82 lines
2.5 KiB
Python
82 lines
2.5 KiB
Python
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"""
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This script postprocesses data gathered during a CI run, computes certain metrics
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from them, and uploads these metrics to DataDog.
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This script is expected to be executed from within a GitHub Actions job.
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It expects the following environment variables:
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- DATADOG_SITE: path to the DataDog API endpoint
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- DATADOG_API_KEY: DataDog API token
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- DD_GITHUB_JOB_NAME: Name of the current GitHub Actions job
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And it also expects the presence of a binary called `datadog-ci` to be in PATH.
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It can be installed with `npm install -g @datadog/datadog-ci`.
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Usage:
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```bash
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$ python3 upload-build-metrics.py <path-to-CPU-usage-CSV>
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```
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`path-to-CPU-usage-CSV` is a path to a CSV generated by the `src/ci/cpu-usage-over-time.py` script.
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"""
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import argparse
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import csv
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import os
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import subprocess
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import sys
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from pathlib import Path
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from typing import List
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def load_cpu_usage(path: Path) -> List[float]:
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usage = []
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with open(path) as f:
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reader = csv.reader(f, delimiter=',')
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for row in reader:
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# The log might contain incomplete rows or some Python exception
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if len(row) == 2:
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try:
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idle = float(row[1])
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usage.append(100.0 - idle)
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except ValueError:
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pass
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return usage
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def upload_datadog_measure(name: str, value: float):
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"""
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Uploads a single numeric metric for the current GitHub Actions job to DataDog.
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"""
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print(f"Metric {name}: {value:.4f}")
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datadog_cmd = "datadog-ci"
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if os.getenv("GITHUB_ACTIONS") is not None and sys.platform.lower().startswith("win"):
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# Due to weird interaction of MSYS2 and Python, we need to use an absolute path,
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# and also specify the ".cmd" at the end. See https://github.com/rust-lang/rust/pull/125771.
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datadog_cmd = "C:\\npm\\prefix\\datadog-ci.cmd"
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subprocess.run([
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datadog_cmd,
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"measure",
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"--level", "job",
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"--measures", f"{name}:{value}"
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],
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check=False
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)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(
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prog="DataDog metric uploader"
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)
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parser.add_argument("cpu-usage-history-csv")
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args = parser.parse_args()
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build_usage_csv = vars(args)["cpu-usage-history-csv"]
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usage_timeseries = load_cpu_usage(Path(build_usage_csv))
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if len(usage_timeseries) > 0:
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avg_cpu_usage = sum(usage_timeseries) / len(usage_timeseries)
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else:
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avg_cpu_usage = 0
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upload_datadog_measure("avg-cpu-usage", avg_cpu_usage)
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