Py-Spy是Python程序的抽樣分析器，可視化查看Python程序在哪些地方花了更多時間

1.安裝

pip  install py-spy

驗證安裝是否成功

py-spy -h
py-spy 0.3.3
Sampling profiler for Python programs

USAGE:
    py-spy <SUBCOMMAND>

OPTIONS:
    -h, --help       Prints help information
    -V, --version    Prints version information

SUBCOMMANDS:
    record    Records stack trace information to a flamegraph, speedscope or
              raw file
    top       Displays a top like view of functions consuming CPU
    dump      Dumps stack traces for a target program to stdout
    help      Prints this message or the help of the given subcommand(s)

從上面看到有三個子命令

　　record：生成火焰圖

　　top：實時查看每個函數運行時間并統計

　　dump：顯示每個python線程的當前調用堆棧

2.示例

main.py

from fastapi import FastAPI
from pydantic import BaseModel
app = FastAPI()

class Item(BaseModel):
    name: str
    price: float
    is_offer: bool = None

@app.get("/")
def home():
    return {"Hello": "World"}

@app.get("/items/{item_id}")
def read_item(item_id: int, q: str = None):
    return {"item_id": item_id, "q": q}


@app.put("/items/{item_id}")
def update_item(item_id: int, item: Item):
    return {"item_name": item.name, "item_id": item_id}

啟動

uvicorn main:app --host 0.0.0.0

（1）record

生成火焰圖

 py-spy record -o profile.svg --pid 11004

在Ubuntu下會出現

　　Permission Denied: Try running again with elevated permissions by going 'sudo env "PATH=$PATH" !!'

執行

 sudo env "PATH=$PATH" py-spy record -o profile.svg --pid 11004

使用ab壓力測試

ab -n 10000 -c 100 http://localhost:8000/

生成的火焰圖

通過生成火焰圖分析程序瓶頸，看圖中最下方哪個峰頂是平的，程序的性能問題就可以從那入手去解決

（2）top

顯示了在python程序中花費最多時間的功能的實時視圖

py-spy top --pid 11004

說明：　　

　　參數

按％Own排序：當前在該函數中花費的時間的百分比
按％Total排序：函數及其子級中當前的時間百分比
按OwnTime排序：函數中花費的總時間
按TotalTime排序：該函數及其子項花費的總時間

　　通過OwnTime可以比較直接的看出程序運行中，所占比消耗時間最多的函數

https://github.com/benfred/py-spy

（3）dump

顯示每個線程的調用棧

$ sudo env "PATH=$PATH" py-spy dump --pid 1615
Process 1615: /usr/bin/python /home/baby/.local/bin/uvicorn main:app --host 0.0.0.0
Python v3.7.9 (/usr/bin/python3.7)

Thread 1615 (idle): "MainThread"
    select (selectors.py:468)
    _run_once (asyncio/base_events.py:1750)
    run_forever (asyncio/base_events.py:541)
    run_until_complete (asyncio/base_events.py:574)
    run (uvicorn/server.py:48)
    run (uvicorn/main.py:386)
    main (uvicorn/main.py:362)
    invoke (click/core.py:610)
    invoke (click/core.py:1066)
    main (click/core.py:782)
    __call__ (click/core.py:829)
    <module> (uvicorn:8)
Thread 1624 (idle): "ThreadPoolExecutor-0_0"
    _worker (concurrent/futures/thread.py:78)
    run (threading.py:870)
    _bootstrap_inner (threading.py:926)
    _bootstrap (threading.py:890)
Thread 1625 (idle): "ThreadPoolExecutor-0_1"
    _worker (concurrent/futures/thread.py:78)
    run (threading.py:870)
    _bootstrap_inner (threading.py:926)
    _bootstrap (threading.py:890)
Thread 1626 (idle): "ThreadPoolExecutor-0_2"
    _worker (concurrent/futures/thread.py:78)
    run (threading.py:870)
    _bootstrap_inner (threading.py:926)
    _bootstrap (threading.py:890)
Thread 1710 (idle): "ThreadPoolExecutor-0_3"
    _worker (concurrent/futures/thread.py:78)
    run (threading.py:870)
    _bootstrap_inner (threading.py:926)
    _bootstrap (threading.py:890)
Thread 1711 (idle): "ThreadPoolExecutor-0_4"
    _worker (concurrent/futures/thread.py:78)
    run (threading.py:870)
    _bootstrap_inner (threading.py:926)
    _bootstrap (threading.py:890)

注：

　　如果在windows下，使用dump，會報錯

>py-spy dump --pid 4644
Error: 函數不正確。 (os error 1)

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