💡 Problem Formulation: In Python programming, it is common to face situations where data clean-up is necessary. In this article, we look into the problem of removing numbers with repeating digits from a list. For instance, given the input [123, 112, 331, 456], the desired output would be [123, 456], as the numbers 112 and 331 have repeating digits.
Method 1: Using Iteration and Set
This method involves iterating over the list of numbers and checking if the number of unique digits using a set is less than the total number of digits in the number. This method is explicit and easy to understand, making it ideal for beginners.
Here’s an example:
def remove_repeating(numbers):
result = [num for num in numbers if len(str(num)) == len(set(str(num)))]
return result
my_numbers = [123, 112, 331, 456]
print(remove_repeating(my_numbers))Output:
[123, 456]
This snippet defines a function called remove_repeating() that takes a list of numbers as an argument. It uses list comprehension to iterate through the numbers and retain only those that have a distinct set of digits—indicating no repetitions.
Method 2: Regular Expression Matching
Python’s re module can be used to define a pattern that matches repeating digits and filter out those numbers. This method is more sophisticated and requires understanding of regular expressions, which can be more efficient for large datasets.
Here’s an example:
import re
def remove_repeating(numbers):
pattern = r'(\d).*\1'
return [num for num in numbers if not re.search(pattern, str(num))]
my_numbers = [123, 112, 331, 456]
print(remove_repeating(my_numbers))Output:
[123, 456]
The code defines a function remove_repeating() that utilizes the regular expression module to define a pattern that matches any number with repeating digits. The list comprehension filters only those numbers that do not match the pattern.
Method 3: Using a Custom Function
This method employs a custom function that checks for repeating digits by comparing each digit with every other digit in the number. This approach does not require additional modules and is quite straightforward in its logic.
Here’s an example:
def has_repeating_digits(number):
digits = str(number)
for i, digit in enumerate(digits):
if digit in digits[:i] + digits[i + 1:]:
return True
return False
def remove_repeating(numbers):
return [num for num in numbers if not has_repeating_digits(num)]
my_numbers = [123, 112, 331, 456]
print(remove_repeating(my_numbers))Output:
[123, 456]
The function has_repeating_digits() is used to check if a number has repeating digits. This boolean function is then used in the remove_repeating() function to filter numbers without repeating digits using a list comprehension.
Method 4: Using the itertools.groupby Function
The itertools.groupby function is a powerful tool in Python that can help identify and group repeating characters. By checking if any group is larger than 1, we can determine if there are repeating digits.
Here’s an example:
from itertools import groupby
def remove_repeating(numbers):
return [num for num in numbers if all(len(list(group)) == 1 for _, group in groupby(str(num)))]
my_numbers = [123, 112, 331, 456]
print(remove_repeating(my_numbers))Output:
[123, 456]
This function remove_repeating() makes use of the groupby function to iterate over groups of repeating digits. If all groups contain only one digit, it means there are no repeating digits, so the number is included in the result.
Bonus One-Liner Method 5: Using Set and Filter
An elegant one-liner solution utilizes the set data structure within a filter function to extract numbers with unique digits. This method showcases the concise power of Python’s functional programming capabilities.
Here’s an example:
my_numbers = [123, 112, 331, 456] print(list(filter(lambda num: len(str(num)) == len(set(str(num))), my_numbers)))
Output:
[123, 456]
This one-liner uses a lambda function that returns True if the number has all unique digits. The filter() function applies this lambda to each element, and the resulting filter object is converted to a list to print the filtered numbers.
Summary/Discussion
- Method 1: Set and Iteration. Simple and beginner-friendly. May not be the most efficient for large datasets.
- Method 2: Regular Expressions. Offers high performance and is powerful for pattern matching. However, it requires knowledge of regex patterns, which can be complex.
- Method 3: Custom Function. Understandable logic and does not rely on external libraries. It is not as concise or as optimized as other methods.
- Method 4: itertools.groupby. Utilizes standard library tools and is efficient. However, its syntax and behavior might be less intuitive for those unfamiliar with itertools.
- Bonus Method 5: Set and Filter One-Liner. Extremely concise and showcases Python’s functional programming aspect. It may sacrifice some readability for brevity.