获取进程信息 .pids() # 所有进程ID .Process(3776) # 获取指定进程ID=3776 -> p p.name() # 进程名称'python3.6' p.exe() # 进程exe路径 p.cwd() # 进程工作目录 p.cmdline() # 进程启动的命令行p.ppid() # 父进程ID p.parent() # 父进程 p.chil
Memory of current process import psutil def print_memory_usage(): process = psutil.Process() print(f"Memory usage: {process.memory_info().rss / 1024 ** 2:.2f} MB") print_memory_usage() # Print memory usage before and after deleting large objects Outer merge 合并 ### method1 weigth_...
if UNIX: return GetMemInfoUnix() return GetMemInfoWindows()def GetMemInfoUnix() -> Dict[str, int]: ''' 获取内存信息(unix)Returns --- dict DESCRIPTION.''' mem = psutil.virtual_memory() memInfo: dict = { 'memTotal': ToSizeInt(mem.total, 'MB'), 'memFree...
psutil.swap_memory():获取交换内存的使用信息。 1. 2. Disk psutil.disk_partitions(all=False):获取硬盘分区信息。 psutil.disk_usage(path):获取硬盘使用信息。 psutil.disk_io_counters(perdisk=False,nowrap=True):获取磁盘IO信息。 1. 2. 3. Network psutil.net_io_counters(pernic=False):获取网络IO信...
Get access to the Salt software package repository here: supervisor 5113 - Supervisor process control system for UNIX foreman 4965 MIT- Manage Procfile-based applications psutil 4564 - Cross-platform lib for process and system monitoring in Python pexpect 1448 - A Python module for controlling ...
一、psutil简介 psutil是一个开源且跨平台(http://code.google.com/p/psutil/)的库,能够轻松实现获取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。它主要应用于系统监控,分析和限制系统资源及进程的管理。它实现了同等命令行工具提供的功能,如ps、top、lsof、netstat、ifconfig、who、df、kill、...
Nice looking web dashboard written in Flask that can display data about your system and its processes as returned by psutil.github.com Shared by @mgrouchy500 Lines or Less Awesome repository of how things work with computers and software. I am ...
Python库 | psutil-3.1.1-cp34-none-win32.whl python库,解压后可用。 资源全名:psutil-3.1.1-cp34-none-win32.whl 上传者:qq_38161040时间:2022-03-23 PyPI 官网下载 | incuna_test_utils-3.1.1-py2.py3-none-any.whl 资源来自pypi官网,解压后可用。 资源全名:incuna_test_utils-3.1.1-py2.py3-...
代码如下## 剩余的物理内存 free = str(round(psutil.virtual_memory().free / (1024.0 * 1024.0...
This is because computers need different storage requirements and speed tradeoffs for integers as compared to strings. One last thing you should know about how Python's heap is managed is that you have zero control over it. Now you may be wondering, how do we then write memory-efficient ...