Is Python Strongly Typed or Weakly Typed?

Is Python's Type System Strong or Weak?

The statement "Python is strongly typed" seems paradoxical, considering that it allows type changes at runtime, such as:

bob = 1
bob = "bob"

However, Python's type system is indeed strong, but dynamic.

Strong Typing:

Strong typing ensures that the type of a variable does not change unexpectedly. In Python, every expression has a type that can be determined at runtime using the type() function. Assigning a value of a different type to a variable requires an explicit conversion.

Dynamic Typing:

Dynamic typing means that the type of a variable is associated with its value, not with the variable itself. In Python, variables do not have explicit types; they can name any value. When the value assigned to a variable changes, so does the type of the variable.

In the example above, bob initially has the value 1 and thus the type int. After the assignment to "bob", bob has the value "bob" and the type str.

Comparison to Weak and Static Typing:

Contrast Python's strong, dynamic typing with the following types:

• Weak static typing (e.g., C): Variables have types, but conversions between types are often implicit. This can lead to errors when different types are treated as equivalent.
• Strong static typing (e.g., Haskell): Variables have explicit types that cannot change. Conversions between types require explicit casts.

Strength of Type System:

The "strongness" of a type system is not binary. Python's type system is strong in that it enforces explicit type conversions. However, it is still possible to use overloaded operators to achieve implicit conversions between certain types. This is a design choice that balances flexibility with type safety.

Ultimately, Python's strong, dynamic type system provides flexibility and expressiveness while still ensuring that the type of a variable does not change unexpectedly.

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