def load_verb_dict(filename):
""" Loads a verb dictionary from a json file """
try:
with open(filename, 'r') as f:
verb_dict = json.load(f)
except FileNotFoundError:
print(file_not_found_msg(filename))
else:
return verb_dict
def load_taxonomy(filename):
""" Loads a taxonomy object from a pickle file """
try:
with open(filename, 'rb') as f:
taxonomy = pickle.load(f)
except FileNotFoundError:
print(file_not_found_msg(filename))
else:
return taxonomy
def load_curriculum(filename):
""" Loads a curriculum object from a pickle file """
try:
with open(filename, 'rb') as f:
curriculum = pickle.load(f)
except FileNotFoundError:
print(file_not_found_msg(filename))
else:
return curriculum
def set_filename_LOs(self, filename):
""" Sets the name of the file containing the learning outcomes """
if filename == "": return
try:
with open(filename, 'r') as f:
pass
except FileNotFoundError:
print(file_not_found_msg(filename))
else:
self.filename_LOs_txt = filename
return self.filename_LOs_txt
def set_num_strands_from_file(self, filename=""):
""" Sets the number of strands from the number of blank lines in a file """
if filename == "": # Default to self attribute if no filename provided
filename = self.filename_LOs_txt
tmp, self.num_of_strands = self.num_of_strands, 0
try:
with open (filename, 'r') as f:
self.num_of_strands = 1 + sum(1 if line == '\n' else 0 for line in f)
except FileNotFoundError:
print (file_not_found_msg(filename))
self.num_of_strands = tmp
def user_input_filename_LOs(self):
""" Asks the user for the name of the input text file containing the learning outcomes """
while True:
filename = input("Enter the file name of the learning outcome text file: ")
try:
with open(filename, 'r') as f:
pass
except FileNotFoundError:
print (file_not_found_msg(filename))
else:
self.filename_LOs_txt = filename
break
def set_num_verb_cats_from_file(self, filename=""):
""" Sets the number of verb categories from the number of lines in a file """
if filename == "": # Default to self attribute if no filename provided
filename = self.filename_verbs_txt
tmp, self.num_of_verb_cats = self.num_of_verb_cats, 0
try:
with open(filename, 'r') as f:
self.num_of_verb_cats = sum(1 for line in f)
except FileNotFoundError:
print(file_not_found_msg(filename))
self.num_of_verb_cats = tmp
else:
return self.num_of_verb_cats
def user_input_filename_verbs(self):
""" Asks user for the name of the input text file containing the verbs"""
while True:
filename = input(
"Enter the file name of your verb list text file: ")
try:
with open(filename, 'r') as f:
pass
except FileNotFoundError:
print(file_not_found_msg(filename))
else:
self.filename_verbs_txt = filename # Also returned below if needed
break
return filename
def load_LOs_from_file(self, filename=""):
""" Creates a list of lists of learning outcome objects and loads their text from a file. Each inner list is a list of learning outcome objects pertaining to a perticular strand """
if filename == "":
filename = self.filename_LOs_txt
strand_idx = 0
try:
with open(filename, 'r') as f:
for line in f:
if line == '\n': # strands are blank line separated
strand_idx += 1
self.LOs.append([]) # Create new list for the next strand
else:
LO = LearningOutcome(line.lower().strip())
self.LOs[strand_idx].append(LO)
except FileNotFoundError:
print(file_not_found_msg(filename))