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Convention based, effortless serialization and deserialization

Project description

Convention Based, Effortless Serialization & Deserialization

uniserde can convert Python classes to/from JSON and BSON without effort from your side. Simply define the classes, and the library does the rest.

Define your types as classes with type annotations, and use one of uniserde's serializers / deserializers:

import uniserde
from datetime import datetime, timezone
from dataclasses import dataclass
from bson import ObjectId


@dataclass
class Person:
    id: ObjectId
    name: str
    birth_date: datetime


betty = Person(
    id=ObjectId(),
    name="Betty",
    birth_date=datetime(year=1988, month=12, day=1, tzinfo=timezone.utc),
)

serde = uniserde.JsonSerde()
print(serde.as_json(betty))

This will print a dictionary similar to this one

{
    'id': '62bc6c77792fc617c52499d0',
    'name': 'Betty',
    'birthDate': '1988-12-01T00:00:00+00:00'
}

You can easily convert this to a string using Python's built-in json module if that's what you're after.

API

The API is extremely simple. Functions/Classes you might be interested in are:

  • JsonSerde is used to serialize/deserialize Python values to/from JSON. It takes some configuration options like custom handlers for specific types.

    Use JsonSerde.as_json to serialize a Python object to JSON, and JsonSerde.from_json to deserialize a JSON object to a Python object.

  • BsonSerde is like JsonSerde, but for BSON. In addition to serialization & deserialization, it also supports MongoDB schema generation.

    Use BsonSerde.as_bson to serialize a Python object to BSON, BsonSerde.from_bson to deserialize a BSON object to a Python object, and BsonSerde.as_mongodb_schema to generate a MongoDB schema from a Python class.

  • SerdeErrro: The error raised when something goes wrong during serialization or deserialization, e.g. when a required field is missing.

  • Sometimes a class simply acts as a type-safe base, but you really just want to serialize the children of that class. In that case you can decorate the class with @as_child. This will store an additional type field in the result, so the correct child class can be instantiated when deserializing.

  • Custom serialization / deserialization can be achieved by giving custom handlers to the Serde instances or by defining the appropriate methods on your classes:

    • _uniserde_as_json_
    • _uniserde_as_bson_
    • _uniserde_from_json_
    • _uniserde_from_bson_
    • _uniserde_as_mongodb_schema_

    When called, these are passed the same parameters:

    • The JsonSerde / BsonSerde instance doing the serialization/deserialization
    • The value to be serialized/deserialized
    • As which type to serialize/deserialize the value (This is needed e.g. for generics, that may not know the type of all of their child attributes).

    (_uniserde_as_monogodb_schema_ only receives the Serde instance and the type, since there is no value to process.)

  • The library also exposes a couple handy type definitions:

    • Jsonable, Bsonable -- Any type which can occur in a JSON / BSON file respectively, i.e. (bool, int, float, ...)
    • JsonDoc, BsonDoc -- A dictionary mapping strings to Jsonables / Bsonable

JSON Conventions

Python JSON Notes
bool bool
int float
float float
str str
tuple list
list list
set list
Optional value or None
Any as-is The value is kept unchanged, without any checks.
Literal[str] str
enum.Enum str Enum values are mapped to their name (NOT value!)
enum.Flag list[str] Each flag is encoded the same way a regular enum.Enum value would.
custom class dict Each attribute is stored as key, in lowerCamelCase. If marked with as_child, an additional type field is added.
bytes str base64 encoded
datetime.datetime str as ISO 8601 - with timezone. Naïve datetimes are intentionally not supported. Do yourself a favor and don't use them.
datetime.timedelta float duration, in seconds
dict[str, ...] dict
bson.ObjectId str
pathlib.Path str Paths are made absolute before serialization.
uuid.UUID str

BSON Conventions

BSON mostly uses the same conventions as JSON, with just a few changes:

Python BSON Notes
custom class dict Same as JSON, but any fields named id are renamed to _id to match MongoDB.
bytes bytes
datetime.datetime datetime.datetime Serialization requires a timezone be set. Deserialization imputes UTC, to match MongoDB.
bson.ObjectId bson.ObjectId
uuid.UUID uuid.UUID

In addition, BSON serialization/deserialization will rename any fields named id to _id. This way they match MongoDB's expectations and can be used as primary keys.

MongoDB Schema Generation

If you are working with MongoDB you will come to appreciate the automatic schema generation. Calling uniserde.as_mongodb_schema on any supported class will return a MongoDB compatible JSON schema without hassle.

For example, here's the result of uniserde.as_mongodb_schema(Person) with the Person class above:

{
    'type': 'object',
    'properties': {
        '_id': {
            'bsonType': 'objectId'
        },
        'name': {
            'type': 'string'
        },
        'birthDate': {
            'bsonType': 'date'
        }
    },
    'additionalProperties': False,
    'required': [
        '_id',
        'name',
        'birthDate'
    ]
}

Lazy Deserialization

Normally, serialization happens all at once: You tell uniserde to create a class instance from a JSON, uniserde processes all of the fields and returns the finished class.

This works great, but can be wasteful if you are working with large documents and only need to access few fields. To help with this, you can pass lazy=True when deserializing any object. uniserde will then hold off deserializing fields until they are accessed for the first time, saving precious processing time.

A word of caution: Data is validated as it is deserialized. Since lazy deserialization defers work until the data is accessed, this means any data you don't access also won't be validated. Thus, lazy serialization can be a very powerful tool for speeding up interactions with large objects, but you should only use when you are absolutely certain the data is correct. (For example because you have just fetched the object from your own, trusted, database.)

Maximizing performance

Whenever uniserde needs to serialize a type, it builds a handler specifically for that type. That handler is then cached in the active Serde instance, so that any future serialization / deserialization of that type is much faster. Thus, to get maximum performance, you can create one global Serde instance configure it to your liking then reuse it every time you need one.

Limitations

  • Recursive types are not supported
  • Support for Union is currently very limited. Really only Optional is supported (which Python internally maps to Union)
  • Literal currently only supports strings
  • Examples for custom serialization / deserialization
  • Extend as_child, to allow marking some classes as abstract. i.e. their parents/children can be serialized, but not those classes themselves
  • Being able to specify additional limitations to fields would be nice:
    • must match regex
    • minimum / maximum
    • custom validation functions
  • more Unit tests (custom de-serializers!?)
  • Add more examples to the README
    • show custom serializers/deserializers
    • recommended usage
  • calling uniserde.serialize on non-classes causes problems, because the serialization as_type is guessed incorrectly. e.g. [1, 2, 3] will be incorrectly serialized as list rather than list[int].

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