Cyclic references
As described in the cyclic references section, Pydantic detects cyclic
references in validation inputs and raises a ValidationError with the recursion_loop
error type, rather than a RecursionError. The same applies during serialization, where a ValueError is raised.
This example shows how these errors can be caught in validators and serializers to drop the cyclic references and still produce a result.
Because this ValidationError is raised without actually exceeding the maximum
recursion depth, you can catch and handle it without needing to worry about the limited remaining recursion depth:
from __future__ import annotations
from collections.abc import Generator
from contextlib import contextmanager
from dataclasses import field
from pydantic import BaseModel, ValidationError, field_validator
def is_recursion_validation_error(exc: ValidationError) -> bool:
errors = exc.errors()
return len(errors) == 1 and errors[0]['type'] == 'recursion_loop'
@contextmanager
def suppress_recursion_validation_error() -> Generator[None]:
try:
yield
except ValidationError as exc:
if not is_recursion_validation_error(exc):
raise exc
class Node(BaseModel):
id: int
children: list[Node] = field(default_factory=list)
@field_validator('children', mode='wrap')
@classmethod
def drop_cyclic_references(cls, children, h):
try:
return h(children)
except ValidationError as exc:
if not (
is_recursion_validation_error(exc)
and isinstance(children, list)
):
raise exc
value_without_cyclic_refs = []
for child in children:
with suppress_recursion_validation_error():
value_without_cyclic_refs.extend(h([child]))
return h(value_without_cyclic_refs)
# Create data with cyclic references representing the graph 1 -> 2 -> 3 -> 1
node_data = {'id': 1, 'children': [{'id': 2, 'children': [{'id': 3}]}]}
node_data['children'][0]['children'][0]['children'] = [node_data]
print(Node.model_validate(node_data))
#> id=1 children=[Node(id=2, children=[Node(id=3, children=[])])]
Similarly, if Pydantic encounters a recursive reference during serialization, rather than waiting
for the maximum recursion depth to be exceeded, a ValueError is raised immediately:
from pydantic import TypeAdapter
# Create data with cyclic references representing the graph 1 -> 2 -> 3 -> 1
node_data = {'id': 1, 'children': [{'id': 2, 'children': [{'id': 3}]}]}
node_data['children'][0]['children'][0]['children'] = [node_data]
try:
# Try serializing the circular reference as JSON
TypeAdapter(dict).dump_json(node_data)
except ValueError as exc:
print(exc)
"""
Error serializing to JSON: ValueError: Circular reference detected (id repeated)
"""
This can also be handled if desired:
from dataclasses import field
from typing import Any
from pydantic import (
SerializerFunctionWrapHandler,
TypeAdapter,
field_serializer,
)
from pydantic.dataclasses import dataclass
@dataclass
class NodeReference:
id: int
@dataclass
class Node(NodeReference):
children: list['Node'] = field(default_factory=list)
@field_serializer('children', mode='wrap')
def serialize(
self, children: list['Node'], handler: SerializerFunctionWrapHandler
) -> Any:
"""
Serialize a list of nodes, handling circular references by excluding the children.
"""
try:
return handler(children)
except ValueError as exc:
if not str(exc).startswith('Circular reference'):
raise exc
result = []
for node in children:
try:
serialized = handler([node])
except ValueError as exc:
if not str(exc).startswith('Circular reference'):
raise exc
result.append({'id': node.id})
else:
result.append(serialized)
return result
# Create a cyclic graph:
nodes = [Node(id=1), Node(id=2), Node(id=3)]
nodes[0].children.append(nodes[1])
nodes[1].children.append(nodes[2])
nodes[2].children.append(nodes[0])
print(nodes[0])
#> Node(id=1, children=[Node(id=2, children=[Node(id=3, children=[...])])])
# Serialize the cyclic graph:
print(TypeAdapter(Node).dump_python(nodes[0]))
"""
{
'id': 1,
'children': [{'id': 2, 'children': [{'id': 3, 'children': [{'id': 1}]}]}],
}
"""