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Version: 0.14

Basic Serialization

This page covers basic serialization patterns in pyfory.

Basic Object Serialization​

Serialize and deserialize Python objects with a simple API:

import pyfory

# Create Fory instance
fory = pyfory.Fory(xlang=True)

# Serialize any Python object
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​

Fory automatically handles dataclasses and custom types:

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

@dataclass
class Person:
    name: str
    age: int
    scores: List[int]
    metadata: Dict[str, str]

# Python mode - supports all Python types including dataclasses
fory = pyfory.Fory(xlang=False, ref=True)
fory.register(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 shared references and circular dependencies safely:

import pyfory

f = pyfory.Fory(ref=True)  # Enable reference tracking

# Handle circular references safely
class Node:
    def __init__(self, value):
        self.value = value
        self.children = []
        self.parent = None

root = Node("root")
child = Node("child")
child.parent = root  # Circular reference
root.children.append(child)

# Serializes without infinite recursion
data = f.serialize(root)
result = f.deserialize(data)
assert result.children[0].parent is result  # Reference preserved

API Reference​

Serialization Methods​

# Serialize to bytes
data: bytes = fory.serialize(obj)
data: bytes = fory.dumps(obj)  # Alias

# Deserialize from bytes
obj = fory.deserialize(data)
obj = fory.loads(data)  # Alias

With Out-of-Band Buffers​

# Serialize with buffer callback
buffer_objects = []
data = fory.serialize(obj, buffer_callback=buffer_objects.append)

# Deserialize with buffers
buffers = [obj.getbuffer() for obj in buffer_objects]
obj = fory.deserialize(data, buffers=buffers)

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()
for obj in objects:
    data = fory.dumps(obj)

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