def check_weight(weight):
if weight == -1 or (weight != 0 and weight != 100):
ut.sprint(
"WARNING: Invalid answer weight for multiple choice question: "
+ str(weight))
return False
return True
def parse_multiple_choice_question(q_name, index):
"""
Parse multiple choice question answers.
Parameters
----------
q_name: str
name of the question
index: int
index of the question in cell array
Returns
-------
[obj]
parsed answers
obj
extra attributes to add to the question
"""
aindex = index + 1
length_check = len(cells) <= aindex
cell_type_check = cells[aindex]["metadata"]["ctype"] != "answer"
if length_check or cell_type_check:
raise Exception(
"WARNING: multiple choice question has no answer cell.")
answers, extra = parse_multiple_answers_question(q_name, index)
def check_weight(weight):
if weight == -1 or (weight != 0 and weight != 100):
ut.sprint(
"WARNING: Invalid answer weight for multiple choice question: "
+ str(weight))
return False
return True
found_true = False
final_answers = []
for answer in answers:
weight = answer["answer_weight"]
if not check_weight(weight):
ut.sprint("WARNING: invalid weight in answer list for question " +
q_name)
continue
if weight > 0:
if found_true:
ut.sprint("WARNING: multiple correct answers in question " +
q_name +
", consider changing to multiple answers questions")
continue
else:
found_true = True
final_answers += [answer]
return final_answers, extra
def parse_question(index):
"""
Parse Question.
Parameters
----------
index: int
index of the question in cell array
Returns
-------
obj
parsed question
"""
question = {}
for key, val, in cells[index]["metadata"].items():
if key == "ctype":
continue
elif key == "quesnum":
question["question_name"] = str(val)
else:
question[key] = val
if "question_type" not in question:
ut.sprint(
"WARNING: question does not have question-type, not including question"
)
return None
if "points_possible" not in question:
question["points_possible"] = 1
q_type = question["question_type"]
if q_type not in supp_q_types:
ut.sprint("WARNING: unsupported question type of " + q_type)
return None
if "warning" in supp_q_types[q_type]:
ut.sprint("WARNING: " + supp_q_types[q_type]["warning"])
try:
question["answers"], extra = supp_q_types[q_type]["parser"](
question["question_name"], index)
except Exception as e:
ut.sprint(str(e))
return None
question_text, image_paths = parse_md_text(cells[index]["source"])
question["question_text"] = question_text
extra["image_paths"] = image_paths
question = {**question, **extra}
return question
def parse_md_text(text):
"""
Parse markdown into HTML, also check for latex.
Parameters
----------
text: str
text to parse
Returns
-------
str
parsed text with Canvas latex
[str]
list of paths to images linked from this text
"""
text = md.convert(text)
html = BeautifulSoup(text, 'html.parser')
image_paths = []
for image in html.find_all("img"):
image_name = image.get("src")
image_path = os.path.join(file_dir, image.get("src"))
image_path = os.path.abspath(image_path)
if os.path.islink(image_path): continue
if not os.path.exists(image_path):
ut.sprint(
"WARNING: image was not a link and does not exist on this computer: "
+ image_path)
image_paths += [{"name": image_name, "path": image_path}]
begin = 0
while text.find("$$", begin) != -1:
start = text.find("$$", begin)
if start - 1 >= 0 and text[start - 1] == "\\":
begin += 2
continue
end = text.find("$$", start + 2)
if end == -1:
break
latex_str = to_canvas(text[start + 2:end])
text = text.replace(text[start:end + 2], latex_str)
begin += len(latex_str)
begin = 0
while text.find("$", begin) != -1:
start = text.find("$", begin)
if start - 1 >= 0 and text[start - 1] == "\\":
begin += 1
continue
end = text.find("$", start + 1)
if end == -1:
break
latex_str = to_canvas(text[start + 1:end], True)
text = text.replace(text[start:end + 1], latex_str)
begin += len(latex_str)
return text.replace("\\", ""), image_paths
def parse_numerical_question(q_name, index):
"""
Parse numerical question answers.
Parameters
----------
q_name: str
name of the question
index: int
index of the question in cell array
Returns
-------
[obj]
parsed answers
obj
extra attributes to add to the question
"""
aindex = index + 1
length_check = len(cells) <= aindex
cell_type_check = cells[aindex]["metadata"]["ctype"] != "answer"
if length_check or cell_type_check:
raise Exception("WARNING: numerical question has no answer cell.")
answers = []
for line in cells[index + 1]["source"].split("\n"):
if line.startswith("*"):
v1 = 0
v2 = 0
answer = {"answer_text": "", "answer_weight": 100}
text = line[1:].strip(" ")
if "," not in text:
if ":" in text:
ut.sprint(
"WARNING: numerical answer has one value but has answer type, "
+ "only one of these is allowed")
v1 = float(text)
answer["numerical_answer_type"] = "exact_answer"
elif ":" not in text:
ind = text.index(",")
v1 = float(text[:ind].strip(" "))
v2 = float(text[ind + 1:].strip(" "))
answer["numerical_answer_type"] = "exact_answer"
else:
ind = text.index(":")
vals = text[:ind]
answer["numerical_answer_type"] = text[ind +
1:].strip(" ").replace(
"-", "_")
ind = vals.index(",")
v1 = float(vals[:ind].strip(" "))
v2 = float(vals[ind + 1:].strip(" "))
if answer["numerical_answer_type"] == "exact_answer":
answer["answer_exact"] = v1
answer["answer_error_margin"] = v2
elif answer["numerical_answer_type"] == "range_answer":
answer["answer_range_start"] = v1
answer["answer_range_end"] = v2
elif answer["numerical_answer_type"] == "precision_answer":
answer["answer_approximate"] = v1
answer["answer_precision"] = v2
else:
ut.sprint("WARNING: numerical answer type not supported: " +
answer["numerical_answer_type"])
continue
answers += [answer]
return answers, {}
def md2canvas(url, notebook_file, token, token_file, course_id, save_settings,
quiz_id, dump, no_upload, hush, reset):
"""
Parse file into quiz and upload to Canvas.
"""
# Set printing settings
ut.hush = hush
# Check argument validity
if not notebook_file or not path.exists(notebook_file):
print("Invalid notebook file.")
return
if not notebook_file.endswith(".md") and \
not notebook_file.endswith(".ipynb"):
print("Notebook file must be Markdown or Jupyter Notebook.")
return
if token and token_file:
print("Only one of token or token file can be used.")
return
if token_file and not path.exists(token_file):
print("Invalid token file.")
return
if no_upload and not dump:
print(
"WARNING: not dumping to file or uploading, nothing will happen.")
# Get/Set configuration
if token_file:
with open(token_file, mode="r") as tf:
token = tf.read()
config_file = path.join(path.dirname(path.realpath(__file__)),
"config.yaml")
if not path.exists(config_file):
with open(config_file, "w") as f:
f.close()
reset = True
with open(config_file, "r") as f:
config = yaml.load(f, Loader=yaml.FullLoader)
if not config:
config = {}
if save_settings or reset:
if url:
config["url"] = url
elif reset:
config["url"] = "https://canvas.ubc.ca"
if token:
config["token"] = token
elif reset:
config["token"] = "11224~PLAy00HrlbYVp7a6DV0a6X7pGQ13uLukhxF4ouz3JUeDJ" + \
"R9dzY0hazkcDOlUuY0t"
if course_id:
config["course_id"] = course_id
elif reset:
config["course_id"] = "51824"
with open(config_file, "w") as wf:
yaml.dump(config, wf)
if not no_upload:
if not url:
url = config["url"]
if not token:
token = config["token"]
if not course_id:
course_id = str(config["course_id"])
ut.sprint("Parsing the quiz at " + notebook_file)
quiz = m2j.parse_quiz(notebook_file)
if dump:
with open(dump, "w") as f:
json.dump(f, quiz)
if not no_upload:
ut.sprint("Uploading quiz to Canvas with following settings:")
ut.sprint(" URL = " + url)
ut.sprint(" Token = " + token[:4] + (len(token) - 8) * "*" +
token[-4:])
ut.sprint(" Course ID = " + course_id)
if quiz_id:
ut.sprint(" Quiz ID = " + quiz_id)
j2c.update_quiz(cv, quiz, url, token, course_id, quiz_id)
else:
j2c.upload_quiz(cv, quiz, url, token, course_id)