**π‘ Problem Formulation:** You have a Python dictionary where each key is associated with a list of numeric values. You want to find out which key corresponds to the list with the largest range (difference between the maximum and minimum values). For instance, given the input `{'A': [1, 2, 3], 'B': [4, 5, 6, 7], 'C': [8, 9]}`

, the desired output is `'B'`

, as the range of list B (3) is the largest.

## Method 1: Iterate and Compare Ranges

This method involves iterating through the dictionary items, calculating the range of each list, comparing it with the maximum found so far, and updating the key with the maximum range. It requires no additional imports and uses basic Python functionality, making it very straightforward.

Here’s an example:

numbers_dict = {'A': [1, 2, 3], 'B': [4, 5, 6, 7], 'C': [8, 9]} max_range_key = None max_range_value = -float('inf') for key, values in numbers_dict.items(): current_range = max(values) - min(values) if current_range > max_range_value: max_range_key = key max_range_value = current_range print(max_range_key)

Output:

B

This snippet creates a dictionary named `numbers_dict`

and initializes two variables, `max_range_key`

and `max_range_value`

, for tracking the key with the maximum range. It then loops through each item in the dictionary, calculates the range of its list, and updates our tracking variables accordingly. Finally, it prints the key with the highest range.

## Method 2: Using max() Function with key Argument

The built-in `max()`

function can be utilized effectively here by providing a custom `key`

function that returns the range of the list of values. This method boils down the problem to a single line of Python code inside the `max()`

call and is a very pythonic solution.

Here’s an example:

numbers_dict = {'A': [1, 2, 3], 'B': [4, 5, 6, 7], 'C': [8, 9]} max_range_key = max(numbers_dict, key=lambda k: max(numbers_dict[k]) - min(numbers_dict[k])) print(max_range_key)

Output:

B

The example uses the `max()`

function with a lambda function as the `key`

argument that computes the range of the list corresponding to each key. The `max()`

function then returns the key with the largest range, which is printed out.

## Method 3: Using List Comprehension and zip()

This approach employs list comprehension to create a list of ranges for each key’s list and the `zip()`

function to pair each key with its corresponding range. It then uses the `max()`

function to find the largest range, and its corresponding key.

Here’s an example:

numbers_dict = {'A': [1, 2, 3], 'B': [4, 5, 6, 7], 'C': [8, 9]} ranges = [max(lst) - min(lst) for lst in numbers_dict.values()] keys = list(numbers_dict.keys()) max_range_key = keys[ranges.index(max(ranges))] print(max_range_key)

Output:

B

This code first computes a list of ranges using list comprehension. It then creates a separate list of keys from the dictionary. By finding the index of the maximum value in the list of ranges and retrieving the key at the same index from the keys list, we get the key associated with the maximum range.

## Method 4: Using a Custom Function and max()

Create a custom function that computes the range of a given list and use it with the `max()`

function to directly obtain the key with the largest range. This method is clean, testable, and easily maintainable.

Here’s an example:

def calc_range(lst): return max(lst) - min(lst) numbers_dict = {'A': [1, 2, 3], 'B': [4, 5, 6, 7], 'C': [8, 9]} max_range_key = max(numbers_dict, key=lambda k: calc_range(numbers_dict[k])) print(max_range_key)

Output:

B

This example defines a function `calc_range`

which calculates the range of a list. The `max()`

function is then used with a lambda that calls `calc_range`

for each list associated with a key in the dictionary. The key with the largest resulting range is returned and printed out.

## Bonus One-Liner Method 5: Using map() and max()

This approach combines the `map()`

function with `max()`

to obtain the key corresponding to the maximum range in a condensed one-liner. This method showcases a functional programming style.

Here’s an example:

numbers_dict = {'A': [1, 2, 3], 'B': [4, 5, 6, 7], 'C': [8, 9]} max_range_key = max(zip(numbers_dict.keys(), map(lambda v: max(v) - min(v), numbers_dict.values())))[0] print(max_range_key)

Output:

B

The one-liner uses `map()`

to apply a lambda function that calculates the range to each list of values. The resulting ranges are paired with the keys using `zip()`

, and the pair with the maximum range is found using `max()`

. The first element of this pair (the key) is the desired output.

## Summary/Discussion

**Method 1:**Iterate and Compare Ranges. Strengths are its simplicity and clarity. Weaknesses include potentially verbose code and manual tracking of maximum values.**Method 2:**Using max() Function with key Argument. Its strength lies in its succinct and pythonic approach. The weakness is that the lambda function recalculates the min and max for each comparison.**Method 3:**Using List Comprehension and zip(). Strengths include readability and effective use of Python constructs. Weaknesses might be a bit more memory usage due to the storage of all ranges.**Method 4:**Using a Custom Function and max(). It provides clear and maintainable code. As with Method 2, it can be inefficient due to recalculating min and max multiple times.**Method 5:**Bonus One-Liner Using map() and max(). This method is very concise, showcasing a functional programming style. However, the single-line complexity might make it harder to understand for beginners.