Python逐行内存分析器？

Question

I'm looking to generate, from a large Python codebase, a summary of heap usage or memory allocations over the course of a function's run.

I'm familiar with heapy , and it's served me well for taking "snapshots" of the heap at particular points in my code, but I've found it difficult to generate a "memory-over-time" summary with it. I've also played with line_profiler , but that works with run time, not memory.

My fallback right now is Valgrind with massif , but that lacks a lot of the contextual Python information that both Heapy and line_profiler give. Is there some sort of combination of the latter two that give a sense of memory usage or heap growth over the execution span of a Python program?

Answer 1

I would use sys.settrace at program startup to register a custom tracer function. The custom_trace_function will be called for each line of code. Then you can use that function to store information gathered by heapy or meliae in a file for later processing.

Here is a very simple example which logs the output of hpy.heap() each second to a plain text file:

import sys
import time
import atexit
from guppy import hpy

_last_log_time = time.time()
_logfile = open('logfile.txt', 'w')

def heapy_profile(frame, event, arg):
    currtime = time.time()
    if currtime - _last_log_time < 1:
        return
    _last_log_time = currtime
    code = frame.f_code
    filename = code.co_filename
    lineno = code.co_firstlineno
    idset = hpy().heap()
    logfile.write('%s %s:%s\n%s\n\n' % (currtime, filename, lineno, idset))
    logfile.flush()

atexit.register(_logfile.close)
sys.settrace(heapy_profile)

Answer 2

您可能对memory_profiler感兴趣。