# 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__)

# ----------------------------------------------------------------------------
# contains the kowledge state of each student.
class Knowledge(object):
    def __init__(self, depgraph, state={}):
        self.depgraph = depgraph
        self.state = state   # {node: level, node: level, ...}

        self.topic = self.topic_generator()
        self.current_topic = next(self.topic)

        self.questions = self.generate_questions_for_topic(self.current_topic)
        self.current_question = None
        self.finished_questions = []

    # ------------------------------------------------------------------------
    def topic_generator(self):
        self.topic_sequence = nx.topological_sort(self.depgraph) # FIXME for now...
        for t in self.topic_sequence:
            if self.state.get(t, 0.0) > 0.999:
                continue
            self.questions = self.generate_questions_for_topic(t)
            logger.info(f'Generated {len(self.questions)} questions for topic "{t}"')
            yield t

    # ------------------------------------------------------------------------
    def generate_questions_for_topic(self, topic):
        factory = self.depgraph.node[topic]['factory']
        return [q.generate() for q in factory]

    # ------------------------------------------------------------------------
    def get_current_question(self):
        return self.current_question

    # ------------------------------------------------------------------------
    def get_current_topic(self):
        return self.current_topic

    # ------------------------------------------------------------------------
    def get_knowledge_state(self):
        return [(t, self.state.get(t, 0.0)) for t in self.topic_sequence]

    # ------------------------------------------------------------------------
    def get_topic_progress(self):
        return len(self.finished_questions) / (len(self.finished_questions) + len(self.questions))

    # --- generates a new question given the current state -------------------
    def new_question(self):
        logger.debug('Knowledge.new_question()')

        if self.current_question is None or self.current_question.get('grade', 0.0) > 0.9999:

            while not self.questions:
                # finished topic!
                self.state[self.current_topic] = 1.0
                self.finished_questions = []
                try:
                    self.current_topic = next(self.topic)
                except StopIteration:
                    self.topic = self.topic_generator()
                    self.current_topic = next(self.topic)
                    self.questions = self.generate_questions_for_topic(self.current_topic)

            self.current_question = self.questions.pop(0)
            self.current_question['start_time'] = datetime.now()
            self.finished_questions.append(self.current_question) # FIXME not yet finished...

            return self.current_question

    # --- checks answer ------------------------------------------------------
    #     returns current question with correction, time and comments updated
    def check_answer(self, answer):
        logger.debug(f'Knowledge.check_answer({answer})')
        question = self.current_question
        if question is not None:
            question['finish_time'] = datetime.now()
            question.correct(answer)

        return question