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title Basic Serialization
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license Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements. See the NOTICE file distributed with this work for additional information regarding copyright ownership. The ASF licenses this file to You under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

This page covers the Python xlang quickstart. pyfory.Fory() defaults to xlang mode with compatible schema evolution; examples set xlang=True explicitly so the mode choice is visible.

Basic Object Serialization

Serialize and deserialize Python objects with a simple API:

import pyfory

fory = pyfory.Fory(xlang=True)

# Serialize xlang-compatible values
data = fory.dumps({"name": "Alice", "age": 30, "scores": [95, 87, 92]})

# Deserialize back to Python object
obj = fory.loads(data)
print(obj)  # {'name': 'Alice', 'age': 30, 'scores': [95, 87, 92]}

Note: dumps()/loads() are aliases for serialize()/deserialize(). Both APIs are identical, use whichever feels more intuitive.

Custom Class Serialization

Use dataclasses and type annotations for stable xlang payloads:

import pyfory
from dataclasses import dataclass
from typing import List, Dict

@dataclass
class Person:
    name: str
    age: pyfory.Int32
    scores: List[pyfory.Int32]
    metadata: Dict[str, str]

fory = pyfory.Fory(xlang=True, ref=True)
fory.register(Person, typename="example.Person")
person = Person("Bob", 25, [88, 92, 85], {"team": "engineering"})
data = fory.serialize(person)
result = fory.deserialize(data)
print(result)  # Person(name='Bob', age=25, ...)

Reference Tracking & Circular References

Handle repeated references safely when the payload uses xlang-compatible types:

import pyfory

f = pyfory.Fory(xlang=True, ref=True)

shared = ["shared"]
value = [shared, shared]

data = f.serialize(value)
result = f.deserialize(data)
assert result[0] is result[1]

For arbitrary Python object graphs, local classes, functions, and methods, use Native Serialization.

Performance Tips

  1. Disable ref=True if not needed: Reference tracking has overhead
  2. Use type_id instead of typename: Integer IDs are faster than string names
  3. Reuse Fory instances: Create once, use many times
  4. Enable Cython: Make sure ENABLE_FORY_CYTHON_SERIALIZATION=1
# Good: Reuse instance
fory = pyfory.Fory(xlang=True)
for obj in objects:
    data = fory.dumps(obj)

# Bad: Create new instance each time
for obj in objects:
    fory = pyfory.Fory(xlang=True)  # Wasteful!
    data = fory.dumps(obj)

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