[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

mesa_frames/concrete/datacollector.py

@@ -175,7 +175,7 @@ def _collect_agent_reporters(self, current_model_step: int, batch_id: int):
         Collect agent-level data using the agent_reporters, including unique agent IDs
 
         Constructs a LazyFrame with one column per reporter and
-        includes 
+        includes
         - agent_id : unique identifier for each agent
         - step, seed and batch columns for context.
         - Columns for all requested agent reporters.
@@ -187,9 +187,15 @@ def _collect_agent_reporters(self, current_model_step: int, batch_id: int):
                 agent_set = self._model.sets[reporter]
 
                 if hasattr(agent_set, "df"):
-                    df = agent_set.df.select(["id", col_name]).rename({"id": "agent_id"})
+                    df = agent_set.df.select(["id", col_name]).rename(
+                        {"id": "agent_id"}
+                    )
                 elif hasattr(agent_set, "to_polars"):
-                    df = agent_set.to_polars().select(["id", col_name]).rename({"id": "agent_id"})
+                    df = (
+                        agent_set.to_polars()
+                        .select(["id", col_name])
+                        .rename({"id": "agent_id"})
+                    )
                 else:
                     records = []
                     for agent in agent_set.values():
@@ -199,30 +205,43 @@ def _collect_agent_reporters(self, current_model_step: int, batch_id: int):
                             agent_id = agent.id
                         else:
                             agent_id = None
-                        records.append({"agent_id": agent_id, col_name: getattr(agent, col_name, None)})
+                        records.append(
+                            {
+                                "agent_id": agent_id,
+                                col_name: getattr(agent, col_name, None),
+                            }
+                        )
                     df = pl.DataFrame(records)
             else:
                 df = reporter(self._model)
                 if not isinstance(df, pl.DataFrame):
-                    raise TypeError(f"Agent reporter {col_name} must return a Polars DataFrame")
-                
-            df = df.with_columns([
-                pl.lit(current_model_step).alias("step"),
-                pl.lit(str(self.seed)).alias("seed"),
-                pl.lit(batch_id).alias("batch"),
-            ])
+                    raise TypeError(
+                        f"Agent reporter {col_name} must return a Polars DataFrame"
+                    )
+
+            df = df.with_columns(
+                [
+                    pl.lit(current_model_step).alias("step"),
+                    pl.lit(str(self.seed)).alias("seed"),
+                    pl.lit(batch_id).alias("batch"),
+                ]
+            )
             all_agent_frames.append(df)
 
         if all_agent_frames:
             merged_df = all_agent_frames[0]
             for next_df in all_agent_frames[1:]:
                 if "agent_id" not in next_df.columns:
                     continue
-                merged_df = merged_df.join(next_df, on=["agent_id", "step", "seed", "batch"], how="outer")
+                merged_df = merged_df.join(
+                    next_df, on=["agent_id", "step", "seed", "batch"], how="outer"
+                )
 
             agent_lazy_frame = merged_df.lazy()
-            self._frames.append(("agent", current_model_step, batch_id, agent_lazy_frame))
-                
+            self._frames.append(
+                ("agent", current_model_step, batch_id, agent_lazy_frame)
+            )
+
     @property
     def data(self) -> dict[str, pl.DataFrame]:
         """