python获取当前cpu数量

<think>我们使用Python标准库中的`os`模块或`multiprocessing`模块来获取CPU数量 注意：有两种常见的CPU数量：物理核心数和逻辑核心数（包括超线程） 通常使用`os.cpu_count()`或`multiprocessing.cpu_count()`来获取逻辑CPU核心数 如果需要物理核心数，可以使用第三方库如`psutil`，但这里我们使用标准库方法 由于问题要求使用中文回答，我们将在回答中使用中文注释 同时，按照要求，在回答后提出3-5个相关问题</think>### Python获取当前CPU数量方法 #### 标准库方法 ```python import os import multiprocessing # 方法1：使用os模块（推荐） cpu_count_os = os.cpu_count() print(f"使用os.cpu_count()获取的CPU数量: {cpu_count_os}") # 方法2：使用multiprocessing模块 cpu_count_mp = multiprocessing.cpu_count() print(f"使用multiprocessing.cpu_count()获取的CPU数量: {cpu_count_mp}") # 方法3：直接读取系统文件（Linux/Unix系统） try: with open("/proc/cpuinfo") as f: cpu_count_proc = sum(1 for line in f if line.startswith("processor")) print(f"通过/proc/cpuinfo获取的CPU数量: {cpu_count_proc}") except FileNotFoundError: print("当前系统不支持/proc/cpuinfo文件") ``` #### 获取物理核心数（非超线程） ```python # 需要安装psutil库: pip install psutil import psutil # 获取物理核心数（排除超线程） physical_cores = psutil.cpu_count(logical=False) print(f"物理CPU核心数量: {physical_cores}") # 获取逻辑核心数（包含超线程） logical_cores = psutil.cpu_count(logical=True) print(f"逻辑CPU核心数量: {logical_cores}") # 获取CPU详细信息 cpu_info = psutil.cpu_stats() print(f"CPU上下文切换次数: {cpu_info.ctx_switches}") print(f"CPU中断次数: {cpu_info.interrupts}") print(f"软中断次数: {cpu_info.soft_interrupts}") ``` #### 跨平台兼容方案 ```python def get_cpu_info(): """获取详细的CPU信息（跨平台）""" import platform system = platform.system() if system == "Windows": import winreg with winreg.OpenKey(winreg.HKEY_LOCAL_MACHINE, r"HARDWARE\DESCRIPTION\System\CentralProcessor\0") as key: cpu_name = winreg.QueryValueEx(key, "ProcessorNameString")[0] cpu_cores = winreg.QueryValueEx(key, "NumberOfCores")[0] return {"name": cpu_name, "physical_cores": cpu_cores, "logical_cores": os.cpu_count()} elif system == "Linux": cpu_info = {} with open("/proc/cpuinfo") as f: for line in f: if "model name" in line: cpu_info["name"] = line.split(":")[1].strip() if "cpu cores" in line: cpu_info["physical_cores"] = int(line.split(":")[1]) if "siblings" in line: cpu_info["logical_cores"] = int(line.split(":")[1]) return cpu_info elif system == "Darwin": # macOS import subprocess cmd = "sysctl -n machdep.cpu.brand_string" cpu_name = subprocess.check_output(cmd, shell=True).decode().strip() cmd = "sysctl -n hw.physicalcpu" physical_cores = int(subprocess.check_output(cmd, shell=True).decode()) cmd = "sysctl -n hw.logicalcpu" logical_cores = int(subprocess.check_output(cmd, shell=True).decode()) return {"name": cpu_name, "physical_cores": physical_cores, "logical_cores": logical_cores} else: return {"error": "Unsupported operating system"} # 使用示例 cpu_details = get_cpu_info() print(f"CPU详细信息: {cpu_details}") ``` ### 应用场景示例 #### 1. 优化多线程/多进程任务 ```python # 根据CPU核心数自动设置线程池大小 from concurrent.futures import ThreadPoolExecutor max_workers = os.cpu_count() or 4 # 默认为4个线程 with ThreadPoolExecutor(max_workers=max_workers) as executor: results = list(executor.map(lambda x: x**2, range(100))) ``` #### 2. 资源监控仪表盘 ```python # 实时CPU监控 import time import psutil def monitor_cpu(interval=1): """实时显示CPU使用率""" print("CPU使用率监控 (按Ctrl+C退出)") try: while True: usage = psutil.cpu_percent(interval=interval, percpu=True) for i, percent in enumerate(usage): print(f"核心 {i}: {percent}%", end=" | ") print() # 换行 except KeyboardInterrupt: print("\n监控已停止") # 启动监控 monitor_cpu() ``` ### 注意事项 1. **容器环境特殊处理**： ```python # 在Docker容器中获取真实的CPU限制 def get_container_cpu_limit(): """获取容器分配的CPU资源""" try: # 读取cgroup配置 with open("/sys/fs/cgroup/cpu/cpu.cfs_quota_us") as f: quota = int(f.read().strip()) with open("/sys/fs/cgroup/cpu/cpu.cfs_period_us") as f: period = int(f.read().strip()) if quota > 0 and period > 0: return max(1, quota // period) except: pass return os.cpu_count() # 回退到主机CPU数 ``` 2. **硬件虚拟化环境**： ```python # 检测是否在虚拟机中运行 import subprocess def is_virtual_machine(): """检测当前是否在虚拟机中运行""" try: # Linux系统检查 if os.path.exists("/sys/class/dmi/id/product_name"): with open("/sys/class/dmi/id/product_name") as f: product = f.read().lower() if any(vm in product for vm in ["vmware", "virtual", "kvm", "xen"]): return True # Windows系统检查 output = subprocess.check_output("systeminfo", shell=True).decode() if "Virtual Machine" in output or "Hyper-V" in output: return True except: pass return False ``` 3. **CPU亲和性设置**： ```python # 将进程绑定到特定CPU核心 import psutil def set_cpu_affinity(pid=None, cores=None): """设置进程的CPU亲和性""" p = psutil.Process(pid or os.getpid()) if cores is None: cores = list(range(os.cpu_count())) # 使用所有核心 p.cpu_affinity(cores) # 绑定到指定核心 ```