线程池 在web服务中实现加速

1. web服务的架构和特点

2.使用线程池ThreadPoolExecutor加速

3. 代码fastapi实现web服务并加速

import json
import time
import uvicorn
from fastapi import FastAPI
app = FastAPI()
import time
from functools import wraps
def timethis(func):
    '''
    Decorator that reports the execution time.
    '''
    @wraps(func)
    def wrapper(*args, **kwargs):
        start = time.time()
        result = func(*args, **kwargs)
        end = time.time()
        print(func.__name__, end-start)
        return result
    return wrapper
def do_file():
    time.sleep(0.1)
    return 'result file'
def do_db():
    time.sleep(0.2)
    return 'result db'
def do_api():
    time.sleep(0.3)
    return 'result api'
from concurrent.futures import ThreadPoolExecutor
import concurrent.futures
@app.get('/')
@timethis
def index():
    with concurrent.futures.ThreadPoolExecutor() as pool:
        read_file = pool.submit(do_file)
        read_api = pool.submit(do_api)
        read_db = pool.submit(do_db)
        return json.dumps({
            "read_file":read_file.result(),
            "read_api":read_api.result(),
            "read_db":read_db.result()
        })
if __name__ == '__main__':
    uvicorn.run(app,host='127.0.0.1',port=8000)
##############
index 0.6029112339019775
INFO:     127.0.0.1:55583 - "GET / HTTP/1.1" 200 OK
vs
index 0.3037288188934326
INFO:     127.0.0.1:55264 - "GET / HTTP/1.1" 200 OK