AsyncIO in Python 3.5: When to Use and When to Avoid Await

When working with asyncio in Python 3.5, it's crucial to understand the appropriate scenarios for using the await syntax.

When to Use Await

Await should be used for asynchronous functions that perform I/O operations. This includes functions that access the file system, the network, or any other resource that may block the execution of the event loop. By using await, the task will be paused until the I/O operation completes, allowing the event loop to process other tasks in the meantime.

Examples of When to Use Await:

• Downloading data from a URL: content = await download(url)
• Opening and reading a file: data = await open_file(filename)
• Sending a request over the network: result = await send_request(data)

When to Avoid Await

Avoid await for functions that do not perform I/O operations. Using await for synchronous code can introduce unnecessary overhead and increase execution time.

Examples of When to Avoid Await:

• Parsing data: parsed_data = parse(input)
• Simple calculations: result = calculate(a, b)
• Manipulating objects: object.value = new_value

Special Considerations:

• Long-running Synchronous Operations: Avoid synchronous operations that take a long time to complete (e.g., over 50 ms) within asynchronous functions. This can block the event loop and prevent other tasks from executing.
• Separate Process for Long Synchronous Operations: If a long-running synchronous operation is necessary, it can be moved to a separate process, freeing the event loop for other tasks.
• ThreadPoolExecutor for I/O Operations: Use ThreadPoolExecutor for I/O operations that should not block the event loop (e.g., requests.get). This can improve performance by avoiding the overhead associated with ProcessPoolExecutor.