yasoo 0.12.6

Yet another serializer of objects

yasoo: Serialize the Data You Have

A python serializer of attrs and dataclass objects that doesn't rely on type hints.

Why yasoo

yasoo adds type data to the serialized data, so deserialization doesn't need to rely on type hints.

Moreover, if you have a field that can contain multiple types of values, or a field which contains some specific implementation of an abstract class, yasoo has no problem with that.

For example, this code works fine:

from attr import attrs, attrib
from yasoo import serialize, deserialize

@attrs
class Foo:
    a = attrib()

@attrs
class Bar:
    foo: Foo = attrib()

serialized = serialize(Bar(foo=5))
assert(deserialize(serialized).foo == 5)

Usage

Basic Usage

For simple objects, use:

from yasoo import serialize, deserialize

with open(path, 'w') as f:
    json.dump(serialize(obj), f)

with open(path) as f:
    obj = deserizlie(json.load(f))

Advanced Usage

Deserializing Collections of Objects

You can deserialize collections of objects:

from attr import attrs, attrib
from yasoo import serialize, deserialize
from yasoo.typing import List_

@attrs
class Foo:
    a = attrib()

foos = [Foo(a=i) for i in range(5)]
serialized = serialize(foos)
de_foos = deserialize(serialized, obj_type=List_[Foo])
assert de_foos == foos

Notice that passing the object type as List[Foo] won't give you the type of de_foos, but using yasoo.typing.List_ will fix this.

Custom (De)Serializers

For objects that need custom serialization/deserialization, you can register your own methods:

from attr import attrs, attrib, asdict
from yasoo import serialize, deserialize, serializer, deserializer

@attrs
class Foo:
    bar = attrib(converter=lambda x: x * 2)

    def set_foobar(self, foobar):
        self.foobar = foobar

    @serializer
    def serialize(self: 'Foo'):
        result = asdict(self)
        if hasattr(self, 'foobar'):
            result['foobar'] = self.foobar
        return result

    @staticmethod
    @deserializer
    def deserialize(data: dict) -> 'Foo':
        foo = Foo(data['bar'] / 2)
        if 'foobar' in data:
            foo.set_foobar(data['foobar'])
        return foo

Notice that registering custom methods with forward reference (i.e. 'Foo' instead of Foo) requires passing the globals parameter to serialize/deserialize, e.g.

serialize(obj, globals=globals())

Using Type Hints

If you want to avoid having the __type key in your serialized data, you can set the type_key parameter to None when calling serialize.

For this to work all fields in the serialized class that are not json-serializable should have a type hint.

Serializing Sequences

By default all sequences found in the data will be converted to list in the serialization process. If you want to be able to deserialize them back to anything other than a list, set the preserve_iterable_types parameter to True when calling serialize.

Note: setting the preserve_iterable_types parameter to True will cause all iterables that are not list to be serialized as dictionaries with their type saved under the type_key.

Multiple Serialization Methods For The Same Type

If you want to define a custom serialization method for a type for a specific use case, without affecting the default serializer, you can create another instance of Serializer and register the method on that instance. For example:

from yasoo import Serializer, serializer, serialize

@serializer
def serialize_foo(foo: Foo):
    return {'bar': foo.bar}

my_serializer = Serializer()

@my_serializer.register()
def serialize_foo_another_way(foo: Foo):
    return {'bar': foo.bar * 2}

serialize(Foo(bar=5))  # returns {'bar': 5, '__type': 'Foo'}
my_serializer.serialize(Foo(bar=5))  # returns {'bar': 10, '__type': 'Foo'}