Data Structures

Python’s built-in collections

Python ships four general-purpose container types in the language core — no imports required.

Type	Syntax	Mutable	Ordered	Duplicates
`list`	`[1, 2, 3]`	yes	yes	yes
`tuple`	`(1, 2, 3)`	no	yes	yes
`dict`	`{"a": 1}`	yes	yes (3.7+)	keys: no
`set`	`{1, 2, 3}`	yes	no	no

Each type has a distinct strength: lists for ordered sequences, tuples for fixed records, dicts for key-value lookup, and sets for membership tests and set algebra.

Choosing the right collection

Reach for a list when you need to append, sort, or index items by position.
Use a tuple when the data is fixed and positional meaning matters (e.g., an RGB colour, a database row).
Use a dict when you need fast key-based lookup or want to group named attributes without defining a class.
Use a set when uniqueness is the primary concern or you need union / intersection / difference operations.

Runnable overview

Open in an online REPL

from collections import namedtuple

# --- list ---
nums = [1, 2, 3, 4, 5]
print('list:', nums)
print('sum:', sum(nums))

# --- tuple unpacking ---
coords = (10, 20, 30)
x, y, z = coords
print('tuple unpack:', x, y, z)

# --- dict (insertion order preserved since Python 3.7) ---
scores = {'alice': 95, 'bob': 87, 'carol': 92}
print('dict:', scores)
print('alice score:', scores['alice'])

# --- set (duplicates removed automatically) ---
unique = {3, 1, 4, 1, 5, 9, 2, 6, 5}
print('set:', sorted(unique))

# --- namedtuple: lightweight named record ---
Point = namedtuple('Point', ['x', 'y'])
p = Point(3, 4)
print('namedtuple:', p.x, p.y)