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EnglishPal/app/Article.py

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Python
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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
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)
2022-01-27 17:01:03 +08:00
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)