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EnglishPal/app/Article.py

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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
from model.article import get_number_of_articles, get_article, get_article_by_id
path_prefix = '/var/www/wordfreq/wordfreq/'
path_prefix = './' # comment this line in deployment
def total_number_of_essays():
get_number_of_articles()
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):
if existing_articles is None:
existing_articles = {
"index" : 0, # 为 article_ids 的索引
"article_ids": [] # 之前显示文章的id列表越后越新
}
if existing_articles["index"] > len(existing_articles["article_ids"])-1:
result = list(get_article()) # 转为一个list
else:
result = [get_article_by_id(existing_articles["article_ids"][existing_articles["index"]])]
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 = None
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
if existing_articles["index"] > len(existing_articles["article_ids"])-1: # 下一篇
flag_get_article = False
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["article_ids"] 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["article_ids"].append(d.article_id) # 列表添加新的文章id下面进行
flag_get_article = True
break
if not flag_get_article:
existing_articles["index"] -= 1
else: # 上一篇
d = random.choice(result)
text_level = text_difficulty_level(d.text, d3)
today_article = None
if d:
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)
}
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)