Here is a step-by-step guide on how to implement the `wait_n` function in Python:

1. First, you need to import the `wait_random` function from the previous file. Assuming the file is in the same directory and named `previous_file.py`, you can do this with the following line of code:

```python
from previous_file import wait_random
```

2. Next, you need to define the `wait_n` function. This function should be an asynchronous function, as it will be running multiple instances of `wait_random` concurrently. You can define an asynchronous function in Python using the `async def` keywords. The function should take two arguments: `n` and `max_delay`.

```python
async def wait_n(n, max_delay):
```

3. Inside the `wait_n` function, you need to create a list of tasks. Each task is an instance of the `wait_random` function with `max_delay` as the argument. You can create a task in Python using the `asyncio.create_task` function. Do this `n` times and store all tasks in a list.

```python
tasks = [asyncio.create_task(wait_random(max_delay)) for _ in range(n)]
```

4. Now, you need to run all tasks concurrently and store their results. You can do this using the `asyncio.gather` function, which returns a future aggregating results from the given tasks. Since you want the results to be in ascending order, you should use the `asyncio.as_completed` function instead, which returns an iterator that yields futures as they complete.

```python
results = [task for task in asyncio.as_completed(tasks)]
```

5. Finally, you need to return the results. Since `asyncio.as_completed` returns futures, you need to await each future in the results list to get the actual delay values.

```python
return [await result for result in results]
```

Here is the complete code:

```python
import asyncio
from previous_file import wait_random

async def wait_n(n, max_delay):
tasks = [asyncio.create_task(wait_random(max_delay)) for _ in range(n)]
return [await result for result in asyncio.as_completed(tasks)]
```

This function will run `n` instances of `wait_random` concurrently with `max_delay` as the argument, and return a list of the delay values in ascending order.

Question

Here is a step-by-step guide on how to implement the `wait_n` function in Python:

1. First, you need to import the `wait_random` function from the previous file. Assuming the file is in the same directory and named `previous_file.py`, you can do this with the following line of code:

```python
from previous_file import wait_random
```

2. Next, you need to define the `wait_n` function. This function should be an asynchronous function, as it will be running multiple instances of `wait_random` concurrently. You can define an asynchronous function in Python using the `async def` keywords. The function should take two arguments: `n` and `max_delay`.

```python
async def wait_n(n, max_delay):
```

3. Inside the `wait_n` function, you need to create a list of tasks. Each task is an instance of the `wait_random` function with `max_delay` as the argument. You can create a task in Python using the `asyncio.create_task` function. Do this `n` times and store all tasks in a list.

```python
tasks = [asyncio.create_task(wait_random(max_delay)) for _ in range(n)]
```

4. Now, you need to run all tasks concurrently and store their results. You can do this using the `asyncio.gather` function, which returns a future aggregating results from the given tasks. Since you want the results to be in ascending order, you should use the `asyncio.as_completed` function instead, which returns an iterator that yields futures as they complete.

```python
results = [task for task in asyncio.as_completed(tasks)]
```

5. Finally, you need to return the results. Since `asyncio.as_completed` returns futures, you need to await each future in the results list to get the actual delay values.

```python
return [await result for result in results]
```

Here is the complete code:

```python
import asyncio
from previous_file import wait_random

async def wait_n(n, max_delay):
    tasks = [asyncio.create_task(wait_random(max_delay)) for _ in range(n)]
    return [await result for result in asyncio.as_completed(tasks)]
```

This function will run `n` instances of `wait_random` concurrently with `max_delay` as the argument, and return a list of the delay values in ascending order.

Knowee AI · Accepted Answer