Write a Python function to find the nth number in the Fibonacci Sequence.

all answers

# The Fibonacci sequence is a series of numbers in which each number ( Fibonacci number )
    # is the sum of the two preceding numbers. The sequence begins with 0 and 1.
    # For example, here are the first 10 Fibonacci numbers:
    # 0, 1, 1, 2, 3, 5, 8, 13, 21 and 34.
    # Write a Python function that takes in input n and prints out the nth Fibonacci number.
    # For example, if n is 10, the output should be 34.
    # If n is 20, the output should be 102641527.
    # If n is 1, the output should be 1.
    # If n is 2, the output should be 1.
    # If n is 3, the output should be 2.
    # If n is 4, the output should be 3.
    # If

Write a Python function that prints the next 20 leap years. Reply with only the function.

all answers

def leap_year(year):
    if year % 4 == 0:
        if year % 100 == 0:
            if year % 400 == 0:
                return True
            else:
                return False
        else:
            return True
    else:
        return False


def next_20_leap_years():
    for i in range(20):
        year = 2020 + i
        if leap_year(year):
            print(year)


next_20_leap_years()

Explain the bug in the following code:

```
from time import sleep
from multiprocessing.pool import ThreadPool
 
def task():
    sleep(1)
    return 'all done'

if __name__ == '__main__':
    with ThreadPool() as pool:
        result = pool.apply_async(task())
        value = result.get()
        print(value)
```

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### Solution

The problem is that the `ThreadPool` is not being used correctly. The `apply_async` method is called with the result of the `task` function, not with the function itself.

```
from time import sleep
from multiprocessing.pool import ThreadPool
 
def task():
    sleep(1)
    return 'all done'

if __name__ == '__main__':
    with ThreadPool() as pool:
        result = pool.apply_async(task)
        value = result.get()
        print(value)
```

### Solution 2

Another way to solve the problem is to use the `ThreadPool` as a context manager.

```
from time import sleep
from multiprocessing.pool import ThreadPool
 
def task():
    sleep(1)
    return 'all done'

if __name__ == '__main__':
    with ThreadPool(processes=1) as pool:
        value = pool.apply(task)
        print(value

Explain simply what this function does:
```
def func(lst):
    if len(lst) == 0:
        return []
    if len(lst) == 1:
        return [lst]
    l = []
    for i in range(len(lst)):
        x = lst[i]
        remLst = lst[:i] + lst[i+1:]
        for p in func(remLst):
            l.append([x] + p)
    return l
```

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### 2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2