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# Python Data Class
A data class is a class decorated with `@dataclass` from the `dataclasses` module, introduced in Python 3.7. It utilizes PEP 526 variable annotations to automatically generate boilerplate special methods (dunder methods)—such as `__init__()`, `__repr__()`, and `__eq__()`—directly into the class namespace based on the defined attributes.
## Basic Syntax
To define a data class, apply the `@dataclass` decorator and declare class variables with type hints.
```python theme={"dark"}
from dataclasses import dataclass
@dataclass
class Point:
x: float
y: float
z: float = 0.0 # Attribute with a default value
```
When the Python interpreter processes this decorator, it dynamically synthesizes the following methods:
1. **`__init__(self, x: float, y: float, z: float = 0.0)`**: Initializes the instance variables.
2. **`__repr__(self)`**: Returns a string representation, e.g., `Point(x=1.0, y=2.0, z=0.0)`.
3. **`__eq__(self, other)`**: Compares the class instances as if they were tuples of their fields.
## Decorator Parameters
The `@dataclass` decorator accepts several boolean arguments to control which methods are generated and how the class behaves:
```python theme={"dark"}
@dataclass(
init=True, # Generates __init__()
repr=True, # Generates __repr__()
eq=True, # Generates __eq__()
order=False, # Generates __lt__(), __le__(), __gt__(), __ge__()
unsafe_hash=False, # Forces generation of __hash__()
frozen=False, # Makes instances immutable (read-only)
match_args=True, # Generates __match_args__ for structural pattern matching
kw_only=False, # Forces all fields to be keyword-only arguments (Python 3.10+)
slots=False # Generates __slots__ for memory optimization (Python 3.10+)
)
class Configuration:
pass
```
Setting `frozen=True` simulates immutability by overriding `__setattr__()` and `__delattr__()` to raise a `FrozenInstanceError` if attribute modification is attempted after initialization. It also automatically generates a `__hash__()` method, making the instances hashable.
## The `field()` Function
For granular control over individual attributes, the `field()` function is used. It allows you to exclude specific fields from generated methods or handle mutable default values.
```python theme={"dark"}
from dataclasses import dataclass, field
from typing import List
@dataclass
class Node:
id: int
# default_factory prevents shared state across instances for mutable types
children: List['Node'] = field(default_factory=list)
# Exclude from __repr__ and __init__
internal_cache: dict = field(default_factory=dict, repr=False, init=False)
```
Key parameters of `field()` include:
* `default`: The default value for the field.
* `default_factory`: A zero-argument callable called to initialize a field's value (required for mutable types like `list` or `dict`).
* `init`: If `False`, the field is excluded from the generated `__init__()`.
* `repr`: If `False`, the field is excluded from the generated `__repr__()`.
* `compare`: If `False`, the field is excluded from generated equality and ordering methods.
## Post-Initialization Processing
Because the `@dataclass` decorator overwrites the `__init__()` method, custom initialization logic cannot be placed there. Instead, the `dataclasses` module provides the `__post_init__()` hook.
If defined on the class, the generated `__init__()` method will automatically call `__post_init__()` immediately after all fields have been initialized.
```python theme={"dark"}
@dataclass
class Rectangle:
width: float
height: float
area: float = field(init=False)
def __post_init__(self):
# Executes after width and height are bound to self
self.area = self.width * self.height
```
If the class is defined with `frozen=True`, `__post_init__()` must use `object.__setattr__(self, 'name', value)` to bypass the immutability constraints during the post-initialization phase.
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