Python data types define the kind of value a variable holds and the operations that can be performed on it. Python is dynamically typed, so you don’t need to declare variable types explicitly.

1. Basic Data Types

name = "Viet"       # str
age = 25            # int
price = 99.99       # float
is_active = True    # bool
result = None       # NoneType

Use type() to inspect a value’s type:

print(type(age))  # <class 'int'>

2. Collection Types

Python provides four common collection types:

numbers = [1, 2, 2, 3]              # list
coordinates = (10, 20)              # tuple
unique_numbers = {1, 2, 3}          # set
user = {"name": "Viet", "age": 25}  # dict

3. Type Conversion

Convert values using built-in functions such as int(), float(), str(), and bool().

age = int("25")
price = float("19.99")
message = str(100)

Invalid conversions can raise exceptions, such as ValueError.

4. Dynamic Typing vs. Type Hints

Python allows a variable to reference values of different types.

value = 10
value = "hello"

Type hints document expected types and support static analysis, but Python does not enforce them automatically at runtime.

def add(a: int, b: int) -> int:
    return a + b