run_benchmarks.py

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
			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, 2):

				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)

				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)