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second pass in capa cleanup:

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- each response can now render its own xhtml
  - cleaned up LoncapaProblem.extract_html
This commit is contained in:
ichuang
2012-06-09 21:29:11 -04:00
committed by Matthew Mongeau
parent ff9f8c9779
commit a3d24d41f5
3 changed files with 89 additions and 141 deletions
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119
common/lib/capa/capa_problem.py
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@@ -23,7 +23,6 @@ import scipy
import struct
from lxml import etree
from lxml.etree import Element
from xml.sax.saxutils import unescape
from util import contextualize_text
@@ -36,6 +35,7 @@ import eia
log = logging.getLogger(__name__)
# dict of tagname, Response Class -- this should come from auto-registering
response_types = {'numericalresponse': NumericalResponse,
'formularesponse': FormulaResponse,
'customresponse': CustomResponse,
@@ -47,20 +47,13 @@ response_types = {'numericalresponse': NumericalResponse,
'optionresponse': OptionResponse,
'symbolicresponse': SymbolicResponse,
}
entry_types = ['textline', 'schematic', 'choicegroup', 'textbox', 'imageinput', 'optioninput']
solution_types = ['solution'] # extra things displayed after "show answers" is pressed
response_properties = ["responseparam", "answer"] # these get captured as student responses
# How to convert from original XML to HTML
# We should do this with xlst later
entry_types = ['textline', 'schematic', 'choicegroup', 'textbox', 'imageinput', 'optioninput']
solution_types = ['solution'] # extra things displayed after "show answers" is pressed
response_properties = ["responseparam", "answer"] # these get captured as student responses
# special problem tags which should be turned into innocuous HTML
html_transforms = {'problem': {'tag': 'div'},
"numericalresponse": {'tag': 'span'},
"customresponse": {'tag': 'span'},
"externalresponse": {'tag': 'span'},
"schematicresponse": {'tag': 'span'},
"formularesponse": {'tag': 'span'},
"symbolicresponse": {'tag': 'span'},
"multiplechoiceresponse": {'tag': 'span'},
"text": {'tag': 'span'},
"math": {'tag': 'span'},
}
@@ -74,18 +67,6 @@ global_context = {'random': random,
# These should be removed from HTML output, including all subelements
html_problem_semantics = ["responseparam", "answer", "script"]
# These should be removed from HTML output, but keeping subelements
html_skip = ["numericalresponse", "customresponse", "schematicresponse", "formularesponse", "text", "externalresponse", 'symbolicresponse']
# removed in MC
## These should be transformed
#html_special_response = {"textline":inputtypes.textline.render,
# "schematic":inputtypes.schematic.render,
# "textbox":inputtypes.textbox.render,
# "formulainput":inputtypes.jstextline.render,
# "solution":inputtypes.solution.render,
# }
class LoncapaProblem(object):
'''
@@ -142,7 +123,8 @@ class LoncapaProblem(object):
self.context = self.extract_context(self.tree, seed=self.seed)
# pre-parse the XML tree: modifies it to add ID's and perform some in-place transformations
# this also creates the list (self.responders) of Response instances for each question in the problem
# this also creates the dict (self.responders) of Response instances for each question in the problem.
# the dict has keys = xml subtree of Response, values = Response instance
self.preprocess_problem(self.tree, correct_map=self.correct_map, answer_map=self.student_answers)
def __unicode__(self):
@@ -166,7 +148,7 @@ class LoncapaProblem(object):
used to give complex problems (eg programming questions) multiple points.
'''
maxscore = 0
for responder in self.responders:
for responder in self.responders.values():
if hasattr(responder,'get_max_score'):
try:
maxscore += responder.get_max_score()
@@ -182,6 +164,10 @@ class LoncapaProblem(object):
return maxscore
def get_score(self):
'''
Compute score for this problem. The score is the number of points awarded.
Returns an integer, from 0 to get_max_score().
'''
correct = 0
for key in self.correct_map:
if self.correct_map[key] == u'correct':
@@ -206,7 +192,7 @@ class LoncapaProblem(object):
self.student_answers = answers
self.correct_map = dict()
log.info('%s: in grade_answers, answers=%s' % (self,answers))
for responder in self.responders:
for responder in self.responders.values():
results = responder.get_score(answers) # call the responsetype instance to do the actual grading
self.correct_map.update(results)
return self.correct_map
@@ -218,24 +204,14 @@ class LoncapaProblem(object):
(see capa_module)
"""
answer_map = dict()
for responder in self.responders:
for responder in self.responders.values():
results = responder.get_answers()
answer_map.update(results) # dict of (id,correct_answer)
# This should be handled in each responsetype, not here.
# example for the following: <textline size="5" correct_answer="saturated" />
for responder in self.responders:
for entry in responder.inputfields:
answer = entry.get('correct_answer') # correct answer, when specified elsewhere, eg in a textline
if answer:
answer_map[entry.get('id')] = contextualize_text(answer, self.context)
# include solutions from <solution>...</solution> stanzas
# Tentative merge; we should figure out how we want to handle hints and solutions
for entry in self.tree.xpath("//" + "|//".join(solution_types)):
answer = etree.tostring(entry)
if answer:
answer_map[entry.get('id')] = answer
if answer: answer_map[entry.get('id')] = answer
return answer_map
@@ -244,7 +220,7 @@ class LoncapaProblem(object):
the dicts returned by grade_answers and get_question_answers. (Though
get_question_answers may only return a subset of these."""
answer_ids = []
for responder in self.responders:
for responder in self.responders.values():
answer_ids.append(responder.get_answers().keys())
return answer_ids
@@ -252,7 +228,7 @@ class LoncapaProblem(object):
'''
Main method called externally to get the HTML to be rendered for this capa Problem.
'''
return contextualize_text(etree.tostring(self.extract_html(self.tree)[0]), self.context)
return contextualize_text(etree.tostring(self.extract_html(self.tree)), self.context)
# ======= Private ========
def extract_context(self, tree, seed=struct.unpack('i', os.urandom(4))[0]): # private
@@ -264,12 +240,11 @@ class LoncapaProblem(object):
Problem XML goes to Python execution context. Runs everything in script tags
'''
random.seed(self.seed)
context = {'global_context': global_context} # save global context in here also
context.update(global_context) # initialize context to have stuff in global_context
context['__builtins__'] = globals()['__builtins__'] # put globals there also
context['the_lcp'] = self # pass instance of LoncapaProblem in
context = {'global_context': global_context} # save global context in here also
context.update(global_context) # initialize context to have stuff in global_context
context['__builtins__'] = globals()['__builtins__'] # put globals there also
context['the_lcp'] = self # pass instance of LoncapaProblem in
#for script in tree.xpath('/problem/script'):
for script in tree.findall('.//script'):
stype = script.get('type')
if stype:
@@ -288,16 +263,20 @@ class LoncapaProblem(object):
return context
def extract_html(self, problemtree): # private
''' Helper function for get_html. Recursively converts XML tree to HTML
'''
Main (private) function which converts Problem XML tree to HTML.
Calls itself recursively.
Returns Element tree of XHTML representation of problemtree.
Calls render_html of Response instances to render responses into XHTML.
Used by get_html.
'''
if problemtree.tag in html_problem_semantics:
return
problemid = problemtree.get('id') # my ID
# used to be
# if problemtree.tag in html_special_response:
if problemtree.tag in inputtypes.get_input_xml_tags():
# status is currently the answer for the problem ID for the input element,
# but it will turn into a dict containing both the answer and any associated message
@@ -334,31 +313,25 @@ class LoncapaProblem(object):
use='capa_input')
return render_object.get_html() # function(problemtree, value, status, msg) # render the special response (textline, schematic,...)
tree = Element(problemtree.tag)
if problemtree in self.responders: # let each Response render itself
return self.responders[problemtree].render_html(self.extract_html)
tree = etree.Element(problemtree.tag)
for item in problemtree:
subitems = self.extract_html(item)
if subitems is not None:
for subitem in subitems:
tree.append(subitem)
for (key, value) in problemtree.items():
tree.set(key, value)
item_xhtml = self.extract_html(item) # nothing special: recurse
if item_xhtml is not None:
tree.append(item_xhtml)
if tree.tag in html_transforms:
tree.tag = html_transforms[problemtree.tag]['tag']
else:
for (key, value) in problemtree.items(): # copy attributes over if not innocufying
tree.set(key, value)
tree.text = problemtree.text
tree.tail = problemtree.tail
if problemtree.tag in html_transforms:
tree.tag = html_transforms[problemtree.tag]['tag']
# Reset attributes. Otherwise, we get metadata in HTML
# (e.g. answers)
# TODO: We should remove and not zero them.
# I'm not sure how to do that quickly with lxml
for k in tree.keys():
tree.set(k, "")
# TODO: Fix. This loses Element().tail
#if problemtree.tag in html_skip:
# return tree
return [tree]
return tree
def preprocess_problem(self, tree, correct_map=dict(), answer_map=dict()): # private
'''
@@ -370,7 +343,7 @@ class LoncapaProblem(object):
Also create capa Response instances for each responsetype and save as self.responders
'''
response_id = 1
self.responders = []
self.responders = {}
for response in tree.xpath('//' + "|//".join(response_types)):
response_id_str = self.problem_id + "_" + str(response_id)
response.attrib['id'] = response_id_str # create and save ID for this response
@@ -389,7 +362,7 @@ class LoncapaProblem(object):
answer_id = answer_id + 1
responder = response_types[response.tag](response, inputfields, self.context, self.system) # instantiate capa Response
self.responders.append(responder) # save in list in self
self.responders[response] = responder # save in list in self
# <solution>...</solution> may not be associated with any specific response; give IDs for those separately
# TODO: We should make the namespaces consistent and unique (e.g. %s_problem_%i).