问题

I am trying to understand the behavior of Uvicorn. I have create a sample fastapi app which mainly sleep for 5 seconds.

import time
from datetime import datetime

from fastapi import FastAPI

app = FastAPI()

counter = 0

@app.get("/")
def root():
    global counter
    counter = counter + 1
    my_id = counter
    print(f'I ({my_id}) am feeling sleepy')
    time.sleep(5)
    print(f'I ({my_id}) am done sleeping')
    return {}

I called my app using the following command of Apache Bench:

ab -n 5 -c 5 http://127.0.0.1:8000/

Output:

I (1) am feeling sleepy  -- 0s
I (1) am done sleeping   -- 5s
I (2) am feeling sleepy  -- 5s
I (3) am feeling sleepy  -- 5s
I (4) am feeling sleepy  -- 5s
I (5) am feeling sleepy  -- 5s
I (2) am done sleeping   -- 10s
I (4) am done sleeping   -- 10s
I (3) am done sleeping   -- 10s
I (5) am done sleeping   -- 10s

Why are requests running concurrently? I ran the app as:

uvicorn main:app --workers 1

Please note that I did not use the async keyword so for me everything should be completely synchronous.

From the FastAPI docs:

> When you declare a path operation function with normal def instead of
> async def, it is run in an external threadpool that is then awaited,
> instead of being called directly (as it would block the server).

Where is this threadpool? As I am using sleep, I though the only worker available would be completely blocked.

<details>
<summary>英文:</summary>

Understanding Uvicorn asynchrounous behavior

I am trying to understand the behavior of Uvicorn. I have create a sample fastapi app which mainly sleep for 5 seconds.

    import time
    from datetime import datetime
    
    
    from fastapi import FastAPI
    
    
    app = FastAPI()
    
    counter = 0
    
    @app.get(&quot;/&quot;)
    def root():
        global counter
        counter = counter + 1
        my_id = counter
        print(f&#39;I ({my_id}) am feeling sleepy&#39;)
        time.sleep(5)
        print(f&#39;I ({my_id}) am done sleeping&#39;)
        return {}



I called my app using the following command of Apache Bench:

    ab -n 5 -c 5 http://127.0.0.1:8000/

Output:

    I (1) am feeling sleepy  -- 0s
    I (1) am done sleeping   -- 5s
    I (2) am feeling sleepy  -- 5s
    I (3) am feeling sleepy  -- 5s
    I (4) am feeling sleepy  -- 5s
    I (5) am feeling sleepy  -- 5s
    I (2) am done sleeping   -- 10s
    I (4) am done sleeping   -- 10s
    I (3) am done sleeping   -- 10s
    I (5) am done sleeping   -- 10s


Why are requests running concurrently? I ran the app as:

    uvicorn main:app --workers 1

Please note that I did not use the async keyword so for me everything should be completely synchronous.

From the FastAPI docs:

&gt; When you declare a path operation function with normal def instead of
&gt; async def, it is run in an external threadpool that is then awaited,
&gt; instead of being called directly (as it would block the server).

Where is this threadpool? As I am using sleep, I though the only worker available would be completely blocked.


</details>


# 答案1
**得分**: 3

FastAPI 使用 Starlette，后者在幕后使用 AnyIO。默认提供了一个包含 40 个线程的线程池来处理同步请求。这个线程池是用于处理并发同步请求的多次执行的魔法背后的关键。

这可以进行配置：

```python
from anyio.lowlevel import RunVar
from anyio import CapacityLimiter

app = FastAPI()

@app.on_event("startup")
def startup():
    print("start")
    RunVar("_default_thread_limiter").set(CapacityLimiter(2))

来源：https://github.com/tiangolo/fastapi/issues/4221#issuecomment-982260467

鸣谢 @MatsLindh。

from anyio.lowlevel import RunVar
from anyio import CapacityLimiter

app = FastAPI()

@app.on_event("startup")
def startup():
    print("start")
    RunVar("_default_thread_limiter").set(CapacityLimiter(2))