# 5 Best Ways to Test if Different Float Sizes are Subtypes of the Python Floating Class

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π‘ Problem Formulation: When dealing with floating-point numbers in Python, it’s essential to understand their hierarchy and how different float sizes relate to the base ‘float’ class. The goal is to test whether various floating-point types, regardless of their precision or storage size, are considered subtypes of Python’s built-in floating class. These methods will provide outputs indicating inheritance relationships.

## Method 1: Using the `isinstance()` Function

This method involves using Python’s built-in function `isinstance()`, which checks if an object is an instance of a class or of a subclass thereof. For our purpose, this function will help determine if a given floating-point variable, no matter its size, is an instance of Python’s `float` class, thus confirming it as a subtype.

Here’s an example:

```float_var = 3.14    # A standard float variable
print(isinstance(float_var, float))```

Output: `True`

This code snippet creates a floating-point variable `float_var` and then checks if it is an instance of the `float` class. As expected, `isinstance()` returns `True`, confirming that standard floating-point variables are indeed of the type `float`.

## Method 2: Using the `issubclass()` Function

The `issubclass()` function is another built-in function that we can use to verify the subtype relationship. It checks for class inheritance directly rather than instance membership. In Python’s numeric tower, the float class does not have explicit subtypes for different sizes, so this method is more educational about inheritance patterns.

Here’s an example:

`print(issubclass(float, object))`

Output: `True`

In this example, we check if `float` is a subclass of `object`, which is the base class for all new-style classes in Python. Every class in Python 3 is a subclass of `object`, hence why `True` is returned.

## Method 3: Checking Class Hierarchy with `__bases__` Attribute

The `__bases__` attribute of a class returns a tuple containing the base classes of the class. Utilizing this attribute will allow us to investigate the class hierarchy and determine if different float sizes are derived from the float class.

Here’s an example:

`print(float.__bases__)`

Output: `(<class 'object'>,)`

By examining the base classes of the `float` class, we can see that its only direct superclass is `object`. Since Python does not have different floating-point types with various precision as subclasses of `float`, this confirms that there’s a single `float` type directly under `object`.

## Method 4: Utilizing the `type()` Function

This method involves the `type()` function, which returns the type of an object. If we assign different floating-point values of different sizes to variables, we can use `type()` to confirm their type is indeed `float`.

Here’s an example:

```num_small = 1.5e-5
num_large = 1.5e306
print(type(num_small) == float, type(num_large) == float)```

Output: `True True`

Regardless of the precision or size of the floating-point value assigned to `num_small` and `num_large`, the `type()` function confirms that both are instances of the `float` class.

## Bonus One-Liner Method 5: Using a Simple Ternary Operator

A Pythonic one-liner that employs a ternary operator can swiftly determine the type of a variable. It combines the utility of `type()` with concise syntax to verify if a variable is a subtype of `float`.

Here’s an example:

```your_float = 0.0
result = "Float subclass" if type(your_float) == float else "Not a Float subclass"
print(result)```

Output: `Float subclass`

By setting a floating-point number to `your_float`, and using the ternary operator to check its type, we quickly ascertain that the number is indeed a subtype of `float`, demonstrating the simplicity of the one-liner for this purpose.

## Summary/Discussion

• Method 1: Using `isinstance()`. Strengths: Straightforward and widely-used for type-checking. Weaknesses: Can only be used with instances, not types themselves.
• Method 2: Using `issubclass()`. Strengths: Directly checks class inheritance. Weaknesses: Not practical for inspecting float subtypes as Python does not define different sizes of floats as unique subclasses.
• Method 3: Checking class hierarchy with `__bases__`. Strengths: Inspects the class hierarchy directly. Weaknesses: May not offer practical subtype information for built-in types like float, which typically don’t have subtypes.
• Method 4: Utilizing the `type()` Function. Strengths: Simple and effective for checking the object’s type. Weaknesses: Does not explicitly check for subtype relationships.
• Method 5: Using a Simple Ternary Operator. Strengths: Pythonic and concise one-liner. Weaknesses: Limited to simple type checks and does not convey detailed inheritance information.