How does the aiosqlite module work in Python?

Question

I have a basic understanding of asynchronous programming, but I'm having trouble conceptualizing how I/O operations can be optimized in a single-threaded environment when using aiosqlite. Specifically, I'm struggling to understand how asynchronous querying and insertion into tables can improve performance.

In traditional synchronous programming with sqlite3, I can comprehend the benefits of I/O optimization, but I'm unsure how aiosqlite achieves this efficiency asynchronously. Could someone provide insights into how aiosqlite manages to optimize I/O operations when the queries involve table searches and asynchronous content insertion?

Furthermore, if there are any specific strategies, techniques, or patterns that I should be aware of when working with aiosqlite to maximize its performance, I would greatly appreciate your guidance. Thank you for your assistance!

I looked at the following code: https://github.com/omnilib/aiosqlite/blob/40442815b1a9a67b6f458fe56a1f4717c6f6c74c/aiosqlite/core.py#LL111C5-L111C5

async def _execute(self, fn, *args, **kwargs):
        """Queue a function with the given arguments for execution."""
        if not self._running or not self._connection:
            raise ValueError("Connection closed")

        function = partial(fn, *args, **kwargs)
        future = asyncio.get_event_loop().create_future()

        self._tx.put_nowait((future, function))

        return await future

I don't understand what self._tx.put_nowait((future, function)) really does for example.