# 5 Best Ways to Find the Length of the Longest Possible Stick in Python

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π‘ Problem Formulation: This article aims to tackle the challenge of finding the length of the longest stick that can be formed from a given collection of stick lengths. The problem entails processing a list of integers that represent different stick lengths and determining the maximum stick length that can be achieved by connecting any two. For instance, given an input list `[2, 3, 1, 4]`, the longest stick possible would be of length `4` (i.e., by selecting the stick of length 4 directly).

## Method 1: Using Max Function

This method employs the built-in Python function `max()` to directly determine the length of the longest stick in the list. It is the most straightforward approach to solve the problem and is highly efficient, especially when dealing with larger datasets.

Here’s an example:

```def longest_stick(sticks):
return max(sticks)

print(longest_stick([2, 3, 1, 4]))
```

Output: `4`

The function `longest_stick()` receives a list of integers and uses `max()` to return the greatest value, which represents the longest stick.

## Method 2: Sorting and Selecting Last Element

This method sorts the list in ascending order and then returns the last element which would be the longest one. While sorting takes extra time, this method works well if further operations with sorted lists are required afterward.

Here’s an example:

```def longest_stick(sticks):
return sorted(sticks)[-1]

print(longest_stick([2, 3, 1, 4]))
```

Output: `4`

The function `longest_stick()` sorts the list of stick lengths and then selects the last element, conveniently the largest, and returns it as the longest stick length.

## Method 3: Iterative Comparison

In this technique, we iterate through the list, comparing each element with the current maximum to find the longest stick. It’s a traditional approach for those preferring a manual and detailed control over the algorithm’s flow.

Here’s an example:

```def longest_stick(sticks):
max_length = sticks[0]
for stick in sticks[1:]:
if stick > max_length:
max_length = stick
return max_length

print(longest_stick([2, 3, 1, 4]))
```

Output: `4`

Starting from the first stick length as the initial maximum, the `longest_stick()` function iterates through the remaining lengths, updating the maximum as needed, and ultimately returns the maximum at the end of iteration.

## Method 4: Using Heapq to Extract Max

The `heapq` module provides a way to efficiently extract the maximum element from a list. By maintaining the list properties of a heap, the largest element can be retrieved directly. This is typically more efficient than sorting the entire list if we’re only interested in the maximum value.

Here’s an example:

```import heapq

def longest_stick(sticks):
return heapq.nlargest(1, sticks)[0]

print(longest_stick([2, 3, 1, 4]))
```

Output: `4`

The function `longest_stick()` uses `heapq.nlargest()` to return a list with the single largest element from the original list, which is then accessed using index `[0]`.

## Bonus One-Liner Method 5: Using Lambda with Max

This elegant one-liner uses a lambda function within the `max()` function call to achieve the same result as Method 1. It showcases Python’s functional programming abilities and results in concise and readable code.

Here’s an example:

```print(max([2, 3, 1, 4], key=lambda x: x))
```

Output: `4`

The lambda function passed to `max()` simply returns the value of the element it receives, which effectively makes `max()` operate normally and return the largest element in the list.

## Summary/Discussion

• Method 1: Using Max Function. Straightforward and very efficient. Best for simple cases where only the maximum length is required.
• Method 2: Sorting and Selecting Last Element. Involves additional sorting steps that might be unnecessary but can be useful if further sorted processing is mandatory.
• Method 3: Iterative Comparison. Offers detailed control and avoids built-in functions. It’s slower than `max()` but more educational for understanding the mechanics of maximum value comparison.
• Method 4: Using Heapq to Extract Max. Efficient for large datasets where only the max element is needed without sorting the whole list. More complex usage than the simple `max()` function.
• Method 5: Bonus One-Liner. Ideal for concise code lovers. Provides a quick, functional programming-based solution, although it may be overkill for such a simple task.