docs/guide/python/basic-serialization.md

---
title: Basic Serialization
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id: basic_serialization
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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:

```python
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:

```python
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, name="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:

```python
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](native-serialization.md).

## Performance Tips

1. **Disable `ref=True` if not needed**: Reference tracking has overhead
2. **Use type_id instead of name**: 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`

```python
# 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)
```

## Related Topics

- [Configuration](configuration.md) - Fory parameters
- [Type Registration](type-registration.md) - Registration patterns
- [Native Serialization](native-serialization.md) - Functions and lambdas
- [Out-of-Band Serialization](out-of-band.md) - Buffer callback APIs