✨ Added additional result refinement terms to get_runs

CHANGELOG.md

@@ -2,7 +2,8 @@
 
 ## Unreleased
 
-- Improve handling of Conda based environments in metadata collection.
+- Improves handling of Conda based environments in metadata collection.
+- Adds additional options to `Client.get_runs`.
 
 ## [v2.1.2](https://github.com/simvue-io/client/releases/tag/v2.1.2) - 2025-06-25
 

simvue/client.py

@@ -186,9 +186,12 @@ def get_runs(
         filters: list[str] | None,
         *,
         system: bool = False,
+        attributes: list[str] | None = None,
+        metadata: bool = False,
         metrics: bool = False,
         alerts: bool = False,
-        metadata: bool = False,
+        system_info: bool = False,
+        timing_info: bool = False,
         output_format: typing.Literal["dict", "objects", "dataframe"] = "objects",
         count_limit: pydantic.PositiveInt | None = 100,
         start_index: pydantic.NonNegativeInt = 0,
@@ -202,6 +205,9 @@ def get_runs(
         filters: list[str] | None
             set of filters to apply to query results. If None is specified
             return all results without filtering.
+        attributes : list[str] | None, optional
+            specify specific attributes to retrieve for runs.
+            Default of None includes all.
         metadata : bool, optional
             whether to include metadata information in the response.
             Default False.
@@ -211,6 +217,12 @@ def get_runs(
         alerts : bool, optional
             whether to include alert information in the response.
             Default False.
+        system_info : bool, optional
+            whether to include system information in the response.
+            Default False.
+        timing_info: bool, optional
+            whether to include timing information in the response.
+            Default False.
         output_format : Literal['dict', objects', 'dataframe'], optional
             the structure of the response
                 * dict - dictionary of values.
@@ -252,11 +264,13 @@ def get_runs(
         _runs = Run.get(
             count=count_limit,
             offset=start_index,
+            attributes=json.dumps(attributes),
             filters=json.dumps(filters),
             return_basic=True,
+            return_system=system_info,
+            return_timing=timing_info,
             return_metrics=metrics,
             return_alerts=alerts,
-            return_system=system,
             return_metadata=metadata,
             sorting=[dict(zip(("column", "descending"), a)) for a in sort_by_columns]
             if sort_by_columns

tests/functional/test_client.py

@@ -1,4 +1,3 @@
-from logging import critical
 import pytest
 import uuid
 import random
@@ -8,8 +7,6 @@
 import pathlib
 import time
 
-import requests
-import pytest_mock
 import tempfile
 import simvue.client as svc
 from simvue.exception import ObjectNotFoundError
@@ -226,23 +223,35 @@ def test_get_artifacts_as_files(
 @pytest.mark.client
 @pytest.mark.object_retrieval
 @pytest.mark.parametrize(
-    "output_format,sorting",
+    "output_format,sorting,system_info,timing_info,metrics,metadata,alerts,attributes",
     [
-        ("dict", None),
-        ("dataframe", [("created", True), ("started", True)]),
-        ("objects", [("metadata.test_identifier", True)]),
+        ("dict", None, False, True, False, True, False, ["test_engine"]),
+        ("dataframe", [("created", True), ("started", True)], True, False, True, False, True, None),
+        ("objects", [("metadata.test_identifier", True)], False, False, False, False, False, None),
     ],
     ids=("dict-unsorted", "dataframe-datesorted", "objects-metasorted"),
 )
 def test_get_runs(
     create_test_run: tuple[sv_run.Run, dict],
     output_format: str,
     sorting: list[tuple[str, bool]] | None,
+    system_info: bool,
+    timing_info: bool,
+    metrics: bool,
+    metadata: bool,
+    alerts: bool,
+    attributes: list[str] | None
 ) -> None:
     client = svc.Client()
 
     _result = client.get_runs(
-        filters=[], output_format=output_format, count_limit=10, sort_by_columns=sorting
+        filters=[],
+        output_format=output_format,
+        count_limit=10,
+        sort_by_columns=sorting,
+        timing_info=True,
+        system_info=True,
+        attributes=attributes
     )
 
     if output_format == "dataframe":