feat: Add UUID_SET/TIME_UUID_SET support and update type system docs

Add Set(Uuid) and Set(TimeUuid) as feature types with full roundtrip support, backward compatibility, and documentation for all UUID types. Signed-off-by: soojin <soojin@dable.io> Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
feast-dev · ntkathole · Apr 1, 2026 · Feb 8, 2026 · Feb 8, 2026 · Feb 8, 2026
commit fe0bfb209de46b7d6d924b4a29fcf2fdae839257
@@ -9,7 +9,8 @@ Feast supports the following categories of data types:
 
 - **Primitive types**: numerical values (`Int32`, `Int64`, `Float32`, `Float64`), `String`, `Bytes`, `Bool`, and `UnixTimestamp`.
 - **Domain-specific primitives**: `PdfBytes` (PDF binary data for RAG/document pipelines) and `ImageBytes` (image binary data for multimodal pipelines). These are semantic aliases over `Bytes` and must be explicitly declared in schema — no backend infers them.
-- **Array types**: ordered lists of any primitive type, e.g. `Array(Int64)`, `Array(String)`.
+- **UUID types**: `Uuid` and `TimeUuid` for universally unique identifiers. Stored as strings at the proto level but deserialized to `uuid.UUID` objects in Python.
+- **Array types**: ordered lists of any primitive type, e.g. `Array(Int64)`, `Array(String)`, `Array(Uuid)`.
 - **Set types**: unordered collections of unique values for any primitive type, e.g. `Set(String)`, `Set(Int64)`. Set types are not inferred by any backend and must be explicitly declared. They are best suited for online serving use cases.
 - **Map types**: dictionary-like structures with string keys and values that can be any supported Feast type (including nested maps), e.g. `Map`, `Array(Map)`.
 - **JSON type**: opaque JSON data stored as a string at the proto level but semantically distinct from `String` — backends use native JSON types (`jsonb`, `VARIANT`, etc.), e.g. `Json`, `Array(Json)`.

@@ -24,6 +24,8 @@ Feast supports the following data types:
 | `Bytes` | `bytes` | Binary data |
 | `Bool` | `bool` | Boolean value |
 | `UnixTimestamp` | `datetime` | Unix timestamp (nullable) |
+| `Uuid` | `uuid.UUID` | UUID (any version) |
+| `TimeUuid` | `uuid.UUID` | Time-based UUID (version 1) |
 
 ### Domain-Specific Primitive Types
 
@@ -52,6 +54,8 @@ All primitive types have corresponding array (list) types:
 | `Array(Bytes)` | `List[bytes]` | List of binary data |
 | `Array(Bool)` | `List[bool]` | List of booleans |
 | `Array(UnixTimestamp)` | `List[datetime]` | List of timestamps |
+| `Array(Uuid)` | `List[uuid.UUID]` | List of UUIDs |
+| `Array(TimeUuid)` | `List[uuid.UUID]` | List of time-based UUIDs |
 
 ### Set Types
 
@@ -67,6 +71,8 @@ All primitive types (except `Map` and `Json`) have corresponding set types for s
 | `Set(Bytes)` | `Set[bytes]` | Set of unique binary data |
 | `Set(Bool)` | `Set[bool]` | Set of unique booleans |
 | `Set(UnixTimestamp)` | `Set[datetime]` | Set of unique timestamps |
+| `Set(Uuid)` | `Set[uuid.UUID]` | Set of unique UUIDs |
+| `Set(TimeUuid)` | `Set[uuid.UUID]` | Set of unique time-based UUIDs |
 
 **Note:** Set types automatically remove duplicate values. When converting from lists or other iterables to sets, duplicates are eliminated.
 
@@ -169,7 +175,7 @@ from datetime import timedelta
 from feast import Entity, FeatureView, Field, FileSource
 from feast.types import (
     Int32, Int64, Float32, Float64, String, Bytes, Bool, UnixTimestamp,
-    Array, Set, Map, Json, Struct
+    Uuid, TimeUuid, Array, Set, Map, Json, Struct
 )
 
 # Define a data source
@@ -199,6 +205,8 @@ user_features = FeatureView(
         Field(name="profile_picture", dtype=Bytes),
         Field(name="is_active", dtype=Bool),
         Field(name="last_login", dtype=UnixTimestamp),
+        Field(name="session_id", dtype=Uuid),
+        Field(name="event_id", dtype=TimeUuid),
 
         # Array types
         Field(name="daily_steps", dtype=Array(Int32)),
@@ -209,12 +217,16 @@ user_features = FeatureView(
         Field(name="document_hashes", dtype=Array(Bytes)),
         Field(name="notification_settings", dtype=Array(Bool)),
         Field(name="login_timestamps", dtype=Array(UnixTimestamp)),
+        Field(name="related_session_ids", dtype=Array(Uuid)),
+        Field(name="event_chain", dtype=Array(TimeUuid)),
 
         # Set types (unique values only — see backend caveats above)
         Field(name="visited_pages", dtype=Set(String)),
         Field(name="unique_categories", dtype=Set(Int32)),
         Field(name="tag_ids", dtype=Set(Int64)),
         Field(name="preferred_languages", dtype=Set(String)),
+        Field(name="unique_device_ids", dtype=Set(Uuid)),
+        Field(name="unique_event_ids", dtype=Set(TimeUuid)),
 
         # Map types
         Field(name="user_preferences", dtype=Map),
@@ -250,6 +262,34 @@ tag_list = [100, 200, 300, 100, 200]
 tag_ids = set(tag_list)  # {100, 200, 300}
 ```
 
+### UUID Type Usage Examples
+
+UUID types store universally unique identifiers natively, with support for both random UUIDs and time-based UUIDs:
+
+```python
+import uuid
+
+# Random UUID (version 4) — use Uuid type
+session_id = uuid.uuid4()  # e.g., UUID('a8098c1a-f86e-11da-bd1a-00112444be1e')
+
+# Time-based UUID (version 1) — use TimeUuid type
+event_id = uuid.uuid1()  # e.g., UUID('6ba7b810-9dad-11d1-80b4-00c04fd430c8')
+
+# UUID values are returned as uuid.UUID objects from get_online_features()
+response = store.get_online_features(
+    features=["user_features:session_id"],
+    entity_rows=[{"user_id": 1}],
+)
+result = response.to_dict()
+# result["session_id"][0] is a uuid.UUID object
+
+# UUID lists
+related_sessions = [uuid.uuid4(), uuid.uuid4(), uuid.uuid4()]
+
+# UUID sets (unique values)
+unique_devices = {uuid.uuid4(), uuid.uuid4()}
+```
+
 ### Map Type Usage Examples
 
 Maps can store complex nested data structures:

@@ -61,6 +61,8 @@ message ValueType {
     TIME_UUID = 37;
     UUID_LIST = 38;
     TIME_UUID_LIST = 39;
+    UUID_SET = 40;
+    TIME_UUID_SET = 41;
   }
 }
 
@@ -104,6 +106,8 @@ message Value {
     string time_uuid_val = 37;
     StringList uuid_list_val = 38;
     StringList time_uuid_list_val = 39;
+    StringSet uuid_set_val = 40;
+    StringSet time_uuid_set_val = 41;
   }
 }
 

@@ -40,9 +40,11 @@
 
 
 def _json_safe(val: Any) -> Any:
-    """Convert uuid.UUID objects to strings for JSON serialization."""
+    """Convert uuid.UUID objects and sets to JSON-serializable form."""
     if isinstance(val, uuid_module.UUID):
         return str(val)
+    if isinstance(val, set):
+        return [str(v) if isinstance(v, uuid_module.UUID) else v for v in val]
     if isinstance(val, list):
         return [str(v) if isinstance(v, uuid_module.UUID) else v for v in val]
     return val

@@ -1177,6 +1177,9 @@ def _get_sample_values_by_type(self) -> dict[ValueType, list[Any]]:
             ValueType.UNIX_TIMESTAMP_LIST: [[_utc_now()]],
             ValueType.UUID_LIST: [[uuid.uuid4(), uuid.uuid4()]],
             ValueType.TIME_UUID_LIST: [[uuid.uuid1(), uuid.uuid1()]],
+            # Set types
+            ValueType.UUID_SET: [{uuid.uuid4(), uuid.uuid4()}],
+            ValueType.TIME_UUID_SET: [{uuid.uuid1(), uuid.uuid1()}],
         }
 
     @staticmethod

@@ -122,6 +122,14 @@ def to_arrow(self, include_event_timestamps: bool = False) -> pa.Table:
                         else v
                         for v in values
                     ]
+            elif isinstance(first_valid, set):
+                inner = next((e for e in first_valid if e is not None), None)
+                if isinstance(inner, uuid_module.UUID):
+                    result[key] = [
+                        [str(e) for e in v] if isinstance(v, set) else v for v in values
+                    ]
+                else:
+                    result[key] = [list(v) if isinstance(v, set) else v for v in values]
         return pa.Table.from_pydict(result)
 
     def to_tensor(