"ttl_field": "ttl"

message SegmentInfo {
  int64 ID = 1;
  int64 collectionID = 2;
  int64 partitionID = 3;
  string insert_channel = 4;
  int64 num_of_rows = 5;
  common.SegmentState state = 6;
  int64 max_row_num = 7 [deprecated = true]; // deprecated, we use the binary size to control the segment size but not a estimate rows.
  uint64 last_expire_time = 8;
  msg.MsgPosition start_position = 9;
  msg.MsgPosition dml_position = 10;
  // binlogs consist of insert binlogs
  repeated FieldBinlog binlogs = 11;
  repeated FieldBinlog statslogs = 12;
  // deltalogs consists of delete binlogs. FieldID is not used yet since delete is always applied on primary key
  repeated FieldBinlog deltalogs = 13;
  bool createdByCompaction = 14;
  repeated int64 compactionFrom = 15;
  uint64 dropped_at = 16; // timestamp when segment marked drop
  // A flag indicating if:
  // (1) this segment is created by bulk insert, and
  // (2) the bulk insert task that creates this segment has not yet reached `ImportCompleted` state.
  bool is_importing = 17;
  bool is_fake = 18;

  // denote if this segment is compacted to other segment.
  // For compatibility reasons, this flag of an old compacted segment may still be False.
  // As for new fields added in the message, they will be populated with their respective field types' default values.
  bool compacted = 19;

  // Segment level, indicating compaction segment level
  // Available value: Legacy, L0, L1, L2
  // For legacy level, it represent old segment before segment level introduced
  // so segments with Legacy level shall be treated as L1 segment
  SegmentLevel level = 20;
  int64 storage_version = 21;

  int64 partition_stats_version = 22;
  // use in major compaction, if compaction fail, should revert segment level to last value
  SegmentLevel last_level = 23;
  // use in major compaction, if compaction fail, should revert partition stats version to last value 
  int64 last_partition_stats_version = 24;

  // used to indicate whether the segment is sorted by primary key.
  bool is_sorted = 25;

  // textStatsLogs is used to record tokenization index for fields.
  map<int64, TextIndexStats> textStatsLogs = 26;
  repeated FieldBinlog bm25statslogs = 27;

  // This field is used to indicate that some intermediate state segments should not be loaded.
  // For example, segments that have been clustered but haven't undergone stats yet.
  bool is_invisible = 28;


  // jsonKeyStats is used to record json key index for fields.
  map<int64, JsonKeyStats> jsonKeyStats = 29;
    // This field is used to indicate that the segment is created by streaming service.
  // This field is meaningful only when the segment state is growing.
  // If the segment is created by streaming service, it will be a true.
  // A segment generated by datacoord of old arch, will be false.
  // After the growing segment is full managed by streamingnode, the true value can never be seen at coordinator.
  bool is_created_by_streaming = 30;
  bool is_partition_key_sorted = 31;

  // manifest_path stores the fullpath of LOON manifest file of segemnt data files.
  // we could keep the fullpath since one segment shall only have one active manifest
  // and we could keep the possiblity that manifest stores out side of collection/partition/segment path
  string manifest_path = 32;

  // expirQuantiles records the expiration timestamps of the segment
  // at the 20%, 40%, 60%, 80%, and 100% data distribution levels
  repeated int64 expirQuantiles = 33;
}

schema = client.create_schema(auto_id=False, description="test entity ttl")
schema.add_field("id", DataType.INT64, is_primary=True)
schema.add_field("ttl", DataType.TIMESTAMPTZ, nullable=True)
schema.add_field("vector", DataType.FLOAT_VECTOR, dim=dim)

prop = {"ttl_field": "ttl"}
client.create_collection(
    collection_name,
    schema=schema,
    enable_dynamic_field=True,
    properties=prop,
)

rows = [
    {"id": 0, "vector": [random.random() for _ in range(dim)], "ttl": None},
    {"id": 1, "vector": [random.random() for _ in range(dim)], "ttl": None},
    {"id": 2, "vector": [random.random() for _ in range(dim)], "ttl": None},
    {"id": 3, "vector": [random.random() for _ in range(dim)], "ttl": "2025-12-31T00:00:00Z"},
    {"id": 4, "vector": [random.random() for _ in range(dim)], "ttl": "2025-12-31T01:00:00Z"},
    {"id": 5, "vector": [random.random() for _ in range(dim)], "ttl": "2025-12-31T02:00:00Z"},
    {"id": 6, "vector": [random.random() for _ in range(dim)], "ttl": "2025-12-31T03:00:00Z"},
    {"id": 7, "vector": [random.random() for _ in range(dim)], "ttl": "2025-12-31T04:00:00Z"},
    {"id": 8, "vector": [random.random() for _ in range(dim)], "ttl": "2025-12-31T23:59:59Z"},
]

insert_result = client.insert(collection_name, rows)
client.flush(collection_name)

index_params = client.prepare_index_params()
index_params.add_index(
    field_name="vector",
    index_type="IVF_FLAT",
    index_name="vector",
    metric_type="L2",
    params={"nlist": 128},
)
client.create_index(collection_name, index_params=index_params)

client.load_collection(collection_name)

query_expr = "id > 0"
res = client.query(
    collection_name,
    query_expr,
    output_fields=["id", "ttl"],
    limit=100,
)
print(res)