dataclass

Dataclasses

Auto-generate boilerplate (__init__, __repr__, __eq__) for data-holding classes.

Files

File	Description
example.py	Basic, frozen, and default_factory dataclasses

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Descriptive Example

Scenario

Model a team with a name and a list of members — safely handle mutable defaults.

from dataclasses import dataclass, field, replace

@dataclass
class Team:
    name: str
    members: list[str] = field(default_factory=list)

    def add(self, member):
        self.members.append(member)

t1 = Team("Alpha")
t2 = Team("Beta")
t1.add("Alice")

print(t1)   # Team(name='Alpha', members=['Alice'])
print(t2)   # Team(name='Beta', members=[])  — independent list!

Immutable dataclass

@dataclass(frozen=True, order=True)
class Point:
    x: float
    y: float

p = Point(1.0, 2.0)
# p.x = 5        # FrozenInstanceError
print(Point(1, 2) < Point(3, 4))   # True (order=True)

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Interview Q&A

Q1: What does @dataclass auto-generate?
A: __init__, __repr__, and optionally __eq__, __order__, __hash__ depending on parameters.

Q2: Dataclass vs NamedTuple?
A: Dataclass: mutable by default (unless frozen), regular class. NamedTuple: immutable, tuple subclass, lighter weight.

Q3: Why field(default_factory=list) instead of members=[]?
A: Mutable default trap — [] is shared across instances. default_factory calls list() per instance.

Q4: What does frozen=True do?
A: Makes instances immutable. Enables hashing (if all fields hashable). Raises FrozenInstanceError on attribute assignment.

Q5: Dataclass vs dict for data?
A: Dataclass: type safety, IDE autocomplete, validation hooks, immutability option. Dict: flexible keys, JSON-native, no schema.

Q6: Can dataclasses use __slots__?
A: Yes — @dataclass(slots=True) in Python 3.10+ combines both features.

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Run

python3 example.py