Data Class: Data Class is a type of class that is used to store data without any functionality. These data classes are just regular classes having the main purpose to store state and data without knowing the constraints and logic behind it. Whenever you create a class that mostly contains attributes and certain properties to deal with the data and its representation.
Example:
Python3
# Importing dataclass module from dataclasses import dataclass # Annotation @dataclass # Class with attributes class GeeksArticle(): """A class for holding an article content""" # Attributes Declaration # using Type Hints topic: str contributor: str language: str upvotes: int # A DataClass object article = GeeksArticle("DataClasses", "nightfury1", "Python", 1) print(article) |
Output:
GfgArticle(topic=’DataClasses’, contributor=’nightfury1’, language=’Python’, upvotes=1)
NamedTuple: The NamedTuple is a class that contains the data like a dictionary format stored under the ‘collections‘ module. It stored the data in a key-value format where each key having mapped to more values. So, we access those data using a specific key or can use the indexes.
Example:
Python3
# Python script to demonstrate namedtuple() # importing nametuple() from collections module from collections import namedtuple # Declaring namedtuple() Contributor = namedtuple('Contributor', ['topic', 'author', 'post']) # Adding values C = Contributor('Difference between DataClass vs NamedTuple vs Object in Python', 'night_fury1', 'Technical Content Writer Intern') # Access using index print ("The Article Topic : ", end ="") print (C[0]) # Access using name print ("The Article Contributor Name : ", end ="") print (C.author) # Access using getattr() print ("The Article Contributor Post : ", end ="") print (getattr(C, 'post')) |
Output:
The Article Topic : Difference between DataClass vs NamedTuple vs Object in Python
The Article Contributor Name : night_fury1
The Article Contributor Post : Technical Content Writer Intern
Object: An object is simply a collection of data (variables) and methods (functions) that act on those data. In other words, we say that Object is an instance of the class.
Example:
Python3
# Python script for demostraation of object class Gfg: def __init__(self, topic, contributor): self.topic = topic self.contributor = contributor def myfunc(self): print("Article: ", self.topic) print("Contributor: ", self.contributor) # objects creation g = Gfg("Difference between DataClass vs NamedTuple vs Object in Python", "nightfury1") # function call g.myfunc() |
Output:
Article: Difference between DataClass vs NamedTuple vs Object in Python
Contributor: nightfury1
Table of difference between DataClass, NamedTuple and Object
|
DataClass |
NamedTuple |
Object |
|
|---|---|---|---|
| Creation | DataClass is slower than others while creating data objects (2.94 µs). | NamedTuple is the faster one while creating data objects (2.01 µs). | An object is slower than DataClass but faster than NamedTuple while creating data objects (2.34 µs). |
| Read Property | Equal to Object & faster than NamedTuple while reading the data objects (24.7 ns). | NamedTuple is slower than others in reading data objects (26.9 ns). | Equal to DataClass & Faster than NamedTuple (24.7 ns). |
| Nested Property | Faster than others while nesting data objects & their properties (48.1 ns). | Slower than others in nesting data objects (75.8 ns). | Faster than NamedTuple but slower than DataClass (52.1 ns). |
| Execute Function | Faster than NamedTuple but slower than objects (829 ns). | Slower than others in Function Execution (946 ns). | Fastest in Function execution on data objects (821 ns). |
| Size | 56 bytes | 80 bytes | 56 bytes |
