dataclasses (Python 3.6 Backport)

0.8 · maintenance · verified Thu Apr 09

The `dataclasses` library is a backport of the standard library `dataclasses` module, designed specifically for Python 3.6. It provides the `@dataclass` decorator and related utilities, enabling simpler creation of data-holding classes without boilerplate. Its current version is 0.8. As it targets a specific, older Python version, its release cadence is stable and infrequent, with no new feature development anticipated.

Warnings

breaking This library is exclusively for Python 3.6. Installing it on Python 3.7 or newer is redundant and can cause subtle issues if you rely on features specific to this backport or expect it to override the standard library module. Python 3.7+ includes `dataclasses` as a built-in module.
Fix: Remove `dataclasses` from your project's dependencies when upgrading to Python 3.7 or newer. The standard library module will be used automatically.
gotcha When using type hints in Python 3.6 with `dataclasses`, `from __future__ import annotations` is highly recommended. Without it, you may encounter `NameError` for forward references or issues with complex type hints (e.g., `list[str]`, `dict[str, int]`). Alternatively, string literal type hints (e.g., `field: 'MyClass'`) can be used.
Fix: Add `from __future__ import annotations` at the top of your module, or use string literal type hints for any forward references or complex generic types.
gotcha This backport provides the functionality of `dataclasses` as it existed in Python 3.7. It does not include features introduced in later Python versions, such as `kw_only` or `slots=True` (Python 3.10+).
Fix: If these newer features are required, consider upgrading your Python environment to 3.10 or newer. There is no workaround to enable these features in the 3.6 backport.

Install

pip install dataclasses Install for Python 3.6

Imports

dataclass
```
from dataclasses import dataclass
```
field
```
from dataclasses import field
```

Quickstart

Define a simple data class using the `@dataclass` decorator. Note the `from __future__ import annotations` which is highly recommended for type hints in Python 3.6 to handle forward references and complex types gracefully. Mutable default values for fields should use `default_factory`.

from __future__ import annotations # Recommended for Python 3.6 type hints
from dataclasses import dataclass, field

@dataclass
class User:
    id: int
    name: str = "Guest"
    email: str | None = None  # Using Union syntax (PEP 604) or typing.Optional
    tags: list[str] = field(default_factory=list)

# Example usage
user1 = User(id=1, name="Alice")
user2 = User(id=2, email="bob@example.com")

print(user1)
print(user2)

assert user1.name == "Alice"
assert user2.tags == []

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