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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>
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‎docs/getting-started/concepts/feast-types.md‎

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@@ -5,7 +5,7 @@ To make this possible, Feast itself has a type system for all the types it is ab
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Feast's type system is built on top of [protobuf](https://github.com/protocolbuffers/protobuf). The messages that make up the type system can be found [here](https://github.com/feast-dev/feast/blob/master/protos/feast/types/Value.proto), and the corresponding python classes that wrap them can be found [here](https://github.com/feast-dev/feast/blob/master/sdk/python/feast/types.py).
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Feast supports primitive data types (numerical values, strings, bytes, booleans and timestamps). The only complex data type Feast supports is Arrays, and arrays cannot contain other arrays.
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Feast supports primitive data types (numerical values, strings, bytes, booleans, timestamps, and UUIDs). Feast also supports complex data types: Arrays, Sets, and Maps. Arrays and Sets cannot contain other Arrays or Sets. For a complete reference of all supported types, see the [Type System reference](../../reference/type-system.md).
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Each feature or schema field in Feast is associated with a data type, which is stored in Feast's [registry](registry.md). These types are also used to ensure that Feast operates on values correctly (e.g. making sure that timestamp columns used for [point-in-time correct joins](point-in-time-joins.md) actually have the timestamp type).
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‎docs/reference/type-system.md‎

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@@ -24,6 +24,8 @@ Feast supports the following data types:
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| `Bytes` | `bytes` | Binary data |
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| `Bool` | `bool` | Boolean value |
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| `UnixTimestamp` | `datetime` | Unix timestamp (nullable) |
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| `Uuid` | `uuid.UUID` | UUID (any version) |
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| `TimeUuid` | `uuid.UUID` | Time-based UUID (version 1) |
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### Array Types
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@@ -39,6 +41,8 @@ All primitive types have corresponding array (list) types:
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| `Array(Bytes)` | `List[bytes]` | List of binary data |
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| `Array(Bool)` | `List[bool]` | List of booleans |
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| `Array(UnixTimestamp)` | `List[datetime]` | List of timestamps |
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| `Array(Uuid)` | `List[uuid.UUID]` | List of UUIDs |
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| `Array(TimeUuid)` | `List[uuid.UUID]` | List of time-based UUIDs |
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### Set Types
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@@ -54,6 +58,8 @@ All primitive types (except Map) have corresponding set types for storing unique
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| `Set(Bytes)` | `Set[bytes]` | Set of unique binary data |
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| `Set(Bool)` | `Set[bool]` | Set of unique booleans |
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| `Set(UnixTimestamp)` | `Set[datetime]` | Set of unique timestamps |
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| `Set(Uuid)` | `Set[uuid.UUID]` | Set of unique UUIDs |
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| `Set(TimeUuid)` | `Set[uuid.UUID]` | Set of unique time-based UUIDs |
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**Note:** Set types automatically remove duplicate values. When converting from lists or other iterables to sets, duplicates are eliminated.
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@@ -77,7 +83,7 @@ from datetime import timedelta
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from feast import Entity, FeatureView, Field, FileSource
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from feast.types import (
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Int32, Int64, Float32, Float64, String, Bytes, Bool, UnixTimestamp,
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Array, Set, Map
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Uuid, TimeUuid, Array, Set, Map
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)
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# Define a data source
@@ -107,7 +113,9 @@ user_features = FeatureView(
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Field(name="profile_picture", dtype=Bytes),
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Field(name="is_active", dtype=Bool),
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Field(name="last_login", dtype=UnixTimestamp),
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Field(name="session_id", dtype=Uuid),
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Field(name="event_id", dtype=TimeUuid),
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# Array types
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Field(name="daily_steps", dtype=Array(Int32)),
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Field(name="transaction_history", dtype=Array(Int64)),
@@ -117,13 +125,17 @@ user_features = FeatureView(
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Field(name="document_hashes", dtype=Array(Bytes)),
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Field(name="notification_settings", dtype=Array(Bool)),
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Field(name="login_timestamps", dtype=Array(UnixTimestamp)),
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Field(name="related_session_ids", dtype=Array(Uuid)),
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Field(name="event_chain", dtype=Array(TimeUuid)),
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# Set types (unique values only)
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Field(name="visited_pages", dtype=Set(String)),
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Field(name="unique_categories", dtype=Set(Int32)),
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Field(name="tag_ids", dtype=Set(Int64)),
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Field(name="preferred_languages", dtype=Set(String)),
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Field(name="unique_device_ids", dtype=Set(Uuid)),
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Field(name="unique_event_ids", dtype=Set(TimeUuid)),
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# Map types
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Field(name="user_preferences", dtype=Map),
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Field(name="metadata", dtype=Map),
@@ -151,6 +163,34 @@ tag_list = [100, 200, 300, 100, 200]
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tag_ids = set(tag_list) # {100, 200, 300}
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```
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### UUID Type Usage Examples
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UUID types store universally unique identifiers natively, with support for both random UUIDs and time-based UUIDs:
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```python
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import uuid
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# Random UUID (version 4) — use Uuid type
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session_id = uuid.uuid4() # e.g., UUID('a8098c1a-f86e-11da-bd1a-00112444be1e')
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# Time-based UUID (version 1) — use TimeUuid type
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event_id = uuid.uuid1() # e.g., UUID('6ba7b810-9dad-11d1-80b4-00c04fd430c8')
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# UUID values are returned as uuid.UUID objects from get_online_features()
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response = store.get_online_features(
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features=["user_features:session_id"],
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entity_rows=[{"user_id": 1}],
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)
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result = response.to_dict()
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# result["session_id"][0] is a uuid.UUID object
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# UUID lists
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related_sessions = [uuid.uuid4(), uuid.uuid4(), uuid.uuid4()]
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# UUID sets (unique values)
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unique_devices = {uuid.uuid4(), uuid.uuid4()}
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```
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### Map Type Usage Examples
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Maps can store complex nested data structures:

‎protos/feast/types/Value.proto‎

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@@ -57,6 +57,8 @@ message ValueType {
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TIME_UUID = 31;
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UUID_LIST = 32;
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TIME_UUID_LIST = 33;
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UUID_SET = 34;
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TIME_UUID_SET = 35;
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}
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}
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string time_uuid_val = 31;
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StringList uuid_list_val = 32;
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StringList time_uuid_list_val = 33;
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StringSet uuid_set_val = 34;
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StringSet time_uuid_set_val = 35;
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}
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}
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‎sdk/python/feast/infra/online_stores/remote.py‎

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

‎sdk/python/feast/on_demand_feature_view.py‎

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@@ -1108,6 +1108,9 @@ def _get_sample_values_by_type(self) -> dict[ValueType, list[Any]]:
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ValueType.UNIX_TIMESTAMP_LIST: [[_utc_now()]],
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ValueType.UUID_LIST: [[uuid.uuid4(), uuid.uuid4()]],
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ValueType.TIME_UUID_LIST: [[uuid.uuid1(), uuid.uuid1()]],
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# Set types
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ValueType.UUID_SET: [{uuid.uuid4(), uuid.uuid4()}],
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ValueType.TIME_UUID_SET: [{uuid.uuid1(), uuid.uuid1()}],
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}
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@staticmethod

‎sdk/python/feast/online_response.py‎

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

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