Metadata-Version: 2.1
Name: dataclasses_serialization
Version: 1.3.1
Summary: Serialize/deserialize Python dataclasses to various other data formats
Home-page: https://github.com/madman-bob/python-dataclasses-serialization
Author: Robert Wright
Author-email: madman.bob@hotmail.co.uk
License: MIT
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: dataclasses
Requires-Dist: more-properties >=1.1.0
Requires-Dist: typing-inspect
Requires-Dist: toolz
Requires-Dist: toposort

# dataclasses_serialization

`dataclasses_serialization` provides serializers/deserializers for transforming between Python dataclasses, and JSON and BSON objects.

## Basic Usage

Suppose we have the following dataclass:

```python
from dataclasses import dataclass


@dataclass
class InventoryItem:
    name: str
    unit_price: float
    quantity_on_hand: int
```

Then we may serialize/deserialize it to/from JSON by using `JSONSerializer`

```pycon
>>> from dataclasses_serialization.json import JSONSerializer
>>> JSONSerializer.serialize(InventoryItem("Apple", 0.2, 20))
{'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20}

>>> JSONSerializer.deserialize(InventoryItem, {'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20})
InventoryItem(name='Apple', unit_price=0.2, quantity_on_hand=20)
```

### Mongo

As Mongo collections store objects as BSON, you can use `BSONSerializer` to dump dataclasses directly into Mongo.

```python
from dataclasses_serialization.bson import BSONSerializer

    
collection.insert_one(BSONSerializer.serialize(item))

item = BSONSerializer.deserialize(InventoryItem, collection.find_one())
```

## Custom Serializers

To create a custom serializer, create an instance of `dataclasses_serialization.serializer_base.Serializer`:

```python
from dataclasses_serialization.serializer_base import noop_serialization, noop_deserialization, dict_serialization, dict_deserialization, list_deserialization, Serializer


JSONSerializer = Serializer(
    serialization_functions={
        dict: lambda dct: dict_serialization(dct, key_serialization_func=JSONSerializer.serialize, value_serialization_func=JSONSerializer.serialize),
        list: lambda lst: list(map(JSONSerializer.serialize, lst)),
        (str, int, float, bool, type(None)): noop_serialization
    },
    deserialization_functions={
        dict: lambda cls, dct: dict_deserialization(cls, dct, key_deserialization_func=JSONSerializer.deserialize, value_deserialization_func=JSONSerializer.deserialize),
        list: lambda cls, lst: list_deserialization(cls, lst, deserialization_func=JSONSerializer.deserialize),
        (str, int, float, bool, type(None)): noop_deserialization
    }
)
```

## Reference

### `dataclasses_serialization.serializer_base`

A collection of utilities to make it easier to create serializers.

- `isinstance(o, t)`, `issubclass(cls, clsinfo)`

  Extended versions of the builtin `isinstance` and `issubclass`, to treat `dataclass` as a superclass for dataclasses, and to be usable with supported `typing` types.

- `noop_serialization(obj)`, `noop_deserialization(cls, obj)`

  The trivial serialization/deserialization functions, which serialize by doing nothing.

- `dict_to_dataclass(cls, dct, deserialization_func=noop_deserialization)`

  The inverse of `dataclasses.asdict`, which deserializes a dictionary `dct` to a dataclass `cls`, using `deserialization_func` to deserialize the fields of `cls`.

  Fields are deserialized using the type provided by the dataclass.
  So bound generic dataclasses may be deserialized, while unbound ones may not.

- `union_deserialization(type_, obj, deserialization_func=noop_deserialization)`

  Deserialize a `Union` `type_`, by trying each type in turn, and returning the first that does not raise a `DeserializationError`.

  As `Optional`s are implemented as `Union`s, this function also works for them.

- `dict_serialization(obj, key_serialization_func=noop_serialization, value_serialization_func=noop_serialization)`, `dict_deserialization(type_, obj, key_deserialization_func=noop_deserialization, value_deserialization_func=noop_deserialization)`

  Serialize/deserialize a dictionary `obj` by applying the appropriate serialization/deserialization functions to keys and values.

- `list_deserialization(type_, obj, deserialization_func=noop_deserialization)`

  Deserialize a list `obj` by applying the deserialization function to its values.

- `Serializer(serialization_functions, deserialization_functions)`

  The general serialization class.

  Takes two dictionaries of serialization and deserialization functions, and defers to them appropriately when serializing/deserializing and object by the `serialize` and `deserialize` methods.
  Serializer functions take a single parameter, the object to be serialized, and returns a serialized version of it.
  Deserializer functions take two parameters, the desired type of the deserialized object, and the object to be deserialized.

  If an object's type cannot be found directly in the serialization/deserialization functions, the `Serializer` uses its closest ancestor - raising an error in case of ambiguity.

  By default `dataclass`es are serialized as though they are `dict`s.
  Similarly, `dataclass`es are deserialized using `dict_to_dataclass`, and `Union`s using `union_deserialization`, using itself as the nested deserialization function.

  Serialize a Python object with `serializer.serialize(obj)`, and deserialize with `serializer.deserialize(cls, serialized_obj)`.

  Register more serialization/deserialization functions with `serializer.register_serializer(cls, func)`, `serializer.register_deserializer(cls, func)`, and `serializer.register(cls, serialization_func, deserialization_func)`.
  They can also be used as decorators like so:

  ```python
  @serializer.register_serializer(int)
  def int_serializer(obj):
      ...
  ```

  ```python
  @serializer.register_deserializer(int)
  def int_deserializer(cls, obj):
      ...
  ```

- `SerializationError`, `DeserializationError`

  Errors to be raised when serialization/deserialization fails, respectively.

### `dataclasses_serialization.json`

- `JSONSerializer`

  Serializer/deserializer between Python dataclasses and JSON objects.

  ```pycon
  >>> JSONSerializer.serialize(InventoryItem("Apple", 0.2, 20))
  {'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20}

  >>> JSONSerializer.deserialize(InventoryItem, {'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20})
  InventoryItem(name='Apple', unit_price=0.2, quantity_on_hand=20)
  ```

- `JSONSerializerMixin`

  Adds `as_json` and `from_json` methods to dataclasses when used as a mixin.

  ```python
  @dataclass
  class InventoryItem(JSONSerializerMixin):
      ...
  ```

  ```pycon
  >>> InventoryItem("Apple", 0.2, 20).as_json()
  {'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20}

  >>> InventoryItem.from_json({'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20})
  InventoryItem(name='Apple', unit_price=0.2, quantity_on_hand=20)
  ```

- `JSONStrSerializer`

  Serializer/deserializer between Python dataclasses and JSON strings.

  ```pycon
  >>> JSONStrSerializer.serialize(InventoryItem("Apple", 0.2, 20))
  '{"name": "Apple", "unit_price": 0.2, "quantity_on_hand": 20}'

  >>> JSONStrSerializer.deserialize(InventoryItem, '{"name": "Apple", "unit_price": 0.2, "quantity_on_hand": 20}')
  InventoryItem(name='Apple', unit_price=0.2, quantity_on_hand=20)
  ```

- `JSONStrSerializerMixin`

  Adds `as_json_str` and `from_json_str` methods to dataclasses when used as a mixin.

  ```python
  @dataclass
  class InventoryItem(JSONStrSerializerMixin):
      ...
  ```

  ```pycon
  >>> InventoryItem("Apple", 0.2, 20).as_json_str()
  '{"name": "Apple", "unit_price": 0.2, "quantity_on_hand": 20}'

  >>> InventoryItem.from_json_str('{"name": "Apple", "unit_price": 0.2, "quantity_on_hand": 20}')
  InventoryItem(name='Apple', unit_price=0.2, quantity_on_hand=20)
  ```

### `dataclasses_serialization.bson`

- `BSONSerializer`

  Serializer/deserializer between Python dataclasses and BSON objects.

  ```pycon
  >>> BSONSerializer.serialize(InventoryItem("Apple", 0.2, 20))
  {'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20}

  >>> BSONSerializer.deserialize(InventoryItem, {'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20})
  InventoryItem(name='Apple', unit_price=0.2, quantity_on_hand=20)
  ```

- `BSONSerializerMixin`

  Adds `as_bson` and `from_bson` methods to dataclasses when used as a mixin.

  ```python
  @dataclass
  class InventoryItem(BSONSerializerMixin):
      ...
  ```

  ```pycon
  >>> InventoryItem("Apple", 0.2, 20).as_bson()
  {'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20}

  >>> InventoryItem.from_bson({'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20})
  InventoryItem(name='Apple', unit_price=0.2, quantity_on_hand=20)
  ```

- `BSONStrSerializer`

  Serializer/deserializer between Python dataclasses and binary BSON strings.

- `BSONStrSerializerMixin`

  Adds `as_bson_str` and `from_bson_str` methods to dataclasses when used as a mixin.

  ```python
  @dataclass
  class InventoryItem(BSONStrSerializerMixin):
      ...
  ```

## Installation

Install and update using the standard Python package manager [pip](https://pip.pypa.io/en/stable/):

```bash
pip install dataclasses_serialization
```
