更新测试错误article中的提示信息并回退vocabulary版本
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@ -116,7 +116,7 @@ def get_today_article(user_word_list, visited_articles):
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"article_body": "This is a default article for testing purposes.",
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"source": "Default Source",
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"question": "What is this article about?",
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"answer": "It's a default article for testing.",
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"answer": "It's a default article for testing.Please contact the administrator",
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"ratio": 0.0
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}
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else:
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@ -1,61 +1,171 @@
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import os
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import pickle
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import random
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import re
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from collections import defaultdict
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from datetime import datetime, timedelta
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# 模拟的测试数据，实际使用时应从文件加载
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_TEST_MOCK = {
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'simple': 2, 'apple': 1, 'happy': 2, 'open': 3, 'like': 2, 'work': 2, 'make': 2, 'money': 2,
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'source': 3, 'software': 3, 'successful': 4, 'project': 3, 'develop': 3, 'process': 3,
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'available': 4, 'organizations': 4,
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'extinct': 6, 'modification': 7, 'apparently': 7, 'abruptly': 7, 'rentable': 7, 'predictable': 6,
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'pasture': 7, 'putrid': 7, 'frivolous': 8, 'sessile': 8, 'dearth': 7, 'presumptuous': 7,
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'fringe': 8, 'economics': 5, 'summarize': 5, 'stare': 5, 'eagerly': 5, 'completely': 4, 'maintained': 5,
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'geological': 6, 'embryological': 7, 'coadaptation': 8, 'exterminated': 7, 'contingencies': 7,
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'intercrossing': 6, 'coleopterous': 8, 'marin': 5, 'organised': 5, 'monopoly': 8, 'inorganic': 7,
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'xyz': 0, '': 0
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}
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import snowballstemmer
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from flask import session
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# 词汇表加载
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def load_record(pickle_fname):
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try:
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with open(pickle_fname, 'rb') as f:
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d = pickle.load(f)
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return d
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except FileNotFoundError:
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return _TEST_MOCK
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with open(pickle_fname, 'rb') as f:
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d = pickle.load(f)
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return d
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# 判断是否是英文单词
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def is_english_word(word):
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pattern = re.compile(r'^[a-zA-Z]+$')
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return bool(pattern.match(word))
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# 判断日期格式是否有效
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def is_valid_datetime_string(date_string, format='%Y%m%d%H%M'):
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try:
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datetime.strptime(date_string, format)
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return True
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except ValueError:
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return False
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# 去除非单词字符
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def remove_non_words(input_string):
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cleaned_string = re.sub(r'[^a-zA-Z\s]', '', input_string)
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words = cleaned_string.split()
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return ' '.join(words)
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# 主类：词汇水平估算器
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class VocabularyLevelEstimator:
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_test = load_record('words_and_tests.p') # map a word to the sources where it appears
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# 词汇表（单词：【"雅思","高考"...】）
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_test = load_record('static\words_and_tests.p') # 词汇到测试来源的映射
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@property
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def level(self):
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total = 0.0 # 总评分
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num = 0 # 计算的单词数
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for word in self.word_lst:
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num += 1
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if word in self._test:
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print(f'{word} : {self._test[word]}') # 输出单词及其来源
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else:
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print(f'{word}') # 输出没有评分的单词
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return total / num if num else 0.0 # 返回平均值
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def get_word_level(self, word):
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# 常见高频词汇列表
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other = ['went', 'heard', 'i', 'feet', 'got', 'been', 'gone', 'done', 'had', 'said', 'seen', 'made',
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'taken', 'come', 'gotten', 'got ', 'ran', 'eaten', 'written', 'found', 'given', 'told',
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'brought', 'kept', 'stood', 'sat', 'won', 'bought', 'caught', 'begun', 'drank', 'rang', 'sang',
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'swam', 'blew', 'drew', 'flew', 'grew', 'knew', 'threw', 'shown', 'broken', 'chosen', 'forgotten',
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'spoke', 'woke', 'woken', 'driven', 'fell', 'given', 'risen', 'mistaken', 'ridden', 'lain', 'lied']
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if word not in self._test: return 3 # 如果词汇不在测试数据中，返回3级
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if word in other: return 3 # 如果是常见的高频词汇，返回3级
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k = self._test[word]
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# 根据词汇的来源设置等级
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if 'CET4' in k:
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return 4
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elif 'OXFORD3000' in k:
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return 5
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elif 'CET6' in k or 'GRADUATE' in k:
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return 6
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elif 'OXFORD5000' in k or 'IELTS' in k:
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return 7
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elif 'BBC' in k:
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return 8
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# 用户词汇水平类
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class UserVocabularyLevel(VocabularyLevelEstimator):
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# 过滤后的用户生词库
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filtered_frequency = []
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def __init__(self, d):
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if d:
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self.d = d # 用户的生词库
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self.word_lst = list(d.keys())
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self.filter_user_frequency()
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def filter_user_frequency(self):
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# 过滤出最近一周的生词，用于计算用户词汇水平
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stemmer = snowballstemmer.stemmer('english')
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range_datetime = (datetime.now() - timedelta(days=7)).strftime('%Y%m%d%H%M')
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self.filtered_frequency = []
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for word in self.d:
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if is_english_word(word) and is_valid_datetime_string(self.d[word][0]):
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if self.d[word][0] > range_datetime and word not in self.filtered_frequency:
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self.filtered_frequency.append(stemmer.stemWord(word))
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@property
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def level(self):
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total = 0.0
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valid_count = 0
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for word in self.word_lst:
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if word in self._test:
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total += self._test[word]
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valid_count += 1
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if valid_count != 0 and total != 0:
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total += (valid_count * valid_count) / 100
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return total / valid_count if valid_count > 0 else 0
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num = 0
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if not self.filtered_frequency: return 0.0
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for word in self.filtered_frequency:
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num += 1
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total += self.get_word_level(word)
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return total / num if num else 0.0
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class UserVocabularyLevel(VocabularyLevelEstimator):
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def __init__(self, d):
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if not isinstance(d, dict):
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raise TypeError("Input must be a dictionary")
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self.d = d
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self.word_lst = list(d.keys())
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# just look at the most recently-added words
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# 文章词汇难度类
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class ArticleVocabularyLevel(VocabularyLevelEstimator):
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difficulty_word = dict()
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def __init__(self, content):
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if not isinstance(content, str):
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raise TypeError("Content must be a string")
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self.content = content
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self.word_lst = re.findall(r'\b[a-zA-Z]+\b', content.lower())
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if content:
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self.content = remove_non_words(content)
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self.word_lst = self.content.lower().split()
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self.select_difficulty_word()
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def select_difficulty_word(self, n=10):
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self.difficulty_word = {}
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stemmer = snowballstemmer.stemmer('english')
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for word in self.word_lst:
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original_word = stemmer.stemWord(word)
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self.difficulty_word[original_word] = self.get_word_level(original_word)
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if self.difficulty_word:
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sorted_words = sorted(self.difficulty_word.items(), key=lambda item: item[1], reverse=True)
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top_words = sorted_words[:n]
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self.difficulty_word = {word: difficulty for word, difficulty in top_words}
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@property
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def level(self):
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total = 0.0
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num = 0
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if not self.difficulty_word: return 0.0
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for word in self.difficulty_word:
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num += 1
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total += self.difficulty_word[word]
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return total / num if num else 0.0
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if __name__ == '__main__':
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d = load_record('frequency_mrlan85.pickle')
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d = load_record('static/frequency/frequency_sb.pickle') # 加载用户词汇数据
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print(d)
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user = UserVocabularyLevel(d)
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print(user.level) # level is a property
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article = ArticleVocabularyLevel('This is an interesting article')
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print(article.level)
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print('用户词汇水平：')
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print(user.level) # 输出用户的词汇水平
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s = """Energetic = haze dynamic = vigorous = animated Such is Love , Plain like Water
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port him to stand up. She scolded him for not having waken her up. He said that he could manage. A serious quarrel was about to burst out again.
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I called them from Zhuhai, the beautiful city of relaxation and exciting views. I wanted to depict to them how pretty a city Zhuhai is."""
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article = ArticleVocabularyLevel(s)
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print('文章词汇难度：')
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print(article.level) # 输出文章的词汇难度
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# 测试文章保存
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with open('test/article_test.p', 'wb') as file:
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pickle.dump(s, file)
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with open('test/article_test.p', 'rb') as file:
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loaded_data = pickle.load(file)
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print(loaded_data)
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