大调整

13 计算设备/map-reduce/tf-91.py

@@ -1,56 +1,56 @@
-# -*- coding: utf-8 -*-
-from collections import Counter
-from cppy.cp_util import *
-from multiprocessing.pool import ThreadPool
-
-
-#
-# 多线程
-#
-def process_chunk(chunk):
-    # 过滤停用词
-    stop_words = get_stopwords()
-    words = [ w for w in chunk if ( not w in stop_words ) and len(w) >= 3 ]
-    return Counter(words)
-
-
-def merge_counts(counts_list):
-    # 合并多个Counter对象
-    total_counts = Counter()
-    for counts in counts_list:
-        total_counts += counts
-    return total_counts
-
-
-def thread_function(chunk, counts_list):
-    word_count = process_chunk(chunk)
-    counts_list.append(word_count)
-
-
-@timing_decorator
-def main():
-    # 读取文件内容
-    content = re_split(read_file(testfilepath))
-    chunk_size = 1000 # 可以根据实际情况调整块大小
-    chunks = [content[i:i + chunk_size] for i in range(0, len(content), chunk_size)]
-
-    # 使用多线程池，每个线程处理一个块
-    pool = ThreadPool(len(content)//chunk_size+1)
-    counts_list = pool.map(process_chunk, chunks)
-    pool.close()
-    pool.join()
-
-    # 合并计数
-    total_counts = merge_counts(counts_list)
-
-    # 输出最高频的n个词
-    print_word_freqs(total_counts.most_common(10))
-
-
-if __name__ == '__main__':
-    main()
-
-
-
-
-
+# -*- coding: utf-8 -*-
+from collections import Counter
+from cppy.cp_util import *
+from multiprocessing.pool import ThreadPool
+
+
+#
+# 多线程
+#
+def process_chunk(chunk):
+    # 过滤停用词
+    stop_words = get_stopwords()
+    words = [ w for w in chunk if ( not w in stop_words ) and len(w) >= 3 ]
+    return Counter(words)
+
+
+def merge_counts(counts_list):
+    # 合并多个Counter对象
+    total_counts = Counter()
+    for counts in counts_list:
+        total_counts += counts
+    return total_counts
+
+
+def thread_function(chunk, counts_list):
+    word_count = process_chunk(chunk)
+    counts_list.append(word_count)
+
+
+@timing_decorator
+def main():
+    # 读取文件内容
+    content = re_split(read_file(testfilepath))
+    chunk_size = 1000 # 可以根据实际情况调整块大小
+    chunks = [content[i:i + chunk_size] for i in range(0, len(content), chunk_size)]
+
+    # 使用多线程池，每个线程处理一个块
+    pool = ThreadPool(len(content)//chunk_size+1)
+    counts_list = pool.map(process_chunk, chunks)
+    pool.close()
+    pool.join()
+
+    # 合并计数
+    total_counts = merge_counts(counts_list)
+
+    # 输出最高频的n个词
+    print_word_freqs(total_counts.most_common(10))
+
+
+if __name__ == '__main__':
+    main()
+
+
+
+
+

13 计算设备/map-reduce/tf-92.py

@@ -1,49 +1,49 @@
-# -*- coding: utf-8 -*-
-import multiprocessing
-from collections import Counter
-from cppy.cp_util import *
-
-
-#
-# 多进程
-#
-def process_chunk(chunk):
-    # 过滤停用词
-    stop_words = get_stopwords()
-    words = [ w for w in chunk if ( not w in stop_words ) and len(w) >= 3 ]
-    return Counter(words)
-
-
-def merge_counts(counts_list):
-    # 合并多个Counter对象
-    total_counts = Counter()
-    for counts in counts_list:
-        total_counts += counts
-    return total_counts
-
-
-@timing_decorator
-def main():
-    # 读取文件内容
-    content = re_split(read_file(testfilepath))
-
-    # 分割文件内容为多个块，每个块由一个进程处理
-    chunk_size = 1000  # 可以根据实际情况调整块大小
-    chunks = [content[i:i + chunk_size] for i in range(0, len(content), chunk_size)]
-
-    # 使用多进程处理每个块
-    pool = multiprocessing.Pool(processes=multiprocessing.cpu_count())
-    counts_list = pool.map(process_chunk, chunks)
-    pool.close()
-    pool.join()
-
-    # 合并计数
-    total_counts = merge_counts(counts_list)
-
-    # 输出最高频的n个词
-    print_word_freqs(total_counts.most_common(10))
-
-
-if __name__ == '__main__':
-    main()
-
+# -*- coding: utf-8 -*-
+import multiprocessing
+from collections import Counter
+from cppy.cp_util import *
+
+
+#
+# 多进程
+#
+def process_chunk(chunk):
+    # 过滤停用词
+    stop_words = get_stopwords()
+    words = [ w for w in chunk if ( not w in stop_words ) and len(w) >= 3 ]
+    return Counter(words)
+
+
+def merge_counts(counts_list):
+    # 合并多个Counter对象
+    total_counts = Counter()
+    for counts in counts_list:
+        total_counts += counts
+    return total_counts
+
+
+@timing_decorator
+def main():
+    # 读取文件内容
+    content = re_split(read_file(testfilepath))
+
+    # 分割文件内容为多个块，每个块由一个进程处理
+    chunk_size = 1000  # 可以根据实际情况调整块大小
+    chunks = [content[i:i + chunk_size] for i in range(0, len(content), chunk_size)]
+
+    # 使用多进程处理每个块
+    pool = multiprocessing.Pool(processes=multiprocessing.cpu_count())
+    counts_list = pool.map(process_chunk, chunks)
+    pool.close()
+    pool.join()
+
+    # 合并计数
+    total_counts = merge_counts(counts_list)
+
+    # 输出最高频的n个词
+    print_word_freqs(total_counts.most_common(10))
+
+
+if __name__ == '__main__':
+    main()
+

16 其它/对象设计模式/观察者模式/Observer.py

@@ -1,77 +1,77 @@
-import os,re,string,operator
-from collections import Counter
-
-# TextProcessor 类负责处理文本并计算词频。当文本处理完成后，它会通过 notify 方法通知所有注册的观察者。
-# WordFrequencyObserver 类是一个具体的观察者，它实现了 update 方法来接收词频更新并打印前10个最常见的单词。
-class Subject:
-    def __init__(self):
-        self._observers = []
-    # 不能随意改变，所以肯定是私有
-    def attach(self, observer):
-        self._observers.append(observer)
-
-    def detach(self, observer):
-        self._observers.remove(observer)
-
-    def notify(self, word_freqs):
-        for observer in self._observers:
-            observer.update(word_freqs)
-# 关注，取消关注，通知有更新,Subject类是用来创建一个类，对订阅者（即观察者）列表进行维护
-
-class Observer:
-    def update(self, word_freqs):
-        pass
-# 定义一个抽象的Observer
-# 而下面的是一个具体的Observer类
-class WordFrequencyObserver(Observer):
-    def update(self, word_freqs):
-        print("词频已经被更新:")
-        self.print_word_freqs(word_freqs)
-
-    def print_word_freqs(self, word_freqs):
-        sorted_freqs = sorted(word_freqs.items(), key=operator.itemgetter(1), reverse=True)
-        for (w, c) in sorted_freqs[:10]:
-            print(f"{w}: {c}")
-
-# 对文本进行分析
-class TextProcessor:
-    def __init__(self, subject: Subject):
-#subject是Subject的子类，类型注解，单独写也可以
-        self._subject = subject
-        self._stop_words:str = set()
-#是一个集合（其实这里需要表明是str）
-    def load_stop_words(self, path_to_file):
-        with open(path_to_file, encoding='utf-8') as f:
-            self._stop_words = set(line.strip().lower() for line in f)
-
-    def process_text(self, path_to_file):
-        with open(path_to_file, encoding='utf-8') as f:
-            data = f.read()
-            word_list = self.re_split(data)
-            filtered_words = self.filter_words(word_list)
-            word_freqs = self.count_frequencies(filtered_words)
-            self._subject.notify(word_freqs)
-
-    def re_split(self, data):
-        pattern = re.compile('[\W_]+')
-        return pattern.sub(' ', data).lower().split()
-
-    def filter_words(self, word_list):
-        return [w for w in word_list if w not in self._stop_words and len(w) >= 3]
-
-    def count_frequencies(self, word_list):
-        return Counter(word_list)
-
-# 开始测试
-if __name__ == "__main__":
-    stopwordfilepath = r'C:\Users\asus\Desktop\cppy余悦批注\cppy\data\stop_words.txt'
-    testfilepath = r'C:\Users\asus\Desktop\cppy余悦批注\cppy\data\pride-and-prejudice.txt'
-
-    # 调用实例
-    subject = Subject()
-    observer = WordFrequencyObserver()
-    subject.attach(observer)
-
-    text_processor = TextProcessor(subject)
-    text_processor.load_stop_words(stopwordfilepath)
+import os,re,string,operator
+from collections import Counter
+
+# TextProcessor 类负责处理文本并计算词频。当文本处理完成后，它会通过 notify 方法通知所有注册的观察者。
+# WordFrequencyObserver 类是一个具体的观察者，它实现了 update 方法来接收词频更新并打印前10个最常见的单词。
+class Subject:
+    def __init__(self):
+        self._observers = []
+    # 不能随意改变，所以肯定是私有
+    def attach(self, observer):
+        self._observers.append(observer)
+
+    def detach(self, observer):
+        self._observers.remove(observer)
+
+    def notify(self, word_freqs):
+        for observer in self._observers:
+            observer.update(word_freqs)
+# 关注，取消关注，通知有更新,Subject类是用来创建一个类，对订阅者（即观察者）列表进行维护
+
+class Observer:
+    def update(self, word_freqs):
+        pass
+# 定义一个抽象的Observer
+# 而下面的是一个具体的Observer类
+class WordFrequencyObserver(Observer):
+    def update(self, word_freqs):
+        print("词频已经被更新:")
+        self.print_word_freqs(word_freqs)
+
+    def print_word_freqs(self, word_freqs):
+        sorted_freqs = sorted(word_freqs.items(), key=operator.itemgetter(1), reverse=True)
+        for (w, c) in sorted_freqs[:10]:
+            print(f"{w}: {c}")
+
+# 对文本进行分析
+class TextProcessor:
+    def __init__(self, subject: Subject):
+#subject是Subject的子类，类型注解，单独写也可以
+        self._subject = subject
+        self._stop_words:str = set()
+#是一个集合（其实这里需要表明是str）
+    def load_stop_words(self, path_to_file):
+        with open(path_to_file, encoding='utf-8') as f:
+            self._stop_words = set(line.strip().lower() for line in f)
+
+    def process_text(self, path_to_file):
+        with open(path_to_file, encoding='utf-8') as f:
+            data = f.read()
+            word_list = self.re_split(data)
+            filtered_words = self.filter_words(word_list)
+            word_freqs = self.count_frequencies(filtered_words)
+            self._subject.notify(word_freqs)
+
+    def re_split(self, data):
+        pattern = re.compile('[\W_]+')
+        return pattern.sub(' ', data).lower().split()
+
+    def filter_words(self, word_list):
+        return [w for w in word_list if w not in self._stop_words and len(w) >= 3]
+
+    def count_frequencies(self, word_list):
+        return Counter(word_list)
+
+# 开始测试
+if __name__ == "__main__":
+    stopwordfilepath = r'C:\Users\asus\Desktop\cppy余悦批注\cppy\data\stop_words.txt'
+    testfilepath = r'C:\Users\asus\Desktop\cppy余悦批注\cppy\data\pride-and-prejudice.txt'
+
+    # 调用实例
+    subject = Subject()
+    observer = WordFrequencyObserver()
+    subject.attach(observer)
+
+    text_processor = TextProcessor(subject)
+    text_processor.load_stop_words(stopwordfilepath)
     text_processor.process_text(testfilepath)

16 其它/状态机/81A.py

@@ -1,59 +1,59 @@
-# -*- coding: utf-8 -*-
-import cppy.cp_util as util
-from collections import Counter
-
-
-class WordFrequencyStateMachine:
-    def __init__(self, file_path):
-        self.file_path = file_path
-        self.content = None
-        self.words = None
-        self.word_freq = None
-        self.state = 'IDLE'
-
-    def transition_to_read_file(self):
-        try:
-            with open(self.file_path, 'r', encoding='utf-8') as file:
-                self.content = file.read()
-                self.state = 'WORDS_SPLIT'
-        except FileNotFoundError:
-            print(f"文件 {self.file_path} 未找到。")
-        except Exception as e:
-            print(f"读取文件时发生错误: {e}")
-
-    def transition_to_split_words(self):
-        if self.content is not None:
-            self.words = util.extract_str_words(self.content)
-            self.state = 'CALCULATE_FREQ'
-        else:
-            print("文件内容为空，无法分割单词。")
-
-    def transition_to_calculate_freq(self):
-        if self.words is not None:
-            self.word_freq = Counter(self.words)
-            self.state = 'DONE'
-        else:
-            print("单词列表为空，无法计算词频。")
-
-    def run(self):
-        while self.state != 'DONE':
-            if self.state == 'IDLE':
-                self.transition_to_read_file()
-            elif self.state == 'WORDS_SPLIT':
-                self.transition_to_split_words()
-            elif self.state == 'CALCULATE_FREQ':
-                self.transition_to_calculate_freq()
-            else:
-                print(f"未知状态: {self.state}")
-                break
-
-        return self.word_freq
-
-    # 使用状态机计算词频
-
-
-state_machine = WordFrequencyStateMachine(util.testfilepath)
-word_frequencies = state_machine.run()
-
-# 打印结果
+# -*- coding: utf-8 -*-
+import cppy.cp_util as util
+from collections import Counter
+
+
+class WordFrequencyStateMachine:
+    def __init__(self, file_path):
+        self.file_path = file_path
+        self.content = None
+        self.words = None
+        self.word_freq = None
+        self.state = 'IDLE'
+
+    def transition_to_read_file(self):
+        try:
+            with open(self.file_path, 'r', encoding='utf-8') as file:
+                self.content = file.read()
+                self.state = 'WORDS_SPLIT'
+        except FileNotFoundError:
+            print(f"文件 {self.file_path} 未找到。")
+        except Exception as e:
+            print(f"读取文件时发生错误: {e}")
+
+    def transition_to_split_words(self):
+        if self.content is not None:
+            self.words = util.extract_str_words(self.content)
+            self.state = 'CALCULATE_FREQ'
+        else:
+            print("文件内容为空，无法分割单词。")
+
+    def transition_to_calculate_freq(self):
+        if self.words is not None:
+            self.word_freq = Counter(self.words)
+            self.state = 'DONE'
+        else:
+            print("单词列表为空，无法计算词频。")
+
+    def run(self):
+        while self.state != 'DONE':
+            if self.state == 'IDLE':
+                self.transition_to_read_file()
+            elif self.state == 'WORDS_SPLIT':
+                self.transition_to_split_words()
+            elif self.state == 'CALCULATE_FREQ':
+                self.transition_to_calculate_freq()
+            else:
+                print(f"未知状态: {self.state}")
+                break
+
+        return self.word_freq
+
+    # 使用状态机计算词频
+
+
+state_machine = WordFrequencyStateMachine(util.testfilepath)
+word_frequencies = state_machine.run()
+
+# 打印结果
 util.print_word_freqs(word_frequencies.most_common(10))

16 其它/状态机/81B.py

@@ -1,33 +1,33 @@
-# -*- coding: utf-8 -*-
-import cppy.cp_util as util
-
-# 每一列是一个数据元素和一个公式,第一列是输入数据，所以没有公式
-all_words = [(), None]
-non_stop_words = [(), util.extract_str_words]
-frequencies = [(), util.get_frequencies]
-sorted_data = [(), util.sort_dict]
-
-# 整个电子表格
-all_columns = [all_words, non_stop_words,\
-                frequencies, sorted_data]
-
-# 每次输入数据后调用此方法
-def update():
-    global all_columns
-    for c in all_columns[1::]:
-        if c[1] == util.extract_str_words:
-            c[0] = c[1](all_words[0])
-        elif c[1] == util.get_frequencies:
-            c[0] = c[1](non_stop_words[0])
-        elif c[1] == util.sort_dict:
-            c[0] = c[1](frequencies[0])
-
-# 将固定数据加载到第一列中
-all_words[0] = util.read_file(util.testfilepath)
-# 调用update函数遍历列表
-update()
-
-#打印结果
-util.print_word_freqs(sorted_data[0])
-
-
+# -*- coding: utf-8 -*-
+import cppy.cp_util as util
+
+# 每一列是一个数据元素和一个公式,第一列是输入数据，所以没有公式
+all_words = [(), None]
+non_stop_words = [(), util.extract_str_words]
+frequencies = [(), util.get_frequencies]
+sorted_data = [(), util.sort_dict]
+
+# 整个电子表格
+all_columns = [all_words, non_stop_words,\
+                frequencies, sorted_data]
+
+# 每次输入数据后调用此方法
+def update():
+    global all_columns
+    for c in all_columns[1::]:
+        if c[1] == util.extract_str_words:
+            c[0] = c[1](all_words[0])
+        elif c[1] == util.get_frequencies:
+            c[0] = c[1](non_stop_words[0])
+        elif c[1] == util.sort_dict:
+            c[0] = c[1](frequencies[0])
+
+# 将固定数据加载到第一列中
+all_words[0] = util.read_file(util.testfilepath)
+# 调用update函数遍历列表
+update()
+
+#打印结果
+util.print_word_freqs(sorted_data[0])
+
+