Consider when to use `spawn_blocking` in relation to `block_on` and GIL-holding Python calls

I had my first truly successful experience with ChatGPT in debugging #450 / #451.

The core issue was that we needed to release the GIL before calling `block_on`.

But one thing I'm not really clear on is when we need to use `spawn_blocking`

Suggested from ChatGPT:

Yes — you absolutely should use tokio::task::spawn_blocking if you're inside a PyO3-exposed #[pyfunction] and want to:

1. 
   

   Call a Python async function (i.e., get a coroutine),

   
   


2. 
   

   Convert it into a Rust future (using pyo3-asyncio),

   
   


3. 
   

   await it using a shared runtime (e.g. with block_on),

   
   


4. 
   

   All while not blocking the GIL or the async runtime.

   
   

🧠 Why spawn_blocking is needed

When you're in a PyO3 #[pyfunction], you're usually:

• 
  

  In a synchronous context, meaning you can't .await.

  
  


• 
  

  Already holding the GIL, so calling block_on directly would block the thread while holding the GIL — 💀 deadlock risk!

  
  


• 
  

  The async Python function (coroutine) might try to acquire the GIL (e.g. return a result), which leads to the deadlock.

  
  

Thus, you need to:

✅ Release the GIL using py.allow_threads(...)

✅ Run blocking code using tokio::task::spawn_blocking(...)

✅ Use a shared Tokio runtime, not per-call Runtime::new()

✅ Safe Pattern in #[pyfunction]:

#[pyfunction]

fn call_py_async_blocking(py: Python) -> PyResult<i32> {

    // Release the GIL to prevent deadlock

    let result = py.allow_threads(|| {

        // Use spawn_blocking to avoid blocking the async runtime

        tokio::task::spawn_blocking(move || {

            // Use a shared runtime

            pyo3_asyncio::tokio::get_runtime().block_on(async {

                // GIL needed to create coroutine

                let coro = Python::with_gil(|py| {

                    let module = py.import("mymodule")?;

                    let coroutine = module.call_method1("py_add", (10, 20))?;

                    pyo3_asyncio::tokio::into_future(coroutine)

                })?;


                // Await the coroutine

                let result = coro.await?;

                // Extract value from PyAny

                Python::with_gil(|py| result.extract::<i32>(py))

            })

        })

    });

    // Handle any async errors

    result.unwrap()

}

🔁 Summary

Step | Reason
-- | --
py.allow_threads(...) | Releases the GIL to avoid deadlocks
spawn_blocking(...) | Avoids blocking the async runtime
Runtime::block_on(...) | Runs async code from sync context
Python::with_gil(...) | Needed to create coroutine and extract results safely

🔧 Pro Tips

• 
  

  Use once_cell or lazy_static to create a shared Runtime if pyo3_asyncio::tokio::get_runtime() isn't set up.

  
  


• 
  

  Never block_on without allow_threads and spawn_blocking — it will work sometimes then crash in production under load 🧨

  
  

Let me know if you want me to generate a working minimal example (Rust + Python module) with everything wired up — I can do that too.

Start by reviewing issues #450 and #451, then trace the uses of py.allow_threads, tokio::task::spawn_blocking, block_on, and pyo3_asyncio::tokio::get_runtime mentioned here. Done means reaching a project-specific decision, backed by the relevant call sites and tests, about when each mechanism is appropriate.

Written by the indexing model from the issue text.