How Do Truthy and Falsy Values Differ from True and False in Python?

Unveiling the Truth and Falsity: Truthiness vs. True and Falsiness vs. False in Python

While boolean values True and False represent absolute logical conditions, Python introduces concepts of "truthy" and "falsy" values. These distinctions come into play when evaluating expressions in conditional statements (e.g., if-else, while loops).

Defining Truthy and Falsy Values

Truthy and falsy values differ from true and false in their susceptibility to logical checks. Specifically, all values in Python are considered truthy except for a specific set of "falsy" values:

• None
• False
• Zero-valued numbers (0, 0.0, 0j, etc.)
• Empty strings, lists, tuples, sets, dicts, and other collections
• Objects with bool__() returning False or __len__() returning 0 (if __bool is undefined)

Using Truthy and Falsy Values

The main application of truthy and falsy values lies in conditional statements, where Python interprets non-boolean values as follows:

• Truthy values: Evaluated as True in if statements, loop conditions, and other boolean contexts.
• Falsy values: Evaluated as False in if statements, loop conditions, and other boolean contexts.

Distinguishing Truthiness and Truth, Falsiness and Falsehood

It's crucial to note that truthy values are not necessarily true, and falsy values are not necessarily false. For example, an empty string or list may be considered falsy in a logical check, but they are not explicitly false. This distinction allows for more flexible and nuanced evaluations in programming.

Example:

Consider the following Python code:

Output:

In this example, "Hello" is truthy although it is not strictly True, and the empty list [] is falsy although it is not False. None, on the other hand, is considered neither truthy nor falsy.

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