5 Best Ways to Check if a Number is Within a Range in Python

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💡 Problem Formulation: When working with data in Python, it’s common to check whether a number falls within a specific range. The ability to efficiently validate this can be critical, for example, when parsing user input or evaluating conditions. Consider the situation where your input is an integer value, say 10, and you want to test if it is within the range of 1 to 20. The output should be a boolean value indicating whether the number meets the range criteria.

Method 1: Using Comparison Operators

This method directly utilizes Python’s comparison operators to check whether a number falls within a range. It’s arguably the most straightforward approach to perform this check, as it involves writing a simple conditional statement that returns a boolean value.

Here’s an example:

number = 10
is_in_range = 1 <= number <= 20
print(is_in_range)

Output: True

In this snippet, we assign the value 10 to the variable number and use comparison operators to evaluate if it lies between 1 and 20. The variable is_in_range holds the result, which is then printed.

Method 2: Using the range() Function

The range() function in Python creates a sequence of numbers and can be combined with the in keyword to check for inclusiveness within that sequence. This method is useful when working with sequences directly.

Here’s an example:

number = 10
is_in_range = number in range(1, 21)
print(is_in_range)

Output: True

By creating a range from 1 to 21 (the upper bound is non-inclusive), we can simply use the in keyword to check if number is a part of this sequence. This method easily checks the presence of the number in the generated range.

Method 3: Using a Custom Function

Defining a custom function allows for reusability and encapsulation. The function can be called with different numbers and ranges without rewriting the condition each time. This can be a clean and modular approach within a larger codebase.

Here’s an example:

def is_number_in_range(number, range_start, range_end):
    return range_start <= number <= range_end

number = 10
print(is_number_in_range(number, 1, 20))

Output: True

The custom function is_number_in_range() takes a number and range boundaries as arguments and returns a boolean after evaluation. This example illustrates a straightforward and maintainable way to check for range inclusiveness.

Method 4: Using Math Library Functions

This method leverages Python’s built-in math module to clamp the number within a range and then compare it to the original number. This is especially useful when the range is a part of a more complex numerical computation.

Here’s an example:

import math

number = 10
range_start = 1
range_end = 20

clamped_number = math. clamp(number, range_start, range_end)
is_in_range = number == clamped_number

print(is_in_range)

Output: True

The math.clamp() function constrains number within the given range_start and range_end. Comparing the clamped value to the original number tells us if it was already within the range. This method may be less straightforward but allows for a different approach in certain contexts.

Bonus One-Liner Method 5: Using Logical And

This concise method uses a logical AND operation within a single expression to check range inclusiveness. It’s a compact one-liner that’s great for inline checks.

Here’s an example:

print(1 <= (number := 10) <= 20)

Output: True

The walrus operator (:=) assigns 10 to number and immediately checks it against the range bounds. This one-liner method is efficient and Pythonic, suitable for quick checks without the need for additional variables.

Summary/Discussion

  • Method 1: Comparison Operators. Straightforward and readable. Mostly suitable for simple, one-off checks.
  • Method 2: Use of range(). Intuitive and pythonic. It can potentially introduce a slight overhead when dealing with very large ranges, as it creates a range object.
  • Method 3: Custom Function. Flexible and maintainable. Additional effort to define the function, but offers reusability and better structure for complex applications.
  • Method 4: Math Library Functions. More suited for numerical contexts. Slightly less intuitive than other methods and requires importing an additional module.
  • Method 5: Logical And One-Liner. Compact and elegant. While concise, it can be less readable to those unfamiliar with the walrus operator.