fix: update pandas Series float conversion to address deprecation warnings

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "redisbench-admin"
-version = "0.11.35"
+version = "0.11.37"
 description = "Redis benchmark run helper. A wrapper around Redis and Redis Modules benchmark tools ( ftsb_redisearch, memtier_benchmark, redis-benchmark, aibench, etc... )."
 authors = ["filipecosta90 <[email protected]>","Redis Performance Group <[email protected]>"]
 readme = "README.md"

redisbench_admin/compare/args.py

@@ -131,6 +131,7 @@ def create_compare_arguments(parser):
     parser.add_argument("--simple-table", type=bool, default=False)
     parser.add_argument("--use_metric_context_path", type=bool, default=False)
     parser.add_argument("--testname_regex", type=str, default=".*", required=False)
+    parser.add_argument("--test-regex", type=str, default=".*", required=False)
     parser.add_argument(
         "--regressions-percent-lower-limit",
         type=float,

redisbench_admin/compare/compare.py

@@ -315,25 +315,22 @@ def compare_command_logic(args, project_name, project_version):
         comparison_summary = "In summary:\n"
         if total_stable > 0:
             comparison_summary += (
-                "- Detected a total of {} stable tests between versions.\n".format(
-                    total_stable,
-                )
+                f"- Detected a total of {total_stable} stable tests between versions.\n"
             )
 
         if total_unstable > 0:
             comparison_summary += (
-                "- Detected a total of {} highly unstable benchmarks.\n".format(
-                    total_unstable
-                )
+                f"- Detected a total of {total_unstable} highly unstable benchmarks.\n"
             )
         if total_improvements > 0:
-            comparison_summary += "- Detected a total of {} improvements above the improvement water line.\n".format(
-                total_improvements
+            comparison_summary += (
+                f"- Detected a total of {total_improvements} improvements above the improvement water line.\n"
             )
         if total_regressions > 0:
-            comparison_summary += "- Detected a total of {} regressions bellow the regression water line {}.\n".format(
-                total_regressions, args.regressions_percent_lower_limit
+            comparison_summary += (
+                f"- Detected a total of {total_regressions} regressions bellow the regression water line {args.regressions_percent_lower_limit}%.\n"
             )
+        comparison_summary += "\n"
 
         comment_body += comparison_summary
         comment_body += "\n"
@@ -1102,9 +1099,9 @@ def get_v_pct_change_and_largest_var(
             comparison_values.append(tuple[1])
 
         comparison_df = pd.DataFrame(comparison_values)
-        comparison_median = float(comparison_df.median())
+        comparison_median = float(comparison_df.median().iloc[0])
         comparison_v = comparison_median
-        comparison_std = float(comparison_df.std())
+        comparison_std = float(comparison_df.std().iloc[0])
         if verbose:
             logging.info(
                 "comparison_datapoints: {} value: {}; std-dev: {}; median: {}".format(

redisbench_admin/utils/remote.py

@@ -629,6 +629,15 @@ def push_data_to_redistimeseries(rts, time_series_dict: dict, expire_msecs=0):
         )
         for timeseries_name, time_series in time_series_dict.items():
             try:
+                arch = "x86_64"
+                if "arch" in time_series["labels"]:
+                    arch = time_series["labels"]["arch"]
+                if arch == "aarch64" and "aarch64" not in timeseries_name:
+                    original_timeseries_name = timeseries_name
+                    timeseries_name = f"{timeseries_name}/arch/{arch}"
+                    logging.warning(
+                        f"overriding key named {original_timeseries_name} given it does not contain arch and it's not x86_64. new key={timeseries_name}"
+                    )
                 exporter_create_ts(rts, time_series, timeseries_name)
                 for timestamp, value in time_series["data"].items():
                     try: