Python includes ten core container types organised into three categories: sequences, sets, and mappings. Each container holds references to other objects and supports membership tests (in).

Sequences (7 Types)

Sequences are ordered and indexable collections. Some are mutable; others are not.

1. list

• Mutable, ordered collection of arbitrary objects
• Allows duplicates
• Syntax: fruits = ['apple', 'banana', 'cherry']

2. tuple

• Immutable, ordered collection
• Allows duplicates
• Syntax: coords = (10, 20, 30)

3. range

• Immutable sequence of integers
• Defined by start, stop, step
• Efficient for loops, no full list in memory
• Syntax: for i in range (1, 5): # 1, 2, 3, 4

4. str

• Immutable sequence of Unicode characters
• Supports slicing, concatenation
• Syntax: greeting = "Hello, World!"

5. bytes

• Immutable sequence of bytes (0–255)
• Use for binary data
• Syntax: data = b’\x01\x02\x03′

6. bytearray

• Mutable counterpart to bytes
• Supports in-place modification
• Syntax: buf = bytearray(b’\x00\x01′)

buf[0] = 0xFF

7. memoryview

• View on buffer-supporting objects (bytes, bytearray)
• Allows slicing without copying
• Syntax: mv = memoryview(b’abcdef’)

slice_mv = mv[2:4] # b’cd’

Sets (2 Types)

Sets store unordered, unique elements. Fast membership and set operations.

8. set

• Mutable collection of unique, hashable objects
• Syntax: primes = {2, 3, 5, 7}

primes.add(11)

9. frozenset

• Immutable version of set
• Can be used as dictionary keys or elements of another set
• Syntax: frozen = frozenset([1, 2, 2, 3]) # {1, 2, 3}

Mappings (1 Type)

Mappings associate keys with values.

10. dict

• Mutable collection of key→value pairs
• Keys must be hashable and unique
• Supports iteration over keys, values, items
• Syntax: person = {‘name’: ‘Alice’, ‘age’: 30}

person['city'] = ‘Tokyo’

Each of these containers has its performance characteristics and use cases. It can be mutable or immutable types.