from WordFreq import WordFreq from wordfreqCMD import youdao_link, sort_in_descending_order from UseSqlite import InsertQuery, RecordQuery import pickle_idea, pickle_idea2 import os import random, glob import hashlib from datetime import datetime from flask import Flask, request, redirect, render_template, url_for, session, abort, flash, get_flashed_messages from difficulty import get_difficulty_level, text_difficulty_level, user_difficulty_level path_prefix = '/var/www/wordfreq/wordfreq/' path_prefix = './' # comment this line in deployment def total_number_of_essays(): rq = RecordQuery(path_prefix + 'static/wordfreqapp.db') rq.instructions("SELECT * FROM article") rq.do() result = rq.get_results() return len(result) def get_article_title(s): return s.split('\n')[0] def get_article_body(s): lst = s.split('\n') lst.pop(0) # remove the first line return '\n'.join(lst) def get_today_article(user_word_list, existing_articles): rq = RecordQuery(path_prefix + 'static/wordfreqapp.db') if existing_articles is None: existing_articles = [0, []] # existing_articles[0]:为existing_articles[1]的索引;existing_articles[1]:之前显示文章的id列表,越后越新 if existing_articles[0] > len(existing_articles[1])-1: rq.instructions("SELECT * FROM article") else: rq.instructions('SELECT * FROM article WHERE article_id=%d' % (existing_articles[1][existing_articles[0]])) rq.do() result = rq.get_results() random.shuffle(result) # Choose article according to reader's level d1 = load_freq_history(path_prefix + 'static/frequency/frequency.p') d2 = load_freq_history(path_prefix + 'static/words_and_tests.p') d3 = get_difficulty_level(d1, d2) d = {} d_user = load_freq_history(user_word_list) user_level = user_difficulty_level(d_user, d3) # more consideration as user's behaviour is dynamic. Time factor should be considered. text_level = 0 flag = False if existing_articles[0] > len(existing_articles[1])-1: # 下一篇 for reading in result: text_level = text_difficulty_level(reading['text'], d3) factor = random.gauss(0.8, 0.1) # a number drawn from Gaussian distribution with a mean of 0.8 and a stand deviation of 1 if reading['article_id'] not in existing_articles[1] and within_range(text_level, user_level, (8.0 - user_level) * factor): # 新的文章之前没有出现过且符合一定范围的水平 d = reading existing_articles[1].append(d['article_id']) # 列表添加新的文章id;下面进行 flag = True break else: # 上一篇 d = random.choice(result) text_level = text_difficulty_level(d['text'], d3) flag = True today_article = None if flag: today_article = { "user_level": '%4.2f' % user_level, "text_level": '%4.2f' % text_level, "date": d['date'], "article_title": get_article_title(d['text']), "article_body": get_article_body(d['text']), "source": d["source"], "question": get_question_part(d['question']), "answer": get_answer_part(d['question']) } else: existing_articles[0] -= 1 return existing_articles, today_article def load_freq_history(path): d = {} if os.path.exists(path): d = pickle_idea.load_record(path) return d def within_range(x, y, r): return x > y and abs(x - y) <= r def get_question_part(s): s = s.strip() result = [] flag = 0 for line in s.split('\n'): line = line.strip() if line == 'QUESTION': result.append(line) flag = 1 elif line == 'ANSWER': flag = 0 elif flag == 1: result.append(line) return '\n'.join(result) def get_answer_part(s): s = s.strip() result = [] flag = 0 for line in s.split('\n'): line = line.strip() if line == 'ANSWER': flag = 1 elif flag == 1: result.append(line) return '\n'.join(result)