by Dynamic-typed and Strongly typed languages are two concepts in programming languages related to how variables are handled and how type rules are enforced.
Dynamic–Typed Languages:
In dynamically typed languages, the type of a variable is determined at runtime rather than at compile-time. This means you don’t need to explicitly declare the type of a variable when you write the code. The interpreter infers the type based on the value assigned to the variable.
Characteristics:
- Runtime Type Checking: The type of a variable is checked during execution, allowing variables to change type on the fly.
- Flexibility: Since variables can change types, dynamically typed languages offer more flexibility and can be more concise and easier to write.
- Potential for Runtime Errors: Because type errors are not caught until the code is executed, there’s a higher potential for runtime errors.
Examples:
- Python:
x = 5 # x is an integer
x = “Hello” # now x is a string
- JavaScript:
let x = 5; // x is a number
x = “Hello”; // now x is a string
Strongly Typed Languages:
A strongly typed language enforces strict type rules and does not allow implicit type conversion between different data types. This means that once a variable is assigned a type, it cannot be used in ways that are inconsistent with that type without an explicit conversion.
Characteristics:
- Type Safety: Strongly typed languages prevent operations on incompatible types, reducing bugs and unintended behaviors.
- Explicit Conversions: If you need to convert between types, you must do so explicitly, ensuring that the programmer is aware of and controls the conversion.
- Compile-Time and Runtime Checks: Type enforcement can happen both at compile-time and runtime, depending on the language.
Examples:
- Java (strongly typed, statically typed):
int x = 5;
// x = “Hello”; // This would cause a compile-time error
- Python (strongly typed, dynamically typed):
x = 5
# x + “Hello” # This would cause a runtime TypeError
Combining Both Concepts:
Languages can be both dynamic and strongly typed. This means they determine types at runtime but enforce strict type rules once those types are known. Python is a prime example of this combination:
- Python:
x = 10 # x is an integer
y = “20” # y is a string
# z = x + y # This raises a TypeError because you can’t add an integer to a string without explicit conversion
Static vs. Dynamic and Strong vs. Weak Typing:
It’s important to distinguish between the dynamic/static and strong/weak typing spectra:
- Static Typing: Types are checked at compile-time (e.g., Java, C++).
- Dynamic Typing: Types are checked at runtime (e.g., Python, JavaScript).
- Strong Typing: Strict enforcement of type rules (e.g., Python, Java).
- Weak Typing: More permissive type rules and implicit conversions (e.g., JavaScript).
