init-commit

internbootcamp/libs/wordladder/main.py

@@ -0,0 +1,128 @@
+import random
+from libs.wordladder.solver_main import solver_main2
+from unittest.mock import patch
+from libs.wordladder.file_io import *
+
+"""
+原代码地址:https://github.com/marrow16/pyWordLadder/tree/master
+solver_main.py solver_main()是原程序main.py main()
+现在使用main.py() solver_main2() solve2()
+"""
+
+def main():
+    """
+    弃用,现在用solver,此方法为无参数测试方法,所有需要参数全部来自config.json,打印结果
+    原程序需要sys.args输入
+    str     start_word  修改为传参
+    str     end_word    修改为传参
+    int     ladder      修改为自动递增直到答案足够/上限
+    y/n     打印所有     修改为打印+后处理
+    y/n     重新运行     预输入"n"截断
+    """
+    param_data = {
+        "start_word" : "",
+        "end_word" : "",
+        "solutions" : 0,
+        "max_ladder" : 0,
+        "output_filepath" : "",
+        "is_nlp": True
+        }
+    
+    if is_param_random():
+        if is_word_random():
+            param_data["start_word"] , param_data["end_word"] = get_random_puzzle()
+        else:
+            words = get_random_words(get_random_mode_word_length())
+            param_data["start_word"] = words[0]
+            param_data["end_word"] = words[1]
+    else:
+        param_data["start_word"] = get_specify_mode_start_word()
+        param_data["end_word"] = get_specify_mode_end_word()
+    param_data["solutions"] = get_solutions_count()
+    param_data["max_ladder"] = get_ladders_count()
+    param_data["output_filepath"] = get_output_filepath()
+    param_data["is_nlp"] = is_nl_describe()
+    print(param_data)
+
+    # 预输入数据 目的截断所有后续需要y/n的sys.args输入
+    inputs = iter(['n'] * 100)
+
+    # 模拟 input()
+    with patch("builtins.input", lambda _: next(inputs)):
+        solver_main2(param_data)
+
+def solver(start_word:str,end_word:str):
+    """
+    :param  start_word:str      第一个单词
+    :param  end_word:str        最后一个单词
+    :return solutions:list[str] n条可能的解 (config.json控制)
+    """
+    param_data = {
+        "start_word" : start_word,
+        "end_word" : end_word,
+        "solutions" : 0,
+        "max_ladder" : 0,
+        "output_filepath" : "",
+        "is_nlp": True
+        }
+    
+    # if is_param_random():
+    #     if is_word_random():
+    #         param_data["start_word"] , param_data["end_word"] = get_random_puzzle()
+    #     else:
+    #         words = get_random_words(get_random_mode_word_length())
+    #         param_data["start_word"] = words[0]
+    #         param_data["end_word"] = words[1]
+    # else:
+    #     param_data["start_word"] = get_specify_mode_start_word()
+    #     param_data["end_word"] = get_specify_mode_end_word()
+    param_data["solutions"] = get_solutions_count()
+    param_data["max_ladder"] = get_ladders_count()
+    param_data["output_filepath"] = get_output_filepath()
+    param_data["is_nlp"] = is_nl_describe()
+    print(param_data)
+
+    # 预输入数据 目的截断所有后续需要y/n的sys.args输入
+    inputs = iter(['n'] * 100)
+
+    # 模拟 input()
+    with patch("builtins.input", lambda _: next(inputs)):
+        return solver_main2(param_data)
+
+def get_random_puzzle():
+    random_number = random.randint(2, 15)
+    words = get_random_words(random_number)
+    start_word = words[0]
+    end_word = words[1]
+    
+    return start_word,end_word
+
+def get_random_words(size):
+    #:param n:int 单词长度
+    #:return :["word1","word2"]
+    if not (2 <= size <= 15):
+        raise ValueError("参数n必须在2到15之间")
+    file_path = f'libs/wordladder/words/resources/dictionary-{size}-letter-words.txt'
+
+    try:
+        # 读取文件中的所有单词
+        with open(file_path, 'r', encoding='utf-8') as file:
+            words = [line.strip() for line in file.readlines()]
+        
+        if len(words) < 2:
+            raise ValueError("文件中的单词数量不足两个")
+        
+        # 随机选择两个不同的单词
+        selected_words = random.sample(words, 2)
+        
+        return selected_words
+    
+    except FileNotFoundError:
+        print(f"文件 {file_path} 未找到")
+        return []
+    except Exception as e:
+        print(f"发生错误: {e}")
+        return []
+
+if __name__ == '__main__':
+    main()