Tutorial 22 why python data classes are amazing krish naik hindi

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certainly! python data classes, introduced in python 3.7, are a powerful feature that simplifies the creation of classes for storing data. they provide an easy way to define classes without having to write boilerplate code for methods like `__init__`, `__repr__`, and `__eq__`.

### what are data classes?

data classes are a decorator that automatically adds special methods to classes. they are great for creating classes that primarily store data and provide a clear structure for that data.

### benefits of data classes
1. **less boilerplate**: you don’t have to write repetitive code for initializers, string representations, and equality checks.
2. **readability**: data classes make the code easier to read and understand, as they clearly define the data structure.
3. **immutability**: you can create immutable data classes by using the `frozen=true` parameter.
4. **type annotations**: data classes encourage the use of type annotations, which improves code clarity and helps with static type checking.

### how to create a data class

here’s a step-by-step tutorial including code examples:

#### step 1: import the data class module

to use data classes, you need to import the `dataclass` decorator from the `dataclasses` module.
#### step 2: define a data class

you can create a data class by using the `@dataclass` decorator above a class definition. here’s a simple example:
**output:**
#### step 3: using data class features

1. **automatic `__init__` method**: the `__init__` method is generated automatically based on the class variables.

2. **automatic `__repr__` method**: the `__repr__` method is also generated, which provides a nice string representation of the object.

3. **automatic `__eq__` method**: the `__eq__` method is generated to compare two instances based on their data.
4. **default values**: you can assign default values to the fields.
5. **immutability**: to make a data class immutable, set `frozen=true`.
### conclusion

data classes are ...

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