Extensible JSON module to serialize all objects.
Project description
JSON* is an extensible json module to serialize all objects!
jsonstar
extends Python's standard JSON encoder and decoder to easily handle your custom types.
This means you won't have to transform your custom types into dictionaries with primitive types before encoding them to JSON. And you won't have to parse back the encoded strings into your custom types after decoding them from JSON.
How to install it?
pip install jsonstar
How to start using it?
The jsonstar
module provides the same API as the standard json
module, so you can use it as a drop in replacement.
Simply change your import from import json
to import jsonstar as json
and you're good to go.
Why use it?
Consider you have a pydantic Employee
class that you want to serialize to JSON.
from decimal import Decimal
from datetime import date
from pydantic import BaseModel
class Employee(BaseModel):
name: str
salary: Decimal
birthday: date
roles: set
employee = Employee(
name="John Doe",
salary=Decimal("1000.00"),
birthday=date(1990, 1, 1),
roles={"A", "B", "C"},
)
The standard json
module can't serialize the employee
instance, requiring you to call its dict
method.
This will not sufice, because the standard json
module don't know how to encode Decimal
, date
and set
.
Your solution would include some trasnfomation of the employee
instance and its attributes before encoding it to JSON.
That is where jsonstar
shines by providing default encoder for common types like pydantic.BaseModel
,
decimal.Decimal
, datetime.date
and set
. And allowing you to easily add your own encoders.
from jsonstar as json
print(json.dumps(employee))
# {"name": "John Doe", "salary": "1000.00", "birthday": "1990-01-01", "roles": ["A", "B", "C"]}
What default encoders are provided?
By default, jsonstar
provides encoders for the following types:
attrs
classesdataclasses.dataclass
classesdatetime.date
datetime.datetime
datetime.time
datetime.timedelta
decimal.Decimal
frozenset
pydantic.BaseModel
set
uuid.UUID
Configurable default encoders
For some complex types like Django Models, an opinionated default encoder would not work for everyone.
This is why instead of providing a default encoder for Django Models, jsonstar
provides you a configurable
encoder class to allow you to define the desired encoding behavior.
import jsonstar as json
from jsonstar import DjangoModelEncoder
json.register_default_encoder(Model, DjangoModelEncoder(exclude=[DjangoModelEncoder.RELATIONSHIPS]))
The above code will register a default encoder for the Model
class that will return all fields, excluding
relationships.
Can jsonstar
add more default encoders?
Yes. If you think that a default encoder for a common type is missing, please open an issue or a pull request. See the How to contribute section for more details.
How do I add my own encoder?
First you need to decide if you want your encoder to be available everywhere on your project or just for a specific code block.
- Default encoders are globally available and will be used anywhere in your project.
- Instance encoders are available only for the
JSONEncoderStar
instance that you register them.
Also you have two types of encoders to choose from:
- Typed encoders are used to encode a specific type identified by
isinstance
. - Functional encoders are used to encode an object based on arbitraty logic.
How to add a default encoder?
To add a default encoder use the register_default_encoder
function on the jsonstar
module.
import jsonstar as json
from decimal import Decimal
def two_decimals_encoder(obj):
"""Encodes a decimal with only two decimal places."""
return str(obj.quantize(Decimal("1.00")))
json.register_default_encoder(Decimal, two_decimals_encoder)
How to add an instance encoder?
An instance encoder can be added in three ways:
- Using the
register
method on theJSONEncoderStar
instance. - Passing the encoder to the
JSONEncoderStar
initialization. - Passing the encoder to the
dumps
function.
import jsonstar as json
from decimal import Decimal
def two_decimals_encoder(obj):
"""Encodes a decimal with only two decimal places."""
return str(obj.quantize(Decimal("1.00")))
# 1. Using the `register` method on the `JSONEncoderStar` instance.
encoder1 = json.JSONEncoderStar()
encoder1.register(two_decimals_encoder, Decimal)
# 2. Passing the encoder to the `JSONEncoderStar` initialization.
encoder2 = json.JSONEncoderStar(typed_encoders={Decimal: two_decimals_encoder})
# 3. Passing the encoder to the `dumps` function.
print(json.dumps(data, cls={Decimal: two_decimas_encoder}))
How to add a typed encoder?
Typed encoders are specific to a type and it's inherited types.
When registering a typed encoder, you simply pass the encoder and the type to the chosen registration method.
When you add a typed encoder, jsonstar
will check if any base class already has a registered encoder make sure the
more generic encoder is used last, respecting Python's Method Resolution Order (MRO).
How to add a functional encoder?
Functional encoders are used to encode an object based on arbitraty logic and not specific to a type.
To register a functional encoder, you simply pass the encoder to the chosen registration method omiting the type.
All functional encoders are called only for objects that do not have a registered typed encoder.
Contributing
Pull requests are welcome and must have associated tests.
For major changes, please open an issue first to discuss what you would like to change.
License
Author
Henrique Bastos henrique@bastos.net
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