修复部分bug #34

README.md

@@ -16,6 +16,8 @@
 <details>
 <summary><strong>更新日志(点击展开)：</strong></summary>
 
+* 2023.12.03 增加分析聊天记录的功能，生成词云、绘制折线图等
+* 2023.12.03 修复部分bug,更改获取wx文件夹方式 [#34](https://github.com/xaoyaoo/PyWxDump/issues/34)
 * 2023.12.01 为exe添加图标
 * 2023.11.30 优化命令行界面
 * 2023.11.29 添加异形wxid获取方式，添加用户路径自动获取，重建说明文档，对新手更友好

pywxdump/analyse/analyser.py

@@ -0,0 +1,370 @@
+# -*- coding: utf-8 -*-#
+# -------------------------------------------------------------------------------
+# Name:         analyser.py
+# Description:  
+# Author:       xaoyaoo
+# Date:         2023/12/01
+# -------------------------------------------------------------------------------
+import sqlite3
+import time
+from collections import Counter
+import pandas as pd
+
+from pywxdump.analyse import parse_xml_string
+
+
+def read_msgs(MSG_path, selected_talker=None, start_time=time.time() * 3600 * 24 * 365, end_time=time.time()):
+    """
+    读取消息内容-MSG.db 包含IsSender，StrContent，StrTalker，ype，SubType，CreateTime，MsgSvrID
+    :param MSG_path: MSG.db 路径
+    :param selected_talker: 选中的聊天对象
+    :param start_time: 开始时间 时间戳10位
+    :param end_time: 结束时间 时间戳10位
+    :return:
+    """
+    type_name_dict = {
+        1: {0: "文本"},
+        3: {0: "图片"},
+        34: {0: "语音"},
+        43: {0: "视频"},
+        47: {0: "动画表情"},
+        49: {0: "文本", 1: "类文本消息", 5: "卡片式链接", 6: "文件", 8: "上传的GIF表情",
+             19: "合并转发聊天记录", 33: "分享的小程序", 36: "分享的小程序", 57: "带有引用的文本",
+             63: "视频号直播或回放等",
+             87: "群公告", 88: "视频号直播或回放等", 2000: "转账消息", 2003: "红包封面"},
+        50: {0: "语音通话"},
+        10000: {0: "系统通知", 4: "拍一拍", 8000: "系统通知"}
+    }
+
+    # 连接 MSG_ALL.db 数据库，并执行查询
+    db1 = sqlite3.connect(MSG_path)
+    cursor1 = db1.cursor()
+
+    if isinstance(start_time, str):
+        start_time = time.mktime(time.strptime(start_time, "%Y-%m-%d %H:%M:%S"))
+    if isinstance(end_time, str):
+        end_time = time.mktime(time.strptime(end_time, "%Y-%m-%d %H:%M:%S"))
+
+    if selected_talker is None or selected_talker == "":  # 如果 selected_talker 为 None，则查询全部对话
+        cursor1.execute(
+            "SELECT MsgSvrID,IsSender, StrContent, StrTalker, Type, SubType,CreateTime FROM MSG WHERE CreateTime>=? AND CreateTime<=? ORDER BY CreateTime ASC",
+            (start_time, end_time))
+    else:
+        cursor1.execute(
+            "SELECT MsgSvrID,IsSender, StrContent, StrTalker, Type, SubType,CreateTime FROM MSG WHERE StrTalker=? AND CreateTime>=? AND CreateTime<=? ORDER BY CreateTime ASC",
+            (selected_talker, start_time, end_time))
+    result1 = cursor1.fetchall()
+    cursor1.close()
+    db1.close()
+
+    def get_emoji_cdnurl(row):
+        if row["type_name"] == "动画表情":
+            parsed_content = parse_xml_string(row["StrContent"])
+            if isinstance(parsed_content, dict) and "emoji" in parsed_content:
+                return parsed_content["emoji"].get("cdnurl", "")
+        return row["content"]
+
+    init_data = pd.DataFrame(result1, columns=["MsgSvrID", "IsSender", "StrContent", "StrTalker", "Type", "SubType",
+                                               "CreateTime"])
+    init_data["CreateTime"] = pd.to_datetime(init_data["CreateTime"], unit="s")
+    init_data["AdjustedTime"] = init_data["CreateTime"] - pd.Timedelta(hours=4)
+    init_data["AdjustedTime"] = init_data["AdjustedTime"].dt.strftime("%Y-%m-%d %H:%M:%S")
+    init_data["CreateTime"] = init_data["CreateTime"].dt.strftime("%Y-%m-%d %H:%M:%S")
+    init_data["type_name"] = init_data.apply(lambda x: type_name_dict.get(x["Type"], {}).get(x["SubType"], "未知"),
+                                             axis=1)
+    init_data["content"] = init_data.apply(lambda x: x["StrContent"] if x["type_name"] == "文本" else "", axis=1)
+    init_data["content"] = init_data.apply(get_emoji_cdnurl, axis=1)
+
+    init_data["content_len"] = init_data.apply(lambda x: len(x["content"]) if x["type_name"] == "文本" else 0, axis=1)
+
+    chat_data = init_data[
+        ["MsgSvrID", "IsSender", "StrTalker", "type_name", "content", "content_len", "CreateTime", "AdjustedTime"]]
+
+    return True, chat_data
+
+
+# 绘制直方图
+def draw_hist_all_count(chat_data, out_path="", is_show=False):
+    try:
+        import matplotlib.pyplot as plt
+    except ImportError as e:
+        print("error", e)
+        raise ImportError("请安装matplotlib库")
+    plt.rcParams['font.sans-serif'] = ['SimHei']
+    plt.rcParams['axes.unicode_minus'] = False
+
+    type_count = Counter(chat_data["type_name"])
+
+    # 对type_count按值进行排序，并返回排序后的结果
+    sorted_type_count = dict(sorted(type_count.items(), key=lambda item: item[1], reverse=True))
+
+    plt.figure(figsize=(12, 8))
+    plt.bar(range(len(sorted_type_count)), list(sorted_type_count.values()), tick_label=list(sorted_type_count.keys()))
+    plt.title("消息类型分布图")
+    plt.xlabel("消息类型")
+    plt.ylabel("数量")
+
+    # 设置x轴标签的旋转角度为45度
+    plt.xticks(rotation=-45)
+
+    # 在每个柱上添加数字标签
+    for i, v in enumerate(list(sorted_type_count.values())):
+        plt.text(i, v, str(v), ha='center', va='bottom')
+
+    if out_path != "":
+        plt.savefig(out_path)
+    if is_show:
+        plt.show()
+    plt.close()
+
+
+# 按照interval绘制折线图
+def draw_line_type_name(chat_data, interval="W", type_name_list=None, out_path="", is_show=False):
+    """
+    绘制折线图，横轴为时间，纵轴为消息数量，不同类型的消息用不同的颜色表示
+    :param chat_data:
+    :param interval:
+    :param type_name_list: 消息类型列表，按照列表中的顺序绘制折线图 可选：全部类型、发送、接收、总字数、发送字数、接收字数、其他类型
+    :param out_path:
+    :param is_show:
+    :return:
+    """
+    if type_name_list is None:
+        type_name_list = ["全部类型", "发送", "接收"] + ["总字数", "发送字数", "接收字数"]
+        # type_name_list = ["总字数", "发送字数", "接收字数"]
+
+    try:
+        import matplotlib.pyplot as plt
+        import pandas as pd
+    except ImportError as e:
+        print("error", e)
+        raise ImportError("请安装matplotlib库")
+    plt.rcParams['font.sans-serif'] = ['SimHei']
+    plt.rcParams['axes.unicode_minus'] = False
+
+    chat_data["CreateTime"] = pd.to_datetime(chat_data["CreateTime"])
+    chat_data["AdjustedTime"] = pd.to_datetime(chat_data["AdjustedTime"])
+
+    # interval = interval.lower()
+    interval_dict = {"day": "%Y-%m-%d", "month": "%Y-%m", "year": "%Y", "week": "%Y-%W",
+                     "d": "%Y-%m-%d", "m": "%Y-%m", "y": "%Y", "W": "%Y-%W"
+                     }
+    if interval not in interval_dict:
+        raise ValueError("interval参数错误，可选值为day、month、year、week")
+    chat_data["interval"] = chat_data["AdjustedTime"].dt.strftime(interval_dict[interval])
+
+    # 根据chat_data["interval"]最大值和最小值，生成一个时间间隔列表
+    interval_list = pd.date_range(chat_data["AdjustedTime"].min(), chat_data["AdjustedTime"].max(), freq=interval)
+    interval_list = interval_list.append(pd.Index([interval_list[-1] + pd.Timedelta(days=1)]))  # 最后一天加一天
+
+    # 构建数据集
+    # interval type_name1 type_name2 type_name3
+    # 2021-01 文本数量 其他类型数量 其他类型数量
+    # 2021-02 文本数量 其他类型数量 其他类型数量
+    type_data = pd.DataFrame(columns=["interval"] + list(chat_data["type_name"].unique()))
+    type_data["interval"] = interval_list.strftime(interval_dict[interval])
+    type_data = type_data.set_index("interval")
+    for type_name in chat_data["type_name"].unique():
+        type_data[type_name] = chat_data[chat_data["type_name"] == type_name].groupby("interval").size()
+    type_data["全部类型"] = type_data.sum(axis=1)
+    type_data["发送"] = chat_data[chat_data["IsSender"] == 1].groupby("interval").size()
+    type_data["接收"] = chat_data[chat_data["IsSender"] == 0].groupby("interval").size()
+
+    type_data["总字数"] = chat_data.groupby("interval")["content_len"].sum()
+    type_data["发送字数"] = chat_data[chat_data["IsSender"] == 1].groupby("interval")["content_len"].sum()
+    type_data["接收字数"] = chat_data[chat_data["IsSender"] == 0].groupby("interval")["content_len"].sum()
+
+    type_data = type_data.fillna(0)
+    # 调整typename顺序，使其按照总数量排序，只要最大的5个
+    type_data = type_data.reindex(type_data.sum().sort_values(ascending=False).index, axis=1)
+    if type_name_list is not None:
+        type_data = type_data[type_name_list]
+    else:
+        type_data = type_data.iloc[:, :5]
+
+    # if interval == "W" or interval == "week":  # 改为当前周的周一的日期
+    #     #
+
+    plt.figure(figsize=(12, 8))
+
+    # 绘制折线图
+    for type_name in type_data.columns:
+        plt.plot(type_data.index, type_data[type_name], label=type_name)
+
+    # 设置x轴标签的旋转角度为45度
+    plt.xticks(rotation=-45)
+    # 设置标题、坐标轴标签、图例等信息
+    plt.title("消息类型分布图")
+    plt.xlabel("时间")
+    plt.ylabel("数量")
+
+    plt.legend(loc="upper right")  # 设置图例位置
+
+    # 显示图形
+    if out_path != "":
+        plt.savefig(out_path)
+    if is_show:
+        plt.tight_layout()
+        plt.show()
+    plt.close()
+
+
+
+def wordcloud_generator(chat_data, interval="m", stopwords=None, out_path="", is_show=False, bg_img=None,
+                        font="C:\Windows\Fonts\simhei.ttf"):
+    """
+    词云
+    :param is_show: 是否显示
+    :param img_path: 背景图片路径
+    :param text: 文本
+    :param font: 字体路径
+    :return:
+    """
+    try:
+        from wordcloud import WordCloud, ImageColorGenerator
+        import wordcloud
+        import jieba
+        import numpy as np
+        import matplotlib.pyplot as plt
+        from matplotlib.font_manager import fontManager
+        import pandas as pd
+        import codecs
+        import re
+        from imageio import imread
+    except ImportError as e:
+        print("error", e)
+        raise ImportError("请安装wordcloud,jieba,numpy,matplotlib,pillow库")
+
+    plt.rcParams['font.sans-serif'] = ['SimHei']
+    plt.rcParams['axes.unicode_minus'] = False
+
+    chat_data["CreateTime"] = pd.to_datetime(chat_data["CreateTime"])
+    chat_data["AdjustedTime"] = pd.to_datetime(chat_data["AdjustedTime"])
+
+    # interval = interval.lower()
+    interval_dict = {"day": "%Y-%m-%d", "month": "%Y-%m", "year": "%Y", "week": "%Y-%W",
+                     "d": "%Y-%m-%d", "m": "%Y-%m", "y": "%Y", "W": "%Y-%W"
+                     }
+    if interval not in interval_dict:
+        raise ValueError("interval参数错误，可选值为day、month、year、week")
+    chat_data["interval"] = chat_data["AdjustedTime"].dt.strftime(interval_dict[interval])
+
+    # 根据chat_data["interval"]最大值和最小值，生成一个时间间隔列表
+    interval_list = pd.date_range(chat_data["AdjustedTime"].min(), chat_data["AdjustedTime"].max(), freq=interval)
+    interval_list = interval_list.append(pd.Index([interval_list[-1] + pd.Timedelta(days=1)]))  # 最后一天加一天
+
+    # 构建数据集
+    # interval text_all text_sender text_receiver
+    # 2021-01 文本\n合并 聊天记录\n文本\n合并 聊天记录\n文本\n合并 聊天记录\n
+    def merage_text(x):
+        pattern = re.compile("(\[.+?\])")  # 匹配表情
+        rt = "\n".join(x)
+        rt = pattern.sub('', rt).replace("\n", " ")
+        return rt
+
+    chat_data["content"] = chat_data.apply(lambda x: x["content"] if x["type_name"] == "文本" else "", axis=1)
+
+    text_data = pd.DataFrame(columns=["interval", "text_all", "text_sender", "text_receiver"])
+    text_data["interval"] = interval_list.strftime(interval_dict[interval])
+    text_data = text_data.set_index("interval")
+    # 使用“\n”合并
+    text_data["text_all"] = chat_data.groupby("interval")["content"].apply(merage_text)
+    text_data["text_sender"] = chat_data[chat_data["IsSender"] == 1].groupby("interval")["content"].apply(merage_text)
+    text_data["text_receiver"] = chat_data[chat_data["IsSender"] == 0].groupby("interval")["content"].apply(merage_text)
+
+    def gen_img(texts,out_path,is_show,bg_img,title=""):
+        words = jieba.lcut(texts)
+        res = [word for word in words if word not in stopwords and word.replace(" ", "") != "" and len(word) > 1]
+        count_dict = dict(Counter(res))
+
+        if bg_img:
+            bgimg = imread(open(bg_img, 'rb'))
+            # 获得词云对象，设定词云背景颜色及其图片和字体
+            wc = WordCloud(background_color='white', mask=bgimg, font_path='simhei.ttf', mode='RGBA', include_numbers=False,
+                           random_state=0)
+        else:
+            # 如果你的背景色是透明的，请用这两条语句替换上面两条
+            bgimg = None
+            wc = WordCloud(background_color='white', mode='RGBA', font_path='simhei.ttf', include_numbers=False,
+                           random_state=0,width=500, height=500)  # 如果不指定中文字体路径，词云会乱码
+        wc = wc.fit_words(count_dict)
+
+        fig = plt.figure(figsize=(8, 8))
+        fig.suptitle(title, fontsize=26)
+        ax = fig.subplots()
+
+        ax.imshow(wc)
+        ax.axis('off')
+
+        if out_path != "":
+            plt.savefig(out_path)
+        if is_show:
+            plt.show()
+        plt.close()
+
+    for i in text_data.index:
+        out_path = f"out/img_{i}.png"
+        gen_img(text_data["text_all"][i], out_path=out_path, is_show=False, bg_img=bg_img, title=f"全部({i})")
+        # gen_img(text_data["text_sender"][i], out_path="", is_show=is_show, bg_img=bg_img, title=f"发送_{i}")
+        # gen_img(text_data["text_receiver"][i], out_path="", is_show=is_show, bg_img=bg_img, title=f"接收_{i}")
+        # time.sleep(1)
+
+# 情感分析
+def sentiment_analysis(chat_data, stopwords="", out_path="", is_show=False, bg_img=None):
+    try:
+        from snownlp import SnowNLP
+        import pandas as pd
+        import matplotlib.pyplot as plt
+        import seaborn as sns
+
+    except ImportError as e:
+        print("error", e)
+        raise ImportError("请安装snownlp,pandas,matplotlib,seaborn库")
+
+    sns.set_style('white', {'font.sans-serif': ['simhei', 'FangSong']})
+
+    chats = []
+    for row in chat_data:
+        if row["type_name"] != "文本" or row["content"] == "":
+            continue
+        chats.append(row)
+
+    scores = []
+    for row in chats:
+        s = SnowNLP(row["content"])
+        scores.append(s.sentiments)
+
+    def draw(data):
+        df = pd.DataFrame({'Sentiment Score': data})
+        plt.figure(figsize=(8, 6))
+        sns.histplot(data=df, x='Sentiment Score', kde=True)
+        plt.title("Sentiment Analysis")
+        plt.xlabel("Sentiment Score")
+        plt.ylabel("Frequency")
+
+        if out_path != "":
+            plt.savefig(out_path)
+        if is_show:
+            plt.show()
+        plt.close()
+
+    draw(scores)
+
+
+if __name__ == '__main__':
+    MSG_PATH = r""
+    selected_talker = "wxid_"
+    start_time = time.time() - 3600 * 24 * 50000
+    end_time = time.time()
+    code, chat_data = read_msgs(MSG_PATH, selected_talker, start_time, end_time)
+    # print(chat_data)
+    # code, data, classify_count, all_type_count = merge_chat_data(chat_data, interval="month")
+    # draw_hist_all_count(chat_data, is_show=True)  # 绘制直方图 消息类型分布图
+    # draw_line_type_name(chat_data, is_show=True)  # 绘制折线图 消息类型分布图
+
+    # bg_img = 'img.png'
+    stopwords = ['的', '了', '是', '在', '我', '有', '和', '就', '不', '人', '都', '一', '一个', '上', '也', '很', '到',
+                 '说', '要',
+                 '去', '你', '会', '着', '没有', '看', '好', '自己', '这']
+    wordcloud_generator(chat_data, stopwords=stopwords, out_path="", is_show=True)
+    # sentiment_analysis(chat_data)

pywxdump/command.py

@@ -114,7 +114,7 @@ class MainDecrypt():
         out_path = args.out_path
 
         if not os.path.exists(db_path):
-            print("[-] 数据库路径不存在")
+            print(f"[-] 数据库路径不存在：{db_path}")
             return
 
         if not os.path.exists(out_path):

pywxdump/wx_info/get_wx_info.py

@@ -78,14 +78,17 @@ def get_info_filePath(wxid="all"):
         winreg.CloseKey(key)
         w_dir = value
     except Exception as e:
-        w_dir = "MyDocument:"
+        # 获取文档实际目录
-
+        try:
-    if w_dir == "MyDocument:":
+            # 打开注册表路径
-        profile = os.path.expanduser("~")
+            key = winreg.OpenKey(winreg.HKEY_CURRENT_USER,"Software\\Microsoft\\Windows\\CurrentVersion\\Explorer\\Shell Folders")
-        msg_dir = os.path.join(profile, "Documents", "WeChat Files")
+            documents_path = winreg.QueryValueEx(key, "Personal")[0]# 读取文档实际目录路径
-    else:
+            winreg.CloseKey(key) # 关闭注册表
-        msg_dir = os.path.join(w_dir, "WeChat Files")
+            w_dir = documents_path
-
+        except Exception as e:
+            profile = os.path.expanduser("~")
+            w_dir = os.path.join(profile, "Documents")
+    msg_dir = os.path.join(w_dir, "WeChat Files")
     if wxid == "all" and os.path.exists(msg_dir):
         return msg_dir