JSONSchema generation from Python type hints
Project description
jsonschema-gen is Python type hints parser which can convert function and method annotations into JSONSchema objects.
- Pythonic classes for JSONSchema types
- Extensive type coverage: TypedDict, Generic, NewType, etc.
- No external dependencies
Installation
With pip and python 3.8+:
pip3 install jsonschema-gen
How to use
See the user guide for more info.
Create a parser:
from jsonschema_gen import Parser
parser = Parser(strict=True)
Generate schema for your function or method from Python type hints (see the list of supported types):
from typing import NewType
UserName = NewType('UserName', str)
class UserData:
def get_user(self, name: UserName, active: bool = True) -> dict:
"""Get user by username."""
annotation = parser.parse_function(UserData.get_user, UserData)
The result is an annotation object with input .kwargs
and output .returns
. You can get a JSONSchema compatible dict
using json_repr()
on .kwargs
:
schema = annotation.kwargs.json_repr()
The result would look like this (if converted to JSON with dumps
):
{
"type": "object",
"title": "Get user by username.",
"properties": {
"name": {
"title": "Username",
"type": "string"
},
"active": {
"type": "boolean",
"default": true
}
},
"required": [
"name"
],
"additionalProperties": false
}
Use fastjsonschema or other JSONSchema validation library to create a validator for the schema:
from fastjsonschema import compile
validator = compile(schema)
valiator({'name': 'John', 'email': 'john@dowe'})
Alternatively you can pass the whole class to the parser to get the annotation mapping:
annotations = parser.parse_class(UserData)
annotations['get_user'].kwargs.json_repr()
Compatibility
The Python type hints are vast and yet not well organized, so there could always be some data type I forgot to add here. Read the customization guide to extend the standard list of type parsers.
Some annotations cannot be converted to JSONSchema objects, for example: positional-only arguments, variable positionals, etc. There are different strategies considering these types of parameters.
Python 3.8 compatibility is so-so due to lots of features and changes made in 3.9. However, it still should support most of the functionality.
Also read about the strict mode.
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