Dataclasses - Python Mastery

Dataclasses: Boilerplate-Free Data Classes

Python 3.7 introduced @dataclass — a decorator that automatically generates __init__, __repr__, __eq__, and more from class annotations.

from dataclasses import dataclass, field

# Without dataclass — lots of boilerplate
class PointOld:
    def __init__(self, x, y):
        self.x = x
        self.y = y
    def __repr__(self):
        return f"Point(x={self.x}, y={self.y})"
    def __eq__(self, other):
        return self.x == other.x and self.y == other.y

# With dataclass — clean and concise
@dataclass
class Point:
    x: float
    y: float

p1 = Point(1.0, 2.0)
p2 = Point(1.0, 2.0)
print(p1)           # Point(x=1.0, y=2.0) — __repr__ auto-generated
print(p1 == p2)     # True — __eq__ auto-generated
print(p1.x)         # 1.0

Dataclass Options

from dataclasses import dataclass, field
from datetime import datetime
from typing import List

@dataclass
class Employee:
    name: str
    department: str
    salary: float
    start_date: datetime = field(default_factory=datetime.now)
    skills: List[str] = field(default_factory=list)   # Mutable default!
    _id: int = field(default=0, init=False, repr=False)  # Not in __init__

@dataclass(frozen=True)    # Immutable — like a named tuple
class Config:
    host: str
    port: int = 8080
    debug: bool = False

# frozen=True makes instances hashable
config = Config("localhost", 5432)
# config.port = 3000  # FrozenInstanceError

@dataclass(order=True)     # Generates __lt__, __le__, __gt__, __ge__
class Student:
    gpa: float             # First field used for comparison
    name: str

students = [Student(3.8, "Alice"), Student(3.5, "Bob"), Student(3.9, "Carol")]
sorted(students)   # Sorts by gpa (first field)

Post-init Processing

@dataclass
class Rectangle:
    width: float
    height: float
    area: float = field(init=False)   # Computed, not passed to __init__

    def __post_init__(self):
        """Called after __init__ — validate or compute derived fields"""
        if self.width <= 0 or self.height <= 0:
            raise ValueError("Dimensions must be positive")
        self.area = self.width * self.height

r = Rectangle(4, 5)
print(r.area)    # 20.0

Dataclass vs namedtuple vs regular class

Feature	dataclass	namedtuple	regular class
Mutable	✓	✗	✓
Auto __init__	✓	✓	✗
Auto __repr__	✓	✓	✗
Hashable	Optional (frozen)	✓	Optional
Default values	✓	Limited	✓
Type hints	✓	Limited	Optional

Key Takeaways

@dataclass eliminates boilerplate: auto __init__, __repr__, __eq__
field(default_factory=list): always use this for mutable defaults
frozen=True: makes dataclass immutable and hashable
order=True: auto-generates comparison methods based on field order
__post_init__: for validation and computed fields

Practice Exercises

Create a Product dataclass with name, price, quantity. Add a total_value property computed in __post_init__. Make it orderable by price.
Create a frozen Coordinate dataclass. Use it as a dictionary key to store elevation data.
Refactor the BankAccount class from Lesson 15 using @dataclass.

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