A new function, many typos fixing, and code re-formatting

.gitignore

@@ -130,4 +130,5 @@ dmypy.json
 
 # 自定义
 result
-output
+output
+.idea/*

README.md

@@ -8,6 +8,7 @@
 2. 哪些进程在你不用的时候突然占用大量资源
 3. 监听系统进程资源占用情况
 4. 关注指定程序的资源变动情况
+5. 通过邮件将监控结果发送给用户
 
 理论上该程序跨平台，我在编码的时候也尽力使用兼容性更强的代码，所以即便出现了兼容性问题也应该很容易定位和解决。
 
@@ -39,7 +40,7 @@ python start.py -h
 
 ```text
 $ python start.py -h
-usage: start.py [-h] [-o OUTPUT] [-i INTERVAL] [-f [FILTER ...]]
+usage: start.py [-h] [-o OUTPUT] [-i INTERVAL] [-f [FILTER ...]] [-m]
 
 optional arguments:
   -h, --help            show this help message and exit
@@ -49,6 +50,17 @@ optional arguments:
                         监听时间间隔(毫秒)
   -f [FILTER ...], --filter [FILTER ...]
                         限制监听范围，为进程名(如explorer.exe)
+  -m False/True, --mail False/True
+                        是否使用邮件通知
+  -a ADDRESS, --address ADDRESS
+                        邮件发送方地址
+  -n NAME, --name NAME
+                        邮件发送方地址
+  -p PASSWORD, --password PASSWORD
+                        邮件发送方密钥
+  -r RECEIVER, --receiver RECEIVER
+                        邮件接收方地址
+
 ```
 
 #### 监听所有的进程
@@ -89,6 +101,14 @@ python start.py -f notepad.exe Taskmgr.exe -i 1000
 
 默认情况下会在当前目录的`output`目录下生成结果，里面主要有两项：`summury.txt`文件和`process`文件夹。前者主要记录了一些宏观统计信息。后者则包含了众多被监听的进程数据。数据以`html`的形式提供，每个文件名均为`进程名.html`格式，每个网页内包含了三张图表，可自行查看。
 
+#### 邮件通知
+
+该功能基于[iMail](https://github.com/mtics/iMail)
+
+- 首先需要用户通过指令`-m True`或者`--mail True`来允许使用邮件通知功能
+- 然后用户需要通过指令进行相关配置，详情请见代码。
+- 目前通知会在用户停止监听后，将相关输出发送至指定邮箱。
+
 ## 如何贡献
 
 你可以提交`Issue`或者`Fork+PR`的方式提出你的想法和修改，我会不定期的查看并作出修改。当然，你也可以完全根据项目所属协议进行合法操作。

common.py → SRM/common.py

@@ -1,12 +1,11 @@
-
 # Bytes -> KB MB GB
 def trans_B2KB(val):
     return float(val) / 1024
 
 
 def trans_B2MB(val):
-    return trans_B2KB(val)/1024
+    return trans_B2KB(val) / 1024
 
 
 def trans_B2GB(val):
-    return trans_B2MB(val)/1024
+    return trans_B2MB(val) / 1024

exporter.py → SRM/exporter.py

@@ -1,42 +1,53 @@
+import datetime
+import os
+
 from pyecharts import charts
 from pyecharts import options as opts
-import os
-import datetime
+
+
+def resource_chart(page_title, title, subtitle, x_data, y_data, y_label=''):
+    line_chart = charts.Line(
+        opts.InitOpts(page_title=page_title)
+    ).set_global_opts(
+        title_opts=opts.TitleOpts(title=title, subtitle=subtitle)
+    )
+
+    line_chart.add_xaxis(xaxis_data=x_data)
+    line_chart.add_yaxis(y_label,
+                         y_axis=y_data,
+                         markline_opts=opts.MarkLineOpts(
+                             data=[opts.MarkLineItem(type_="max"), opts.MarkLineItem(type_="average")]),
+                         label_opts=opts.LabelOpts(is_show=False)
+                         )
+
+    return line_chart
 
 
 def exportCharts(process_name, data, output_path):
     page = charts.Page(
         layout=charts.Page.DraggablePageLayout)
 
     page.page_title = "{} 统计信息".format(process_name)
-    line_cpu = charts.Line(
-        opts.InitOpts(page_title="{} CPU占用(%)".format(process_name)))\
-        .set_global_opts(title_opts=opts.TitleOpts(title="CPU占用信息", subtitle="单位: %"))
-    line_cpu.add_xaxis(xaxis_data=data["Time"])
-    line_cpu.add_yaxis("CPU占用(%)", y_axis=data["CPU"], markline_opts=opts.MarkLineOpts(
-        data=[opts.MarkLineItem(type_="max"), opts.MarkLineItem(type_="average")]), label_opts=opts.LabelOpts(is_show=False))
-
-    line_mem = charts.Line(
-        opts.InitOpts(page_title="{} 内存占用(MB)".format(process_name)))\
-        .set_global_opts(title_opts=opts.TitleOpts(title="内存占用信息", subtitle="单位: MB"))
-    line_mem.add_xaxis(xaxis_data=data["Time"])
-    line_mem.add_yaxis("内存(MB)", y_axis=data["MEM"], markline_opts=opts.MarkLineOpts(
-        data=[opts.MarkLineItem(type_="max"), opts.MarkLineItem(type_="average")]), label_opts=opts.LabelOpts(is_show=False))
-
-    line_io = charts.Line(
-        opts.InitOpts(page_title="{} IO写(MB)".format(process_name)))\
-        .set_global_opts(title_opts=opts.TitleOpts(title="IO信息", subtitle="单位: MB"))
-    line_io.add_xaxis(xaxis_data=data["Time"])
-    line_io.add_yaxis("IO写(MB)", y_axis=data["IO"], markline_opts=opts.MarkLineOpts(
-        data=[opts.MarkLineItem(type_="max"), opts.MarkLineItem(type_="average")]), label_opts=opts.LabelOpts(is_show=False))
+
+    line_cpu = resource_chart(page_title="{} CPU占用(%)".format(process_name),
+                              title="CPU占用信息", subtitle="单位: %",
+                              x_data=data["Time"], y_data=data["CPU"], y_label="CPU占用(%)")
+
+    line_mem = resource_chart(page_title="{} 内存占用(MB)".format(process_name),
+                              title="内存占用信息", subtitle="单位: MB",
+                              x_data=data["Time"], y_data=data["MEM"], y_label="内存(MB)")
+
+    line_io = resource_chart(page_title="{} IO写(MB)".format(process_name),
+                             title="IO信息", subtitle="单位: MB",
+                             x_data=data["Time"], y_data=data["IO"], y_label="IO写(MB)")
 
     page.add(line_cpu, line_mem, line_io)
     page.render(os.path.join(output_path, "{}.html".format(process_name)))
 
 
 def export(data_dict: dict, output_path: str, interval):
     process_dat_path = os.path.join(output_path, "process")
-    summury_txt_path = os.path.join(output_path, "summury.txt")
+    summary_txt_path = os.path.join(output_path, "summary.txt")
 
     os.makedirs(process_dat_path, exist_ok=True)
 
@@ -50,8 +61,8 @@ def export(data_dict: dict, output_path: str, interval):
         stat = pm.getStatistic()
         exportCharts(process_name, stat, process_dat_path)
 
-        # 统计summury
-        if(stat["END_TIME"] != None):
+        # 统计summary
+        if stat["END_TIME"] != None:
             close_process_set.add(process_name)
 
             if stop_timestamp < stat["END_TIME"]:
@@ -67,7 +78,7 @@ def export(data_dict: dict, output_path: str, interval):
             # 之后启动的
             start_process_set.add(process_name)
 
-    with open(summury_txt_path, "w") as f:
+    with open(summary_txt_path, "w", encoding='utf-8') as f:
         f.write("======== 汇总 ========\n")
         f.write("报告时间:{}\n".format(datetime.datetime.now()))
         f.write("统计时间段：{} - {}\n".format(start_timestamp, stop_timestamp))

SRM/mail.py

@@ -0,0 +1,65 @@
+import glob
+import os
+
+import iMail
+
+
+class MAIL(object):
+
+    def __init__(self, args):
+
+        # the information for enable mailing
+        self.__sender = {
+            'host': args.mail_server,
+            'address': args.sender_addr,
+            'name': args.sender_name,
+            'pwd': args.pwd,
+            'receivers': args.receivers,
+        }
+
+        self.__output_path = args.output  # the path of outputs
+        self.__enable = args.mail  # whether the mailing system is enabled
+
+    def send_mail(self, subject='监控统计', content='', attachments=None):
+        """
+        Package process monitoring results and send them to users via email
+        """
+
+        # Create an email object for iMail
+        mail_system = iMail.EMAIL(host=self.__sender['host'], sender_addr=self.__sender['address'],
+                                  pwd=self.__sender['pwd'], sender_name=self.__sender['name'])
+
+        # Set the receiver list
+        mail_system.set_receiver(self.__sender['receivers'])
+
+        # New an email
+        mail_system.new_mail(subject=subject, encoding='utf-8')
+
+        # If user does not set the content,
+        #   use the content of 'summary.txt';
+        # Else, attach the file and sent it through email
+        if content == '':
+            with open(os.path.join(self.__output_path, 'summary.txt'), 'r', encoding='utf-8') as file:
+                mail_system.add_text(content=file.read())
+        else:
+            mail_system.add_text(content=content)
+            mail_system.attach_files(os.path.join(self.__output_path, 'summary.txt'))
+
+        # Attach all output files or the specified files
+        if attachments == None:
+            files = glob.glob(os.path.join(self, 'process/*'))
+            mail_system.attach_files(files)
+        else:
+            mail_system.attach_files(attachments)
+
+        mail_system.send_mail()
+
+    def mail(self, subject='监控统计', content='', attachments=None):
+
+        if self.__enable:
+            print("邮件发送中，请等待...")
+            try:
+                self.send_mail(subject, content, attachments)
+                print("邮件发送成功")
+            except Exception as e:
+                print("邮件发送失败: {}，请自行查看".format(e))

monitor.py → SRM/monitor.py

@@ -1,11 +1,12 @@
-import psutil
-import common
+import datetime
+import platform
 import threading
 import time
 from collections import defaultdict
-import datetime
-import exporter
-import platform
+
+import psutil
+
+from SRM import common, exporter
 
 
 def showSystemInfo():
@@ -30,9 +31,9 @@ def showSystemInfo():
 
 
 class ProcessMonitor:
-    '''
+    """
     进程监视器，根据进程名归并，即将子进程并入父进程计算
-    '''
+    """
 
     def __init__(self, process_name: str) -> None:
         self.__process_name = process_name
@@ -67,7 +68,7 @@ def getStatistic(self):
     def __monitorThread(self):
         process_map = {}
 
-        while(self.__is_running):
+        while self.__is_running:
             pid_num = 0
             cpu_loaded = 0.0
             mem = 0.0
@@ -79,7 +80,7 @@ def __monitorThread(self):
                     try:
                         process_map[pid] = psutil.Process(pid=pid)
                         process = process_map[pid]
-                        if(process.name() != self.__process_name):
+                        if process.name() != self.__process_name:
                             # 认为pid被复用了
                             continue
                     except psutil.NoSuchProcess as e:
@@ -103,7 +104,7 @@ def __monitorThread(self):
                 process_map.clear()
 
             self.__recordStat(cpu_loaded, mem, io)
-            time.sleep(self.__interval/1000)
+            time.sleep(self.__interval / 1000)
 
     def __clearStatistic(self):
         self.__statistic.clear()
@@ -128,11 +129,11 @@ def __init__(self) -> None:
         self.__thread = None
         self.__process_map = defaultdict(ProcessMonitor)  # 存放各种进程管理器
 
-    def start(self, interval, filter=set()):
+    def start(self, interval, thread_filter=set()):
         self.__is_running = True
         self.__interval = interval
         self.__thread = threading.Thread(
-            target=self.__threadFunc, args=(set(filter),))
+            target=self.__threadFunc, args=(set(thread_filter),))
         self.__thread.start()
 
     def export(self, data_path):
@@ -144,18 +145,18 @@ def stop(self):
         self.__is_running = False
         self.__thread.join()
 
-    def __threadFunc(self, filter):
-        '''
+    def __threadFunc(self, thread_filter):
+        """
         子线程函数，用于扫描系统所有的进程，并且归类。再将进程分发给子进程进行监听
-        '''
+        """
         # 开启子进程
-        while(self.__is_running):
+        while self.__is_running:
             for process_name, ids in self.__getProcessesInfo().items():
-                if(len(filter) > 0 and process_name not in filter):
+                if len(thread_filter) > 0 and process_name not in thread_filter:
                     continue
                 self.__distributeProcessName(process_name, ids)
 
-            time.sleep(self.__interval/1000)
+            time.sleep(self.__interval / 1000)
 
         # 取消所有线程和子进程
         for _, pm in self.__process_map.items():
@@ -184,6 +185,6 @@ def __distributeProcessName(self, process_name: str, ids: set):
         self.__process_map.get(process_name).setPidSet(ids)
 
     def __processMonitorFunc(self):
-        while(self.__is_running):
+        while self.__is_running:
             pass
         # 取消所有监听

requirements.txt

@@ -1,2 +1,3 @@
 psutil
-pyecharts
+pyecharts
+iMail