Structuring Data In Python¶

Overview¶

Structuring data in Python involves organizing and storing data in ways that make it efficient to access, modify, and analyze. Python provides several built-in data structures and tools to support this.

Core Data Structures¶

Lists¶

Lists are ordered, mutable collections.

Defined using square brackets []
Can store mixed data types
Support indexing and slicing

Example:

numbers = [1, 2, 3, 4]
numbers.append(5)

Tuples¶

Tuples are ordered, immutable collections.

Defined using parentheses ()
Cannot be changed after creation
Useful for fixed data

Example:

point = (10, 20)

Dictionaries¶

Dictionaries store key-value pairs.

Defined using curly braces {}
Keys must be unique and immutable
Values can be any type

Example:

user = {"name": "Alice", "age": 25}
print(user["name"])

Sets¶

Sets are unordered collections of unique elements.

Defined using {} or set()
Automatically remove duplicates
Support set operations

Example:

unique_numbers = {1, 2, 2, 3}

Custom Data Structures¶

Classes¶

Classes allow you to create custom data structures.

Combine data (attributes) and behavior (methods)
Support object-oriented design

Example:

class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

p = Person("Alice", 25)

Data Classes¶

Data classes simplify class creation for storing data.

Introduced in Python 3.7
Automatically generate __init__, __repr__, etc.

Example:

from dataclasses import dataclass

@dataclass
class Person:
    name: str
    age: int

Nested Structures¶

Data structures can be combined to represent complex data.

Example:

students = [
    {"name": "Alice", "grades": [90, 85, 88]},
    {"name": "Bob", "grades": [78, 82, 80]}
]

Benefits: - Represent real-world relationships - Enable hierarchical data organization

Choosing the Right Structure¶

Consider the following:

Use lists for ordered, changeable collections
Use tuples for fixed data
Use dictionaries for fast key-based lookup
Use sets for uniqueness and membership testing

Summary¶

Effective data structuring in Python helps:

Improve performance
Simplify code
Enhance readability and maintainability

Common tools include lists, tuples, dictionaries, sets, and classes.