Martin-Molinero
f8b258d329
Python Virtual Environments / build (push) Has been cancelled
Benchmarks / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
Regression Tests / build (push) Has been cancelled
Research Regression Tests / build (push) Has been cancelled
* New Fundamental Data * Minor CIK lookup fix * Handle live mode & delete unexisting properties * Minor coarse fundamental adjustment * Add fundamental history support * Fix unit tests * Performance improvements * Fixes * Minor regression algorithm fix * Improvements. Add FundamentalUniverseSelectionModel * Change default values * Fix unit test * Minor tweaks * Fix unit test * Minor error handling improvement * Fix rebase
63 lines
2.2 KiB
Python
63 lines
2.2 KiB
Python
import os
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import re
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import sys
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import json
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import subprocess
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import statistics
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from pathlib import Path
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dataPath = '../../../Data'
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if len(sys.argv) > 1:
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dataPath = sys.argv[1]
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print(f'Using data path {dataPath}')
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results = {}
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for baseDirectory in ["Algorithm.CSharp/Benchmarks", "Algorithm.Python/Benchmarks"]:
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language = baseDirectory[len("Algorithm") + 1:baseDirectory.index("/")]
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resultsPerLanguage = {}
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for algorithmFile in sorted(os.listdir(baseDirectory)):
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if algorithmFile.endswith(("py", "cs")):
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algorithmName = Path(algorithmFile).stem
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if "Fine" in algorithmName:
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# we skip fundamental benchmarks for now
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continue
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algorithmLocation = "QuantConnect.Algorithm.CSharp.dll" if language == "CSharp" else os.path.join("../../../", baseDirectory, algorithmFile)
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print(f'Start running algorithm {algorithmName} language {language}...')
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dataPointsPerSecond = []
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benchmarkLengths = []
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for x in range(1, 2):
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subprocess.run(["dotnet", "./QuantConnect.Lean.Launcher.dll",
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"--data-folder " + dataPath,
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"--algorithm-language " + language,
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"--algorithm-type-name " + algorithmName,
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"--algorithm-location " + algorithmLocation,
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"--log-handler ConsoleErrorLogHandler",
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"--close-automatically true"],
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cwd="./Launcher/bin/Release",
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stdout=subprocess.DEVNULL,
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stderr=subprocess.DEVNULL)
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algorithmLogs = os.path.join("./Launcher/bin/Release", algorithmName + "-log.txt")
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file = open(algorithmLogs, 'r')
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for line in file.readlines():
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for match in re.findall(r"(\d+)k data points per second", line):
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dataPointsPerSecond.append(int(match))
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for match in re.findall(r" completed in (\d+)", line):
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benchmarkLengths.append(int(match))
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averageDps = statistics.mean(dataPointsPerSecond)
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averageLength = statistics.mean(benchmarkLengths)
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resultsPerLanguage[algorithmName] = { "average-dps": averageDps, "samples": dataPointsPerSecond, "average-length": averageLength }
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print(f'Performance for {algorithmName} language {language} avg dps: {averageDps}k samples: [{",".join(str(x) for x in dataPointsPerSecond)}] avg length {averageLength} sec')
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results[language] = resultsPerLanguage
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with open("benchmark_results.json", "w") as outfile:
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json.dump(results, outfile)
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