typegraph3 0.1.2rc3

Type Auto Switch

TypeGraph

TypeGraph is a Python library designed for type conversion between various types, including custom types, built-in types, and structural types (such as lists, sets, and dictionaries). It supports both synchronous and asynchronous conversion methods.

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Features

• Register type converters for synchronous and asynchronous functions.
• Automatically convert function arguments based on type annotations.
• Support for subclass, union types, and structural types conversion.
• Visualize the conversion graph using mermaid syntax.

Installation

Install the required dependencies with the following command:

pip install typegraph3

Or

pdm add typegraph3

Getting Started

Example: Synchronous Converter

Register and use a synchronous converter:

from typegraph import PdtConverter

converter = PdtConverter()

@converter.register_converter(int, str)
def int_to_str(value: int) -> str:
    return str(value)

result = converter.convert(10, str)  # "10"
print(result)

Example: Asynchronous Converter

Register and use an asynchronous converter:

import asyncio
from typegraph import PdtConverter

converter = PdtConverter()

@converter.async_register_converter(str, int)
async def str_to_int(value: str) -> int:
    return int(value)

async def test_async_conversion():
    result = await converter.async_convert("10", int)  # 10
    print(result)

asyncio.run(test_async_conversion())

Example: Protocol Types

from typing import Protocol, TypedDict, runtime_checkable
from dataclasses import dataclass

from typegraph import PdtConverter

t = PdtConverter()

class Person(Protocol):
    name: str
    phone: str
    address: str

    def get_name(self) -> str:
        ...

class PersonDict(TypedDict):
    name: str
    phone: str
    address: str

class A:
    name: str
    phone: str
    address: str

    def __init__(self, name: str, phone: str, address: str):
        self.name = name
        self.phone = phone
        self.address = address

    def get_name(self) -> str:
        return self.name

@dataclass
class B:
    name: str
    phone: str
    address: str

@t.register_converter(dict, PersonDict)
def convert_dict_to_persondict(data: dict):
    return PersonDict(
        name=data["name"],
        phone=data["phone"],
        address=data["address"]
    )

@t.register_converter(Person, str)
def convert_person_to_str(data: Person):
    return f"{data.name} {data.phone} {data.address}"

@t.register_converter(dict, A)
def convert_dict_to_a(data: dict):
    return A(data["name"], data["phone"], data["address"])

@t.register_converter(dict, B)
def convert_dict_to_b(data: dict):
    return B(data["name"], data["phone"], data["address"])

@t.auto_convert()
def test(a: str):
    return a

d = {"name": "John", "phone": "123", "address": "123"}

t.convert([d], list[str], debug=True)

t.show_mermaid_graph()

graph TD;
dict-->PersonDict
dict-->A
dict-->B
Person-->str

t.show_mermaid_graph()

graph TD;
dict-->PersonDict
dict-->A
dict-->B
Person-->str
A-.->Person

Converting dict[str, str] to <class 'str'> using [<class 'dict'>, <class '__main__.A'>, <class '__main__.Person'>, <class 'str'>], <function TypeConverter.get_converter.<locals>.<lambda>.<locals>.<lambda> at 0x7f1f3306fac0>

['John 123 123']

Auto-Convert Decorator

Automatically convert function arguments based on type annotations:

Synchronous

from typegraph import PdtConverter

converter = PdtConverter()

@converter.register_converter(str, int)
def str_to_int(value: str) -> int:
    return int(value)

@converter.auto_convert()
def add_one(x: int) -> int:
    return x + 1

result = add_one("10")  # 11
print(result)

Asynchronous

from typegraph import PdtConverter
import asyncio

converter = PdtConverter()

@converter.async_register_converter(str, int)
async def str_to_int(value: str) -> int:
    return int(value)

@converter.async_auto_convert()
async def add_one(x: int) -> int:
    return x + 1

async def test_async():
    result = await add_one("10")  # 11
    print(result)

asyncio.run(test_async())

Testing

Unit tests are provided to ensure the library functions correctly. Run the tests:

pdm test

Tests cover:

• Registration and execution of synchronous converters.
• Registration and execution of asynchronous converters.
• Conversion capability checks.
• Automatic conversion of function arguments (both synchronous and asynchronous).

Visualization

You can visualize the type conversion graph:

from typegraph import PdtConverter

t = PdtConverter()

class Test:
    def __init__(self, t):
        self.t = t

@t.register_converter(float, Test)
def str_to_Test(input_value):
    return Test(input_value)

@t.register_converter(Test, float)
def B_to_float(input_value):
    return float(input_value.t)

@t.register_converter(float, str)
async def float_to_str(input_value):
    return str(input_value)

t.show_mermaid_graph()

graph TD;
float-->Test
float-->str
Test-->float

The graph will be displayed using mermaid syntax, which can be rendered online or in supported environments like Jupyter Notebooks.

Supported Types

• Subclass type
• Union type
• Annotated type Pydantic Annotated[T, Feild(...)]
• Structural type
• Protocol type
• TypedDict type
• Generic type
• Dataclass (Dataclass/BaseModel)

License

This project is licensed under the MIT License.

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any changes.

Contact

If you have any questions or concerns, please open an issue in this repository.