chore: import upstream snapshot with attribution

2026-07-13 13:02:50 +08:00
commit 0fc60fdcb1
5008 changed files with 910633 additions and 0 deletions
@@ -0,0 +1,65 @@
+import os
+import re
+import sys
+import json
+import subprocess
+import statistics
+from pathlib import Path
+
+dataPath = '../../../Data'
+if len(sys.argv) > 1:
+	dataPath = sys.argv[1]
+print(f'Using data path {dataPath}')
+
+results = {}
+for baseDirectory in ["Algorithm.CSharp/Benchmarks", "Algorithm.Python/Benchmarks"]:
+
+	language = baseDirectory[len("Algorithm") + 1:baseDirectory.index("/")]
+	resultsPerLanguage = {}
+
+	for algorithmFile in sorted(os.listdir(baseDirectory)):
+		if algorithmFile.endswith(("py", "cs")):
+
+			algorithmName = Path(algorithmFile).stem
+
+			if "Fine" in algorithmName:
+				# we skip fundamental benchmarks for now
+				continue
+			algorithmLocation = "QuantConnect.Algorithm.CSharp.dll" if language == "CSharp" else os.path.join("../../../", baseDirectory, algorithmFile)
+			print(f'Start running algorithm {algorithmName} language {language}...')
+
+			dataPointsPerSecond = []
+			benchmarkLengths = []
+			for x in range(1, 3):
+
+				subprocess.run(["dotnet", "./QuantConnect.Lean.Launcher.dll",
+					"--data-folder " + dataPath,
+					"--algorithm-language " + language,
+					"--algorithm-type-name " + algorithmName,
+					"--algorithm-location " + algorithmLocation,
+					"--log-handler ConsoleErrorLogHandler",
+					"--close-automatically true"],
+					cwd="./Launcher/bin/Release",
+					stdout=subprocess.DEVNULL,
+					stderr=subprocess.DEVNULL)
+				if x == 1:
+					# skip first run
+					continue
+
+				algorithmLogs = os.path.join("./Launcher/bin/Release", algorithmName + "-log.txt")
+				file = open(algorithmLogs, 'r')
+				for line in file.readlines():
+					for match in re.findall(r"(\d+)k data points per second", line):
+						dataPointsPerSecond.append(int(match))
+					for match in re.findall(r" completed in (\d+)", line):
+						benchmarkLengths.append(int(match))
+
+			averageDps = statistics.mean(dataPointsPerSecond)
+			averageLength = statistics.mean(benchmarkLengths)
+			resultsPerLanguage[algorithmName] = { "average-dps": averageDps, "samples": dataPointsPerSecond, "average-length": averageLength }
+			print(f'Performance for {algorithmName} language {language} avg dps: {averageDps}k samples: [{",".join(str(x) for x in dataPointsPerSecond)}] avg length {averageLength} sec')
+
+	results[language] = resultsPerLanguage
+
+with open("benchmark_results.json", "w") as outfile:
+	json.dump(results, outfile)