knowledge.py
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# python standard library
import random
from datetime import datetime
import logging
# libraries
import networkx as nx
# this project
import questions
# setup logger for this module
logger = logging.getLogger(__name__)
# ----------------------------------------------------------------------------
# kowledge state of each student....??
# ----------------------------------------------------------------------------
class Knowledge(object):
# =======================================================================
# methods that update state
# =======================================================================
def __init__(self, depgraph, state={}, student=''):
self.depgraph = depgraph
self.state = state # {'topic_id': {'level':0.5, 'date': datetime}, ...}
self.student = student
# compute recommended sequence of topics ['a', 'b',...]
self.topic_sequence = nx.topological_sort(self.depgraph)
print(self.topic_sequence)
print(self.depgraph.edges())
# select a topic to do and initialize questions
self.start_topic()
# ------------------------------------------------------------------------
# Start a new topic. If not provided, selects the first with level < 0.8
# If all levels > 0.8, will stay in the last one forever...
# ------------------------------------------------------------------------
def start_topic(self, topic=None):
if topic is None:
for topic in self.topic_sequence:
unlocked = topic in self.state
needs_work = unlocked and self.state[topic]['level'] < 0.8
factory = self.depgraph.node[topic]['factory']
if needs_work and factory:
break
# logger.info(f'{self.student} skipped topic "{topic}"')
else:
factory = self.depgraph.node[topic]['factory']
# FIXME if factory is empty???
self.current_topic = topic
logger.info(f'User "{self.student}" topic set to "{topic}"')
# generate question instances for current topic
questionlist = self.depgraph.node[topic]['questions']
factory = self.depgraph.node[topic]['factory']
self.questions = [factory[qref].generate() for qref in questionlist]
self.current_question = self.questions.pop(0)
self.current_question['start_time'] = datetime.now()
self.finished_questions = []
# ------------------------------------------------------------------------
# returns the current question with correction, time and comments updated
# ------------------------------------------------------------------------
def check_answer(self, answer):
q = self.current_question
q['finish_time'] = datetime.now()
grade = q.correct(answer)
logger.debug(f'User {self.student}: grade = {grade}')
# new question if answer is correct
if grade > 0.999:
self.finished_questions.append(q)
try:
self.current_question = self.questions.pop(0) # FIXME empty?
except IndexError:
self.current_question = None
self.state[self.current_topic] = {
'level': 1.0,
'date': datetime.now()
}
else:
self.current_question['start_time'] = datetime.now()
else:
# FIXME debug this
factory = self.depgraph.node[self.current_topic]['factory']
self.questions.append(factory[q['ref']].generate())
print([q['ref'] for q in self.questions])
return q
# ========================================================================
# pure functions of the state (no side effects)
# ========================================================================
# ------------------------------------------------------------------------
def get_current_question(self):
return self.current_question
# ------------------------------------------------------------------------
def get_current_topic(self):
return self.current_topic
# ------------------------------------------------------------------------
def get_knowledge_state(self): # [('topic', 0.9), ...]
ts = []
for t in self.topic_sequence:
if t in self.state:
ts.append((t, self.state[t]['level']))
else:
ts.append((t, 0.0))
return ts
# ------------------------------------------------------------------------
def get_topic_progress(self):
return len(self.finished_questions) / (1 + len(self.finished_questions) + len(self.questions))