添加了阅读完所有文章的提示
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@ -39,9 +39,9 @@ def get_today_article(user_word_list, had_read_articles):
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"index" : 0, # 为 article_ids 的索引
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"index" : 0, # 为 article_ids 的索引
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"article_ids": [] # 之前显示文章的id列表,越后越新
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"article_ids": [] # 之前显示文章的id列表,越后越新
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}
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}
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if had_read_articles["index"] > len(had_read_articles["article_ids"])-1:
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if had_read_articles["index"] > len(had_read_articles["article_ids"])-1: # 生成新的文章,因此查找所有的文章
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rq.instructions("SELECT * FROM article")
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rq.instructions("SELECT * FROM article")
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else:
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else: # 生成阅读过的文章,因此查询指定 article_id 的文章
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rq.instructions('SELECT * FROM article WHERE article_id=%d' % (had_read_articles["article_ids"][had_read_articles["index"]]))
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rq.instructions('SELECT * FROM article WHERE article_id=%d' % (had_read_articles["article_ids"][had_read_articles["index"]]))
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rq.do()
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rq.do()
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result = rq.get_results()
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result = rq.get_results()
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@ -53,23 +53,33 @@ def get_today_article(user_word_list, had_read_articles):
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d3 = get_difficulty_level(d1, d2)
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d3 = get_difficulty_level(d1, d2)
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d = None
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d = None
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result_of_generate_article = "not found"
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d_user = load_freq_history(user_word_list)
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d_user = load_freq_history(user_word_list)
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user_level = user_difficulty_level(d_user, d3) # more consideration as user's behaviour is dynamic. Time factor should be considered.
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user_level = user_difficulty_level(d_user, d3) # more consideration as user's behaviour is dynamic. Time factor should be considered.
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text_level = 0
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text_level = 0
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if had_read_articles["index"] > len(had_read_articles["article_ids"])-1: # 下一篇
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if had_read_articles["index"] > len(had_read_articles["article_ids"])-1: # 生成新的文章
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flag_get_article = False
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amount_of_had_read_articles = len(had_read_articles["article_ids"])
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for reading in result:
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amount_of_existing_articles = result.__len__()
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text_level = text_difficulty_level(reading['text'], d3)
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if amount_of_had_read_articles == amount_of_existing_articles: # 如果当前阅读过的文章的数量 == 存在的文章的数量,即所有的书本都阅读过了
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factor = random.gauss(0.8,
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result_of_generate_article = "had read all articles"
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0.1) # a number drawn from Gaussian distribution with a mean of 0.8 and a stand deviation of 1
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else:
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if reading['article_id'] not in had_read_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
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test_count = 0
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d = reading
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for k in range(3): # 最多尝试3次
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had_read_articles["article_ids"].append(d['article_id']) # 列表添加新的文章id;下面进行
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test_count += 1
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flag_get_article = True
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for reading in result:
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break
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text_level = text_difficulty_level(reading['text'], d3)
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if not flag_get_article:
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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
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if reading['article_id'] not in had_read_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
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d = reading
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had_read_articles["article_ids"].append(d['article_id']) # 列表添加新的文章id;下面进行
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result_of_generate_article = "found"
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break
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if result_of_generate_article == "found": # 用于成功找到文章后及时退出外层循环
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break
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print(test_count)
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if result_of_generate_article != "found": # 阅读完所有文章,或者循环3次没有找到适合的文章,则对 index+=1 进行回滚
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had_read_articles["index"] -= 1
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had_read_articles["index"] -= 1
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else: # 上一篇
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else: # 生成已经阅读过的文章
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d = random.choice(result)
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d = random.choice(result)
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text_level = text_difficulty_level(d['text'], d3)
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text_level = text_difficulty_level(d['text'], d3)
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@ -86,7 +96,7 @@ def get_today_article(user_word_list, had_read_articles):
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"answer": get_answer_part(d['question'])
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"answer": get_answer_part(d['question'])
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}
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}
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return had_read_articles, today_article
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return had_read_articles, today_article, result_of_generate_article
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def load_freq_history(path):
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def load_freq_history(path):
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@ -71,10 +71,14 @@
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<button onclick="toggle_visibility('answer');">ANSWER</button>
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<button onclick="toggle_visibility('answer');">ANSWER</button>
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<div id="answer" style="display:none;">{{ today_article['answer'] }}</div><br/>
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<div id="answer" style="display:none;">{{ today_article['answer'] }}</div><br/>
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</div>
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</div>
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{% else %}
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{% elif result_of_generate_article == "not found" %}
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<div class="alert alert-success" role="alert">
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<div class="alert alert-success" role="alert">
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<p class="text-muted"><span class="badge bg-success">Notes:</span><br>No article is currently available for you. You can try again a few times or mark new words in the passage to improve your level.</p>
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<p class="text-muted"><span class="badge bg-success">Notes:</span><br>No article is currently available for you. You can try again a few times or mark new words in the passage to improve your level.</p>
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</div>
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</div>
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{% elif result_of_generate_article == "had read all articles" %}
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<div class="alert alert-success" role="alert">
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<p class="text-muted"><span class="badge bg-success">Notes:</span><br>You've read all the articles.</p>
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</div>
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{% endif %}
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{% endif %}
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</div>
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</div>
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@ -135,7 +135,7 @@ def userpage(username):
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words = ''
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words = ''
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for x in lst3:
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for x in lst3:
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words += x[0] + ' '
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words += x[0] + ' '
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had_read_articles, today_article = get_today_article(user_freq_record, session.get('had_read_articles'))
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had_read_articles, today_article, result_of_generate_article = get_today_article(user_freq_record, session.get('had_read_articles'))
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session['had_read_articles'] = had_read_articles
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session['had_read_articles'] = had_read_articles
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if today_article is None:
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if today_article is None:
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session["found_article"] = False
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session["found_article"] = False
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@ -147,6 +147,7 @@ def userpage(username):
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session=session,
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session=session,
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# flashed_messages=get_flashed_messages(), 仅有删除单词的时候使用到flash,而删除单词是异步执行,这里的信息提示是同步执行,所以就没有存在的必要了
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# flashed_messages=get_flashed_messages(), 仅有删除单词的时候使用到flash,而删除单词是异步执行,这里的信息提示是同步执行,所以就没有存在的必要了
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today_article=today_article,
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today_article=today_article,
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result_of_generate_article=result_of_generate_article,
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d_len=len(d),
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d_len=len(d),
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lst3=lst3,
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lst3=lst3,
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yml=Yaml.yml,
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yml=Yaml.yml,
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