semvec/pypi-packages huggingface dataset:
dataclass-factory 2.16
An utility class for creating instances of dataclasses
License: Apache2
Requires Python: >=3.6

# dataclass_factory

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**dataclass_factory** is a modern way to convert dataclasses or other objects to and from more common types like dicts

## Help

See [documentation](https://dataclass-factory.readthedocs.io/) for more details.

## TL;DR

Install
```bash
pip install dataclass_factory
```

Use
```python
from dataclasses import dataclass
import dataclass_factory


@dataclass
class Book:
    title: str
    price: int
    author: str = "Unknown author"


data = {
    "title": "Fahrenheit 451",
    "price": 100,
}

factory = dataclass_factory.Factory()
book: Book = factory.load(data, Book)  # Same as Book(title="Fahrenheit 451", price=100)
serialized = factory.dump(book) 
``` 

## Requirements

* python >= 3.6

You can use `dataclass_factory` with python 3.6 and `dataclass` library installed from pip. 

On python 3.7 it has no external dependencies outside of the Python standard library.

## Advantages

* No schemas or configuration needed for simple cases. Just create `Factory` and call `load`/`dump` methods
* Speed. It is up to 10 times faster than `marshmallow` and `dataclasses.asdict` (see [benchmarks](benchmarks))
* Automatic name style conversion (e.g. `snake_case` to `CamelCase`)
* Automatic skipping of "internal use" fields (with leading underscore)
* Enums, typed dicts, tuples and lists are supported out of the box
* Unions and Optionals are supported without need to define them in schema
* Generic dataclasses can be automatically parsed as well
* Cyclic-referenced structures (such as linked-lists or trees) also can be converted
* Validators, custom parser steps are supported.
* Multiple schemas for single type can be provided to support different ways of parsing of the same type