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# openapi-pydantic
[](https://pypi.org/project/openapi-pydantic/)
[](https://github.com/mike-oakley/openapi-pydantic/blob/main/LICENSE)
OpenAPI schema implemented in [Pydantic](https://github.com/samuelcolvin/pydantic). Both Pydantic 1.8+ and 2.x are supported.
The naming of the classes follows the schema in
[OpenAPI specification](https://github.com/OAI/OpenAPI-Specification/blob/master/versions/3.1.1.md#schema).
> This library is forked from [OpenAPI Schema Pydantic](https://github.com/kuimono/openapi-schema-pydantic) (at version [1.2.4](https://github.com/kuimono/openapi-schema-pydantic/releases/tag/v1.2.4)) which is no longer actively maintained.
## Installation
`pip install openapi-pydantic`
## Try me
```python
from openapi_pydantic import OpenAPI, Info, PathItem, Operation, Response
# Construct OpenAPI by pydantic objects
open_api = OpenAPI(
info=Info(
title="My own API",
version="v0.0.1",
),
paths={
"/ping": PathItem(
get=Operation(
responses={
"200": Response(
description="pong"
)
}
)
)
},
)
# Note: for Pydantic 1.x, replace `model_dump_json` with `json`
print(open_api.model_dump_json(by_alias=True, exclude_none=True, indent=2))
```
Result:
```json
{
"openapi": "3.1.1",
"info": {
"title": "My own API",
"version": "v0.0.1"
},
"servers": [
{
"url": "/"
}
],
"paths": {
"/ping": {
"get": {
"responses": {
"200": {
"description": "pong"
}
},
"deprecated": false
}
}
}
}
```
## Take advantage of Pydantic
Pydantic is a great tool. It allows you to use object / dict / mixed data for input.
The following examples give the same OpenAPI result as above:
```python
from openapi_pydantic import parse_obj, OpenAPI, PathItem, Response
# Construct OpenAPI from dict, inferring the correct schema version
open_api = parse_obj({
"openapi": "3.1.1",
"info": {"title": "My own API", "version": "v0.0.1"},
"paths": {
"/ping": {
"get": {"responses": {"200": {"description": "pong"}}}
}
},
})
# Construct OpenAPI v3.1 schema from dict
# Note: for Pydantic 1.x, replace `model_validate` with `parse_obj`
open_api = OpenAPI.model_validate({
"info": {"title": "My own API", "version": "v0.0.1"},
"paths": {
"/ping": {
"get": {"responses": {"200": {"description": "pong"}}}
}
},
})
# Construct OpenAPI with mix of dict/object
# Note: for Pydantic 1.x, replace `model_validate` with `parse_obj`
open_api = OpenAPI.model_validate({
"info": {"title": "My own API", "version": "v0.0.1"},
"paths": {
"/ping": PathItem(
get={"responses": {"200": Response(description="pong")}}
)
},
})
```
## Use Pydantic classes as schema
- The [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/master/versions/3.0.4.md#schemaObject)
in OpenAPI has definitions and tweaks in JSON Schema, which are hard to comprehend and define a good data class
- Pydantic already has a good way to [create JSON schema](https://pydantic-docs.helpmanual.io/usage/schema/).
Let's not reinvent the wheel.
The approach to deal with this:
1. Use `PydanticSchema` objects to represent the `Schema` in `OpenAPI` object
2. Invoke `construct_open_api_with_schema_class` to resolve the JSON schemas and references
```python
from pydantic import BaseModel, Field
from openapi_pydantic import OpenAPI
from openapi_pydantic.util import PydanticSchema, construct_open_api_with_schema_class
def construct_base_open_api() -> OpenAPI:
# Note: for Pydantic 1.x, replace `model_validate` with `parse_obj`
return OpenAPI.model_validate({
"info": {"title": "My own API", "version": "v0.0.1"},
"paths": {
"/ping": {
"post": {
"requestBody": {"content": {"application/json": {
"schema": PydanticSchema(schema_class=PingRequest)
}}},
"responses": {"200": {
"description": "pong",
"content": {"application/json": {
"schema": PydanticSchema(schema_class=PingResponse)
}},
}},
}
}
},
})
class PingRequest(BaseModel):
"""Ping Request"""
req_foo: str = Field(description="foo value of the request")
req_bar: str = Field(description="bar value of the request")
class PingResponse(BaseModel):
"""Ping response"""
resp_foo: str = Field(description="foo value of the response")
resp_bar: str = Field(description="bar value of the response")
open_api = construct_base_open_api()
open_api = construct_open_api_with_schema_class(open_api)
# print the result openapi.json
# Note: for Pydantic 1.x, replace `model_dump_json` with `json`
print(open_api.model_dump_json(by_alias=True, exclude_none=True, indent=2))
```
Result:
```json
{
"openapi": "3.1.1",
"info": {
"title": "My own API",
"version": "v0.0.1"
},
"servers": [
{
"url": "/"
}
],
"paths": {
"/ping": {
"post": {
"requestBody": {
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/PingRequest"
}
}
},
"required": false
},
"responses": {
"200": {
"description": "pong",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/PingResponse"
}
}
}
}
},
"deprecated": false
}
}
},
"components": {
"schemas": {
"PingRequest": {
"title": "PingRequest",
"required": [
"req_foo",
"req_bar"
],
"type": "object",
"properties": {
"req_foo": {
"title": "Req Foo",
"type": "string",
"description": "foo value of the request"
},
"req_bar": {
"title": "Req Bar",
"type": "string",
"description": "bar value of the request"
}
},
"description": "Ping Request"
},
"PingResponse": {
"title": "PingResponse",
"required": [
"resp_foo",
"resp_bar"
],
"type": "object",
"properties": {
"resp_foo": {
"title": "Resp Foo",
"type": "string",
"description": "foo value of the response"
},
"resp_bar": {
"title": "Resp Bar",
"type": "string",
"description": "bar value of the response"
}
},
"description": "Ping response"
}
}
}
}
```
## Notes
### Use of OpenAPI.model_dump() / OpenAPI.model_dump_json() / OpenAPI.json() / OpenAPI.dict()
When using `OpenAPI.model_dump()` / `OpenAPI.model_dump_json()` / `OpenAPI.json()` / `OpenAPI.dict()` functions,
the arguments `by_alias=True, exclude_none=True` have to be in place.
Otherwise the resulting json will not fit the OpenAPI standard.
```python
# OK (Pydantic 2)
open_api.model_dump_json(by_alias=True, exclude_none=True, indent=2)
# OK (Pydantic 1)
open_api.json(by_alias=True, exclude_none=True, indent=2)
# Not good
open_api.model_dump_json(indent=2)
open_api.json(indent=2)
```
More info about field aliases:
| OpenAPI version | Field alias info |
| --------------- | ---------------- |
| 3.1 | [here](https://github.com/mike-oakley/openapi-pydantic/blob/main/openapi_pydantic/v3/v3_1/README.md#alias) |
| 3.0 | [here](https://github.com/mike-oakley/openapi-pydantic/blob/main/openapi_pydantic/v3/v3_0/README.md#alias) |
### Non-pydantic schema types
Some schema types are not implemented as pydantic classes.
Please refer to the following for more info:
| OpenAPI version | Non-pydantic schema type info |
| --------------- | ----------------------------- |
| 3.1 | [here](https://github.com/mike-oakley/openapi-pydantic/blob/main/openapi_pydantic/v3/v3_1/README.md#non-pydantic-schema-types) |
| 3.0 | [here](https://github.com/mike-oakley/openapi-pydantic/blob/main/openapi_pydantic/v3/v3_0/README.md#non-pydantic-schema-types) |
### Use OpenAPI 3.0 instead of 3.1
Some UI renderings (e.g. Swagger) still do not support OpenAPI 3.1.x.
The old 3.0.x version is available by importing from different paths:
```python
from openapi_pydantic.v3.v3_0 import OpenAPI, ...
from openapi_pydantic.v3.v3_0.util import PydanticSchema, construct_open_api_with_schema_class
```
### Pydantic version compatibility
Compatibility with both major versions of Pydantic (1.8+ and 2.*) is mostly achieved using a module called `compat.py`. It detects the installed version of Pydantic and exports version-specific symbols for use by the rest of the package. It also provides all symbols necessary for type checking. The `compat.py` module is not intended to be imported by other packages, but other packages may find it helpful as an example of how to span major versions of Pydantic.
## Credits
This library is based from the original implementation by Kuimono of [OpenAPI Schema Pydantic](https://github.com/kuimono/openapi-schema-pydantic) which is no longer actively maintained.
## License
[MIT License](https://github.com/mike-oakley/openapi-pydantic/blob/main/LICENSE)
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