Red HatでのPythonツールのパフォーマンスチューニング – 一歩進んだ活用法

sudo yum install python3 python3-pip -y
python3 -m pip install --upgrade pip setuptools

python3 -m venv myenv
source myenv/bin/activate

pip freeze > requirements.txt
pip install -r requirements.txt

import multiprocessing

def worker_function(data):
return data * 2

if <strong>name</strong> == "<strong>main</strong>":
with multiprocessing.Pool(processes=4) as pool:
results = pool.map(worker_function, range(100))

python3 -m cProfile -o output.prof your_script.py
pip install snakeviz
snakeviz output.prof

sudo yum install pypy
pypy your_script.py

import asyncio

async def fetch_data():
await asyncio.sleep(2)
return "data fetched"

async def main():
results = await asyncio.gather(fetch_data(), fetch_data())
print(results)

asyncio.run(main())

from functools import lru_cache

@lru_cache(maxsize=None)
def expensive_function(n):
return sum(i * i for i in range(n))

pip install numpy pandas

sudo sysctl -w vm.dirty_ratio=20
sudo sysctl -w vm.swappiness=10

pip install pytest
pytest your_test_script.py