class MemoryMonitor: def __init__(self): self.keep_measuring = True def measure_usage(self): max_usage = 0 while self.keep_measuring: max_usage = max( max_usage, resource.getrusage(resource.RUSAGE_SELF).ru_maxrss ) sleep(0.1) return max_usage 在这个类的实例上调用measure_usage()时,它...
mem_usage = memory_usage((df['col1'].mean, ())) The memory_usage function is used to measure the memory usage of the df['col1'].mean operation. print(f"Pandas Memory Usage: {max(mem_usage)} MB") The maximum memory usage during the operation is printed. ...
from timeimportsleepclassMemoryMonitor:def__init__(self):self.keep_measuring=True defmeasure_usage(self):max_usage=0whileself.keep_measuring:max_usage=max(max_usage,resource.getrusage(resource.RUSAGE_SELF).ru_maxrss)sleep(0.1)returnmax_usage 在这个类的实例上调用measure_usage()时,它将进入一个循...
import resourcefrom time import sleep classMemoryMonitor:def__init__(self):self.keep_measuring = True defmeasure_usage(self):max_usage = 0while self.keep_measuring:max_usage = max(max_usage,resource.getrusage(resource.RUSAGE_SELF).ru_maxrss)sleep(0.1) return max_usage 1. 1. 1. 1. 1. ...
Memory Usage: This metric measures the amount of memory your code consumes. You can use thememory_profilerpackage in Python to measure memory usage. frommemory_profilerimportprofile@profiledefmy_function():# Your code heremy_function() 1. ...
non-null int64fbs 303 non-null int64restecg 303 non-null int64thalach 303 non-null int64exang 303 non-null int64oldpeak 303 non-null float64slope 303 non-null int64ca 303 non-null int64thal 303 non-null int64target 303 non-null int64dtypes: float64(1), int64(13)memory usage: 33.2 ...
(~1.3 GB reserved memory)foriinrange(N):# Measure memory usageif(i%(N//100)==0):memory_usage=os.popen('free -h').readlines()[1].split()print(("i = %06d | Memory used %s from %s")%(i,memory_usage[2],memory_usage[1]))# Attempt conversiontry:gray=cv2.cvtColor(frame,cv2....
virtual_memory.free/1024/1024/1024 memory_percent = virtual_memory.percent memory_info = "内存使用:%0.2fG,使用率%0.1f%%,剩余内存:%0.2fG" % (used_memory, memory_percent, free_memory) print(memory_info) if __name__ == '__main__': get_disk_info() get_cpu_info() get_memory_info...
| GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |===| | No running processes found | +---+ 测试代码也可以跑了。 测试Python代码 打印ID 准备以下代码: from numba import cuda import os def cpu_print(): print('cpu print') @...
D:\Workspace\_mock>python -m memory_profiler test.py hello world Filename: test.py Line#Mem usage Increment Line Contents=== 2 12.328 MiB 0.000MiB @profile ##这个profile需要加上3deftest():4 12.340 MiB 0.012 MiBprint"hello world" 方法04: ## 利用objgraph进行两个show_growth点之间看到哪些...