def find_answer_by_13(self, sentence: str, remark: str, options: list) -> str:
_logger.d("\nfind_answer_by_13")
_logger.d(sentence)
assist_word = sentence[sentence.find("{") + 1:sentence.find("}")].strip()
_logger.d(assist_word)
_logger.d(remark)
_logger.d(options)
answer_list = self._course.find_detail_by_assist_word(assist_word)
_logger.d(answer_list)
if len(answer_list) == 0:
raise AnswerNotFoundException(13)
for answer in answer_list:
for content in answer["content"]:
if adapter.is_remark_or_sentence_in_example(content["example"], remark, sentence):
# 创建一个临时列表，方便下一步判断答案
tem_list = []
for key in content["example"]:
if key != remark: # 本题是根据题目例句选择与例句同列的例句，故需排除题目例句本身
tem_list.append(content["example"][key])
for sentence in options:
if sentence["content"] in tem_list:
_logger.d(sentence["content"])
return str(sentence["answer_tag"])
for sentence in options:
if Tool.is_str_in_list_by_some_difference(sentence["content"], tem_list):
_logger.d(sentence["content"])
return str(sentence["answer_tag"])
raise AnswerNotFoundException(13)
def find_answer_by_11(self, sentence: str, remark: str, options: list, skip_times: int) -> str:
_logger.d("\nfind_answer_by_11")
_logger.d(sentence)
assist_word = sentence[sentence.find("{") + 1:sentence.find("}")].strip()
_logger.d(assist_word)
_logger.d(options)
# 根据辅助词先行过滤出一个粗略的可能性列表
answer_list = self._course.find_detail_by_assist_word(assist_word)
_logger.d(answer_list)
if len(answer_list) == 0:
# 辅助词过滤出现未适配情况或者出现答案预处理出错的情况
raise AnswerNotFoundException(11)
for answer in answer_list:
for content in answer["content"]:
if adapter.is_remark_or_sentence_in_example(content["example"], remark, sentence):
for mean in options:
tem_list = adapter.process_option_mean(mean["content"])
# 若选项集合与题库集合的交集存在，则说明该选项等于题库中的某个选项
# 由 mean == content["mean"] 拓展适配得来
if len(set(tem_list) & set(adapter.process_word_mean(content["mean"]))) != 0:
if skip_times != 0:
skip_times -= 1
continue
return str(mean["answer_tag"])
vague_answer = adapter.answer_11_1(remark, skip_times, options, answer_list)
if vague_answer:
return vague_answer
vague_answer = adapter.answer_11_2(sentence, remark, skip_times, options, answer_list)
if vague_answer:
return vague_answer
raise AnswerNotFoundException(11)
def find_answer_by_43(self, content, remark, options) -> str:
_logger.d("\nfind_answer_by_43")
_logger.d(content)
content = adapter.process_option_sentence(content) # 合着您传输多个空格就为了增加网页端单词间距显示？？？
_logger.d(content)
_logger.d(options)
for option in options:
answer = self._course.find_detail_by_word(option["content"])
if answer is None:
continue
_logger.d(answer)
if answer is not None:
# 创建一个临时列表，存放例句翻译
tem_list = []
for example in answer["content"]:
for key in example["example"]:
tem_list.append(key)
if remark in tem_list:
if option["sub_options"] is not None:
assist_word = None
position = -2
for example in answer["content"]:
if example["example"].get(remark) is not None:
tem_content = example["example"][remark]
assist_word = tem_content[tem_content.find("{") + 1:tem_content.find("}")]
position = tem_content.find("{")
break
for sub in option["sub_options"]:
if sub["content"] == assist_word and content.find("{") == position:
return option["answer_tag"] + str(sub["answer_tag"])
else:
return option["answer_tag"] + "0"
raise AnswerNotFoundException(43)
def find_answer_by_17(self, content: str, options: list) -> str:
_logger.d("\nfind_answer_by_17")
_logger.d(content)
content = re.sub(r'\s\s', ' ', content)
_logger.d(content)
_logger.d(options)
content_list = adapter.process_option_mean(content)
# 21.3.17修复由群友转交给115***706提交的BUG，我们仍未知道那天是哪位群友的贡献
if content.find("（") != -1:
content_list.extend(adapter.process_option_mean(re.sub(r"（.+）", "", content)))
# 感谢群友104***629提供的错误日志让我意识到了使用了错误的适配函数
content_set = set(content_list)
for word in options:
answer = self._course.find_detail_by_word(word["content"])
_logger.d(answer)
if answer is None: # 选项中可能存在不在课程中的单词，故查询结果可能为空
continue
# 创建一个临时列表
tem_list = []
for mean in answer["content"]:
tem_list.extend(adapter.process_word_mean(mean["mean"]))
if len(set(tem_list) & content_set) != 0:
return str(word["answer_tag"])
# 模糊匹配
answer_dict = {}
for word in options:
answer = self._course.find_detail_by_word(word["content"])
_logger.d(answer)
if answer: # 选项中可能存在不在课程中的单词，故查询结果可能为空
answer_dict[word["content"]] = answer
vague_answer = adapter.answer_17_1(content_list, options, answer_dict)
if vague_answer:
return vague_answer
raise AnswerNotFoundException(17)
def find_answer_by_15(self, word: str, options: list) -> str:
_logger.d("\nfind_answer_by_15")
_logger.d(word)
_logger.d(options)
answer = self._course.find_detail_by_word(word)
_logger.d(answer)
if answer is None:
raise AnswerNotFoundException(15)
# 创建一个临时列表
tem_list = []
for content in answer["content"]:
tem_list.extend(adapter.process_word_mean(content["mean"]))
tem_set = set(tem_list)
for mean in options:
if len(tem_set & set(adapter.process_option_mean(mean["content"]))) != 0:
return str(mean["answer_tag"])
vague_answer = adapter.answer_15_1(tem_list, options)
if vague_answer:
return vague_answer
raise AnswerNotFoundException(15)
def find_answer_by_32(self, remark: str, options: list, blank_count: int,
skip_times: int) -> str:
_logger.d("\nfind_answer_by_32")
_logger.d(remark)
_logger.d(options)
_logger.d(f"{blank_count:d}")
# 选项预处理
option_list = [] # 存放选项中的短语，短语由规定顺序的单词数组构成
for usage in options:
content, _ = adapter.process_content_and_remark(
usage["content"], None)
_logger.d(content, is_show=False)
option_list.extend(
re.split(r"\s+", adapter.process_option_usage(content)))
_logger.d(option_list, is_show=False)
option_set = Set(option_list)
wrong_set = set()
for key, value in self._course.data.items():
for content in value["content"]:
usage_list = content["usage"].get(
remark) or adapter.usage_get_remark(
content["usage"], remark)
if usage_list is not None:
_logger.d(usage_list, is_show=False)
for usage in usage_list:
if len(option_set & Set(usage)) == len(usage):
if skip_times != 0 or adapter.answer_32_2(
options, usage) in wrong_set:
skip_times -= 1
wrong_set.add(
adapter.answer_32_2(options, usage))
continue
if len(usage) == blank_count:
# 因原选项中可能会出现多出空格问题
return adapter.answer_32_2(options, usage)
# 修复题库中同时存在
# "迫切需要": ["an", "urgent", "need"]
# "迫切需要": ["urgent", "need"]
# 导致的答案匹配出错，该BUG由群友183***092提供，156行为其贡献
if len(usage) > blank_count:
# 下列情况为一个选项中存在多个单词（说好的一个单词一个选项呢？？？）
result = adapter.answer_32_1(options, usage)
if result:
return result
raise AnswerNotFoundException(32)
def find_answer_by_51(self, content: str, remark: str, skip_times: int) -> str:
_logger.d("\nfind_answer_by_51")
_logger.d(content)
_logger.d(remark)
content, remark = adapter.process_content_and_remark(content, remark)
usage_list = adapter.process_option_usage(content).split(" ")
usage_list_set = Set(usage_list)
_logger.d(usage_list)
remark_set = set(adapter.process_option_mean(remark))
for key, value in self._course.data.items():
if len(usage_list) == 1:
for i in value["content"]:
if len(remark_set & set(adapter.process_word_mean(i["mean"]))) != 0:
if skip_times != 0:
skip_times -= 1
continue
return key
else:
for content_list in value["content"]:
usages = content_list["usage"].get(remark)\
or adapter.usage_get_remark(content_list["usage"], remark)
if usages is not None:
_logger.d(usages)
for usage in usages:
# 修复长度判断，该bug由群友169***762提供
if len(usage_list) - 1 != len(usage_list_set & Set(usage))\
or len(usage_list) != len(usage):
continue
for index, word in enumerate(usage):
if word != usage_list[index]:
if skip_times != 0:
skip_times -= 1
continue
# 原本只需返回usage[index]即可
# 但因兼容CET4_3的at one's {}'s end(智穷力竭)特殊案例，不得不复杂化
return adapter.answer_51(usage_list[index], usage[index])
vague_answer = adapter.answer_51_1(self._course.data, remark, skip_times, usage_list, usage_list_set)
if vague_answer:
return vague_answer
vague_answer = adapter.answer_51_2(self._course.data, remark, skip_times, usage_list, usage_list_set)
if vague_answer:
return vague_answer
raise AnswerNotFoundException(51)
def find_answer_by_41(self, content: str, remark: str, options: list) -> str:
_logger.d("\nfind_answer_by_41")
_logger.d(content)
content = adapter.process_option_sentence(content) # 合着您传输多个空格就为了增加网页端单词间距显示？？？
_logger.d(content)
_logger.d(options)
for word in options:
answer_list = self._course.find_detail_by_assist_word(word["content"])
if len(answer_list) == 0:
continue
for answer in answer_list:
_logger.d(answer)
if answer is not None:
for example in answer["content"]:
for key in example["example"]:
# 例句翻译相同的情况下，可能出现多个单词用到了同一个例句
if remark == key and content.find("{") == example["example"][key].find("{"):
return str(word["answer_tag"])
raise AnswerNotFoundException(41)
def find_answer_by_53(self, content: str, remark: str) -> str:
_logger.d("\nfind_answer_by_53")
_logger.d(content)
_logger.d(remark)
content = adapter.process_option_sentence(content)
_logger.d(content)
for key, value in self._course.data.items():
for example in value["content"]:
if content == "{}":
# 由 example["mean"] == remark 拓展适配得来
# 感谢群友148***020提供的错误日志，263-269行代码由其帮助得来
if len(Set(adapter.process_word_mean(example["mean"]))
& Set(adapter.process_option_mean(remark))) != 0:
return key
else:
if example["example"].get(remark) is not None:
sentence = example["example"][remark]
# 不同单词可能具有相同例句，因测试其第一个"{"的位置是否相等
if content.find("{") == sentence.find("{"):
return sentence[sentence.find("{") + 1:sentence.find("}")]
raise AnswerNotFoundException(53)