Generate JSON schema from python dataclasses
Project description
dc_schema
Tiny library to generate JSON schema (2020-12) from python dataclasses. No other dependencies, standard library only.
pip install dc-schema
Assumptions
- python 3.9+
Motivation
Create a lightweight, focused solution to generate JSON schema from plain dataclasses. pydantic is a much more mature option, however it also does a lot of other things I didn't want to include here. Deepen my understanding of python dataclasses, typing and JSON schema.
Usage
Basics
Create a regular python dataclass and pass it to get_schema
.
import dataclasses
import datetime
import json
from dc_schema import get_schema
@dataclasses.dataclass
class Book:
title: str
published: bool = False
@dataclasses.dataclass
class Author:
name: str
age: int
dob: datetime.date
books: list[Book]
print(json.dumps(get_schema(Author), indent=2))
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"type": "object",
"title": "Author",
"properties": {
"name": {
"type": "string"
},
"age": {
"type": "integer"
},
"dob": {
"type": "string",
"format": "date"
},
"books": {
"type": "array",
"items": {
"allOf": [
{
"$ref": "#/$defs/Book"
}
]
}
}
},
"required": [
"name",
"age",
"dob",
"books"
],
"$defs": {
"Book": {
"type": "object",
"title": "Book",
"properties": {
"title": {
"type": "string"
},
"published": {
"type": "boolean",
"default": false
}
},
"required": [
"title"
]
}
}
}
Annotations
You can use typing.Annotated + SchemaAnnotation
to attach
metadata to the schema, such as field descriptions, examples, validation (min/max length, regex pattern, ...), etc.
Consult the code for full details.
import dataclasses
import datetime
import json
import typing as t
from dc_schema import get_schema, SchemaAnnotation
@dataclasses.dataclass
class Author:
name: t.Annotated[str, SchemaAnnotation(title="Full name", description="The authors full name")]
age: t.Annotated[int, SchemaAnnotation(minimum=0)]
dob: t.Annotated[t.Optional[datetime.date], SchemaAnnotation(examples=["1990-01-17"])] = None
print(json.dumps(get_schema(Author), indent=2))
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"type": "object",
"title": "Author",
"properties": {
"name": {
"type": "string",
"title": "Full name",
"description": "The authors full name"
},
"age": {
"type": "integer",
"minimum": 0
},
"dob": {
"anyOf": [
{
"type": "string",
"format": "date"
},
{
"type": "null"
}
],
"default": null,
"examples": [
"1990-01-17"
]
}
},
"required": [
"name",
"age"
]
}
To customize the metadata of a dataclass itself, use a SchemaConfig
.
import dataclasses
import json
from dc_schema import get_schema, SchemaAnnotation
@dataclasses.dataclass
class User:
name: str
class SchemaConfig:
annotation = SchemaAnnotation(title="System user", description="A user of the system")
print(json.dumps(get_schema(User), indent=2))
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"type": "object",
"title": "System user",
"description": "A user of the system",
"properties": {
"name": {
"type": "string"
}
},
"required": [
"name"
]
}
Further examples
See the tests for full example usage.
CLI
dc_schema <file_path> <dataclass>
e.g.
dc_schema ./schema.py Author
Other tools
For working with dataclasses or JSON schema:
- https://github.com/konradhalas/dacite - create data classes from dictionaries.
- https://python-jsonschema.readthedocs.io/en/stable/ - validate an object against a JSON schema.
- https://json-schema.org/understanding-json-schema/index.html - nice reference for understanding JSON schema.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file dc_schema-0.0.8.tar.gz
.
File metadata
- Download URL: dc_schema-0.0.8.tar.gz
- Upload date:
- Size: 6.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.1.12 CPython/3.10.0 Linux/5.13.0-39-generic
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 89fed792c63b80a91d4fef723f9aefbca83952eb611fbc168ef8381bf62acbb5 |
|
MD5 | 35c94fa1c779b0ce61f293df3f9b7341 |
|
BLAKE2b-256 | b521bdff5fc8ae03453b23e753a79ebfcfa7e44b9ff40e5a7d364e2456a997ad |
File details
Details for the file dc_schema-0.0.8-py3-none-any.whl
.
File metadata
- Download URL: dc_schema-0.0.8-py3-none-any.whl
- Upload date:
- Size: 6.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.1.12 CPython/3.10.0 Linux/5.13.0-39-generic
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | c5990a2ce8fa22ccf18789b11db2440eeddcd36727cd7d3b6c802366d92ef17a |
|
MD5 | 67cd3dc64d280006118011d92b9ff1b9 |
|
BLAKE2b-256 | 484c69eb48bd94bbb9da06f5c019e951d3f07c14e1f3cec7fbf950f1d2536728 |