How to install Python with pyenv version manager

🐍 Python Collection Data Types

⚖️ Quick Comparison Table

Type	Ordered	Mutable	Unique	Indexable	Duplicates Allowed	Notable Use Case
list	✅	✅	❌	✅	✅	General-purpose sequence
tuple	✅	❌	❌	✅	✅	Fixed-size data
set	❌	✅	✅	❌	❌	Unique elements, set operations
frozenset	❌	❌	✅	❌	❌	Immutable set
dict	✅	✅	✅ (keys)	✅ (by key)	✅ (values only)	Key-value pairs
deque	✅	✅	❌	Limited (0, -1)	✅	Fast double-ended queue
namedtuple	✅	❌	❌	✅, attr access	✅	Tuple with field names
defaultdict	✅	✅	✅ (keys)	✅ (by key)	✅ (values only)	Dict with auto-init for missing keys
Counter	✅	✅	✅ (keys)	✅ (by key)	✅ (values count duplicates)	Counting/frequency of elements

🔹 dict keys must be unique
🔹 Tuples can be used as dict keys if they’re hashtable (no lists inside)

Immutable Data Types Table

Type	Description	Example
int	Integer numbers	x = 10
float	Floating-point numbers	x = 3.14
bool	Boolean values	x = True
str	String (sequence of characters)	x = "hello"
tuple	Immutable ordered sequence	x = (1, 2, 3)
frozenset	Immutable set	x = frozenset([1, 2, 3])
bytes	Immutable byte sequence	x = b'data'
complex	Complex numbers	x = 2 + 3j
NoneType	Represents 'no value'	x = None

Collection Operations Time Complexity(BigO) Table

Collection	Operation	Time Complexity	Example
list	Indexing	O(1)	x = lst[2]
list	Append	O(1) amortized	lst.append(10)
list	Insert (start/middle)	O(n)	lst.insert(1, 99)
list	Pop (end)	O(1)	x = lst.pop()
list	Pop (start)	O(n)	x = lst.pop(0)
list	Remove by value	O(n)	lst.remove(10)
list	Membership test	O(n)	if 5 in lst: pass
list	Iteration	O(n)	for x in lst: pass
list	Sort	O(n log n)	lst.sort()
list	Slicing	O(k)	sub = lst[1:4]
tuple	Indexing	O(1)	x = tpl[1]
tuple	Membership test	O(n)	if 3 in tpl: pass
tuple	Iteration	O(n)	for x in tpl: pass
tuple	Concatenation	O(n + m)	tpl3 = tpl1 + tpl2
tuple	Slicing	O(k)	sub = tpl[1:3]
set	Add	O(1)	s.add(5)
set	Remove	O(1)	s.remove(5)
set	Membership test	O(1)	if 5 in s: pass
set	Iteration	O(n)	for x in s: pass
frozenset	Membership test	O(1)	if 2 in fs: pass
frozenset	Iteration	O(n)	for x in fs: pass
dict	Get	O(1)	x = d['key']
dict	Set	O(1)	d['key'] = 10
dict	Delete	O(1)	del d['key']
dict	Membership test	O(1)	if 'key' in d: pass
dict	Iteration	O(n)	for k, v in d.items(): pass

📦 1. list

• ✅ Mutable
• ✅ Ordered
• ❌ Not Unique
• ✅ Indexable
• ✅ Duplicates allowed

Use case: Dynamic, ordered collections with duplicates.

my_list = [1, 2, 3, 4]
my_list.append(4)
my_list.insert(0, 0)
my_list[0] = 10

🔒 2. tuple

• ❌ Immutable
• ✅ Ordered
• ❌ Not Unique
• ✅ Indexable
• ✅ Duplicates allowed

Use case: Fixed-size data, coordinates, function return values.

position = (10, 20)
# position[0] = 5  # ❌ Error

🧺 3. set

• ✅ Mutable
• ❌ Unordered
• ✅ Unique
• ❌ Indexable
• ❌ Duplicates not allowed

Use case: Unordered collections with no duplicates, set operations.

unique_items = {1, 2, 3}
unique_items.add(4)
unique_items.discard(2)

🧭 4. dict

• ✅ Mutable
• ✅ Ordered (Python 3.7+)
• ✅ Unique keys
• ✅ Key-based access
• ✅ Duplicates allowed for values

Use case: Fast key-value lookup, structured data.

person = {"name": "Alice", "age": 30}
person["age"] = 31

🧊 5. frozenset

• ❌ Immutable
• ❌ Unordered
• ✅ Unique
• ❌ Indexable
• ❌ Duplicates not allowed

Use case: Hashtable version of set, usable as dict or set key.

fset = frozenset([1, 2, 3])
# fset.add(4)  # ❌ Error

📚 6. collections.deque

• ✅ Mutable
• ✅ Ordered
• ❌ Not Unique
• ✅ Indexable (partial)
• ✅ Duplicates allowed

Use case: Fast appends/pops from both ends (queue/stack).

from collections import deque
dq = deque([1, 2, 3])
dq.appendleft(0)
dq.pop()

📊 7. collections.namedtuple

• ❌ Immutable
• ✅ Ordered
• ❌ Unique not enforced
• ✅ Indexable and attribute access

Use case: Tuple with named fields, lightweight class alternative.

from collections import namedtuple
Point = namedtuple("Point", "x y")
p = Point(10, 20)
print(p.x, p[1])

📐 8. collections.defaultdict

• ✅ Mutable
• ✅ Ordered (Python 3.7+)
• ✅ Unique keys
• ✅ Key-based access

Use case: Dict with default factory (no KeyError on missing keys).

from collections import defaultdict
d = defaultdict(int)
d["a"] += 1

🔁 9. collections.Counter

• ✅ Mutable
• ✅ Ordered (in output)
• ✅ Unique keys
• ✅ Key-based access

Use case: Count frequency of items (e.g., words, characters).

from collections import Counter
c = Counter("banana")
print(c["a"])  # 3

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Exercises

NamedTuple

from typing import NamedTuple

class Point(NamedTuple):
    x: float
    y: float

p = Point(1.5, 2.5)
print(p.x, p.y)       # 1.5 2.5
print(p[0], p[1])     # 1.5 2.5

class Color(NamedTuple):
    red: int
    green: int
    blue: int

white = Color(255, 255, 255)
print(white.red)  # 255

class ApiResponse(NamedTuple):
    status_code: int
    message: str
    data: dict

res = ApiResponse(200, "OK", {"user": "kenan"})
print(res.status_code, res.data["user"])  # 200 kenan

Tuples

A tuple is a collection which is ordered and unchangeable or immutable.

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