type-serialize 2.1.0
Serialize with type annotations
License: MIT License
Requires Python: >=3.8
Keywords: serialize, deserialize

# type-serialize

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Serialize with type annotations

## Features

- Supported in Python 3.9 and later.
- Serialize classes without additional code.
  - Custom classes
  - [@dataclas](https://docs.python.org/3/library/dataclasses.html#dataclasses.dataclass)
  - [NamedTuple](https://docs.python.org/3/library/typing.html#typing.NamedTuple)
  - [Enum](https://docs.python.org/3/library/enum.html#enum.Enum)
  - (Experimental) [numpy.ndarray](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy-ndarray)
- Deserialization using type annotations.
- No dependencies
- <del>Compress serialization results: bz2, gzip, lzma, zlib</del> - Removed to focus on 'serialization' itself.

## Overview

To pass a custom object to the [json.dumps](https://docs.python.org/3/library/json.html#json.dumps)
and [json.loads](https://docs.python.org/3/library/json.html#json.loads) functions,
there is the following method.

- Expand [json.JSONEncoder](https://docs.python.org/3/library/json.html#json.JSONEncoder)
  and [json.JSONDecoder](https://docs.python.org/3/library/json.html#json.JSONDecoder).
- Convert to built-in Python object supported by
  [json.JSONEncoder](https://docs.python.org/3/library/json.html#json.JSONEncoder) and
  [json.JSONDecoder](https://docs.python.org/3/library/json.html#json.JSONDecoder).

Both methods require additional code and have some problems.

- Problem of not checking symbols when manipulating strings.
- When adding/deleting/editing a property, all related codes must be changed together.
- Painful typecasting (as the biggest problem).

As a way to hide these problems with a library and use serialization and deserialization,
I chose **[type annotations](https://docs.python.org/3/library/typing.html)**.
(Although the library is complicated; haha...) There are some additional advantages to using this.

- Static type checking using [mypy](https://mypy.readthedocs.io/en/stable/).
- Autocomplete in IDE like PyCharm.

### Things to know

- All public fields are serialized.
- Methods are not serialized.
- Private fields that start with an underscore (`_`) are not serialized.
- Members specified with the `@property` decorator are not serialized.
- When deserializing, all fields must be type-annotated.
- A value of `None` is ignored by the serialization target.
- When deserializing, the `__init__` function must have **NO** required arguments.
- Implement `__serialize__` to override the serialization method.
- Implement `__deserialize__` to override the deserialization method.

## Installation

```shell
pip install type-serialize
```

## Usage

### Serializable python object

```python
from dataclasses import dataclass
from type_serialize import deserialize, serialize


@dataclass
class Sample:
    field1: str
    field2: int


data = Sample(field1="a", field2=100)
obj = serialize(data)
assert isinstance(obj, dict)
assert obj["field1"] == "a"
assert obj["field2"] == 100
print(obj)

result = deserialize(obj, Sample)
assert isinstance(result, Sample)
assert data == result
print(result)
```

### Override serialize and deserialize

```python
from dataclasses import dataclass
from type_serialize import deserialize, serialize


@dataclass
class Sample:
    value: int

    def __serialize__(self):
        return {"a": self.value}

    def __deserialize__(self, data) -> None:
        self.value = data["a"]

    def __init__(self, value=100):
        self.value = value


test = Sample(value=200)
obj = serialize(test)
assert isinstance(obj, dict)
assert obj["a"] == 200
print(obj)

result = deserialize(obj, Sample)
assert isinstance(result, Sample)
assert test == result
print(result)
```

## License

See the [LICENSE](./LICENSE) file for details. In summary,
**type-serialize** is licensed under the **MIT license**.