Dataclasses (@dataclass, Python 3.7+) huzalisha kiotomatiki methods za boilerplate kwa classes ambazo kimsingi hushikilia data. __slots__ ni optimization inayopunguza memory na kuongeza kasi ya ufikiaji wa attribute kwa kuepuka __dict__ ya kila instance.
from dataclasses import dataclass
# ❌ without dataclass — lots of repetitive boilerplate
class Point:
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, self.y) == (other.x, other.y)
# ✅ with @dataclass — all of the above generated automatically
@dataclass
class Point:
x: int
y: int
p = Point(1, 2)
p # Point(x=1, y=2) — __repr__ generated
p == Point(1, 2) # True — __eq__ generated
@dataclass huzalisha __init__, __repr__, __eq__ (na kwa hiari ordering/hashing) kutoka kwa fields zenye annotation — ikiondoa boilerplate ya kuchosha, yenye kukosea.
from dataclasses import dataclass, field
@dataclass(frozen=True) # frozen → immutable (hashable, usable as dict key)
class Config:
name: str
tags: list = field(default_factory=list) # mutable default done safely
timeout: int = 30 # default value
frozen=True hufanya instances kuwa immutable; field(default_factory=list) hutoa kwa usalama defaults zinazobadilika (ikiepuka mtego wa shared-mutable-default).
# normally, each instance has a __dict__ to store attributes (flexible but memory-heavy)
class Regular:
def __init__(self, x, y): self.x, self.y = x, y
# __slots__ → fixed attribute set, NO per-instance __dict__
class Slotted:
__slots__ = ("x", "y") # only these attributes allowed
def __init__(self, x, y): self.x, self.y = x, y
s = Slotted(1, 2)
s.z = 3 # ❌ AttributeError — can't add attributes not in __slots__
Kawaida kila instance huhifadhi attributes katika __dict__ ya dynamic. __slots__ hutangaza seti maalum ya attributes zinazohifadhiwa katika muundo wa kushikamana, wa kudumu badala yake — ikihifadhi memory kubwa na kuongeza kasi ya ufikiaji, kwa gharama ya unyumbufu (huwezi kuongeza attributes za kiholela).
@dataclass(slots=True) # Python 3.10+ — dataclass WITH __slots__
class Point:
x: int
y: int
@dataclass → any class that's mostly data (DTOs, configs, records) — cleaner, less code
__slots__ → when you create MANY instances (millions) and memory/speed matters
(e.g. nodes in a big data structure, large simulations)
Dataclasses ni kipengele cha kisasa kinachotumika sana kinachoondoa boilerplate inayojirudia kwa classes zinazoshikilia data — kikifanya code kuwa safi, isiyokosea sana, na inayosomeka zaidi (__init__/__repr__/__eq__ zinazozalishwa kiotomatiki, pamoja na immutability na defaults salama).
Ni mbadala wa kisasa wa kiidiomatiki kwa kuandika classes hizo kwa mkono au kutumia namedtuple unapohitaji mutability/methods. __slots__ ni optimization ya utendaji iliyolengwa inayopunguza kwa maana memory na kuongeza kasi ya ufikiaji wa attribute unapotengeneza idadi kubwa ya objects.
Kujua zote mbili — @dataclass kwa modeli safi ya data ya kila siku na __slots__ (sasa zinazoweza kuunganishwa kupitia slots=True) kwa hot paths za memory-critical — kunaakisi mbinu bora za sasa za kuandika Python classes zenye ufanisi, zinazodumishika.
Maktaba ya maswali ya mahojiano ya IT yenye majibu ya kina — kutoka Junior hadi Senior.
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