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Table of Contents
Understanding the Challenges of Combinatorial Existence Verification
Solution 1: Process unique number combinations—use sets (Sets)
core concepts
Implementation steps
Sample code
Code analysis
Run the example
Things to note
Solution 2: Process combinations containing repeated numbers - use counter (Counter)
Summary and best practices
Home Backend Development Python Tutorial A strategy for efficiently checking whether a number combination exists in Python

A strategy for efficiently checking whether a number combination exists in Python

Oct 15, 2025 pm 03:09 PM

A strategy for efficiently checking whether a number combination exists in Python

This article aims to explore how to efficiently determine whether the number combination entered by the user already exists in a predefined number set in Python. The article will elaborate on the verification method of using Python's built-in set data structure to handle unique number combinations, and using collections.Counter to handle scenarios containing repeated number combinations, aiming to provide an accurate and flexible combination existence verification solution.

Understanding the Challenges of Combinatorial Existence Verification

During development, we often encounter scenarios where we need to check whether a specific number combination already exists in a known number pool. For example, given a used number string '1,2,3,4,5,8', when the user enters a new combination '1,3', we need to determine whether both numbers 1 and 3 can be found in '1,2,3,4,5,8'. Raw string inclusion checks (such as if user_key in used_keys) can only determine an exact match of a substring and cannot recognize non-consecutive or reordered number combinations. For example, '1,3' is not a substring of '1,2,3,4,5,8', but its constituent numbers 1 and 3 do exist in the used number pool. Therefore, we need a smarter way to verify the availability of each individual number in the combination.

Solution 1: Process unique number combinations—use sets (Sets)

When each number in the number pool is unique, or we only care about whether the number itself exists and not the number of occurrences, Python's set is an ideal tool to solve such problems. The characteristic of a set is that its elements are unique and unordered, making it very suitable for membership and subset judgment.

core concepts

The core idea of ??this scheme is to convert both used numbers and user-entered number combinations into sets. It then determines whether the combination is available by determining whether the user's set of combinations is a subset of the set of used numbers. If the user's combination set is a subset of the used numbers set, it means that all numbers in the combination already exist in the used numbers pool.

Implementation steps

  1. Data preprocessing: Split the comma-separated string (whether it is numbers or user input) into a list of numeric strings through the split(',') method.
  2. Convert to Set: Convert these lists of numeric strings into set objects.
  3. Subset judgment: Use the issubset() method to check whether the set of user combinations is a subset of the used number set.

Sample code

 # Assuming used numbers, each number is considered unique used_keys_str = '1,2,3,4,5,8'
# Convert the string into a number set available_numbers = set(used_keys_str.split(','))
# Print the set of used numbers, for example: {'1', '2', '4', '5', '8'}

user_key_input = input("Please enter your new combination (for example: 1,3):")

# Convert the combination of user input into a set of numbers input_numbers = set(user_key_input.split(','))

# Check whether the combination entered by the user is a subset of the available numbers if input_numbers.issubset(available_numbers):
    print(f"Your combination ({user_key_input}) already exists.")
else:
    print("Combination available.")

Code analysis

  • used_keys_str.split(','): Split the string '1,2,3,4,5,8' into ['1', '2', '3', '4', '5', '8'].
  • set(...): Convert the list to a set, such as {'1', '2', '3', '4', '5', '8'}.
  • input_numbers.issubset(available_numbers): This is the key step. It checks whether each element in the input_numbers collection exists in the available_numbers collection.

Run the example

  • Enter 1,3:

    • available_numbers = {'1', '2', '3', '4', '5', '8'}
    • input_numbers = {'1', '3'}
    • {'1', '3'} is a subset of {'1', '2', '3', '4', '5', '8'}.
    • Output: Your combination (1,3) already exists. (correct)
  • Enter 1,9:

    • available_numbers = {'1', '2', '3', '4', '5', '8'}
    • input_numbers = {'1', '9'}
    • {'1', '9'} is not a subset of {'1', '2', '3', '4', '5', '8'} (because '9' does not exist).
    • Output: Combinations available. (correct)

Things to note

This method assumes that the input combination strictly follows the comma separated format of 1,2. In practical applications, additional verification of user input must be performed to prevent program errors caused by input that contains non-numeric characters or does not conform to the format.

Solution 2: Process combinations containing repeated numbers - use counter (Counter)

In some advanced scenarios, there may be duplicate numbers in the number pool, and we need to account for these duplications. For example, if the used numbers are '1,2,2,4,5,8', and when the user enters '2,2', we should think that this combination already exists, and when entering '4,4', we should think that the combination is unavailable (because 4 only appears once). In this case, simple set subset judgment is not enough, we need to know the number of occurrences of each number. Python's collections.Counter is a powerful tool for dealing with this type of problem.

core concepts

Counter is a dictionary subclass used to store a count of hashable objects. It can conveniently count the occurrences of each element in the list. By comparing two Counter objects, we can determine whether the number of a combination and its number of occurrences are satisfied in the other combination.

Implementation steps

  1. Data preprocessing: Also split the comma-separated string into a list of numeric strings using the split(',') method.
  2. Convert to Counter: Use collections.Counter to convert these list of numeric strings into Counter objects, which will count the occurrences of each number.
  3. Counter comparison: Use the comparison operator (

Sample code

 from collections import Counter

# Assume numbers used, consider duplication used_keys_str_with_duplicates = '1,2,2,4,5,8'
# Convert the string into a Counter object available_numbers_counter = Counter(used_keys_str_with_duplicates.split(','))
# Print the used number counter, for example: Counter({'2': 2, '1': 1, '4': 1, '5': 1, '8': 1})

user_key_input_with_duplicates = input("Please enter your new combination (for example: 2,2):")

# Convert the combination of user input into a Counter object input_numbers_counter = Counter(user_key_input_with_duplicates.split(','))

# Check if the count of combinations entered by the user is satisfied by the count of available numbers if input_numbers_counter <h4> Code analysis</h4>
  • Counter(used_keys_str_with_duplicates.split(',')): Convert ['1', '2', '2', '4', '5', '8'] to Counter({'2': 2, '1': 1, '4': 1, '5': 1, '8': 1}).
  • input_numbers_counter

Run the example

  • Enter 2,2:

    • available_numbers_counter = Counter({'2': 2, '1': 1, '4': 1, '5': 1, '8': 1})
    • input_numbers_counter = Counter({'2': 2})
    • Counter({'2': 2}) has all element counts less than or equal to available_numbers_counter.
    • Output: Your combination (2,2) already exists. (correct)
  • Enter 4,4:

    • available_numbers_counter = Counter({'2': 2, '1': 1, '4': 1, '5': 1, '8': 1})
    • input_numbers_counter = Counter({'4': 2})
    • The count of '4' in input_numbers_counter is 2, while the count of '4' in available_numbers_counter is 1, which does not satisfy the condition of less than or equal to.
    • Output: Combinations available. (correct)

Summary and best practices

Choosing set or counter depends on your specific needs:

  • Use set: When you only care about the existence of the number itself, regardless of the number of occurrences, or when all numbers should be considered unique, set is a more concise and efficient choice.
  • Using collections.Counter: Counter provides an exact solution when you need to deal with repetitive nature of numbers and the existence of a combination depends on the available quantity of each number.

In actual development, in addition to choosing the correct data structure, you should also pay attention to the following points:

  • Input verification: User input is always strictly verified to ensure that it is in the correct format and only contains expected characters to enhance the robustness of the program.
  • Performance considerations: For extremely large amounts of data, although set and Counter operations are usually very efficient (the average time complexity is close to O(1)), the overhead of data preprocessing (such as split operations) should also be taken into consideration.
  • Clarify the requirements: Before starting to code, clarify whether the repetition of numbers needs to be considered in the business logic. This will directly determine which solution you choose.

Through the above method, we can flexibly and efficiently check the existence of number combinations in Python according to different business needs.

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