to show the answer to the problem. "
"A default value can be set in Advanced Settings."),
scope=Scope.settings,
default="finished",
values=[
{"display_name": "Always", "value": "always"},
{"display_name": "Answered", "value": "answered"},
{"display_name": "Attempted", "value": "attempted"},
{"display_name": "Closed", "value": "closed"},
{"display_name": "Finished", "value": "finished"},
{"display_name": "Past Due", "value": "past_due"},
{"display_name": "Never", "value": "never"}]
)
force_save_button = Boolean(
help="Whether to force the save button to appear on the page",
scope=Scope.settings,
default=False
)
rerandomize = Randomization(
display_name="Randomization",
help="Defines how often inputs are randomized when a student loads the problem. "
"This setting only applies to problems that can have randomly generated numeric values. "
"A default value can be set in Advanced Settings.",
default="never",
scope=Scope.settings,
values=[
{"display_name": "Always", "value": "always"},
{"display_name": "On Reset", "value": "onreset"},
{"display_name": "Never", "value": "never"},
{"display_name": "Per Student", "value": "per_student"}
]
)
data = String(help="XML data for the problem", scope=Scope.content, default="<problem></problem>")
correct_map = Dict(help="Dictionary with the correctness of current student answers",
scope=Scope.user_state, default={})
input_state = Dict(help="Dictionary for maintaining the state of inputtypes", scope=Scope.user_state)
student_answers = Dict(help="Dictionary with the current student responses", scope=Scope.user_state)
done = Boolean(help="Whether the student has answered the problem", scope=Scope.user_state)
seed = Integer(help="Random seed for this student", scope=Scope.user_state)
weight = Float(
display_name="Problem Weight",
help=("Defines the number of points each problem is worth. "
"If the value is not set, each response field in the problem is worth one point."),
values={"min": 0, "step": .1},
scope=Scope.settings
)
markdown = String(help="Markdown source of this module", default=None, scope=Scope.settings)
source_code = String(
help="Source code for LaTeX and Word problems. This feature is not well-supported.",
scope=Scope.settings
)
text_customization = Dict(
help="String customization substitutions for particular locations",
scope=Scope.settings
# TODO: someday it should be possible to not duplicate this definition here
# and in inheritance.py
)
use_latex_compiler = Boolean(
help="Enable LaTeX templates?",
default=False,
scope=Scope.settings
)
class CapaModule(CapaFields, XModule):
class CapaModule(CapaMixin, XModule):
"""
An XModule implementing LonCapa format problems, implemented by way of
capa.capa_problem.LoncapaProblem
......@@ -200,385 +40,6 @@ class CapaModule(CapaFields, XModule):
"""
super(CapaModule, self).__init__(*args, **kwargs)
due_date = get_extended_due_date(self)
if self.graceperiod is not None and due_date:
self.close_date = due_date + self.graceperiod
else:
self.close_date = due_date
if self.seed is None:
self.choose_new_seed()
# Need the problem location in openendedresponse to send out. Adding
# it to the system here seems like the least clunky way to get it
# there.
self.system.set('location', self.location.url())
try:
# TODO (vshnayder): move as much as possible of this work and error
# checking to descriptor load time
self.lcp = self.new_lcp(self.get_state_for_lcp())
# At this point, we need to persist the randomization seed
# so that when the problem is re-loaded (to check/view/save)
# it stays the same.
# However, we do not want to write to the database
# every time the module is loaded.
# So we set the seed ONLY when there is not one set already
if self.seed is None:
self.seed = self.lcp.seed
except Exception as err: # pylint: disable=broad-except
msg = u'cannot create LoncapaProblem {loc}: {err}'.format(
loc=self.location.url(), err=err)
# TODO (vshnayder): do modules need error handlers too?
# We shouldn't be switching on DEBUG.
if self.system.DEBUG:
log.warning(msg)
# TODO (vshnayder): This logic should be general, not here--and may
# want to preserve the data instead of replacing it.
# e.g. in the CMS
msg = u'<p>{msg}</p>'.format(msg=cgi.escape(msg))
msg += u'<p><pre>{tb}</pre></p>'.format(
tb=cgi.escape(traceback.format_exc()))
# create a dummy problem with error message instead of failing
problem_text = (u'<problem><text><span class="inline-error">'
u'Problem {url} has an error:</span>{msg}</text></problem>'.format(
url=self.location.url(),
msg=msg)
)
self.lcp = self.new_lcp(self.get_state_for_lcp(), text=problem_text)
else:
# add extra info and raise
raise Exception(msg), None, sys.exc_info()[2]
self.set_state_from_lcp()
assert self.seed is not None
def choose_new_seed(self):
"""
Choose a new seed.
"""
if self.rerandomize == 'never':
self.seed = 1
elif self.rerandomize == "per_student" and hasattr(self.system, 'seed'):
# see comment on randomization_bin
self.seed = randomization_bin(self.system.seed, self.location.url)
else:
self.seed = struct.unpack('i', os.urandom(4))[0]
# So that sandboxed code execution can be cached, but still have an interesting
# number of possibilities, cap the number of different random seeds.
self.seed %= MAX_RANDOMIZATION_BINS
def new_lcp(self, state, text=None):
"""
Generate a new Loncapa Problem
"""
if text is None:
text = self.data
return LoncapaProblem(
problem_text=text,
id=self.location.html_id(),
state=state,
seed=self.seed,
system=self.system,
)
def get_state_for_lcp(self):
"""
Give a dictionary holding the state of the module
"""
return {
'done': self.done,
'correct_map': self.correct_map,
'student_answers': self.student_answers,
'input_state': self.input_state,
'seed': self.seed,
}
def set_state_from_lcp(self):
"""
Set the module's state from the settings in `self.lcp`
"""
lcp_state = self.lcp.get_state()
self.done = lcp_state['done']
self.correct_map = lcp_state['correct_map']
self.input_state = lcp_state['input_state']
self.student_answers = lcp_state['student_answers']
self.seed = lcp_state['seed']
def get_score(self):
"""
Access the problem's score
"""
return self.lcp.get_score()
def max_score(self):
"""
Access the problem's max score
"""
return self.lcp.get_max_score()
def get_progress(self):
"""
For now, just return score / max_score
"""
score_dict = self.get_score()
score = score_dict['score']
total = score_dict['total']
if total > 0:
if self.weight is not None:
# scale score and total by weight/total:
score = score * self.weight / total
total = self.weight
try:
return Progress(score, total)
except (TypeError, ValueError):
log.exception("Got bad progress")
return None
return None
def get_html(self):
"""
Return some html with data about the module
"""
progress = self.get_progress()
return self.system.render_template('problem_ajax.html', {
'element_id': self.location.html_id(),
'id': self.id,
'ajax_url': self.system.ajax_url,
'progress_status': Progress.to_js_status_str(progress),
'progress_detail': Progress.to_js_detail_str(progress),
})
def check_button_name(self):
"""
Determine the name for the "check" button.
Usually it is just "Check", but if this is the student's
final attempt, change the name to "Final Check".
The text can be customized by the text_customization setting.
"""
# The logic flow is a little odd so that _('xxx') strings can be found for
# translation while also running _() just once for each string.
_ = self.runtime.service(self, "i18n").ugettext
check = _('Check')
final_check = _('Final Check')
# Apply customizations if present
if 'custom_check' in self.text_customization:
check = _(self.text_customization.get('custom_check'))
if 'custom_final_check' in self.text_customization:
final_check = _(self.text_customization.get('custom_final_check'))
# TODO: need a way to get the customized words into the list of
# words to be translated
if self.max_attempts is not None and self.attempts >= self.max_attempts - 1:
return final_check
else:
return check
def should_show_check_button(self):
"""
Return True/False to indicate whether to show the "Check" button.
"""
submitted_without_reset = (self.is_submitted() and self.rerandomize == "always")
# If the problem is closed (past due / too many attempts)
# then we do NOT show the "check" button
# Also, do not show the "check" button if we're waiting
# for the user to reset a randomized problem
if self.closed() or submitted_without_reset:
return False
else:
return True
def should_show_reset_button(self):
"""
Return True/False to indicate whether to show the "Reset" button.
"""
is_survey_question = (self.max_attempts == 0)
if self.rerandomize in ["always", "onreset"]:
# If the problem is closed (and not a survey question with max_attempts==0),
# then do NOT show the reset button.
# If the problem hasn't been submitted yet, then do NOT show
# the reset button.
if (self.closed() and not is_survey_question) or not self.is_submitted():
return False
else:
return True
# Only randomized problems need a "reset" button
else:
return False
def should_show_save_button(self):
"""
Return True/False to indicate whether to show the "Save" button.
"""
# If the user has forced the save button to display,
# then show it as long as the problem is not closed
# (past due / too many attempts)
if self.force_save_button:
return not self.closed()
else:
is_survey_question = (self.max_attempts == 0)
needs_reset = self.is_submitted() and self.rerandomize == "always"
# If the student has unlimited attempts, and their answers
# are not randomized, then we do not need a save button
# because they can use the "Check" button without consequences.
#
# The consequences we want to avoid are:
# * Using up an attempt (if max_attempts is set)
# * Changing the current problem, and no longer being
# able to view it (if rerandomize is "always")
#
# In those cases. the if statement below is false,
# and the save button can still be displayed.
#
if self.max_attempts is None and self.rerandomize != "always":
return False
# If the problem is closed (and not a survey question with max_attempts==0),
# then do NOT show the save button
# If we're waiting for the user to reset a randomized problem
# then do NOT show the save button
elif (self.closed() and not is_survey_question) or needs_reset:
return False
else:
return True
def handle_problem_html_error(self, err):
"""
Create a dummy problem to represent any errors.
Change our problem to a dummy problem containing a warning message to
display to users. Returns the HTML to show to users
`err` is the Exception encountered while rendering the problem HTML.
"""
log.exception(err.message)
# TODO (vshnayder): another switch on DEBUG.
if self.system.DEBUG:
msg = (
u'[courseware.capa.capa_module] <font size="+1" color="red">'
u'Failed to generate HTML for problem {url}</font>'.format(
url=cgi.escape(self.location.url()))
)
msg += u'<p>Error:</p><p><pre>{msg}</pre></p>'.format(msg=cgi.escape(err.message))
msg += u'<p><pre>{tb}</pre></p>'.format(tb=cgi.escape(traceback.format_exc()))
html = msg
else:
# We're in non-debug mode, and possibly even in production. We want
# to avoid bricking of problem as much as possible
# Presumably, student submission has corrupted LoncapaProblem HTML.
# First, pull down all student answers
student_answers = self.lcp.student_answers
answer_ids = student_answers.keys()
# Some inputtypes, such as dynamath, have additional "hidden" state that
# is not exposed to the student. Keep those hidden
# TODO: Use regex, e.g. 'dynamath' is suffix at end of answer_id
hidden_state_keywords = ['dynamath']
for answer_id in answer_ids:
for hidden_state_keyword in hidden_state_keywords:
if answer_id.find(hidden_state_keyword) >= 0:
student_answers.pop(answer_id)
# Next, generate a fresh LoncapaProblem
self.lcp = self.new_lcp(None)
self.set_state_from_lcp()
# Prepend a scary warning to the student
warning = '<div class="capa_reset">'\
'<h2>Warning: The problem has been reset to its initial state!</h2>'\
'The problem\'s state was corrupted by an invalid submission. ' \
'The submission consisted of:'\
'<ul>'
for student_answer in student_answers.values():
if student_answer != '':
warning += '<li>' + cgi.escape(student_answer) + '</li>'
warning += '</ul>'\
'If this error persists, please contact the course staff.'\
'</div>'
html = warning
try:
html += self.lcp.get_html()
except Exception: # Couldn't do it. Give up
log.exception("Unable to generate html from LoncapaProblem")
raise
return html
def get_problem_html(self, encapsulate=True):
"""
Return html for the problem.
Adds check, reset, save buttons as necessary based on the problem config and state.
"""
try:
html = self.lcp.get_html()
# If we cannot construct the problem HTML,
# then generate an error message instead.
except Exception as err: # pylint: disable=broad-except
html = self.handle_problem_html_error(err)
# The convention is to pass the name of the check button
# if we want to show a check button, and False otherwise
# This works because non-empty strings evaluate to True
if self.should_show_check_button():
check_button = self.check_button_name()
else:
check_button = False
content = {'name': self.display_name_with_default,
'html': html,
'weight': self.weight,
}
context = {'problem': content,
'id': self.id,
'check_button': check_button,
'reset_button': self.should_show_reset_button(),
'save_button': self.should_show_save_button(),
'answer_available': self.answer_available(),
'attempts_used': self.attempts,
'attempts_allowed': self.max_attempts,
}
html = self.system.render_template('problem.html', context)
if encapsulate:
html = u'<div id="problem_{id}" class="problem" data-url="{ajax_url}">'.format(
id=self.location.html_id(), ajax_url=self.system.ajax_url
) + html + "</div>"
# now do all the substitutions which the LMS module_render normally does, but
# we need to do here explicitly since we can get called for our HTML via AJAX
html = self.system.replace_urls(html)
if self.system.replace_course_urls:
html = self.system.replace_course_urls(html)
if self.system.replace_jump_to_id_urls:
html = self.system.replace_jump_to_id_urls(html)
return html
def handle_ajax(self, dispatch, data):
"""
This is called by courseware.module_render, to handle an AJAX call.
......@@ -637,535 +98,6 @@ class CapaModule(CapaFields, XModule):
return json.dumps(result, cls=ComplexEncoder)
def is_past_due(self):
"""
Is it now past this problem's due date, including grace period?
"""
return (self.close_date is not None and
datetime.datetime.now(UTC()) > self.close_date)
def closed(self):
"""
Is the student still allowed to submit answers?
"""
if self.max_attempts is not None and self.attempts >= self.max_attempts:
return True
if self.is_past_due():
return True
return False
def is_submitted(self):
"""
Used to decide to show or hide RESET or CHECK buttons.
Means that student submitted problem and nothing more.
Problem can be completely wrong.
Pressing RESET button makes this function to return False.
"""
# used by conditional module
return self.lcp.done
def is_attempted(self):
"""
Has the problem been attempted?
used by conditional module
"""
return self.attempts > 0
def is_correct(self):
"""
True iff full points
"""
score_dict = self.get_score()
return score_dict['score'] == score_dict['total']
def answer_available(self):
"""
Is the user allowed to see an answer?
"""
if self.showanswer == '':
return False
elif self.showanswer == "never":
return False
elif self.system.user_is_staff:
# This is after the 'never' check because admins can see the answer
# unless the problem explicitly prevents it
return True
elif self.showanswer == 'attempted':
return self.attempts > 0
elif self.showanswer == 'answered':
# NOTE: this is slightly different from 'attempted' -- resetting the problems
# makes lcp.done False, but leaves attempts unchanged.
return self.lcp.done
elif self.showanswer == 'closed':
return self.closed()
elif self.showanswer == 'finished':
return self.closed() or self.is_correct()
elif self.showanswer == 'past_due':
return self.is_past_due()
elif self.showanswer == 'always':
return True
return False
def update_score(self, data):
"""
Delivers grading response (e.g. from asynchronous code checking) to
the capa problem, so its score can be updated
'data' must have a key 'response' which is a string that contains the
grader's response
No ajax return is needed. Return empty dict.
"""
queuekey = data['queuekey']
score_msg = data['xqueue_body']
self.lcp.update_score(score_msg, queuekey)
self.set_state_from_lcp()
self.publish_grade()
return dict() # No AJAX return is needed
def handle_ungraded_response(self, data):
"""
Delivers a response from the XQueue to the capa problem
The score of the problem will not be updated
Args:
- data (dict) must contain keys:
queuekey - a key specific to this response
xqueue_body - the body of the response
Returns:
empty dictionary
No ajax return is needed, so an empty dict is returned
"""
queuekey = data['queuekey']
score_msg = data['xqueue_body']
# pass along the xqueue message to the problem
self.lcp.ungraded_response(score_msg, queuekey)
self.set_state_from_lcp()
return dict()
def handle_input_ajax(self, data):
"""
Handle ajax calls meant for a particular input in the problem
Args:
- data (dict) - data that should be passed to the input
Returns:
- dict containing the response from the input
"""
response = self.lcp.handle_input_ajax(data)
# save any state changes that may occur
self.set_state_from_lcp()
return response
def get_answer(self, _data):
"""
For the "show answer" button.
Returns the answers: {'answers' : answers}
"""
event_info = dict()
event_info['problem_id'] = self.location.url()
self.system.track_function('showanswer', event_info)
if not self.answer_available():
raise NotFoundError('Answer is not available')
else:
answers = self.lcp.get_question_answers()
self.set_state_from_lcp()
# answers (eg <solution>) may have embedded images
# but be careful, some problems are using non-string answer dicts
new_answers = dict()
for answer_id in answers:
try:
new_answer = {answer_id: self.system.replace_urls(answers[answer_id])}
except TypeError:
log.debug(u'Unable to perform URL substitution on answers[%s]: %s',
answer_id, answers[answer_id])
new_answer = {answer_id: answers[answer_id]}
new_answers.update(new_answer)
return {'answers': new_answers}
# Figure out if we should move these to capa_problem?
def get_problem(self, _data):
"""
Return results of get_problem_html, as a simple dict for json-ing.
{ 'html': <the-html> }
Used if we want to reconfirm we have the right thing e.g. after
several AJAX calls.
"""
return {'html': self.get_problem_html(encapsulate=False)}
@staticmethod
def make_dict_of_responses(data):
"""
Make dictionary of student responses (aka "answers")
`data` is POST dictionary (webob.multidict.MultiDict).
The `data` dict has keys of the form 'x_y', which are mapped
to key 'y' in the returned dict. For example,
'input_1_2_3' would be mapped to '1_2_3' in the returned dict.
Some inputs always expect a list in the returned dict
(e.g. checkbox inputs). The convention is that
keys in the `data` dict that end with '[]' will always
have list values in the returned dict.
For example, if the `data` dict contains {'input_1[]': 'test' }
then the output dict would contain {'1': ['test'] }
(the value is a list).
Some other inputs such as ChoiceTextInput expect a dict of values in the returned
dict If the key ends with '{}' then we will assume that the value is a json
encoded dict and deserialize it.
For example, if the `data` dict contains {'input_1{}': '{"1_2_1": 1}'}
then the output dict would contain {'1': {"1_2_1": 1} }
(the value is a dictionary)
Raises an exception if:
-A key in the `data` dictionary does not contain at least one underscore
(e.g. "input" is invalid, but "input_1" is valid)
-Two keys end up with the same name in the returned dict.
(e.g. 'input_1' and 'input_1[]', which both get mapped to 'input_1'
in the returned dict)
"""
answers = dict()
# webob.multidict.MultiDict is a view of a list of tuples,
# so it will return a multi-value key once for each value.
# We only want to consider each key a single time, so we use set(data.keys())
for key in set(data.keys()):
# e.g. input_resistor_1 ==> resistor_1
_, _, name = key.partition('_') # pylint: disable=redefined-outer-name
# If key has no underscores, then partition
# will return (key, '', '')
# We detect this and raise an error
if not name:
raise ValueError(u"{key} must contain at least one underscore".format(key=key))
else:
# This allows for answers which require more than one value for
# the same form input (e.g. checkbox inputs). The convention is that
# if the name ends with '[]' (which looks like an array), then the
# answer will be an array.
# if the name ends with '{}' (Which looks like a dict),
# then the answer will be a dict
is_list_key = name.endswith('[]')
is_dict_key = name.endswith('{}')
name = name[:-2] if is_list_key or is_dict_key else name
if is_list_key:
val = data.getall(key)
elif is_dict_key:
try:
val = json.loads(data[key])
# If the submission wasn't deserializable, raise an error.
except(KeyError, ValueError):
raise ValueError(
u"Invalid submission: {val} for {key}".format(val=data[key], key=key)
)
else:
val = data[key]
# If the name already exists, then we don't want
# to override it. Raise an error instead
if name in answers:
raise ValueError(u"Key {name} already exists in answers dict".format(name=name))
else:
answers[name] = val
return answers
def publish_grade(self):
"""
Publishes the student's current grade to the system as an event
"""
score = self.lcp.get_score()
self.system.publish({
'event_name': 'grade',
'value': score['score'],
'max_value': score['total'],
})
return {'grade': score['score'], 'max_grade': score['total']}
def check_problem(self, data):
"""
Checks whether answers to a problem are correct
Returns a map of correct/incorrect answers:
{'success' : 'correct' | 'incorrect' | AJAX alert msg string,
'contents' : html}
"""
event_info = dict()
event_info['state'] = self.lcp.get_state()
event_info['problem_id'] = self.location.url()
answers = self.make_dict_of_responses(data)
event_info['answers'] = convert_files_to_filenames(answers)
# Too late. Cannot submit
if self.closed():
event_info['failure'] = 'closed'
self.system.track_function('problem_check_fail', event_info)
raise NotFoundError('Problem is closed')
# Problem submitted. Student should reset before checking again
if self.done and self.rerandomize == "always":
event_info['failure'] = 'unreset'
self.system.track_function('problem_check_fail', event_info)
raise NotFoundError('Problem must be reset before it can be checked again')
# Problem queued. Students must wait a specified waittime before they are allowed to submit
if self.lcp.is_queued():
current_time = datetime.datetime.now(UTC())
prev_submit_time = self.lcp.get_recentmost_queuetime()
waittime_between_requests = self.system.xqueue['waittime']
if (current_time - prev_submit_time).total_seconds() < waittime_between_requests:
msg = u'You must wait at least {wait} seconds between submissions'.format(
wait=waittime_between_requests)
return {'success': msg, 'html': ''} # Prompts a modal dialog in ajax callback
try:
correct_map = self.lcp.grade_answers(answers)
self.attempts = self.attempts + 1
self.lcp.done = True
self.set_state_from_lcp()
except (StudentInputError, ResponseError, LoncapaProblemError) as inst:
log.warning("StudentInputError in capa_module:problem_check",
exc_info=True)
# Save the user's state before failing
self.set_state_from_lcp()
# If the user is a staff member, include
# the full exception, including traceback,
# in the response
if self.system.user_is_staff:
msg = u"Staff debug info: {tb}".format(tb=cgi.escape(traceback.format_exc()))
# Otherwise, display just an error message,
# without a stack trace
else:
msg = u"Error: {msg}".format(msg=inst.message)
return {'success': msg}
except Exception as err:
# Save the user's state before failing
self.set_state_from_lcp()
if self.system.DEBUG:
msg = u"Error checking problem: {}".format(err.message)
msg += u'\nTraceback:\n{}'.format(traceback.format_exc())
return {'success': msg}
raise
published_grade = self.publish_grade()
# success = correct if ALL questions in this problem are correct
success = 'correct'
for answer_id in correct_map:
if not correct_map.is_correct(answer_id):
success = 'incorrect'
# NOTE: We are logging both full grading and queued-grading submissions. In the latter,
# 'success' will always be incorrect
event_info['grade'] = published_grade['grade']
event_info['max_grade'] = published_grade['max_grade']
event_info['correct_map'] = correct_map.get_dict()
event_info['success'] = success
event_info['attempts'] = self.attempts
self.system.track_function('problem_check', event_info)
if hasattr(self.system, 'psychometrics_handler'): # update PsychometricsData using callback
self.system.psychometrics_handler(self.get_state_for_lcp())
# render problem into HTML
html = self.get_problem_html(encapsulate=False)
return {'success': success,
'contents': html,
}
def rescore_problem(self):
"""
Checks whether the existing answers to a problem are correct.
This is called when the correct answer to a problem has been changed,
and the grade should be re-evaluated.
Returns a dict with one key:
{'success' : 'correct' | 'incorrect' | AJAX alert msg string }
Raises NotFoundError if called on a problem that has not yet been
answered, or NotImplementedError if it's a problem that cannot be rescored.
Returns the error messages for exceptions occurring while performing
the rescoring, rather than throwing them.
"""
event_info = {'state': self.lcp.get_state(), 'problem_id': self.location.url()}
if not self.lcp.supports_rescoring():
event_info['failure'] = 'unsupported'
self.system.track_function('problem_rescore_fail', event_info)
raise NotImplementedError("Problem's definition does not support rescoring")
if not self.done:
event_info['failure'] = 'unanswered'
self.system.track_function('problem_rescore_fail', event_info)
raise NotFoundError('Problem must be answered before it can be graded again')
# get old score, for comparison:
orig_score = self.lcp.get_score()
event_info['orig_score'] = orig_score['score']
event_info['orig_total'] = orig_score['total']
try:
correct_map = self.lcp.rescore_existing_answers()
except (StudentInputError, ResponseError, LoncapaProblemError) as inst:
log.warning("Input error in capa_module:problem_rescore", exc_info=True)
event_info['failure'] = 'input_error'
self.system.track_function('problem_rescore_fail', event_info)
return {'success': u"Error: {0}".format(inst.message)}
except Exception as err:
event_info['failure'] = 'unexpected'
self.system.track_function('problem_rescore_fail', event_info)
if self.system.DEBUG:
msg = u"Error checking problem: {0}".format(err.message)
msg += u'\nTraceback:\n' + traceback.format_exc()
return {'success': msg}
raise
# rescoring should have no effect on attempts, so don't
# need to increment here, or mark done. Just save.
self.set_state_from_lcp()
self.publish_grade()
new_score = self.lcp.get_score()
event_info['new_score'] = new_score['score']
event_info['new_total'] = new_score['total']
# success = correct if ALL questions in this problem are correct
success = 'correct'
for answer_id in correct_map:
if not correct_map.is_correct(answer_id):
success = 'incorrect'
# NOTE: We are logging both full grading and queued-grading submissions. In the latter,
# 'success' will always be incorrect
event_info['correct_map'] = correct_map.get_dict()
event_info['success'] = success
event_info['attempts'] = self.attempts
self.system.track_function('problem_rescore', event_info)
# psychometrics should be called on rescoring requests in the same way as check-problem
if hasattr(self.system, 'psychometrics_handler'): # update PsychometricsData using callback
self.system.psychometrics_handler(self.get_state_for_lcp())
return {'success': success}
def save_problem(self, data):
"""
Save the passed in answers.
Returns a dict { 'success' : bool, 'msg' : message }
The message is informative on success, and an error message on failure.
"""
event_info = dict()
event_info['state'] = self.lcp.get_state()
event_info['problem_id'] = self.location.url()
answers = self.make_dict_of_responses(data)
event_info['answers'] = answers
# Too late. Cannot submit
if self.closed() and not self.max_attempts == 0:
event_info['failure'] = 'closed'
self.system.track_function('save_problem_fail', event_info)
return {'success': False,
'msg': "Problem is closed"}
# Problem submitted. Student should reset before saving
# again.
if self.done and self.rerandomize == "always":
event_info['failure'] = 'done'
self.system.track_function('save_problem_fail', event_info)
return {'success': False,
'msg': "Problem needs to be reset prior to save"}
self.lcp.student_answers = answers
self.set_state_from_lcp()
self.system.track_function('save_problem_success', event_info)
msg = "Your answers have been saved"
if not self.max_attempts == 0:
msg += " but not graded. Hit 'Check' to grade them."
return {'success': True,
'msg': msg}
def reset_problem(self, _data):
"""
Changes problem state to unfinished -- removes student answers,
and causes problem to rerender itself.
Returns a dictionary of the form:
{'success': True/False,
'html': Problem HTML string }
If an error occurs, the dictionary will also have an
`error` key containing an error message.
"""
event_info = dict()
event_info['old_state'] = self.lcp.get_state()
event_info['problem_id'] = self.location.url()
if self.closed():
event_info['failure'] = 'closed'
self.system.track_function('reset_problem_fail', event_info)
return {'success': False,
'error': "Problem is closed"}
if not self.done:
event_info['failure'] = 'not_done'
self.system.track_function('reset_problem_fail', event_info)
return {'success': False,
'error': "Refresh the page and make an attempt before resetting."}
if self.rerandomize in ["always", "onreset"]:
# Reset random number generator seed.
self.choose_new_seed()
# Generate a new problem with either the previous seed or a new seed
self.lcp = self.new_lcp(None)
# Pull in the new problem seed
self.set_state_from_lcp()
event_info['new_state'] = self.lcp.get_state()
self.system.track_function('reset_problem', event_info)
return {'success': True,
'html': self.get_problem_html(encapsulate=False)}
class CapaDescriptor(CapaFields, RawDescriptor):
"""
......
common/lib/xmodule/xmodule/tests/test_capa_module.py
......@@ -1335,8 +1335,8 @@ class CapaModuleTest(unittest.TestCase):
module = CapaFactory.create(rerandomize=rerandomize)
assert 0 <= module.seed < 1000
@patch('xmodule.capa_module.log')
@patch('xmodule.capa_module.Progress')
@patch('xmodule.capa_base.log')
@patch('xmodule.capa_base.Progress')
def test_get_progress_error(self, mock_progress, mock_log):
"""
Check that an exception given in `Progress` produces a `log.exception` call.
......@@ -1349,7 +1349,7 @@ class CapaModuleTest(unittest.TestCase):
mock_log.exception.assert_called_once_with('Got bad progress')
mock_log.reset_mock()
@patch('xmodule.capa_module.Progress')
@patch('xmodule.capa_base.Progress')
def test_get_progress_calculate_progress_fraction(self, mock_progress):
"""
Check that score and total are calculated correctly for the progress fraction.
......
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment