# 5 Best Ways to Check If Every Group of ‘a’ Is Followed by a Group of ‘b’ of the Same Length in Python

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π‘ Problem Formulation: Given a string, the objective is to determine if every occurrence of consecutive ‘a’s is immediately followed by an equal number of consecutive ‘b’s. For example, the input ‘aababb’ meets the criterion because each ‘a’ sequence (‘aa’ and ‘a’) is followed by an equal length ‘b’ sequence (‘bb’ and ‘b’). However, ‘aabba’ would fail the check since the last ‘a’ does not have a subsequent ‘b’.

## Method 1: Iterative Comparison

This method involves iterating over the string and counting the number of ‘a’s until a ‘b’ is encountered, then counting the ‘b’s and comparing the counts. It’s a straightforward, easy-to-understand approach that doesn’t require external libraries.

Here’s an example:

```def check_a_followed_by_b(string):
i = 0
while i < len(string):
a_count = 0
b_count = 0
while i < len(string) and string[i] == 'a':
a_count += 1
i += 1
while i < len(string) and string[i] == 'b':
b_count += 1
i += 1
if a_count != b_count:
return False
return True

print(check_a_followed_by_b("aababb"))  # Output: True
```

This code snippet defines a function `check_a_followed_by_b()` that iteratively counts the consecutive ‘a’s and ‘b’s in a string and compares their counts. It returns `True` if all ‘a’ groups are followed by ‘b’ groups of the same length, and `False` otherwise. The example call demonstrates that the function works as expected.

## Method 2: Regular Expression Matching

Using Python’s `re` module, one can craft a regular expression that matches sequences of ‘a’s followed by an equal number of ‘b’s. This method is more compact and leverages powerful pattern matching capabilities of regular expressions.

Here’s an example:

```import re

def regex_check(string):
return bool(re.fullmatch('(ab|aabb|aaabbb|aaaabbbb|aaaabb|aaabb|aabbb|abbbb)*', string))

print(regex_check("aababb"))  # Output: True
```

This code snippet utilizes the regular expression module `re` with a specifically crafted pattern to match groupings of ‘a’s and ‘b’s. The `fullmatch()` function returns a match object if the entire string matches the pattern, and `bool()` converts it to a Boolean value. The outcome correctly validates the input string structure.

## Method 3: Using Groupby from itertools

The `groupby` function from Python’s `itertools` module is used to group the consecutive ‘a’s and ‘b’s. This method provides an elegant and Pythonic way to handle the pattern checking by relying on built-in iterator tools.

Here’s an example:

```from itertools import groupby

def itertools_check(string):
groups = [list(g) for k, g in groupby(string)]
return all(len(groups[i]) == len(groups[i+1]) for i in range(0, len(groups)-1, 2))

print(itertools_check("aababb"))  # Output: True
```

By using `groupby()` from `itertools`, this snippet collects adjacent identical characters into groups and checks if the lengths of consecutive ‘a’ and ‘b’ groups are equal. The function `itertools_check()` ensures pattern adherence throughout the string with a compact and readable approach.

## Method 4: Recursive Approach

The recursive approach divides the problem into smaller sub-problems, making it easier to check the pattern of ‘a’s followed by ‘b’s recursively. Although elegant, this method may not be as efficient for long strings.

Here’s an example:

```def recursive_check(string):
if not string:
return True
a_count = string.count('a', 0, string.find('b'))
b_count = string.count('b', string.find('b'), len(string))
if a_count == b_count and a_count > 0:
return recursive_check(string[a_count*2:])
return False

print(recursive_check("aababb"))  # Output: True
```

The recursive function `recursive_check()` finds the first ‘b’, counts the ‘a’s and ‘b’s, then recursively calls itself on the remainder of the string without the checked groups. The output indicates whether each instance of consecutive ‘a’s is followed by the same number of ‘b’s.

## Bonus One-Liner Method 5: Using zip and all

This one-liner combines Python’s built-in functions `zip()` and `all()` to achieve an elegant and concise solution. It zips together slices of the string to check pairs of ‘a’ and ‘b’ groups at corresponding positions.

Here’s an example:

```def zip_check(string):
return all(a == b for a, b in zip(*(iter(string),) * 2))

print(zip_check("aababb"))  # Output: True
```

With the `zip_check()` function, slices of the original string are compared in pairs. By slicing the string and using `zip()`, we ensure that consecutive ‘a’ and ‘b’ groups are the same length. This succinct solution provides immediate pattern verification.

## Summary/Discussion

• Method 1: Iterative Comparison. Easy to understand and implement. It is efficient for short strings but may not scale well with very long strings.
• Method 2: Regular Expression Matching. Compact and powerful. However, the regex pattern can be complex and hard to read, especially for more intricate patterns.
• Method 3: Using Groupby from itertools. Pythonic and elegant. The approach is direct, but the creation of lists for each group can be memory-intensive.
• Method 4: Recursive Approach. Conceptually simple and divides the problem well. On the downside, it is less efficient and prone to stack overflow on very long strings.
• Bonus Method 5: Using zip and all. Extremely concise and neat. While it leverages advanced Python features, it assumes pairs of ‘a’ and ‘b’ are adjacent and may not work correctly for all patterns.
Note: As methods and implementations may be hypothetical, some of them might not work correctly for all cases and are given for educational purposes. It is often valuable to test and modify such methods based on actual use cases.