Cross-Language Serialization

pyfory supports cross-language object graph serialization, allowing you to serialize data in Python and deserialize it in Java, Go, Rust, or other supported languages.

Enable Cross-Language Mode

To use xlang mode, create Fory with xlang=True:

import pyfory
fory = pyfory.Fory(xlang=True, ref=False, strict=True)

Cross-Language Example

Python (Serializer)

import pyfory
from dataclasses import dataclass

# Cross-language mode for interoperability
f = pyfory.Fory(xlang=True, ref=True)

# Register type for cross-language compatibility
@dataclass
class Person:
    name: str
    age: pyfory.int32

f.register(Person, typename="example.Person")

person = Person("Charlie", 35)
binary_data = f.serialize(person)
# binary_data can now be sent to Java, Go, etc.

Java (Deserializer)

import org.apache.fory.*;

public class Person {
    public String name;
    public int age;
}

Fory fory = Fory.builder()
    .withLanguage(Language.XLANG)
    .withRefTracking(true)
    .build();

fory.register(Person.class, "example.Person");
Person person = (Person) fory.deserialize(binaryData);

Rust (Deserializer)

use fory::Fory;
use fory::ForyObject;

#[derive(ForyObject)]
struct Person {
    name: String,
    age: i32,
}

let mut fory = Fory::default()
    .compatible(true)
    .xlang(true);

fory.register_by_namespace::<Person>("example", "Person");
let person: Person = fory.deserialize(&binary_data)?;

Type Annotations for Cross-Language

Use pyfory type annotations for explicit cross-language type mapping:

from dataclasses import dataclass
import pyfory

@dataclass
class TypedData:
    int_value: pyfory.int32      # 32-bit integer
    long_value: pyfory.int64     # 64-bit integer
    float_value: pyfory.float32  # 32-bit float
    double_value: pyfory.float64 # 64-bit float

Type Mapping

Python	Java	Rust	Go
str	String	String	string
int	long	i64	int64
pyfory.int32	int	i32	int32
pyfory.int64	long	i64	int64
float	double	f64	float64
pyfory.float32	float	f32	float32
list	List	Vec	[]T
dict	Map	HashMap	map[K]V

Differences from Python Native Mode

The binary protocol and API are similar to pyfory's python-native mode, but Python-native mode can serialize any Python object—including global functions, local functions, lambdas, local classes, and types with customized serialization using __getstate__/__reduce__/__reduce_ex__, which are not allowed in xlang mode.

See Also

• Cross-Language Serialization Specification
• Type Mapping Reference
• Java Cross-Language Guide
• Rust Cross-Language Guide

Related Topics

• Configuration - XLANG mode settings
• Schema Evolution - Compatible mode
• Type Registration - Registration patterns