0Pricing
FastAPI Backend Development Bootcamp · Lezione

Ripasso di Async/Await in Python

Ripassi i concetti fondamentali della programmazione asincrona in Python, inclusi event loop e coroutine.

Ripasso di Async/Await in Python è una lezione FastAPI Backend Development Bootcamp gratuita su CoddyKit. Questa è la lezione 1 di 4. Puoi leggere la lezione completa qui gratuitamente — poi esercitati direttamente nel browser con un editor di codice integrato e un tutor IA disponibile 24/7. Fa parte del percorso di apprendimento FastAPI Backend Development Bootcamp, e i tuoi progressi si sincronizzano tra il web e l'app CoddyKit. Il corso FastAPI Backend Development Bootcamp include 4 lezioni in totale.

Parti di questa lezione non sono ancora state tradotte e vengono mostrate in inglese.

Intro to Asynchronous Python

Welcome to the world of asynchronous programming in Python! This allows your programs to do multiple things without waiting for each task to finish before starting the next.

It's super useful for tasks that involve waiting, like network requests or reading/writing files, where your program would otherwise just sit idle.

Sync vs. Async: The Wait Game

Imagine cooking dinner:

  • Synchronous: You chop vegetables, then wait for them to cook, then wash dishes. Only one task happens at a time.
  • Asynchronous: You chop vegetables, put them on the stove, and while they're cooking (waiting), you start washing dishes. You're doing multiple things 'concurrently' by switching tasks when one is waiting.

Asynchronous programming helps your program stay busy instead of waiting!

The `async` Keyword: Coroutines

In Python, we use the async keyword to define a special type of function called a coroutine. A coroutine is a function that can be paused and resumed.

It doesn't run immediately when called; instead, it returns a 'coroutine object' that needs to be scheduled by an event loop to run.

import asyncio

async def hello_world():
    print("Hello, async world!")

# Calling it directly doesn't run it!
# It returns a coroutine object.
coro_obj = hello_world()
print(f"Type of coro_obj: {type(coro_obj)}")

# To actually run it, you need an event loop.
# We'll see how in a moment!

`await`: Pausing Execution

The await keyword is used inside an async def function (a coroutine) to pause its execution until another awaitable (like another coroutine or a Future) completes.

When a coroutine awaits something, it temporarily gives control back to the event loop, allowing other tasks to run. This is key to non-blocking behavior.

import asyncio

async def cook_rice():
    print("Starting to cook rice...")
    await asyncio.sleep(2) # Simulate 2 seconds of cooking
    print("Rice is cooked!")

async def chop_veg():
    print("Chopping vegetables...")
    await asyncio.sleep(1) # Simulate 1 second of chopping
    print("Vegetables chopped!")

async def main_meal():
    await chop_veg() # Wait for chopping to finish
    await cook_rice() # Then wait for rice to cook
    print("Dinner is ready!")

# This will run sequentially for now.
# We'll make it concurrent soon!
asyncio.run(main_meal())

The Event Loop: The Orchestrator

Think of the event loop as the conductor of an orchestra. It's responsible for:

  • Scheduling when coroutines run.
  • Handling I/O events (like network data arriving).
  • Switching between tasks when one is waiting (e.g., due to await).

Python's asyncio module provides the infrastructure for the event loop.

Running Async Code with `asyncio.run()`

To execute an asynchronous program, you typically use asyncio.run(). This function:

  • Gets an event loop for the current thread.
  • Runs the provided coroutine until it completes.
  • Manages the event loop's lifecycle.

It's the simplest way to start your top-level async function.

import asyncio

async def say_hello():
    print("Hello from coroutine!")
    await asyncio.sleep(0.5) # Wait for 0.5 seconds
    print("Goodbye from coroutine!")

async def main():
    print("Starting async program...")
    await say_hello()
    print("Async program finished.")

# This is the entry point for your async application
asyncio.run(main())

Simulating Non-Blocking Operations

asyncio.sleep() is an 'awaitable' that pauses the current coroutine for a given time. Crucially, it does NOT block the entire program. While one coroutine is sleeping, the event loop can switch to and run other coroutines.

This is how asynchronous programming achieves concurrency without needing multiple threads.

import asyncio
import time

async def task_one():
    print(f"Task One started at {time.strftime('%X')}")
    await asyncio.sleep(2)
    print(f"Task One finished at {time.strftime('%X')}")

async def task_two():
    print(f"Task Two started at {time.strftime('%X')}")
    await asyncio.sleep(1)
    print(f"Task Two finished at {time.strftime('%X')}")

async def main():
    start_time = time.monotonic()
    await task_one()
    await task_two()
    end_time = time.monotonic()
    print(f"Total time: {end_time - start_time:.2f} seconds")

asyncio.run(main())

Concurrent Execution with `asyncio.gather`

To truly run multiple coroutines concurrently (meaning they can interleave their execution when one awaits), we use asyncio.gather().

asyncio.gather() takes multiple awaitables and schedules them to run 'in parallel' on the event loop, waiting for all of them to complete.

import asyncio
import time

async def fetch_data(delay, name):
    print(f"Fetching {name} data... (starts at {time.strftime('%X')})")
    await asyncio.sleep(delay) # Simulate network request
    print(f"Finished {name} data. (ends at {time.strftime('%X')})")
    return f"Data from {name}"

async def main():
    start_time = time.monotonic()
    # Run fetch_data for 'users' and 'products' concurrently
    user_data, product_data = await asyncio.gather(
        fetch_data(2, "users"),
        fetch_data(1, "products")
    )
    end_time = time.monotonic()
    print(f"\nReceived: {user_data}, {product_data}")
    print(f"Total time: {end_time - start_time:.2f} seconds")

asyncio.run(main())

Async/Await Concepts Check

Which of the following statements about Python's async and await keywords are TRUE?

Refresher Recap & Next Steps

Fantastic! You've refreshed your understanding of Python's asynchronous fundamentals:

  • Asynchronous programming helps manage I/O-bound tasks efficiently.
  • async def defines coroutines, functions that can be paused.
  • await pauses a coroutine, yielding control to the event loop.
  • The event loop orchestrates coroutine execution.
  • asyncio.run() starts your async application.
  • asyncio.gather() allows running multiple coroutines concurrently.

Next, we'll see how FastAPI leverages these powerful concepts to build high-performance web APIs!

Domande Frequenti

La lezione «Ripasso di Async/Await in Python» è gratuita?

Sì — il testo completo di «Ripasso di Async/Await in Python» è gratuito qui sul web. Per esercitarvi in modo interattivo (un editor di codice integrato e un tutor IA 24/7) e sbloccare il resto del corso FastAPI Backend Development Bootcamp, passa a CoddyKit PRO. Il corso FastAPI Backend Development Bootcamp include 4 lezioni in totale.

Cosa imparerò in «Ripasso di Async/Await in Python»?

Ripassi i concetti fondamentali della programmazione asincrona in Python, inclusi event loop e coroutine. Eserciti FastAPI Backend Development Bootcamp con codice pratico che esegui direttamente nel browser, e un tutor IA 24/7 risponde alle tue domande mentre lavori sulla lezione.

Ho bisogno di esperienza per iniziare FastAPI Backend Development Bootcamp?

Non è richiesta alcuna esperienza precedente. FastAPI Backend Development Bootcamp su CoddyKit è strutturato per principianti e studenti avanzati, quindi puoi iniziare da qui o dall'inizio e procedere al tuo ritmo. Questa è la lezione 1 di 4.

Quanto tempo richiede la lezione «Ripasso di Async/Await in Python»?

La maggior parte delle lezioni CoddyKit richiede circa 5–10 minuti. Ogni lezione è breve e interattiva, quindi fai progressi costanti e riprendi esattamente da dove hai lasciato su web e app.

Posso scrivere ed eseguire codice in questa lezione FastAPI Backend Development Bootcamp?

Sì. Ogni lezione FastAPI Backend Development Bootcamp include un editor di codice integrato, quindi scrivi ed esegui codice reale direttamente nel tuo browser e ricevi feedback istantaneo dall'IA — nessuna configurazione locale necessaria.

Tutte le lezioni di questo corso

  1. Ripasso di Async/Await in Python
  2. FastAPI e operazioni asincrone
  3. Eseguire attività in background
  4. WebSocket per la comunicazione in tempo reale
← Torna a FastAPI Backend Development Bootcamp