Merge pull request #367 from simvue-io/hotfix/remove-format-shadowing

Remove shadowing of Python 'format' keyword

Author: kzscisoft

simvue/client.py

@@ -269,7 +269,7 @@ def get_runs(
         metrics: bool = False,
         alerts: bool = False,
         metadata: bool = False,
-        format: typing.Literal["dict", "dataframe"] = "dict",
+        output_format: typing.Literal["dict", "dataframe"] = "dict",
         count: int = 100,
         start_index: int = 0,
     ) -> typing.Union[
@@ -291,7 +291,7 @@ def get_runs(
         alerts : bool, optional
             whether to include alert information in the response.
             Default False.
-        format : Literal['dict', 'dataframe'], optional
+        output_format : Literal['dict', 'dataframe'], optional
             the structure of the response, either a dictionary or a dataframe.
             Default is 'dict'. Pandas must be installed for 'dataframe'.
         count : int, optional
@@ -329,7 +329,7 @@ def get_runs(
 
         response.raise_for_status()
 
-        if format not in ("dict", "dataframe"):
+        if output_format not in ("dict", "dataframe"):
             raise ValueError("Invalid format specified")
 
         json_response = self._get_json_from_response(
@@ -344,7 +344,7 @@ def get_runs(
 
         if response_data := json_response.get("data"):
             return response_data
-        elif format == "dataframe":
+        elif output_format == "dataframe":
             return to_dataframe(response.json())
         else:
             raise RuntimeError("Failed to retrieve runs data")

tests/refactor/test_client.py

@@ -203,16 +203,16 @@ def test_folder_deletion(create_test_run: tuple[sv_run.Run, dict]) -> None:
 @pytest.mark.dependency
 @pytest.mark.client
 @pytest.mark.parametrize("aggregate", (True, False), ids=("aggregated", "normal"))
-@pytest.mark.parametrize("format", ("dict", "dataframe"))
+@pytest.mark.parametrize("output_format", ("dict", "dataframe"))
 @pytest.mark.parametrize("xaxis", ("step", "time", "timestamp"))
 def test_multiple_metric_retrieval(
     create_test_run: tuple[sv_run.Run, dict],
     aggregate: bool,
-    format: typing.Literal["dict", "dataframe"],
+    output_format: typing.Literal["dict", "dataframe"],
     xaxis: typing.Literal["step", "time", "timestamp"],
 ) -> None:
     client = svc.Client()
-    if format == "dataframe":
+    if output_format == "dataframe":
         try:
             import pandas
         except ImportError: