Python is dynamically typed, means we don’t need to declare the type of a variable in advance. In Python, variables don’t have explicitly declared types like in some other programming languages. However, the type of a variable is determined by the value it holds.

Here are the primary types of variables in Python, along with examples :

1. Numeric Types

These types deal with numbers.

• int: Integer values.
  x = 10 # int
• float: Floating-point (decimal) values.
  y = 10.5 # float
• complex: Complex numbers (real + imaginary parts).
  z = 2 + 3j # complex

2. Sequence Types

These types hold a collection of items.

• str: Strings (text data).
  name = "Alice" # str
• list: Ordered, mutable collections.
  fruits = ["apple", "banana", "cherry"] # list
• tuple: Ordered, immutable collections.
  coordinates = (10, 20) # tuple

3. Set Types

Collections of unique, unordered items.

• set: Mutable, unordered collections.
  unique_numbers = {1, 2, 3} # set
• frozenset: Immutable version of a set.
  immutable_set = frozenset({1, 2, 3}) # frozenset

4. Mapping Types

Associative collections (key-value pairs).

• dict: Dictionary type.
  person = {"name": "Alice", "age": 30} # dict


5. Boolean Type

Represents truth values.

• bool: True or False.
  is_active = True # bool


6. Binary Types

Used for binary data.

• bytes: Immutable sequence of bytes.
  data = b"hello" # bytes
• bytearray: Mutable sequence of bytes.
  mutable_data = bytearray(b"hello") # bytearray
• memoryview: Memory view object.
  memory = memoryview(b"hello") # memoryview

7. None Type

Represents the absence of a value.

• NoneType: Special type indicating no value.
  value = None # NoneType

Dynamic Typing

Python is dynamically typed, where type of a variable can change during execution as below :

Type Checking

You can use the type() function to check the type of a variable:

      x = 42

      print(type(x)) # <class ‘int’>

Python also provides hints for specifying types using type annotations: