pydantic-gen generates pydantic schemas from YAML files

Fast and well tested serialization library

Datamodel Code Generator

Data validation using Python type hints

Implement minimal boilerplate CLIs derived from type hints and parse from command line, config files and environment variables.

FastAPI framework, high performance, easy to learn, fast to code, ready for production

This module provides abstract base classes that can be used to test whether a class provides a particular interface; for example, whether it is hashable or whether it is a mapping.

This module provides runtime support for type hints as specified by PEP 484, PEP 526, PEP 544, PEP 586, PEP 589, PEP 591, PEP 612 and PEP 613. The most fundamental support consists of the types Any, Union, Tuple, Callable, TypeVar, and Generic. For full specification please see PEP 484. For a simplified introduction to type hints see PEP 483.

import typing

# preferred
from typing import Dict, List, Union, Any

myvar: Dict = {}

# non-preferred
import typing

myvar: typing.Dict = {}

Code examples

from typing import Mapping, Dict, Any, Union

example1: Dict = {}

example2: Dict[str, Any]

example2: Mapping[str, int]

example3: Union[Dict[str, int], None]

example4: Union[str, None]

def hello(name: str) -> str:
    return f"Hello {name}"

Reference

• Python Docs for Typing

Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy

OpenAPI 2.0 (aka Swagger) and OpenAPI 3 spec validator