Files
pydantic/docs/datamodel_code_generator.md
Arseny Boykov c24d33e5f1 Generate docs exampels for Python 3.10 and above (#4339)
* Generate docs exampels for Python 3.10 and above

Code quality is not great and main intent here is to show the result.

* Fix docs build on 3.9

* Build docs on 3.10

* What's Python 3.1?

* Create temp dir if not exists

* Refactor and improve imlementetion

* Keep runtime typing in examples

* Revert unrelated formatting changes

* Add changes file

* Allow specifying requirements in examples

* Pin autoflake and pyupgrade

* Add docs/build to Makefile lint/format/mypy

* ignore_missing_imports for ansi2html and devtools

* Add .tmp-projections to .gitignore

* Remove dont-upgrade now when Pattern is supported

* Update postponed evaluation examples

Co-authored-by: Samuel Colvin <s@muelcolvin.com>
2022-08-14 17:21:53 +01:00

1.7 KiB

The datamodel-code-generator project is a library and command-line utility to generate pydantic models from just about any data source, including:

  • OpenAPI 3 (YAML/JSON)
  • JSON Schema
  • JSON/YAML Data (which will converted to JSON Schema)

Whenever you find yourself with any data convertible JSON but without pydantic models, this tool will allow you to generate type-safe model hierarchies on demand.

Installation

pip install datamodel-code-generator

Example

In this case, datamodel-code-generator creates pydantic models from a JSON Schema file.

datamodel-codegen  --input person.json --input-file-type jsonschema --output model.py

person.json:

{
  "$id": "person.json",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "title": "Person",
  "type": "object",
  "properties": {
    "first_name": {
      "type": "string",
      "description": "The person's first name."
    },
    "last_name": {
      "type": "string",
      "description": "The person's last name."
    },
    "age": {
      "description": "Age in years.",
      "type": "integer",
      "minimum": 0
    },
    "pets": {
      "type": "array",
      "items": [
        {
          "$ref": "#/definitions/Pet"
        }
      ]
    },
    "comment": {
      "type": "null"
    }
  },
  "required": [
      "first_name",
      "last_name"
  ],
  "definitions": {
    "Pet": {
      "properties": {
        "name": {
          "type": "string"
        },
        "age": {
          "type": "integer"
        }
      }
    }
  }
}

model.py: {!.tmp_examples/generate_models_person_model.md!}

More information can be found on the official documentation