Filename: memory_profiler_test.py Line # Mem usage Increment Line Contents === 3 @profile ...
1defmemory_usage():2mem_available =psutil.virtual_memory().available3mem_process =psutil.Process(os.getpid()).memory_info().rss4returnround(mem_process / 1024 / 1024, 2), round(mem_available / 1024 / 1024, 2)
importpsutil# 获取当前进程IDpid=os.getpid()# 获取当前进程process=psutil.Process(pid)# 获取当前进程的显存使用量(单位:字节)memory_usage=process.memory_info().rssprint(f"当前进程的显存使用量为:{memory_usage}字节") 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 上面的代码中,我们首先获取...
Filename: E:/平时笔记/test/memory_test.py Line Mem usage Increment Occurrences Line Contents 4 36.4 MiB 36.4 MiB 1 @profile # 在需要做性能分析的函数前面加装饰器 @profile 5 6 def my_func1(c): 7 44.1 MiB 7.6 MiB 1 a = [1] * (10 ** c) 8 196.7 MiB 152.6 MiB 1 b = [2] *...
print 'Memoryusage: {0}(MB)'.format(resource.getrusage(resource.RUSAGE_SELF).ru_maxrss/1024) print "Mostcommontypes:" objgraph.show_most_common_types() print "heapis:" print "{0}".format(h) by_refs = h.byrcs print "byreferences: {0}".format(by_refs) ...
'cpu_usage': cpu_usage, 'memory_total': total_memory, 'memory_used': used_memory, 'disk_space_total': total_disk_space, 'disk_space_free': used_disk_space, } # 将系统信息转换为 JSON 格式并发送给客户端 self.wfile.write(json.dumps(system_info).encode('utf-8')) elif self.path =...
import psutil cpu_percent = psutil.cpu_percent()memory_percent = psutil.virtual_memory().percentdisk_percent = psutil.disk_usage('/').percent print(f'CPU: {cpu_percent}%')print(f'Memory: {memory_percent}%')print(f'Disk: {disk_percent}%')9、自动化SSH登录脚本：使用paramiko模块自动化SSH...
| | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |===| | 0 N/A N/A 1673 G /usr/lib/xorg/Xorg 110MiB | | 0 N/A N/A 3015 G /usr/lib/xorg/Xorg 661MiB | | 0 N/A N/A 3251 G /usr/bin/gnome-shell 132MiB | | 0 N/A N/A 1142734 G ...AAAAAA...
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_20240705 = show_model_list('tiger_csi1000_500','20240705').set_index('stock_code').loc[:...
Small memory usage Lets you share memory between multiple processes Index creation is separate from lookup (in particular you can not add more items once the tree has been created) Native Python support, tested with 2.7, 3.6, and 3.7.