pydataclasses 1.0.2

Feature Support

Python Data Classes generally support

• untyped data, typed data, and typed data list

• arbitrary attribute names in the dictionary input

• no python attribute naming conflict or pollution

• lazy and auto object creation on-the-fly

• lazy loading of the dict input (default: enabled)

• synchronous updates of the dict input (default: disabled)

Getting Started

• Install the Python Data Classes

pip install pydataclasses

• Create the Python Data Classes

from pydataclasses import DataClass


class TT(DataClass):

    attr = None


class ONCE(DataClass):

    data = None


class TWICE(ONCE):

    tear = TT
    tears = [TT]

    def __init__(self, *args, **kwargs):

        super(TWICE, self).__init__(*args, **kwargs)

        self.pair = TWICE
        self.pairs = [TWICE]

• Play with the Python Data Classes

old_data = 'hello'
new_data = 'world'
old_dict = {'data': old_data}
new_dict = {'data': new_data}

# lazy and auto object creation on-the-fly
twice = TWICE()
assert twice.pairs[1].tear.attr is None
twice.pairs[1].tear.attr = old_data
assert old_data == twice.pairs[1].tear.attr

# lazy loading of the dict input (default: enabled)
twice = TWICE(old_dict)
assert old_data == twice.data
assert old_dict == twice.__as_dict__(dict, 0)

# synchronous updates of the dict input (default: disabled)
assert old_dict != new_dict
twice = TWICE(old_dict, __sync__=True)
twice.data = new_data
assert old_dict == new_dict

Best Practices

Please

• read and refer to pydataclasses.utils.JSONData as an example

• put a tailored subclass between pydataclasses and your project

• write (or copy from pydataclasses) as many tests as possible for this subclass

from pydataclasses import DataClass


class ProjectDataClass(DataClass):

    def as_dict(self, dict_class=OrderedDict):
        return self.__as_dict__(dict_class, 0)

Release History