Formatting python.

gz · gz · commit 5f753c3aabbf · 2025-02-07T18:49:42.000Z
Signed-off-by: Gerd Zellweger &lt;mail@gerdzellweger.com&gt;
diff --git a/demo/all-packaged/run.py b/demo/all-packaged/run.py
@@ -38,9 +38,9 @@ def main():
         pipeline.start()
         time.sleep(2)
         status = pipeline.status()
-        assert (
-            status == PipelineStatus.RUNNING
-        ), f"FAIL: demo {demo['name']}: expected pipeline to be RUNNING but instead is {status}"
+        assert status == PipelineStatus.RUNNING, (
+            f"FAIL: demo {demo['name']}: expected pipeline to be RUNNING but instead is {status}"
+        )
         pipeline.shutdown()
         print(f"PASS: demo {demo['name']}")
 
diff --git a/python/tests/test_pipeline_builder.py b/python/tests/test_pipeline_builder.py
@@ -492,14 +492,20 @@ def test_avro_format(self):
                     "format": {{
                         "name": "avro",
                         "config": {{
-                            "schema": {json.dumps(json.dumps({
-                                "type": "record",
-                                "name": "items",
-                                "fields": [
-                                    {"name": "id", "type": ["null", "int"]},
-                                    {"name": "name", "type": ["null", "string"]}
-                                ]
-                            }))}
+                            "schema": {
+            json.dumps(
+                json.dumps(
+                    {
+                        "type": "record",
+                        "name": "items",
+                        "fields": [
+                            {"name": "id", "type": ["null", "int"]},
+                            {"name": "name", "type": ["null", "string"]},
+                        ],
+                    }
+                )
+            )
+        }
                         }}
                     }}
                 }}
diff --git a/scripts/compilation_speed_benchmark.py b/scripts/compilation_speed_benchmark.py
@@ -65,7 +65,7 @@ def main():
     program = ""
     times = []
     for i in range(0, len(queries)):
-        print(f"Compiling program with {i+1} queries")
+        print(f"Compiling program with {i + 1} queries")
         program += queries[i]
         program += ";"
         # print(f"program: {program}")
diff --git a/scripts/plot_metrics.py b/scripts/plot_metrics.py
@@ -25,23 +25,29 @@ def parse_data(data_samples):
     for timestamp, sample in enumerate(data_samples):
         for entry in sample:
             key = entry["key"]
-            value = entry["value"].get("Gauge") or entry["value"].get("Counter")  # Handle Gauge and Counter values
-            labels = {label[0]: label[1] for label in entry.get("labels", [])}  # Convert labels to dict
+            value = entry["value"].get("Gauge") or entry["value"].get(
+                "Counter"
+            )  # Handle Gauge and Counter values
+            labels = {
+                label[0]: label[1] for label in entry.get("labels", [])
+            }  # Convert labels to dict
 
             # Extract necessary information
             worker = labels.get("worker", "Total")
             level = labels.get("level", "Total")
             spine = labels.get("id", "Total")
 
             # Append processed entry
-            records.append({
-                "timestamp": timestamp,
-                "key": key,
-                "worker": worker,
-                "level": level,
-                "value": value,
-                "id": spine
-            })
+            records.append(
+                {
+                    "timestamp": timestamp,
+                    "key": key,
+                    "worker": worker,
+                    "level": level,
+                    "value": value,
+                    "id": spine,
+                }
+            )
 
     return pd.DataFrame(records)
 
@@ -52,14 +58,20 @@ def make_plots(data_samples):
 
     # Filter for specific metrics
     df_merges = df[df["key"] == "spine.ongoing_merges"]
-    df_merges_summary = df_merges.groupby(["timestamp", "level"])["value"].agg(
-        ["mean", "max", "min"]).reset_index().melt(
-        id_vars=["timestamp", "level"], var_name="stat", value_name="value")
+    df_merges_summary = (
+        df_merges.groupby(["timestamp", "level"])["value"]
+        .agg(["mean", "max", "min"])
+        .reset_index()
+        .melt(id_vars=["timestamp", "level"], var_name="stat", value_name="value")
+    )
 
     df_batches = df[df["key"] == "spine.batches_per_level"]
-    df_batches_summary = df_batches.groupby(["timestamp", "level"])["value"].agg(
-        ["mean", "max", "min"]).reset_index().melt(
-        id_vars=["timestamp", "level"], var_name="stat", value_name="value")
+    df_batches_summary = (
+        df_batches.groupby(["timestamp", "level"])["value"]
+        .agg(["mean", "max", "min"])
+        .reset_index()
+        .melt(id_vars=["timestamp", "level"], var_name="stat", value_name="value")
+    )
 
     # Get bytes written at every time
     df_disk = df[df["key"] == "disk.total_bytes_written"]
@@ -88,35 +100,45 @@ def make_plots(data_samples):
     # Plot function
     def create_plot(df, title, filename):
         plot = (
-                ggplot(df, aes(x="timestamp", y="value", color="stat", group="stat"))
-                + geom_line(size=1)
-                + facet_wrap("~level", scales="free")
-                + labs(title=title, x="Time", y="Value")
-                + theme_classic()
-                + scale_y_continuous(limits=(0, None))
+            ggplot(df, aes(x="timestamp", y="value", color="stat", group="stat"))
+            + geom_line(size=1)
+            + facet_wrap("~level", scales="free")
+            + labs(title=title, x="Time", y="Value")
+            + theme_classic()
+            + scale_y_continuous(limits=(0, None))
         )
         plot.save(filename, width=12, height=6, dpi=300)
         print(f"Saved {filename}")
 
     # Generate plots
-    create_plot(df_merges, "Current #Batches being merged (Min/Avg/Max from all Spines)", "ongoing_merges.png")
-    create_plot(df_batches, "Current #Batches not being merged (Min/Avg/Max from all Spine)", "batches_per_level.png")
+    create_plot(
+        df_merges,
+        "Current #Batches being merged (Min/Avg/Max from all Spines)",
+        "ongoing_merges.png",
+    )
+    create_plot(
+        df_batches,
+        "Current #Batches not being merged (Min/Avg/Max from all Spine)",
+        "batches_per_level.png",
+    )
 
     plot = (
-            ggplot(df_totals, aes(x="timestamp", y="value", color="metric"))
-            + geom_line(size=1)
-            + facet_grid("metric ~ .", scales="free_y")  # Separate plots for MiB/s and Counts
-            + labs(title="Pipeline Totals", x="Time", y="Value")
-            + theme_classic()
-            + scale_y_continuous(limits=(0, None))
+        ggplot(df_totals, aes(x="timestamp", y="value", color="metric"))
+        + geom_line(size=1)
+        + facet_grid(
+            "metric ~ .", scales="free_y"
+        )  # Separate plots for MiB/s and Counts
+        + labs(title="Pipeline Totals", x="Time", y="Value")
+        + theme_classic()
+        + scale_y_continuous(limits=(0, None))
     )
 
     # Save the plot
     plot.save("pipeline_totals.png", width=12, height=8, dpi=300)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     import sys
 
     samples = get_data_samples(sys.argv[1])
-    make_plots(samples)
+    make_plots(samples)
