feat: benchmark util for assessing performance

ci/benchmark.py

@@ -0,0 +1,46 @@
+#!/usr/bin/env python3
+# This file is a script to run the benchmarking tests for the project.
+
+import subprocess
+import time
+import numpy as np
+import tqdm
+
+
+def main():
+    commands = [
+        "flexmeasures show beliefs --sensor-id 6 --sensor-id 16 --sensor-id 15 --sensor-id 8 --sensor-id 5 --sensor-id 4 --start 2023-01-01T05:00:00.000Z --duration P0Y0M1D",
+        "flexmeasures show beliefs --sensor-id 6 --sensor-id 16 --sensor-id 15 --sensor-id 8 --sensor-id 5 --sensor-id 4 --start 2023-01-01T05:00:00.000Z --duration P0Y0M30D",
+        "flexmeasures show beliefs --sensor-id 6 --sensor-id 16 --sensor-id 15 --sensor-id 8 --sensor-id 5 --sensor-id 4 --start 2023-01-01T05:00:00.000Z --duration P0Y0M60D",
+    ]
+
+    timings = {}
+    max_iterations = 10
+
+    for idx, command in enumerate(commands):
+        for _ in tqdm.tqdm(range(max_iterations)):
+            start = time.perf_counter()
+            run_command(command)
+            stop = time.perf_counter()
+            try:
+                timings[idx].append(start - stop)
+            except KeyError:
+                timings[idx] = [start - stop]
+
+    # Get mean and standard deviation of timings
+    print("All timings are in seconds and iterated {max_iterations} times")
+    for idx, timing in timings.items():
+        print(f"Command {commands[idx]}: {np.mean(timing)} ± {np.std(timing)}")
+
+
+def run_command(command):
+    # Run command using subprocess and check for errors but don't print output
+    try:
+        subprocess.run(command, shell=True, check=True, stdout=subprocess.DEVNULL)
+    except subprocess.CalledProcessError as process_error:
+        print(process_error)
+        exit(1)
+
+
+if __name__ == "__main__":
+    main()