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A Object-JSON Document mapper

Project description

PODM: (P)ython (O)bject - (D)ictionary (M)apper

This library is intended to create objects that easily serialize to dictionaries that can be later stored as JSON or YAML. It is intended as a replacement of jsonpickle for cases where jsonpickle output format is not good at all.

Features:

  • Support for ordered dictionaries or custom mapping classes
  • Custom field serialization/deserialization
  • Validators
  • Json Schema generation

Installation

	pip3 install podm

Some use case samples

from podm import JsonObject, Property, Handler

class DateTimeHandler(Handler):
	"""
	Define a custom handler for datetime objects
	"""
	def encode(self, obj):
		return {
			'year' : obj.year,
			'month' : obj.month,
			'day' : obj.day,
			'hour' : obj.hour,
			'minute' : obj.minute,
			'second' : obj.second,
			'microsecond' : obj.microsecond
		}

	def decode(self, obj_data):
		return datetime(**obj_data)

class Entity(JsonObject):
	"""
	A base class for the object model
	"""
	oid = Property()
	created = Property('created', handler=DateTimeHandler(), default=datetime.now) # Default value when object is instantiated

class Company(Entity):
	company_name = Property('company-name') # Specify a different field name in json.
	description = Property()        

class Sector(Entity):
	employees = Property('employees', default=[])

class Employee(Entity):
	name = Property()

company = Company(
  name='My great company',
  description='....'
)

json_data = company.to_dict()

company_2 = Company.from_dict(json_data)

Deserialize a dictionary with no type information.

data = {
	'company-name' : 'master',
	'description'  : 'some description'
}
company = Company.from_dict(data)

Deserialize a dictionary with type information

Uses the same field as jsonpickle.

data = {
	'py/object' : 'Company',
	'company-name' : 'master',
	'description'  : 'some description'
}
company = JsonObject.parse(data) 

Jsonpickle format support

data = {
	'py/object' : 'Company',
	'py/state': {
		'company-name' : 'master',
		'description'  : 'some description'
	}
}
company = JsonObject.parse(data) 

Automatically generated getters/setters.

If they are declared property accessors will use them instead.

class Company(JsonObject):
	company_name = Property('company-name') # Specify a different field name in json.

# Automatically generated getter
company_name = company.get_company_name()

# Also property accessors
company_name = company.company_name

# And private attributes
company_name = company._company_name

Write custom getters and setters

class Company(JsonObject):
	company_name = Property('company-name') # Specify a different field name in json.

	def get_company_name(self):
		print('Getter called!!!')
		# generated attribute
		return self._company_name

# So, when calling the property getter ...
company_name = company.company_name

# will print 'Getter called!!!'

OrderedDict support

serialized = company.to_dict(OrderedDict)
# serialized data is instance of OrderedDict

class TestObject(JsonObject):
	val1 = Property()

obj = TestObject()
obj.val1 = OrderedDict(key1='value1')

serialized = company.to_dict()
# serialized will be instance of dict, field 'val1' will be instance of OrderedDict

Enum support

It is possible to decide how to serialize/deserialize enums.

class InvoiceType(Enum):
	TYPE_A = 1
	TYPE_B = 2


class Invoice(JsonObject):
	invoice_type = Property(type=InvoiceType, enum_as_str=True)


invoice = Invoice(invoice_type=InvoiceType.TYPE_A)

serialized = invoice.to_dict()

print(serialized['invice_type'])
# Will print 'TYPE_A'

class Invoice(JsonObject):
	invoice_type = Property(type=InvoiceType)


invoice = Invoice(invoice_type=InvoiceType.TYPE_A)

serializd = invoice.to_dict()
print(serialized['invoice_type'])
# Will print 1

Json Schema generation.

Check test cases for examples.

Validators.

Check test cases for examples.

Project details


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