# 5 Best Ways to Check if a String Has M Consecutive 1s or 0s in Python

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π‘ Problem Formulation: In various computational problems, it’s necessary to determine whether a string contains a sequence of consecutive similar elements. Specifically, we want to check if a string has ‘m’ consecutive ‘1’s or ‘0’s. For instance, given the string `"001100111"` and `m=3`, our script should indicate that the string contains a sequence of at least three consecutive ‘1’s.

## Method 1: Using Regular Expression

This method employs Python’s `re` module to use regular expressions for detecting consecutive characters. We construct a pattern that matches any sequence of ‘1’s or ‘0’s of a minimum specified length and search the string for this pattern. The function returns `True` if such a pattern exists and `False` otherwise.

Here’s an example:

```import re

def has_consecutive_values(string, m):
pattern = f'0{{{m},}}|1{{{m},}}'
return re.search(pattern, string) is not None

result = has_consecutive_values("001100111", 3)
print(result)```

Output of this script is: `True`.

This approach involves compiling a dynamic regular expression pattern that looks for either ‘m’ or more ‘0’s or ‘1’s in a string. If the pattern is found, the function returns `True`; otherwise, `False`. Regular expressions are powerful and efficient for string matching tasks.

## Method 2: Iterative Checking

The iterative method checks each character in the string one by one to find a sequence of ‘m’ consecutive ‘1’s or ‘0’s. This is a simple linear search, where we look for a run of similar characters and increase a counter if the consecutive characters match and reset it otherwise.

Here’s an example:

```def has_consecutive_values(string, m):
count = 1
for i in range(1, len(string)):
if string[i] == string[i-1]:
count += 1
if count >= m:
return True
else:
count = 1
return False

result = has_consecutive_values("001100111", 3)
print(result)```

Output of this script is: `True`.

This method employs a simple for loop to iterate over the string. If consecutive characters are the same, a counter is increased. If the counter reaches ‘m’, `True` is returned. This method is straightforward but may not be the most efficient for very large strings as it has to scan the whole string in the worst case.

## Method 3: Using Groupby from itertools

The `itertools.groupby()` function can be used to group any sequence into consecutive identical elements. By using this function, we can find the maximum length of a group of ‘1’s or ‘0’s and compare it with ‘m’ to verify the condition.

Here’s an example:

```from itertools import groupby

def has_consecutive_values(string, m):
return any(len(list(group)) >= m for _, group in groupby(string))

result = has_consecutive_values("001100111", 3)
print(result)```

Output of this script is: `True`.

By utilizing `itertools.groupby()`, the function aggregates the string into groups of consecutive identical characters, then it checks if the length of any group is at least ‘m’. This method is compact and leverages Python’s standard library effectively.

## Method 4: Using the in-build ‘in’ operator

A straightforward check involves using the built-in ‘in’ operator to test for the existence of a substring made of ‘m’ repeated ‘1’s or ‘0’s. This method is best for fixed smaller values of ‘m’, as it becomes less practical for larger sequences.

Here’s an example:

```def has_consecutive_values(string, m):
return ('1' * m in string) or ('0' * m in string)

result = has_consecutive_values("001100111", 3)
print(result)```

Output of this script is: `True`.

This code snippet forms strings composed of ‘m’ consecutive ‘1’s and ‘0’s and uses the ‘in’ operator to check if either is present in the input string. It’s a simple and readable technique but may not scale well with variable ‘m’ since it doesn’t preprocess the original string.

## Bonus One-Liner Method 5: Using lambda and map

This compact one-liner solution uses a lambda function in conjunction with the map function to check for sequences of ‘m’ consecutive ‘1’s or ‘0’s. Despite its brevity, it is powerful and reads well.

Here’s an example:

```result = lambda s, m: bool(sum(map(lambda x: x * m in s, ['1', '0'])))
print(result("001100111", 3))```

Output of this script is: `True`.

In one line, the lambda function maps two strings (‘m’ copies of ‘1’ and ‘0’) checking if either is in the input string, with the boolean result reduced by `sum()`. It’s concise and can handle variable ‘m’, but readability may be compromised for less experienced Python users.

## Summary/Discussion

• Method 1: Regular Expression. Very powerful, but can be slower for very long strings or complex patterns.
• Method 2: Iterative Checking. Simple and intuitive, but potentially less efficient for long strings.
• Method 3: Groupby from itertools. Exploits a powerful standard library function; clean and readable.
• Method 4: In-build ‘in’ operator. Extremely readable, best for smaller or fixed ‘m’; less practical for variable and larger ‘m’ values.
• Method 5: Lambda and map. Compact and elegant; potentially less readable for new developers.