JSON models

jsonmodels is library to make it easier for you to deal with structures that are converted to, or read from JSON.

• Free software: BSD license
• Documentation: http://jsonmodels.rtfd.org
• Source: https://github.com/beregond/jsonmodels

Features

• Fully tested with Python 2.7, 3.3, 3.4, 3.5, 3.6.

• Support for PyPy (see implementation notes in docs for more details).

• Create Django-like models:

  from jsonmodels import models, fields, errors, validators
  
  
  class Cat(models.Base):
  
      name = fields.StringField(required=True)
      breed = fields.StringField()
      love_humans = fields.IntField(nullable=True)
  
  
  class Dog(models.Base):
  
      name = fields.StringField(required=True)
      age = fields.IntField()
  
  
  class Car(models.Base):
  
      registration_number = fields.StringField(required=True)
      engine_capacity = fields.FloatField()
      color = fields.StringField()
  
  
  class Person(models.Base):
  
      name = fields.StringField(required=True)
      surname = fields.StringField(required=True)
      nickname = fields.StringField(nullable=True)
      car = fields.EmbeddedField(Car)
      pets = fields.ListField([Cat, Dog], nullable=True)

• Access to values through attributes:

  >>> cat = Cat()
  >>> cat.populate(name='Garfield')
  >>> cat.name
  'Garfield'
  >>> cat.breed = 'mongrel'
  >>> cat.breed
  'mongrel'

• Validate models:

  >>> person = Person(name='Chuck', surname='Norris')
  >>> person.validate()
  None
  
  >>> dog = Dog()
  >>> dog.validate()
  *** ValidationError: Field "name" is required!

• Cast models to python struct and JSON:

  >>> cat = Cat(name='Garfield')
  >>> dog = Dog(name='Dogmeat', age=9)
  >>> car = Car(registration_number='ASDF 777', color='red')
  >>> person = Person(name='Johny', surname='Bravo', pets=[cat, dog])
  >>> person.car = car
  >>> person.to_struct()
  {
      'car': {
          'color': 'red',
          'registration_number': 'ASDF 777'
      },
      'surname': 'Bravo',
      'name': 'Johny',
      'nickname': None,
      'pets': [
          {'name': 'Garfield'},
          {'age': 9, 'name': 'Dogmeat'}
      ]
  }
  
  >>> import json
  >>> person_json = json.dumps(person.to_struct())

• You don't like to write JSON Schema? Let jsonmodels do it for you:

  >>> person = Person()
  >>> person.to_json_schema()
  {
      'additionalProperties': False,
      'required': ['surname', 'name'],
      'type': 'object',
      'properties': {
          'car': {
              'additionalProperties': False,
              'required': ['registration_number'],
              'type': 'object',
              'properties': {
                  'color': {'type': 'string'},
                  'engine_capacity': {'type': ''},
                  'registration_number': {'type': 'string'}
              }
          },
          'surname': {'type': 'string'},
          'name': {'type': 'string'},
          'nickname': {'type': ['string', 'null']}
          'pets': {
              'items': {
                  'oneOf': [
                      {
                          'additionalProperties': False,
                          'required': ['name'],
                          'type': 'object',
                          'properties': {
                              'breed': {'type': 'string'},
                              'name': {'type': 'string'}
                          }
                      },
                      {
                          'additionalProperties': False,
                          'required': ['name'],
                          'type': 'object',
                          'properties': {
                              'age': {'type': 'number'},
                              'name': {'type': 'string'}
                          }
                      },
                      {
                          'type': 'null'
                      }
                  ]
              },
              'type': 'array'
          }
      }
  }

• Validate models and use validators, that affect generated schema:

  >>> class Person(models.Base):
  ...
  ...     name = fields.StringField(
  ...         required=True,
  ...         validators=[
  ...             validators.Regex('^[A-Za-z]+$'),
  ...             validators.Length(3, 25),
  ...         ],
  ...     )
  ...     age = fields.IntField(
  ...         nullable=True,
  ...         validators=[
  ...             validators.Min(18),
  ...             validators.Max(101),
  ...         ]
  ...     )
  ...     nickname = fields.StringField(
  ...         required=True,
  ...         nullable=True
  ...     )
  ...
  
  >>> person = Person()
  >>> person.age = 11
  >>> person.validate()
  *** ValidationError: '11' is lower than minimum ('18').
  >>> person.age = None
  >>> person.validate()
  None
  
  >>> person.age = 19
  >>> person.name = 'Scott_'
  >>> person.validate()
  *** ValidationError: Value "Scott_" did not match pattern "^[A-Za-z]+$".
  
  >>> person.name = 'Scott'
  >>> person.validate()
  None
  
  >>> person.nickname = None
  >>> person.validate()
  *** ValidationError: Field is required!
  
  >>> person.to_json_schema()
  {
      "additionalProperties": false,
      "properties": {
          "age": {
              "maximum": 101,
              "minimum": 18,
              "type": ["number", "null"]
          },
          "name": {
              "maxLength": 25,
              "minLength": 3,
              "pattern": "/^[A-Za-z]+$/",
              "type": "string"
          },
          "nickname": {,
              "type": ["string", "null"]
          }
      },
      "required": [
          "nickname",
          "name"
      ],
      "type": "object"
  }

  For more information, please see topic about validation in documentation.

• Lazy loading, best for circular references:

  >>> class Primary(models.Base):
  ...
  ...     name = fields.StringField()
  ...     secondary = fields.EmbeddedField('Secondary')
  
  >>> class Secondary(models.Base):
  ...
  ...    data = fields.IntField()
  ...    first = fields.EmbeddedField('Primary')

  You can use either Model, full path path.to.Model or relative imports .Model or ...Model.

• Using definitions to generate schema for circular references:

  >>> class File(models.Base):
  ...
  ...     name = fields.StringField()
  ...     size = fields.FloatField()
  
  >>> class Directory(models.Base):
  ...
  ...     name = fields.StringField()
  ...     children = fields.ListField(['Directory', File])
  
  >>> class Filesystem(models.Base):
  ...
  ...     name = fields.StringField()
  ...     children = fields.ListField([Directory, File])
  
  >>> Filesystem.to_json_schema()
  {
      "type": "object",
      "properties": {
          "name": {"type": "string"}
          "children": {
              "items": {
                  "oneOf": [
                      "#/definitions/directory",
                      "#/definitions/file"
                  ]
              },
              "type": "array"
          }
      },
      "additionalProperties": false,
      "definitions": {
          "directory": {
              "additionalProperties": false,
              "properties": {
                  "children": {
                      "items": {
                          "oneOf": [
                              "#/definitions/directory",
                              "#/definitions/file"
                          ]
                      },
                      "type": "array"
                  },
                  "name": {"type": "string"}
              },
              "type": "object"
          },
          "file": {
              "additionalProperties": false,
              "properties": {
                  "name": {"type": "string"},
                  "size": {"type": "number"}
              },
              "type": "object"
          }
      }
  }

• Compare JSON schemas:

  >>> from jsonmodels.utils import compare_schemas
  >>> schema1 = {'type': 'object'}
  >>> schema2 = {'type': 'array'}
  >>> compare_schemas(schema1, schema1)
  True
  >>> compare_schemas(schema1, schema2)
  False

More

For more examples and better description see full documentation: http://jsonmodels.rtfd.org.