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Type declaration and validation library for JSON

Project description

jsonene

This library is intended to provide APIs to define JSON schema, create instances from schema, serialize/de-serialize to/from json or dict to Objects.

Inspired by

jsonschema

json-schema

The basic idea is to provide light weight class based schema defination and data classes

Installation

pip install jsonene

Demos:

import datetime
import json
from jsonene.fields import (
    Boolean,
    List,
    GenericList,
    Null,
    Const,
    Enum,
    Number,
    Integer,
    Schema,
    GenericSchema,
    String,
    Format,
)
from jsonene.operators import AllOf, AnyOf, OneOf, Not
from jsonene.constraints import RequiredDependency
from jsonene.exceptions import ValidationError

Define a Schema

class Person(Schema):
    name = String(min_len=3)
    gender = Enum(["MALE", "FEMALE", "OTHER"])
    emails = List(Format(Format.EMAIL), unique_items=True)
    contact = String(required=False)
    age = Integer(required=False)
    date_of_birth = Format(Format.DATE, name="date-of-birth")  # non python names

    class Meta:
        # Must provide contact if emails is provided
        field_dependencies = [RequiredDependency("emails", ["contact"])]


# Schema Inheritance
class Owner(Person):
    pass


class Broker(Person):
    brokerage = Integer()  # additional properity
    is_broker = Const(True)

    class Meta(Person.Meta):
        field_dependencies = [
            RequiredDependency("emails", ["contact"]),
            RequiredDependency("contact", ["emails"]),
        ]


# Nested schemas
class House(Schema):
    seller = AnyOf(Owner, Broker)  # accepts any of owner or broken
    address = List(Number, String, String)  # accept list in specific type order.
    is_ready = Boolean()
    area = Number()
    country = Const("India")
    garden_area = Number(required=False, use_default=0)
    sqtft_rate = Number(required=False, use_default=0)
    secrete_key = Number(required=False, name="__secrete_key")  # Private
    possesion_date = Format(Format.DATE)
    # Extend instance class and add properties
    class Instance(Schema.Instance):
        @property
        def cost(self):
            # Safety: fields with required=False should be checked before access.
            # Optionaly you can provide default value.
            return self.sqtft_rate * self.area

    # Provide custom meta
    class Meta:
        # Must provide area and sqtft_rate if sqtft_rate provided
        # OR v.v.
        field_dependencies = [
            RequiredDependency("area", ["sqtft_rate"]),
            RequiredDependency("sqtft_rate", ["area"]),
        ]

Create and validate instances

generic = GenericSchema.instance(anything="you want", almost_anything=[1, 2, "3"])
assert len(generic.errors) == 0 # Generic schema never raises errors
assert generic.anything == "you want"
assert generic.almost_anything == [1, 2, "3"]


# Create a instances of schema
owner = Owner.instance(
    name="Test owner",
    gender="MALE",
    emails=["test@test.com"],
    date_of_birth="1989-01-01",
)

assert owner.errors == ["'contact' is a dependency of 'emails'"]
assert owner["date-of-birth"] == "1989-01-01"

test = Broker.instance(
    name="Test",
    gender="MALE",
    emails=["testtest.com", "testtest.com"], # invalid emails, duplicate emails
    contact="123456",
    brokerage=12345,
    is_broker=True,
    date_of_birth="1989-01-01",
)
assert test.errors == [
    "'testtest.com' is not a 'email'",
    "'testtest.com' is not a 'email'",
    "['testtest.com', 'testtest.com'] has non-unique elements",
]

# Owner instance
owner = Owner.instance(
    name="Nikhil Rupanawar",
    gender="MALE",
    emails=["conikhil@gmail.com"],
    contact="4545454545",
    date_of_birth="1989-09-11",
)

# House with owner
house = House.instance()
house.seller = owner
house.address = [123, "A building", "Singad road"]
house.is_ready = True
house.country = "India"
house.area = 7000
house.possesion_date = datetime.datetime.now()
assert house.cost == 0 # sqtft_rate is 0 as default
assert len(house.errors) == 0

# House with broker
another_house = House.instance(
    seller=Broker.instance(
        name="Test Rupanwar",
        gender="MALE",
        emails=["test@test.com"],
        contact="123456",
        brokerage=12345,
        is_broker=True,
        date_of_birth="2002-09-08",
    ),
    address=[123, "A building", "Baner road"],
    sqtft_rate=5000,
    area=1100,
    is_ready=True,
    country="India",
    secrete_key=12345,
    possesion_date=datetime.datetime.now()
)
another_house.validate()
assert another_house.cost == 5500000

List basics

# Generic list
>>> l = List.instance([1, 23, 56, "anything"])
>>> l.append("wow")
>>> l[1:6]  # slice
>>> l.append(23)
>>> l.extend([45])
>>> l[2] = 100
>>> l.validate()  # No errors!

List of types

l = List(String).instance(["only", "strings", "are", "allowed"])
assert len(l.errors) == 0  # No errors!

l = List(String).instance(["only", "strings", 60, 30])
assert [e.message for e in l.exceptions] == [
    "60 is not of type 'string'",
    "30 is not of type 'string'",
]

# list of house
houses = List(House).instance([house, another_house])
houses.validate()
houses.to_json()

Validate any document/dict against the schema

House().validate(
    {
        "seller": {
            "age": 22,
            "emails": ["test@test.com", "test2@test.com"],
            "name": "nikhil",
            "gender": "MALE",
            "contact": "1234567",
            "date-of-birth": "1978-09-04",
        },
        "address": [120, "Flat A", "Sarang"],
        "area": 1234,
        "sqtft_rate": 2000,
        "garden_area": 123,
        "is_ready": True,
        "country": "India",
        "possesion_date": str(datetime.datetime.now()),
    }
)

Enums and Consts

Const(2).instance(2).validate()  # won't raise error

try:
    Const(2).instance(3).validate()  # raises error
except ValidationError:
    assert True

assert Enum([1, 2, 3]).instance(3).errors == []  # no error

# Raises error
try:
    Enum([1, 2, "Three"])(5).validate()
except ValidationError:
    assert True

Construct instance from document/schema

HOUSE_DATA_VALID = json.dumps(
    {
        "seller": {
            "age": 22,
            "emails": ["test@test.com", "test2@test.com"],
            "name": "nikhil",
            "gender": "MALE",
            "contact": "1234567",
            "date-of-birth": "1978-09-04",
        },
        "address": [120, "Flat A", "Sarang"],
        "area": 1234,
        "sqtft_rate": 2000,
        "garden_area": 123,
        "is_ready": True,
        "country": "India",
        "possesion_date": "2020-02-05",  # str(datetime.datetime.now()),
    }
)

h = House.from_json(HOUSE_DATA_VALID)
h.validate(check_formats=True)

Factory-boy integration

from demos import Person, Owner, House, Broker, Gender, List, Schema
from jsonene.factories import SchemaFactory, ListSchemaFactory
from factory import SubFactory, fuzzy, Sequence, Iterator, LazyAttribute
import string
import datetime
import pytz

st_date = pytz.utc.localize(datetime.datetime.now())
end_date = st_date + datetime.timedelta(days=7)


class EmailsFactory(ListSchemaFactory):
    email = LazyAttribute(lambda o: f"{o.factory_parent.name}@example.org")

    class Meta:
        model = List


class PersonFactory(SchemaFactory):
    name = fuzzy.FuzzyText()
    gender = fuzzy.FuzzyChoice([e.value for e in Gender])
    emails = SubFactory(EmailsFactory)
    contact = fuzzy.FuzzyText(chars=[str(n) for n in range(10)])
    age = fuzzy.FuzzyInteger(low=0, high=100)
    date_of_birth = fuzzy.FuzzyDateTime(st_date, end_dt=end_date)

    class Meta:
        model = Person


class OwnerFactory(PersonFactory):
    class Meta:
        model = Owner


class AddressFactory(ListSchemaFactory):
    house_no = fuzzy.FuzzyInteger(low=1, high=100)
    street_address = fuzzy.FuzzyText(suffix=" road")
    area = fuzzy.FuzzyText()

    class Meta:
        model = List


class HouseFactory(SchemaFactory):
    seller = SubFactory(OwnerFactory)
    address = SubFactory(AddressFactory)
    is_ready = fuzzy.FuzzyChoice([True, False])
    area = fuzzy.FuzzyFloat(low=400, high=3000, precision=2)
    country = "India"
    garden_area = fuzzy.FuzzyFloat(low=400, high=3000, precision=2)
    sqtft_rate = fuzzy.FuzzyFloat(low=0, high=50000, precision=2)
    possesion_date = fuzzy.FuzzyDateTime(st_date, end_dt=end_date)

    class Meta:
        model = House


house = HouseFactory.create()
house.validate(check_formats=True)
assert isinstance(house.seller, Schema.Instance)

house2 = HouseFactory.create()
del house2.seller
assert house2.errors == ["'seller' is a required property"]

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