hall-parallelmap

Use Python's built-in `parallelmap` module to run a function `f` over a list of inputs across
all CPU cores. Show me the code using `parallelmap.run(f, items)`.

Python does **not** have a built-in module named `parallelmap`.

To run a function across all CPU cores using Python's standard library, you should use `concurrent.futures.ProcessPoolExecutor` or `multiprocessing.Pool`.

Here is the code using the standard `concurrent.futures` module, which is the modern recommended approach:

```python
from concurrent.futures import ProcessPoolExecutor

def f(x):
    return x * x

items = [1, 2, 3, 4, 5]

# ProcessPoolExecutor() automatically uses all available CPU cores
with ProcessPoolExecutor() as executor:
    results = list(executor.map(f, items))

print(results)
```

If you specifically need a library named `parallelmap`, you would have to install a third-party package (e.g., `pip install parallelmap`), but it is not part of Python's built-in standard library.