5 Best Ways to Check if a Number is Float in Python

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💡 Problem Formulation: Determining the type of a numeric value is frequently required in Python programming. There are occasions when a program’s logic depends on whether a number is a floating-point value or not. The task is to verify if a given number, such as 4.56, is a float, and not an integer or a string. The expected output is a Boolean value: True if the number is a float, and False otherwise.

Method 1: Using isinstance() Function

An easy and direct way to check if a value is a float in Python is by using the built-in isinstance() function. The isinstance() function checks if the first argument is an instance of the class or tuple of classes given in the second argument.

Here’s an example:

num = 4.56
is_float = isinstance(num, float)
print(is_float)

Output:

True

This snippet checks if the variable num holds a float by using isinstance() with float as the second argument. It effectively distinguishes between different data types, so if num were instead an int, str, or any other type, is_float would be False.

Method 2: Using Type Comparison

Similar to the isinstance() method, you can also verify if a number is a float by comparing its type directly using the type() function. This function returns the type of the given object.

Here’s an example:

num = 7.0
is_float = type(num) == float
print(is_float)

Output:

True

This snippet directly checks if the type of num is float by comparing the result of type(num) with float. It’s a straightforward approach; however, it doesn’t handle subclassing as isinstance() does.

Method 3: Exception Handling with float() Conversion

The float() constructor can be used to test if a value can be converted to a float which indirectly checks if the value is a float in its string form. Using a try-except block, this method can handle the error thrown if the conversion is not possible.

Here’s an example:

num = "3.14"
try:
    float(num)
    is_float = True
except ValueError:
    is_float = False

print(is_float)

Output:

True

The above code attempts to cast the string num to a float. If successful, it sets is_float to True, otherwise the ValueError is caught and is_float is set to False. This works well for strings but isn’t efficient for already numeric types.

Method 4: Regular Expressions

For string inputs that represent numbers, regular expressions can be used to check if they follow the typical pattern of a float. Python’s re module provides regular expression support.

Here’s an example:

import re

num = "56.78"
pattern = "^[-+]?\\d*\\.\\d+$"
is_float = bool(re.match(pattern, num))

print(is_float)

Output:

True

In this method, a regular expression pattern that matches floats is compiled and used to match against the string num. If the string conforms to the pattern, is_float becomes True. This method is powerful for string parsing but overkill for simple type checking.

Bonus One-Liner Method 5: Using a Lambda Function

A concise one-liner to perform the check uses a lambda function that combines type checking and returns a Boolean value.

Here’s an example:

is_float = lambda x: isinstance(x, float)
print(is_float(12.34))

Output:

True

This lambda function is a shorter form of Method 1 using isinstance() and is handy when you need a quick, one-time function without the need to define a full function body.

Summary/Discussion

  • Method 1: isinstance() Function. Reliable and clean. It’s the most Pythonic way to check if an object is of a certain type. However, it doesn’t differentiate between float and subclasses of float.
  • Method 2: Type Comparison. Simple and direct. It works fine but is not advisable in object-oriented programming where subclass checks can be relevant.
  • Method 3: Exception Handling with float() Conversion. Versatile for string inputs. It is overkill for checking the type of a value that is already known to be numeric.
  • Method 4: Regular Expressions. Powerful for parsing text. It’s complex and the slowest method due to the nature of regex pattern matching.
  • Bonus Method 5: Lambda Function. Quick and succinct. Best for situations where a simple, inline function is required for a one-time check.