Python Collections – Lists, Tuples, Sets, Dictionaries

Hello Friends,

Python Collections: Lists, Tuples, Sets, and Dictionaries

Python provides built-in collection data types that allow storing multiple values in a single variable. The most commonly used collections are List, Tuple, Set, and Dictionary.

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1. Python List

A list is an ordered, mutable (changeable) collection that allows duplicate values.

Syntax

list_name = [item1, item2, item3]

Example

fruits = ["apple", "banana", "mango"]
print(fruits)

Accessing List Items

print(fruits[0])

Modifying List

fruits[1] = "orange"
print(fruits)

Common List Methods

fruits.append("grapes")
fruits.remove("apple")
fruits.sort()
print(fruits)

Real-Life Example

marks = [65, 72, 80]
total = sum(marks)
print(total)

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2. Python Tuple

A tuple is an ordered, immutable (cannot be changed) collection.

Syntax

tuple_name = (item1, item2, item3)

Example

colors = ("red", "green", "blue")
print(colors)

Accessing Tuple Items

print(colors[1])

Why Use Tuple?

• Data safety (cannot be modified)
• Faster than lists

Real-Life Example

coordinates = (10.5, 20.3)
print(coordinates)

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3. Python Set

A set is an unordered collection that does not allow duplicate values.

Syntax

set_name = {item1, item2, item3}

Example

numbers = {1, 2, 3, 3, 4}
print(numbers)

Adding and Removing Elements

numbers.add(5)
numbers.remove(2)
print(numbers)

Set Operations

a = {1, 2, 3}
b = {3, 4, 5}

print(a.union(b))
print(a.intersection(b))

Real-Life Example

emails = {"a@gmail.com", "b@gmail.com", "a@gmail.com"}
print(emails)

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4. Python Dictionary

A dictionary stores data in key-value pairs.

Syntax

dict_name = {key1: value1, key2: value2}

Example

student = {"name": "Amit", "age": 21, "course": "Python"}
print(student)

Accessing Dictionary Values

print(student["name"])

Modifying Dictionary

student["age"] = 22
student["city"] = "Delhi"
print(student)

Loop Through Dictionary

for key, value in student.items():
    print(key, ":", value)

Real-Life Example

employee = {
  "id": 101,
  "name": "Ravi",
  "designation": "Tester",
  "salary": 50000
}
print(employee)

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Difference Between List, Tuple, Set, Dictionary

Feature	List	Tuple	Set	Dictionary
Ordered	Yes	Yes	No	Yes
Mutable	Yes	No	Yes	Yes
Duplicates	Yes	Yes	No	Keys: No

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Common Mistakes

• Using index on set
• Trying to modify tuple
• Duplicate keys in dictionary

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Summary

• Lists are flexible and commonly used
• Tuples are immutable and safe
• Sets remove duplicates
• Dictionaries store structured data

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How to Store Ordered and Unique Data in Python

Sometimes we need a data structure that:

• Maintains insertion order
• Does not allow duplicate values

Python does not provide a built-in data type that fully satisfies both conditions. However, there are effective ways to achieve this.

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Option 1: Using List with Manual Duplicate Check (Most Common)

A list maintains order but allows duplicates. We can manually prevent duplicates.

items = []

data = ["apple", "banana", "apple", "mango"]

for item in data:
    if item not in items:
        items.append(item)

print(items)

Output:

['apple', 'banana', 'mango']

Explanation:
The list preserves order and avoids duplicates by checking before inserting.

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Option 2: Using OrderedDict (Best Practice)

OrderedDict from the collections module preserves insertion order and removes duplicates.

from collections import OrderedDict

data = ["apple", "banana", "apple", "mango"]

result = list(OrderedDict.fromkeys(data))
print(result)

Output:

['apple', 'banana', 'mango']

Why This Is Best:

• Preserves order
• Automatically removes duplicates
• Clean and readable

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Option 3: Using dict (Python 3.7+)

Since Python 3.7, dictionaries preserve insertion order.

data = ["apple", "banana", "apple", "mango"]

result = list(dict.fromkeys(data))
print(result)

Output:

['apple', 'banana', 'mango']

Note:
This is the most commonly used modern Python approach.

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Why Not Use Set?

data = ["apple", "banana", "apple", "mango"]
print(set(data))

Output (order not guaranteed):

{'banana', 'apple', 'mango'}

Sets remove duplicates but do NOT preserve order.

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Comparison Table

Approach	Ordered	No Duplicates	Recommended
List + Check	Yes	Yes	Good
OrderedDict	Yes	Yes	Best
dict.fromkeys()	Yes	Yes	Best (Modern)
Set	No	Yes	No

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Real-Life Example

Removing duplicate email IDs while keeping order:

emails = [
  "a@gmail.com",
  "b@gmail.com",
  "a@gmail.com",
  "c@gmail.com"
]

unique_emails = list(dict.fromkeys(emails))
print(unique_emails)

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Summary

• No direct built-in ordered set in Python
• Use dict.fromkeys() for best results
• Use OrderedDict for clarity
• Do not use set when order matters