Psutil + Flask + Pyecharts + Bootstrap 开发动态可视化系统监控
psutil 是一个跨平台库（http://pythonhosted.org/psutil）能够获取到系统运行的进程和系统利用率（包括CPU、内存、磁盘、网络等）信息。主要用来做系统监控，性能分析，进程管理。支持 Linux、Mac OS、Windows 系统。
本文以 psutil 模块获取系统信息开发一个监控 Mac OS 系统的平台。
准备工作
技术选择
监控的系统是 Mac OS 系统
监控系统模块选择 psutil 模块
Web 框架选择的是 Flask 框架
前端 UI 选择的是 Bootstrap UI
动态可视化图表选择 Pyecharts 模块
安装 psutil
pip3 install psutil
安装 Flask、pyecharts、Bootstrap
Flask 的教程是在公众号文章：Web 开发 Flask 介绍
Pyecharts 的教程在公众号文章：Python 图表利器 pyecharts，按照官网 (http://pyecharts.org/#/zh-cn/web_flask) 文档整合 Flask 框架，并使用定时全量更新图表。
Bootstrap 是一个 前端的 Web UI，官网地址是 (https://v4.bootcss.com)
获取系统信息
CPU信息
通过 psutil 获取 CPU 信息
>>> import psutil# 获取当前 CPU 的利用率>>> psutil.cpu_percent()53.8# 获取当前 CPU 的用户/系统/空闲时间>>> psutil.cpu_times()scputimes(user=197483.49, nice=0.0, system=114213.01, idle=1942295.68)# 1/5/15 分钟之内的 CPU 负载>>> psutil.getloadavg()(7.865234375, 5.1826171875, 4.37353515625)# CPU 逻辑个数>>> psutil.cpu_count()4# CPU 物理个数>>> psutil.cpu_count(logical=False)2
在监控平台上每 2 秒请求 url 获取 CPU 负载，并动态显示图表
cpu_percent_dict = {}def cpu():# 当前时间now = time.strftime('%H:%M:%S', time.localtime(time.time()))# CPU 负载cpu_percent = psutil.cpu_percent()cpu_percent_dict[now] = cpu_percent# 保持在图表中 10 个数据if len(cpu_percent_dict.keys()) == 11:cpu_percent_dict.pop(list(cpu_percent_dict.keys())[0])def cpu_line() -> Line:cpu()# 全量更新 pyecharts 图表c = (Line().add_xaxis(list(cpu_percent_dict.keys())).add_yaxis('', list(cpu_percent_dict.values()), areastyle_opts=opts.AreaStyleOpts(opacity=0.5)).set_global_opts(title_opts=opts.TitleOpts(title = now + "CPU负载",pos_left = "center"),yaxis_opts=opts.AxisOpts(min_=0,max_=100,split_number=10,type_="value", name='%')))return c@app.route("/cpu")def get_cpu_chart():c = cpu_line()return c.dump_options_with_quotes()
示例结果
内存
通过 psutil 获取内存和交换区信息
# 系统内存信息 总内存/立刻可用给进程使用的内存/内存负载/已使用内存/空闲内存/当前正在使用或者最近使用的内存/未使用的内存/永久在内存>>> psutil.virtual_memory()svmem(total=8589934592, available=2610610176, percent=69.6, used=4251074560, free=387874816, active=2219110400, inactive=2069094400, wired=2031964160)# 交换区内存 总内存/使用的内存/空闲的内存/负载/系统从磁盘交换进来的字节数(累计)/系统从磁盘中交换的字节数（累积）>>> psutil.swap_memory()sswap(total=2147483648, used=834404352, free=1313079296, percent=38.9, sin=328911147008, sout=3249750016)
在监控平台上每 2 秒请求 url 获取内存负载，并动态显示图表
def memory():memory = psutil.virtual_memory()swap = psutil.swap_memory()# 在 Mac OS 上 未使用内存 = 总内存 - (空闲内存 + 未使用内存)return memory.total, memory.total - (memory.free + memory.inactive), memory.free + memory.inactive, swap.total, swap.used, swap.free, memory.percentdef memory_liquid() -> Gauge:mtotal, mused, mfree, stotal, sused, sfree, mpercent = memory()c = (Gauge().add("", [("", mpercent)]).set_global_opts(title_opts=opts.TitleOpts(title="内存负载", pos_left = "center")))return mtotal, mused, mfree, stotal, sused, sfree, c@app.route("/memory")def get_memory_chart():mtotal, mused, mfree, stotal, sused, sfree, c = memory_liquid()return jsonify({'mtotal': mtotal, 'mused': mused, 'mfree': mfree, 'stotal': stotal, 'sused': sused, 'sfree': sfree, 'liquid': c.dump_options_with_quotes()})
示例结果
磁盘
通过 psutil 获取磁盘大小、分区、使用率和磁盘IO
# 磁盘分区情况>>> psutil.disk_partitions()[sdiskpart(device='/dev/disk1s5', mountpoint='/', fstype='apfs', opts='ro,local,rootfs,dovolfs,journaled,multilabel'), sdiskpart(device='/dev/disk1s1', mountpoint='/System/Volumes/Data', fstype='apfs', opts='rw,local,dovolfs,dontbrowse,journaled,multilabel'), sdiskpart(device='/dev/disk1s4', mountpoint='/private/var/vm', fstype='apfs', opts='rw,local,dovolfs,dontbrowse,journaled,multilabel'), sdiskpart(device='/dev/disk1s3', mountpoint='/Volumes/Recovery', fstype='apfs', opts='rw,local,dovolfs,dontbrowse,journaled,multilabel')]# 磁盘的使用情况 磁盘总大小/已使用大小/空闲大小/负载>>> psutil.disk_usage('/')sdiskusage(total=250790436864, used=10872418304, free=39636717568, percent=21.5)# 磁盘IO 读取次数/写入次数/读取数据/写入数据/磁盘读取所花费的时间/写入磁盘所花费的时间>>> psutil.disk_io_counters()sdiskio(read_count=26404943, write_count=11097500, read_bytes=609467826688, write_bytes=464322912256, read_time=7030486, write_time=2681553)
在监控平台上每 2 秒请求 url 获取磁盘信息，并动态显示图表
disk_dict = {'disk_time':[], 'write_bytes': [], 'read_bytes': [], 'pre_write_bytes': 0, 'pre_read_bytes': 0, 'len': -1}def disk():disk_usage = psutil.disk_usage('/')disk_used = 0# 磁盘已使用大小 = 每个分区的总和partitions = psutil.disk_partitions()for partition in partitions:partition_disk_usage = psutil.disk_usage(partition[1])disk_used = partition_disk_usage.used + disk_usednow = time.strftime('%H:%M:%S', time.localtime(time.time()))count = psutil.disk_io_counters()read_bytes = count.read_byteswrite_bytes = count.write_bytes# 第一次请求if disk_dict['len'] == -1:disk_dict['pre_write_bytes'] = write_bytesdisk_dict['pre_read_bytes'] = read_bytesdisk_dict['len'] = 0return disk_usage.total, disk_used, disk_usage.free# 当前速率=现在写入/读取的总字节-前一次请求写入/读取的总字节disk_dict['write_bytes'].append((write_bytes - disk_dict['pre_write_bytes'])/1024)disk_dict['read_bytes'].append((read_bytes - disk_dict['pre_read_bytes'])/ 1024)disk_dict['disk_time'].append(now)disk_dict['len'] = disk_dict['len'] + 1# 把现在写入/读取的总字节放入前一个请求的变量中disk_dict['pre_write_bytes'] = write_bytesdisk_dict['pre_read_bytes'] = read_bytes# 保持在图表中 50 个数据if disk_dict['len'] == 51:disk_dict['write_bytes'].pop(0)disk_dict['read_bytes'].pop(0)disk_dict['disk_time'].pop(0)disk_dict['len'] = disk_dict['len'] - 1return disk_usage.total, disk_used, disk_usage.freedef disk_line() -> Line:total, used, free = disk()c = (Line(init_opts=opts.InitOpts(width="1680px", height="800px")).add_xaxis(xaxis_data=disk_dict['disk_time']).add_yaxis(series_name="写入数据",y_axis=disk_dict['write_bytes'],areastyle_opts=opts.AreaStyleOpts(opacity=0.5),linestyle_opts=opts.LineStyleOpts(),label_opts=opts.LabelOpts(is_show=False),).add_yaxis(series_name="读取数据",y_axis=disk_dict['read_bytes'],yaxis_index=1,areastyle_opts=opts.AreaStyleOpts(opacity=0.5),linestyle_opts=opts.LineStyleOpts(),label_opts=opts.LabelOpts(is_show=False),).extend_axis(yaxis=opts.AxisOpts(name_location="start",type_="value",is_inverse=True,axistick_opts=opts.AxisTickOpts(is_show=True),splitline_opts=opts.SplitLineOpts(is_show=True),name='KB/2S')).set_global_opts(title_opts=opts.TitleOpts(title="磁盘IO",pos_left="center",pos_top="top",),tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross"),legend_opts=opts.LegendOpts(pos_left="left"),xaxis_opts=opts.AxisOpts(type_="category", boundary_gap=False),yaxis_opts=opts.AxisOpts( type_="value", name='KB/2S'),).set_series_opts(axisline_opts=opts.AxisLineOpts(),))return total, used, free, c@app.route("/disk")def get_disk_chart():total, used, free, c = disk_line()return jsonify({'total': total, 'used': used, 'free': free, 'line': c.dump_options_with_quotes()})
示例结果
网卡
通过 psutil 获取网络接口和网络连接的信息
# 获取网络字节数和包的个数 发送的字节数/收到的字节数/发送的包数/收到的包数>>> psutil.net_io_counters()snetio(bytes_sent=9257984, bytes_recv=231398400, packets_sent=93319, packets_recv=189501, errin=0, errout=0, dropin=0, dropout=0)# 获取当前的网络连接 注意：net_connections() 需要用管理员权限运行 Python 文件>>> psutil.net_connections()[sconn(fd=6, family=<AddressFamily.AF_INET: 2>, type=<SocketKind.SOCK_STREAM: 1>, laddr=addr(ip='192.168.5.31', port=50541), raddr=addr(ip='17.248.159.145', port=443), status='ESTABLISHED', pid=1897),sconn(fd=12, family=<AddressFamily.AF_INET: 2>, type=<SocketKind.SOCK_STREAM: 1>, laddr=addr(ip='192.168.5.31', port=50543), raddr=addr(ip='17.250.120.9', port=443), status='ESTABLISHED', pid=1897),sconn(fd=6, family=<AddressFamily.AF_INET: 2>, type=<SocketKind.SOCK_DGRAM: 2>, laddr=addr(ip='0.0.0.0', port=0), raddr=(), status='NONE', pid=1790),sconn(fd=10, family=<AddressFamily.AF_INET: 2>, type=<SocketKind.SOCK_DGRAM: 2>, laddr=addr(ip='0.0.0.0', port=0), raddr=(), status='NONE', pid=1790),sconn(fd=11, family=<AddressFamily.AF_INET: 2>, type=<SocketKind.SOCK_DGRAM: 2>, laddr=addr(ip='0.0.0.0', port=0), raddr=(), status='NONE', pid=1790),...sconn(fd=30, family=<AddressFamily.AF_INET: 2>, type=<SocketKind.SOCK_DGRAM: 2>, laddr=addr(ip='0.0.0.0', port=137), raddr=(), status='NONE', pid=1),sconn(fd=31, family=<AddressFamily.AF_INET: 2>, type=<SocketKind.SOCK_DGRAM: 2>, laddr=addr(ip='0.0.0.0', port=138), raddr=(), status='NONE', pid=1)]# 获取网络接口信息>>> psutil.net_if_addrs(){'lo0': [snicaddr(family=<AddressFamily.AF_INET: 2>, address='127.0.0.1', netmask='255.0.0.0', broadcast=None, ptp=None),snicaddr(family=<AddressFamily.AF_INET6: 30>, address='::1', netmask='ffff:ffff:ffff:ffff:ffff:ffff:ffff:ffff', broadcast=None, ptp=None), snicaddr(family=<AddressFamily.AF_INET6: 30>, address='fe80::1%lo0', netmask='ffff:ffff:ffff:ffff::', broadcast=None, ptp=None)],...,'utun1': [snicaddr(family=<AddressFamily.AF_INET6: 30>, address='fe80::b519:e5df:2bd4:857e%utun1', netmask='ffff:ffff:ffff:ffff::', broadcast=None, ptp=None)]}# 获取网络接口的状态>>> psutil.net_if_stats(){'lo0': snicstats(isup=True, duplex=<NicDuplex.NIC_DUPLEX_UNKNOWN: 0>, speed=0, mtu=16384),...'utun1': snicstats(isup=True, duplex=<NicDuplex.NIC_DUPLEX_UNKNOWN: 0>, speed=0, mtu=2000)}
在监控平台上每 2 秒请求 url 获取网卡IO，并动态显示图表
net_io_dict = {'net_io_time':[], 'net_io_sent': [], 'net_io_recv': [], 'pre_sent': 0, 'pre_recv': 0, 'len': -1}def net_io():now = time.strftime('%H:%M:%S', time.localtime(time.time()))# 获取网络信息count = psutil.net_io_counters()g_sent = count.bytes_sentg_recv = count.bytes_recv# 第一次请求if net_io_dict['len'] == -1:net_io_dict['pre_sent'] = g_sentnet_io_dict['pre_recv'] = g_recvnet_io_dict['len'] = 0return# 当前网络发送/接收的字节速率 = 现在网络发送/接收的总字节 - 前一次请求网络发送/接收的总字节net_io_dict['net_io_sent'].append(g_sent - net_io_dict['pre_sent'])net_io_dict['net_io_recv'].append(g_recv - net_io_dict['pre_recv'])net_io_dict['net_io_time'].append(now)net_io_dict['len'] = net_io_dict['len'] + 1net_io_dict['pre_sent'] = g_sentnet_io_dict['pre_recv'] = g_recv# 保持在图表中 10 个数据if net_io_dict['len'] == 11:net_io_dict['net_io_sent'].pop(0)net_io_dict['net_io_recv'].pop(0)net_io_dict['net_io_time'].pop(0)net_io_dict['len'] = net_io_dict['len'] - 1def net_io_line() -> Line:net_io()c = (Line().add_xaxis(net_io_dict['net_io_time']).add_yaxis("发送字节数", net_io_dict['net_io_sent'], is_smooth=True).add_yaxis("接收字节数", net_io_dict['net_io_recv'], is_smooth=True).set_series_opts(areastyle_opts=opts.AreaStyleOpts(opacity=0.5),label_opts=opts.LabelOpts(is_show=False),).set_global_opts(title_opts=opts.TitleOpts(title="网卡IO/2秒"),xaxis_opts=opts.AxisOpts(axistick_opts=opts.AxisTickOpts(is_align_with_label=True),is_scale=False,boundary_gap=False,),))return c@app.route("/netio")def get_net_io_chart():c = net_io_line()return c.dump_options_with_quotes()
示例结果
进程
通过 psutil 可以获取所有进程的信息
# 所有进程的 pid>>> psutil.pids()[0, 1, 134, 135, 138, 139, 140, 141, 144, 145, 147, 152, ..., 30400, 97792]# 单个进程>>> p = psutil.Process(30400)# 名称>>> p.name()'pycharm'# 使用内存负载>>> p.memory_percent()12.838459014892578# 启动时间>>> p.create_time()1587029962.493182# 路径>>> p.exe()'/Applications/PyCharm.app/Contents/MacOS/pycharm'# 状态>>> p.status()'running'# 用户名>>> p.username()'imeng'# 内存信息>>> p.memory_info()pmem(rss=1093005312, vms=9914318848, pfaults=7813313, pageins=8448)
列出所有不需要权限的进程
def process():result = []process_list = []pid = psutil.pids()for k, i in enumerate(pid):try:proc = psutil.Process(i)ctime = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(proc.create_time()))process_list.append((str(i), proc.name(), proc.cpu_percent(), proc.memory_percent(), ctime))except psutil.AccessDenied:# 需要管理员权限passexcept psutil.NoSuchProcess:passexcept SystemError:pass# 按负载排序process_list.sort(key=process_sort, reverse=True)for i in process_list:result.append({'PID': i[0], 'name': i[1], 'cpu': i[2], 'mem': "%.2f%%"%i[3], 'ctime': i[4]})return jsonify({'list', result})def process_sort(elem):return elem[3]@app.route("/process")def get_process_tab():c = process()return c@app.route("/delprocess")def del_process():pid = request.args.get("pid")os.kill(int(pid), signal.SIGKILL)return jsonify({'status': 'OK'})
示例结果
process.gif
总结
本文以 Psutil + Flask + Pyecharts + Bootstrap 开发一个简单的系统监控平台，可以算做是本公众号内容的一个学以致用。在 Psutil 还有许多方法文章没有列举感兴趣的小伙伴可以去尝试并使用。