Metadata-Version: 2.1
Name: ntt-json-model
Version: 1.0.0
Summary: Small library for observation mechanism
Home-page: https://github.com/threezinedine/ntt-json-model
Author: threezinedine
Author-email: threezinedine@email.com
License: UNKNOWN
Project-URL: Source, https://github.com/threezinedine/ntt-json-model
Project-URL: Tracker, https://github.com/threezinedine/ntt-json-model/issues
Keywords: json,mvvm,signal,ntt
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Description-Content-Type: text/markdown
License-File: LICENSE

# ntt-json-model
Library with model object which is observable and can be serialize and deserialize from json file

## Example

### With `primitive` data

```python
from ntt_json_model import *

class TestModel(ModelBase):
    def __init__(self, 
                    nValue: int = 3, 
                    strName: str = "Hello",
                    fTemp: float = 3.1,
                    lstScores: List[int] = []) -> None:
        super().__init__()

        IntegerProperty(self, nValue, "_nValue")
        FloatProperty(self, fTemp, "_fTemp")
        StrProperty(self, strName, "_strName")
        ListProperty(self, lstScores, "_lstScores")

    @property
    def Value(self) -> int:
        return self._nValue.GetValue()

    @Value.setter
    def Value(self, nValue: int) -> None:
        self._nValue.SetValue(nValue)

    @property
    def Temp(self) -> str:
        return self._fTemp.GetValue()

    @Temp.setter
    def Temp(self, fTemp: float) -> None:
        self._fTemp.SetValue(fTemp)
    
    @property
    def Name(self) -> str:
        return self._strName.GetValue()

    @Name.setter
    def Name(self, strName: str) -> None:
        self._strName.SetValue(strName)

    @property
    def Scores(self) -> List[int]:
        return self._lstScores.GetValue()

ModelBase.mSubModels[TestModel.__name__] = TestModel

def PrintIfChanged() -> None:
    print("Model has changed")

model = TestModel()
model.Connect(PrintIfChanged)
model.Temp = 3  # ---> "Model has changed"

print(model.ToDict()) 
# Output:
# {
#     "__class__": "TestModel",
#     "_nValue": 3,
#     "_fTemp": 3.0,
#     "_strName": "Hello",
#     "_lstScores": []
# }

model.FromDict({
    "__class__": "TestModel",
    "_nValue": 3,
    "_fTemp": 3.0,
    "_strName": "Hello",
    "_lstScores": [4, 3]
})
```

### `Model` Data

``` python
class TestModelClass(ModelBase):
    def __init__(self, nScore: int = 4, *args, **kwargs) -> None:
        super().__init__()

        IntegerProperty(self, nScore, "_nScore")
        ModelProperty(self, TestModel(*args, **kwargs), "_mTestModel")

    @property
    def Score(self) -> int:
        return self._nScore.GetValue()

    @Score.setter
    def Score(self, nNewScore: int) -> None:
        self._nScore.SetValue(nNewScore)

    @property
    def TestModel(self) -> TestModel:
        return self._mTestModel.GetValue()

ModelBase.mSubModels[TestModelClass.__name__] = TestModelClass
```

### `Model List` Data

```python
class TestModelListClass(ModelBase):
    def __init__(self, fScore: float = 8.5) -> None:
        super().__init__()

        FloatProperty(self, fScore, "_fScore")
        ModelListProperty(self, [], "_mModels")
        
    @property
    def Score(self) -> float:
        return self._fScore.GetValue()

    @Score.setter
    def Score(self, fNewScore: float) -> None:
        self._fScore.SetValue(fNewScore)

    @property
    def Models(self) -> List[TestModelClass]:
        return self._mModels.GetValue()

ModelBase.mSubModels[TestModelListClass.__name__] = TestModelListClass
```

