**π‘ Problem Formulation:** You need a Python program that can verify whether the lengths of a given list of rows (which can be strings, lists, etc.) are in strictly increasing order. For example, given the input `[ "a", "ab", "abc"]`

, the desired output is `True`

since the lengths of the rows are in increasing order: 1, 2, 3.

## Method 1: Using a Straightforward Loop

This method uses a simple for-loop to compare the lengths of consecutive rows, returning False immediately if it finds a row that isn’t longer than the previous one.

Here’s an example:

def increasing_row_lengths(rows): for i in range(len(rows) - 1): if len(rows[i + 1]) <= len(rows[i]): return False return True rows_example = ["hello", "world", "python", "programming"] print(increasing_row_lengths(rows_example))

Output: `False`

In this snippet, the `increasing_row_lengths`

function iterates over the list and compares each element with the next one in terms of length. It returns `False`

if it finds a pair where the next element is not strictly longer, otherwise `True`

. In our example, since “world” and “python” have the same length, it returns `False`

.

## Method 2: Using the ‘all’ Function with a Generator Expression

This method leverages Python’s `all`

function, which returns True if all elements of the iterable are true (or if the iterable is empty). We use a generator expression to compare each row length to the previous one.

Here’s an example:

def increasing_row_lengths(rows): return all(len(rows[i]) < len(rows[i + 1]) for i in range(len(rows) - 1)) rows_example = ["", "hi", "code", "python"] print(increasing_row_lengths(rows_example))

Output: `True`

In this code, the `increasing_row_lengths`

function utilizes the `all`

function with a generator expression that iterates through the row indices. The generator tests if each row is shorter than its successor. It is a concise and efficient method, which returns `True`

for our ascending length example.

## Method 3: Using Zip and List Comprehensions

By combining the zip function with a list comprehension, we can compare consecutive pairs of rows to test the increasing length property, outputting a list of boolean values that can be evaluated with the `all`

function.

Here’s an example:

def increasing_row_lengths(rows): return all(cur < nxt for cur, nxt in zip(rows, rows[1:])) rows_example = ["abc", "defg", "hijkl"] print(increasing_row_lengths(rows_example))

Output: `True`

The code snippet above defines a function that uses list comprehensions in combination with the `zip`

function to create pairs of consecutive rows. It then checks if each current row is shorter than the next, ensuring the lengths are increasing. It’s a concise approach that correctly determines that the example rows increase in length.

## Method 4: Utilizing itertools.tee and starmap

This method uses `itertools.tee`

to create two independent iterators from the original list of rows, then applies `itertools.starmap`

to perform pairwise comparison.

Here’s an example:

from itertools import tee, starmap def increasing_row_lengths(rows): a, b = tee(rows) next(b, None) return all(starmap(lambda x, y: len(x) < len(y), zip(a, b))) rows_example = ["one", "three", "five", "seven"] print(increasing_row_lengths(rows_example))

Output: `True`

The code utilizes the `itertools.tee`

function to duplicate the rows list into two iterators. It advances the second iterator by one using `next`

to skip the first element. By zipping and comparing the iterators element-wise with `itertools.starmap`

, we assert the increasing length condition. This method is slightly more sophisticated and handles large datasets well.

## Bonus One-Liner Method 5: Using itertools.islice for Compactness

This approach is a compact version of the previous method and uses `itertools.islice`

for the same comparison.

Here’s an example:

from itertools import islice def increasing_row_lengths(rows): return all(len(a) < len(b) for a, b in zip(rows, islice(rows, 1, None))) rows_example = ["123", "1234", "12345"] print(increasing_row_lengths(rows_example))

Output: `True`

This one-liner approach is elegant and concise. The `increasing_row_lengths`

function utilizes list slicing with the help of `islice`

to compare the lengths of each row. This is a compact solution that remains readable and expressive, providing the expected `True`

result for rows where each subsequent row is longer than the previous.

## Summary/Discussion

**Method 1:**Simple For-Loop. It’s easy to read and understand. However, it may be considered verbose compared to other more Pythonic methods.

**Method 2:**Using

`all`

and Generator Expressions. This approach is more concise and Pythonic and takes full advantage of built-in functions for readability and simplicity. **Method 3:**Zip and List Comprehensions. Combines two powerful Python idioms for a compact and yet very readable solution. Since it creates an intermediate list, it might not be the most memory efficient for very large datasets.

**Method 4:**itertools.tee and starmap. More advanced use of iterators, suitable for larger datasets, but might be less intuitive for beginners.

**Bonus Method 5:**itertools.islice for Compactness. The most concise method presented, it provides a one-liner solution that maintains readability while being efficient with memory usage.