python改为进行数据预处理

src/agg.py

@@ -1,20 +1,11 @@
 # -*- coding:utf-8 -*-
 import math
 import os
-import re
-import shutil
-import threading
-import time
-from concurrent.futures import ProcessPoolExecutor, as_completed, ThreadPoolExecutor
+from concurrent.futures import ProcessPoolExecutor, as_completed
 
 import jieba
-import redis
-from bitarray import bitarray
-from tqdm import tqdm
 
 import utils
-import logging
-
 from constant import FILE_LONG_TAIL_MERGE
 
 # 文件：长尾词_合并_分词.txt
@@ -47,150 +38,6 @@ CACHE_UNUSED_BITMAP = "unused_bitmap"
 # 字符集：UTF-8
 CHARSET_UTF_8 = "UTF-8"
 
-# redis缓存池
-redis_pool: redis.ConnectionPool = None
-
-# 线程池
-thread_pool: ThreadPoolExecutor = None
-
-# 线程本地变量
-local_var = threading.local()
-
-
-def agg_word(file_path: str):
-    """
-    长尾词聚合
-    :param file_path:
-    :return:
-    """
-
-    # 总长尾词数量
-    # word_total_num = 0
-    word_total_num = 1000000
-
-    # 聚合阈值
-    agg_threshold = 0.8
-
-    # 每份任务计算量
-    task_cal_num = 10000
-
-    # 工作现成(减1是为了留一个处理器给redis)
-    worker_num = os.cpu_count() - 1
-    # worker_num = 1
-
-    # 正则表达式：聚合文件分文件
-    agg_file_pattern = re.compile(r"长尾词_合并_聚合_\d+_\d+.txt", re.I)
-
-    # 最大线程数
-    max_threads = 2
-
-    # redis最大连接数（和工作线程数保持一致，免得浪费）
-    redis_max_conns = max_threads
-
-    # redis缓存
-    m_redis_cache = redis.StrictRedis(host='127.0.0.1', port=6379)
-
-    # 判断文件是否存在
-    for file_name in [FILE_LONG_TAIL_MERGE, FILE_LONG_TAIL_MERGE_SPLIT,
-                      FILE_LONG_TAIL_MERGE_REVERSE_INDEX]:
-        input_file = os.path.join(file_path, file_name)
-        if os.path.exists(input_file) and not os.path.isfile(input_file):
-            raise Exception("文件不存在！文件路径：" + input_file)
-
-    # 归档历史数据文件
-    history_agg_file_list = [file for file in os.listdir(file_path) if agg_file_pattern.match(file)]
-    if len(history_agg_file_list) > 0:
-        archive_path = os.path.join(file_path, DIR_AGG_FILE_ARCHIVE % time.strftime('%Y%m%d%H%M%S'))
-        os.makedirs(archive_path)
-        for history_agg_file in history_agg_file_list:
-            shutil.move(os.path.join(file_path, history_agg_file), archive_path)
-
-    # 缓存关键词位置
-    # word_file = os.path.join(file_path, FILE_LONG_TAIL_MERGE)
-    # word_dict = {}
-    # with open(word_file, "r", encoding="utf-8") as f:
-    #     for position, word in enumerate(f, start=1):
-    #         word = utils.remove_line_break(word)
-    #         if not word:
-    #             continue
-    #         word_dict[position] = word
-    # m_redis_cache.hset(CACHE_WORD, mapping=word_dict)
-    # # 记录总关键词数
-    # word_total_num = len(word_dict)
-    # # 释放内存
-    # del word_dict
-    #
-    # # 缓存分词
-    # word_split_file = os.path.join(file_path, FILE_LONG_TAIL_MERGE_SPLIT)
-    # word_split_dict = {}
-    # with open(word_split_file, "r", encoding=CHARSET_UTF_8) as f:
-    #     for position, word_split_line in enumerate(f, start=1):
-    #         word_split_line = utils.remove_line_break(word_split_line)
-    #         if not word_split_line:
-    #             continue
-    #         word_split_dict[position] = word_split_line
-    # m_redis_cache.hset(CACHE_WORD_STEM, mapping=word_split_dict)
-    # # 释放内存
-    # del word_split_dict
-    #
-    # # 缓存倒排索引
-    # word_reverse_index_file = os.path.join(file_path, FILE_LONG_TAIL_MERGE_REVERSE_INDEX)
-    # word_reverse_index_dict = {}
-    # # 分词
-    # key_pattern = re.compile(r"([^,]+),\[", re.I)
-    # # 索引
-    # index_pattern = re.compile(r"\d+", re.I)
-    # with open(word_reverse_index_file, "r", encoding="utf-8") as f:
-    #     for word_split_line in f:
-    #         key_m = key_pattern.match(word_split_line)
-    #         key = key_m.group(1)
-    #         val = index_pattern.findall(word_split_line[word_split_line.index(","):])
-    #         word_reverse_index_dict[key] = ",".join(val)
-    # m_redis_cache.hset(CACHE_WORD_REVERSE_INDEX, mapping=word_reverse_index_dict)
-    # # 释放内存
-    # del word_reverse_index_dict
-
-    # 先清除，然后重新构建长尾词使用位图
-    m_redis_cache.delete(CACHE_UNUSED_BITMAP)
-    m_redis_cache.setbit(CACHE_UNUSED_BITMAP, word_total_num + 2, 1)
-
-    # 提交任务 并输出结果
-    word_agg_file = os.path.join(file_path, FILE_LONG_TAIL_MERGE_AGG)
-
-    with ProcessPoolExecutor(max_workers=worker_num, initializer=init_process,
-                             initargs=(redis_max_conns, max_threads, file_path)) as process_pool:
-        # 计算任务边界
-        task_list = utils.avg_split_task(word_total_num, task_cal_num, 1)
-
-        # 提交任务
-        process_futures = []
-        for skip_line, pos in enumerate(task_list, start=1):
-            skip_line = (skip_line % worker_num) + 1
-            p_future = process_pool.submit(agg_word_process, agg_threshold, pos[0], pos[1], word_total_num,
-                                           skip_line)
-            process_futures.append(p_future)
-
-        # 显示任务进度
-        with tqdm(total=len(process_futures), desc='文本聚合进度', unit='份', unit_scale=True) as pbar:
-            for p_future in as_completed(process_futures):
-                p_result = p_future.result()
-                # 更新发呆进度
-                pbar.update(1)
-
-        # 关闭线程
-        process_pool.shutdown()
-
-    # 获取子进程结果文件列表，并合并
-    with open(word_agg_file, "w", encoding="UTF-8") as fo:
-        for file in os.listdir(file_path):
-            # 不是处理结果部分跳过
-            if not agg_file_pattern.match(file):
-                continue
-
-            with open(os.path.join(file_path, file), "r", encoding="UTF-8") as fi:
-                for word in fi:
-                    fo.write(word)
-
 
 def prepare_word_split_and_reverse_index(file_path: str):
     """
@@ -217,11 +64,11 @@ def prepare_word_split_and_reverse_index(file_path: str):
     # 分割任务数量
     task_list = utils.avg_split_task(total_line_num, math.ceil(total_line_num / os.cpu_count()))
 
-    # 任务进程处理结果
-    p_result_list = []
-
     # 多进程处理
     with ProcessPoolExecutor(os.cpu_count()) as process_pool:
+        # 任务进程处理结果
+        p_result_list = []
+
         # 提交任务
         process_futures = [process_pool.submit(word_split_reverse, word_input_file, task[0], task[1]) for task in
                            task_list]
@@ -237,14 +84,14 @@ def prepare_word_split_and_reverse_index(file_path: str):
         # 输出分词结果
         split_output_file = os.path.join(file_path, FILE_LONG_TAIL_MERGE_SPLIT)
         with open(split_output_file, "w", encoding="UTF-8") as fo:
-            for start_pos, word_arr_list, reverse_index in p_result_list:
-                for word_arr in word_arr_list:
-                    fo.write("%s\n" % ",".join([str(i) for i in word_arr]))
+            for start_pos, word_list, reverse_index in p_result_list:
+                for word in word_list:
+                    fo.write("%s\n" % word)
 
         # 关键词倒排索引
         word_reverse_index_dict = dict()
         # 合并倒排索引
-        for start_pos, word_arr, reverse_index_dict in p_result_list:
+        for start_pos, word_list, reverse_index_dict in p_result_list:
             for key, value in reverse_index_dict.items():
                 reverse_index_arr = word_reverse_index_dict.get(key)
                 if reverse_index_arr:
@@ -253,8 +100,8 @@ def prepare_word_split_and_reverse_index(file_path: str):
                     word_reverse_index_dict[key] = value
         # 输出倒排索引
         with open(os.path.join(file_path, FILE_LONG_TAIL_MERGE_REVERSE_INDEX), "w", encoding="UTF-8") as fo:
-            for key, value in word_reverse_index_dict.items():
-                fo.write("%s,%s\n" % (key, value))
+            for key, values in word_reverse_index_dict.items():
+                fo.write("%s,%s\n" % (key, ",".join(values)))
 
         # 关闭进程池
         process_pool.shutdown()
@@ -271,13 +118,13 @@ def word_split_reverse(input_file: str, start_pos: int, end_pos: int):
 
     # 加载停用词
     stop_word_dict = utils.load_stop_word()
-    # 关键词存放容器
-    word_arr_list = []
+    # 关键词+分词存放容器
+    word_list = []
     # 倒排索引
-    word_reverse_index = dict()
+    reverse_index = dict()
 
     with open(input_file, "r", encoding="utf-8") as fr:
-        for i, tmp_word in enumerate(fr):
+        for i, word in enumerate(fr):
 
             # start_pos是行数，而i要从0开始
             if i + 1 < start_pos:
@@ -291,198 +138,30 @@ def word_split_reverse(input_file: str, start_pos: int, end_pos: int):
                 break
 
             # 分词
-            word_list = jieba.cut_for_search(tmp_word.replace("\n", ""))
+            word = word.replace("\n", "").replace("\r", "")
+            stem_list = jieba.cut_for_search(word)
 
             # 分词过滤结果
-            word_filter_arr = []
+            stem_filter_arr = []
 
             # 过滤停用词
-            for word in word_list:
-                if word in stop_word_dict:
+            for stem in stem_list:
+                if stem in stop_word_dict:
                     continue
-
-                word_index_arr = word_reverse_index.get(word)
+                # 倒排索引
+                word_index_arr = reverse_index.get(stem)
+                pos = str(cur_pos)
                 if word_index_arr:
-                    word_index_arr.append(cur_pos)
+                    word_index_arr.append(pos)
                 else:
-                    word_reverse_index[word] = [cur_pos]
-
-                word_filter_arr.append(word)
+                    reverse_index[stem] = [pos]
+                # 有效分词
+                stem_filter_arr.append(stem)
 
-            if len(word_filter_arr) == 0:
-                word_arr_list.append([])
+            if len(stem_filter_arr) == 0:
+                word_list.append(word)
             else:
-                word_arr_list.append(word_filter_arr)
-
-    return start_pos, word_arr_list, word_reverse_index
-
-
-def init_process(max_conns: int, max_threads: int, file_path: str):
-    """
-    初始化进程
-    :param max_conns: redis最大连接数量
-    :param max_threads: 线程最大数量
-    :param file_path: 输出文件路径
-    :return:
-    """
-    # redis缓存池 初始化
-    global redis_pool
-    redis_pool = redis.ConnectionPool(host='127.0.0.1', port=6379, max_connections=max_conns)
-
-    global thread_pool
-    thread_pool = ThreadPoolExecutor(max_threads, initializer=init_thread, initargs=(file_path,))
-
-
-def agg_word_process(agg_threshold: float, start_pos: int, end_pos: int, final_pos: int,
-                     skip_line: int):
-    """
-    长尾词聚合处理
-    :param agg_threshold: 聚合阈值
-    :param start_pos: 任务处理开始边界（包含）
-    :param end_pos: 任务处理结束边界（不包含）
-    :param final_pos: 总任务边界
-    :param skip_line: 进度条显示位置
-    :return:
-    """
+                stem_filter_arr.insert(0, word)
+                word_list.append(",".join(stem_filter_arr))
 
-    # 进度长度
-    process_len = 0
-    if end_pos == -1:
-        process_len = final_pos - start_pos
-    else:
-        process_len = end_pos - start_pos
-
-    with tqdm(total=process_len, desc='子进程-%s：文本聚合进度' % os.getpid(), unit='份', unit_scale=True,
-              position=skip_line) as pbar:
-
-        thread_futures = [thread_pool.submit(agg_word_thread, main_word_position, agg_threshold) for main_word_position
-                          in
-                          range(start_pos, end_pos)]
-
-        for t_future in as_completed(thread_futures):
-            t_result = t_future.result()
-            # 更新发呆进度
-            pbar.update(1)
-
-    return
-
-
-def init_thread(file_path: str):
-    """
-    聚合线程初始化
-    :param file_path: 输出文件路径
-    :return:
-    """
-    # 初始化redis客户端
-    local_var.redis_cache = redis.StrictRedis(connection_pool=redis_pool)
-    # 初始化redis管道
-    local_var.redis_pipeline = local_var.redis_cache.pipeline(transaction=False)
-
-    # 生成临时结果文件
-    word_agg_file = os.path.join(file_path,
-                                 FILE_LONG_TAIL_MERGE_AGG_PID % (os.getpid(), threading.current_thread().ident))
-    local_var.file_writer = open(word_agg_file, "w", encoding=CHARSET_UTF_8)
-
-    # 已使用位图副本
-    local_var.unused_bitmap = bitarray()
-
-    # 从倒排索引中获取候选词的位置索引
-    local_var.candidate_position_set = set()
-
-    # 结果列表
-    local_var.result_list = []
-
-
-def agg_word_thread(main_word_position: int, agg_threshold: float):
-    try:
-        # 获取已使用位图副本
-        local_var.unused_bitmap.frombytes(local_var.redis_cache.get(CACHE_UNUSED_BITMAP))
-
-        # 判断主词是否为已使用，是则跳过，否则设置为已使用
-        if local_var.unused_bitmap[main_word_position]:
-            return
-        else:
-            local_var.redis_cache.setbit(CACHE_UNUSED_BITMAP, main_word_position, 1)
-            local_var.unused_bitmap[main_word_position] = 1
-
-        # 获取主词和对应的词根
-        local_var.redis_pipeline.hget(CACHE_WORD, main_word_position)
-        local_var.redis_pipeline.hget(CACHE_WORD_STEM, main_word_position)
-        main_result = local_var.redis_pipeline.execute()
-        main_word = main_result[0]
-        main_word_stem = main_result[1]
-
-        # 如果存在为空则返回
-        if not main_word or not main_word_stem:
-            return
-
-        main_word_stem_list = main_word_stem.decode(CHARSET_UTF_8).split(",")
-
-        # 从倒排索引获取长尾词位置
-        temp_candidate_position_list = local_var.redis_cache.hmget(CACHE_WORD_REVERSE_INDEX, main_word_stem_list)
-        for temp_candidate_position in temp_candidate_position_list:
-            if not temp_candidate_position:
-                continue
-            # 排除已聚合
-            for candidate_position in temp_candidate_position.decode(CHARSET_UTF_8).split(","):
-                if local_var.unused_bitmap[int(candidate_position)]:
-                    continue
-                local_var.candidate_position_set.add(candidate_position)
-
-        # 没有找到需要计算的候选词则跳过
-        if not local_var.candidate_position_set:
-            return
-
-        # 从缓存获取关键词列表、分词列表，如果为空则跳过
-        local_var.redis_pipeline.hmget(CACHE_WORD, local_var.candidate_position_set)
-        local_var.redis_pipeline.hmget(CACHE_WORD_STEM, local_var.candidate_position_set)
-        candidate_result = local_var.redis_pipeline.execute()
-        candidate_word_cache_list = candidate_result[0]
-        candidate_word_stem_cache_list = candidate_result[1]
-        if not candidate_word_cache_list or not candidate_word_stem_cache_list:
-            return
-
-        # 延后编码成字符，以防前面直接返回
-        main_word = main_word.decode(CHARSET_UTF_8)
-
-        # 计算相似度
-        for candidate_position in range(len(local_var.candidate_position_set)):
-
-            # 获取关键词、分词，如果存在为空则跳过
-            candidate_word = candidate_word_cache_list[int(candidate_position)]
-            if not candidate_word:
-                continue
-            candidate_word_stem = candidate_word_stem_cache_list[int(candidate_position)]
-            if not candidate_word_stem:
-                continue
-            candidate_word = candidate_word.decode(CHARSET_UTF_8)
-            candidate_word_stem_list = candidate_word_stem.decode(CHARSET_UTF_8).split(",")
-
-            # 计算相关性
-            try:
-                val = utils.cal_cos_sim(main_word, main_word_stem_list, candidate_word,
-                                        candidate_word_stem_list)
-                if val >= agg_threshold:
-                    local_var.redis_cache.setbit(CACHE_UNUSED_BITMAP, candidate_position, 1)
-                    local_var.result_list.append(candidate_word)
-            except Exception as e:
-                logging.error("主关键词：%s 发生异常，涉及的副关键词信息-关键词：%s，分词：%s" % (
-                    main_word, candidate_word, candidate_word_stem_list), e)
-
-        # 保存结果
-        if not local_var.result_list:
-            return
-        local_var.file_writer.write("%s\n" % main_word)
-        for candidate_word in local_var.result_list:
-            local_var.file_writer.write("%s\n" % candidate_word)
-        local_var.file_writer.write("\n")
-
-    except Exception as e:
-        logging.error("子进程发生异常", e)
-    finally:
-        # 清除容器数据
-        local_var.candidate_position_set.clear()
-        local_var.result_list.clear()
-        local_var.unused_bitmap.clear()
-
-    return
+    return start_pos, word_list, reverse_index

src/money.py

@@ -6,7 +6,7 @@ import zipfile
 import jieba
 
 import utils
-from agg import agg_word
+from agg import prepare_word_split_and_reverse_index
 from constant import FILE_LONG_TAIL_MERGE
 
 # 文件后缀：长尾词.txt
@@ -133,8 +133,8 @@ if __name__ == "__main__":
     filePath = "../data/test"
     # extract_word_from_5118(filePath)
     # merge_word(filePath)
-    # prepare_word_split_and_reverse_index(filePath)
-    agg_word(filePath)
+    prepare_word_split_and_reverse_index(filePath)
+    # agg_word(filePath)
     # word_split_statistics(file_path)
     # tasks = utils.avg_split_task(100, 12, 1)
     # 两者计算余弦值等于：0.8