Understanding Python Dataclasses

DataClasses has been added in a recent addition in python 3.7 as a utility tool for storing data. DataClasses provides a decorator and functions for automatically adding generated special methods such as __init__() , __repr__() and __eq__() to user-defined classes.

DataClass in Python

DataClasses are like normal classes in Python, but they have some basic functions like instantiation, comparing, and printing the classes already implemented.

Installing the DataClasses module:

pip install dataclasses

The syntax of the dataclass is:

Syntax: @dataclasses.dataclass(*, init=True, repr=True, eq=True, order=False, unsafe_hash=False, frozen=False)

Parameters:

init: If true __init__() method will be generated

repr: If true __repr__() method will be generated

eq: If true __eq__() method will be generated

order: If true __lt__(), __le__(), __gt__(), and __ge__() methods will be generated.

unsafe_hash: If False __hash__() method is generated according to how eq and frozen are set

frozen: If true assigning to fields will generate an exception.

DataClass module provides a handy way to make classes less wordy. Let us see the traditional approach without using DataClass.

Python3

# creating a employee class

class employee:

    # init method or constructor

    def __init__(self, name, emp_id, age, city):

        # Instance Variable

        self.name = name

        self.emp_id = emp_id

        self.age = age

        self.city = city

    # magic function to return class object

    def __repr__(self):

        return ("employee (name={}, emp_id={}, age={}, city={} )"

                .format(self.name, self.emp_id, self.age, self.city))

    # magic function to return boolean

    def __eq__(self, check):

        return ((self.name, self.emp_id, self.age, self.city) ==

                ((check.name, check.emp_id, check.age, check.city)))
 
# initialization the object

emp1 = employee("Satyam", "ksatyam858", 21, 'Patna')

emp2 = employee("Anurag", "au23", 28, 'Delhi')

emp3 = employee("Satyam", "ksatyam858", 21, 'Patna')
 
print("employee object are :")

print(emp1)

print(emp2)

print(emp3)
 
# printing new line

print()
 
# referring two object to check equality

print("Data in emp1 and emp2 are same? ", emp1 == emp2)

print("Data in emp1 and emp3 are same? ", emp1 == emp3)

Output

employee object are :
employee (name=Satyam, emp_id=ksatyam858, age=21, city=Patna )
employee (name=Anurag, emp_id=au23, age=28, city=Delhi )
employee (name=Satyam, emp_id=ksatyam858, age=21, city=Patna )

Data in emp1 and emp2 are same?  False
Data in emp1 and emp3 are same?  True

In the above code the biggest problem in passing the argument in __init__, __repr__, and __eq__. Each time it has to copy its properties and return the object. It is a good way of dealing with a small amount of data but supposes we have work with large data. It makes your code more complicated. So, that why DataClass will implement to make your code easier and handy.

Here are the same example, implemented in Python DataClasses.

Python3

# A basic Data Class
# importing dataclass module

from dataclasses import dataclass
 
# A class for holding an employees content
@dataclass

class employee:
 
    # Attributes Declaration

    # using Type Hints

    name: str

    emp_id: str

    age: int

    city: str
 
emp1 = employee("Satyam", "ksatyam858", 21, 'Patna')

emp2 = employee("Anurag", "au23", 28, 'Delhi')

emp3 = employee("Satyam", "ksatyam858", 21, 'Patna')
 
print("employee object are :")

print(emp1)

print(emp2)

print(emp3)
 
# printing new line

print()
 
# referring two object to check equality

print("Data in emp1 and emp2 are same? ", emp1 == emp2)

print("Data in emp1 and emp3 are same? ", emp1 == emp3)

Output:

employee object are :
employee(name=’Satyam’, emp_id=’ksatyam858′, age=21, city=’Patna’)
employee(name=’Anurag’, emp_id=’au23′, age=28, city=’Delhi’)
employee(name=’Satyam’, emp_id=’ksatyam858′, age=21, city=’Patna’)
Data in emp1 and emp2 are same? False
Data in emp1 and emp3 are same? True

In the above code, we don’t need to write a code for __init__, __repr__, and __eq__ function.

dataclasses.Field()

The field() objects describe each defined field.

Syntax: dataclasses.field(*, default=MISSING, default_factory=MISSING, repr=True, hash=None, init=True, compare=True, metadata=None)

Parameters:

default

default_factory

init

repr

hash

compare

metadata

Example: Demonstration of how to view the fields of a dataclass object.

Python3

from dataclasses import dataclass
 
# A class for holding an employees content
@dataclass

class employee:
 
    # Attributes Declaration

    # using Type Hints

    name: str

    emp_id: str

    age: int

    city: str
 
# object of the class

emp = employee("Satyam", "ksatyam858", 21, 'Patna')
 
emp.__dataclass_fields__

Output:

Explanation of the parameters :

default: This field is used to specify default values for this field.

Python3

# default field example

from dataclasses import dataclass, field
 
# A class for holding an employees content
@dataclass

class employee:
 
    # Attributes Declaration

    # using Type Hints

    name: str

    emp_id: str

    age: int

    # default field set

    # city : str = "patna"

    city: str = field(default="patna")
 
emp = employee("Satyam", "ksatyam858", 21)

print(emp)

Output:

employee(name=’Satyam’, emp_id=’ksatyam858′, age=21, city=’patna’)

default_factory: This field accepts a function and returns the initial value of the field, it must be a zero-argument.

Python3

# default factory example

from dataclasses import dataclass, field
 
def get_emp_id():

    id = 2345

    return id
 
# A class for holding an employees content
@dataclass

class employee:
 
    # Attributes Declaration

    # using Type Hints

    name: str

    age: int

    # default factory field

    emp_id: str = field(default_factory=get_emp_id)

    city: str = field(default="patna")
 
# object of dataclass

emp = employee("Satyam", 21)

print(emp)

Output:

employee(name=’Satyam’, age=21, emp_id=2345, city=’patna’)

init : If true this field is included as a parameter to the generated __init__() method.

Python3

# init field example

from dataclasses import dataclass, field
 
# A class for holding an employees content
@dataclass

class employee:
 
    # Attributes Declaration

    # using Type Hints

    name: str

    age: int

    # init field

    emp_id: str

    city: str = field(init=False, default="patna")
 
# object of dataclass

emp = employee("Satyam", "ksatyam858", 21)

print(emp)

Output:

employee(name=’Satyam’, age=’ksatyam858′, emp_id=21, city=’patna’)

repr: If true (the default), this field is included in the string returned by the generated __repr__() method.

Python3

# repr field

from dataclasses import dataclass, field
 
# A class for holding an employees content
@dataclass

class employee:
 
    # Attributes Declaration

    # using Type Hints

    name: str

    age: int

    emp_id: str

    city: str = field(init=False, default="patna", repr=True)
 
emp = employee("Satyam", 21, "ksatyam858"),

print(emp)

Output:

employee(name=’Satyam’, age=21, emp_id=’ksatyam858′, city=’patna’)

If repr is false then:

Python3

city: str = field(init=False, default="patna", repr=False)
 

emp = employee("Satyam", 21, "ksatyam858"),
emp

Output:

employee(name='Satyam', age=21, emp_id='ksatyam858')

hash: If true, this field is included in the generated __hash__() method.

Python3

# hash

from dataclasses import dataclass, field
 
# A class for holding an employees content

@dataclass(unsafe_hash=True)

class employee:
 
    # Attributes Declaration

    # using Type Hints

    name: str

    age: int

    emp_id: str = field(default_factory=get_emp_id)

    city: str = field(init=False, default="patna", repr=True, hash=True)
 
emp = employee("Satyam", "ksatyam858", 21)

hash(emp)

Output:

28166796391311520

If false then it will not consider these field.

Python3

city: str = field(init=False, default="patna", repr=True, hash=False)
 
# object of the class

emp = employee("Satyam", "ksatyam858", 21)

hash(emp)

Output:

6124029366977666702

compare: If true (the default), this field is included in the generated equality and comparison methods (__eq__(), __gt__().

Python3

# hash

from dataclasses import dataclass, field
 
# A class for holding an employees content

@dataclass(unsafe_hash=True)

class employee:
 
    # Attributes Declaration

    # using Type Hints

    name: str

    age: int

    emp_id: str

    city: str = field(init=False, default="patna",

                      repr=True, hash=False, compare=True)
 
emp1 = employee("Satyam", "ksatyam858", 21)

emp2 = employee("Kumar", "satyam.10151", 22)

emp1 == emp2

Output:

False

metadata: This can be a mapping or None. None is treated as an empty dict.

Python3

# hash

from dataclasses import dataclass, field
 
# A class for holding an employees content

@dataclass(unsafe_hash=True)

class employee:
 
    # Attributes Declaration

    # using Type Hints

    name: str

    age: int

    emp_id: str

    city: str = field(init=False, default="patna", repr=True,

                      metadata={'format': 'State'})
 
emp = employee("Satyam", "ksatyam858", 21)

emp.__dataclass_fields__['city'].metadata['format']

Post-init processing

While creating object __post_init__() method call automatically. __init__() code will call a method named __post_init__().

Example: In an employee dataclass, if we want to check employee age, then we can define into the __post_init__() method.

Python3

# A basic Data Class
# importing dataclass module

from dataclasses import dataclass, field
 
# A class for holding an employees content
@dataclass

class employee:
 
    # Attributes Declaration

    # using Type Hints

    name: str

    emp_id: str

    age: int

    city: str
 
    # post init function

    def __post_init__(self):

        if self.age >= 30:

            self.check_age = True

        else:

            self.check_age = False
 
emp = employee("Satyam", "ksatyam858", 21, 'Patna')
emp.check_age

Output:

False

DataClass Inheritance

Inheritance enables us to define a class that takes all the functionality from a parent class.

Example: Child class inherits the properties of the parent class.

Python3

# A basic Data Class
# importing dataclass module

from dataclasses import dataclass, field
 
# parent class
@dataclass

class Staff:

    name: str

    emp_id: str

    age: int
 
# child class
@dataclass

class employee(Staff):

    salary: int
 
emp = employee("Satyam", "ksatyam858", 21, 60000)
emp

Output:

employee(name='Satyam', emp_id='ksatyam858', age=21, salary=60000)

Article Tags :

Python

python-oop-concepts