python / python/cpython

Tachyon’s `--diff-flamegraph` scales times in baseline run to duration of current run

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stdlib topic-profiling type-bug
主要語言
Python
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描述

Bug report

Bug description:

As discussed with @pablogsal during EuroPython sprints:

Using this simple example script (flamegraph_demo.py):

import time

def main():
    f_1()
    f_2()

def f_1():
    time.sleep(0.5)  # change this to 1.5 in the second run

def f_2():
    time.sleep(1)

main()
python -m profiling.sampling run --binary -o baseline.bin flamegraph_demo.py
vim flamegraph_demo.py  # edit f_1 to sleep for 1.5 s
python -m profiling.sampling run --diff-flamegraph baseline.bin -o diff.html flamegraph_demo.py

generates this diff flamegraph:

Image

f_2 is unchanged between both runs, so the “Baseline Self” time should be equal to the “Current Self” and equal to 1 s (that it displays “1 ms” is covered in #154059); however, the baseline for all functions gets scaled with the ratio of total time in this run over total time of the previous run (in this case: 2.5 s / 1.5 s = 1.667).

I can imagine scenarios where this scaling is useful (e.g. when the baseline is generated on a different machine). However, in the common case of running baseline and diff on the same machine, this scaling means that a lot of unchanged functions get colour-coded, which distracts from the few functions that experienced a meaningful change.

CPython versions tested on:

3.15

Operating systems tested on:

macOS

Linked PRs
  • gh-154082

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研究方向

從 profiling.sampling 入口開始,使用 flamegraph_demo.py 重現這些命令,並將 baseline.bin 與 diff.html 進行比較。追蹤 --diff-flamegraph 如何縮放 baseline 時間,並驗證未變更的 f_2 具有相等的 1 s baseline 與目前 self time,且沒有不必要的顏色變更。

由索引模型根據 Issue 內容生成。

評估

技術堆疊
python
領域
performance
Issue 類型
缺陷
難度
3/5
預估耗時
1-2 天
活躍度
停滯
描述清晰度
基本清楚
新手友好度
35/100

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