Make And expression JSON serializable using Pydantic

pyiceberg/expressions/__init__.py

@@ -32,6 +32,8 @@
     Union,
 )
 
+from pydantic import Field
+
 from pyiceberg.expressions.literals import (
     AboveMax,
     BelowMin,
@@ -247,9 +249,10 @@ def as_bound(self) -> Type[BoundReference[L]]:
         return BoundReference[L]
 
 
-class And(BooleanExpression):
+class And(IcebergBaseModel, BooleanExpression):
     """AND operation expression - logical conjunction."""
 
+    type: str = Field(default="and", alias="type")
     left: BooleanExpression
     right: BooleanExpression
 
@@ -289,6 +292,12 @@ def __getnewargs__(self) -> Tuple[BooleanExpression, BooleanExpression]:
         """Pickle the And class."""
         return (self.left, self.right)
 
+    class Config:
+        """Pydantic configuration for And expression serialization."""
+
+        arbitrary_types_allowed = True
+        json_encoders = {BooleanExpression: lambda v: v.model_dump(by_alias=True) if isinstance(v, IcebergBaseModel) else str(v)}
+
 
 class Or(BooleanExpression):
     """OR operation expression - logical disjunction."""

tests/table/test_partitioning.py

@@ -21,6 +21,7 @@
 
 import pytest
 
+from pyiceberg.expressions import And, EqualTo
 from pyiceberg.partitioning import UNPARTITIONED_PARTITION_SPEC, PartitionField, PartitionSpec
 from pyiceberg.schema import Schema
 from pyiceberg.transforms import (
@@ -125,6 +126,13 @@ def test_serialize_partition_spec() -> None:
     )
 
 
+def test_serialize_and_expression() -> None:
+    expr = And(EqualTo("foo", 1), EqualTo("bar", 2))
+    assert expr.model_dump_json(by_alias=True) == (
+        '{"type":"and","left":{"type":"equal_to","term":"foo","literal":1},"right":{"type":"equal_to","term":"bar","literal":2}}'
+    )
+
+
 def test_deserialize_unpartition_spec() -> None:
     json_partition_spec = """{"spec-id":0,"fields":[]}"""
     spec = PartitionSpec.model_validate_json(json_partition_spec)