85 lines
2.2 KiB
Python
85 lines
2.2 KiB
Python
#!/usr/bin/env python3
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import argparse
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import logging
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import os
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import sqlite3
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from pathlib import Path
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import pandas as pd
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import plotly.express as px
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log = logging.getLogger(__name__)
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HERE = Path(os.path.dirname(os.path.realpath(__file__)))
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TABLE_NAME = "dc_stats"
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INTERVALS = [1] # on cron interval is 10min
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def parse_args():
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parser = argparse.ArgumentParser(description="Extract docker stats in a sqlite db")
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parser.add_argument(
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"sqlite",
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nargs="?",
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type=Path,
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help="Path to sqlite file",
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default=HERE / "stats.sqlite",
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)
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parser.add_argument(
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"html",
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nargs="?",
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type=Path,
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help="Path to sqlite file",
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default=HERE / "stats.html",
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)
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parser.add_argument("--debug", "-d", action="store_true", help="Run in debug mode")
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args = parser.parse_args()
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return args.sqlite, args.html, args.debug
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def generate_html_report(sqlite_fn: Path, html_fn: Path):
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# Create your connection.
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cnx = sqlite3.connect(sqlite_fn)
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df = pd.read_sql_query(f"SELECT * FROM {TABLE_NAME}", cnx)
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df = df.set_index("date")
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log.info(f"Find {len(df)} items")
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# df["granu"] = 1
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dfs = pd.DataFrame()
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for i in INTERVALS:
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dfi = df[::i].copy()
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breakpoint()
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# dfi["granu"] = i
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dfs = dfs.append(dfi)
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log.info(f"Find {len(dfs)} items")
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fig = px.area(dfs)
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fig.for_each_trace(lambda trace: trace.update(fillcolor=trace.line.color))
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fig["layout"].pop("updatemenus") # optional, drop animation buttons
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fig.update_layout(transition={"duration": 1e12})
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fig.update_layout(
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title="Utilisation de RAM pour les docker-compose de l'eunuque"
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" (pour voir une stat, mettre la sourie sur le haut des courbes,"
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" vers les points)",
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xaxis_title="Temps",
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yaxis_title="RAM",
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)
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fig.write_html(html_fn, include_plotlyjs="cdn")
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def main():
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sqlite_fn, html_fn, debug = parse_args()
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if debug:
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logging.basicConfig(level=logging.DEBUG)
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else:
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logging.basicConfig(level=logging.INFO)
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generate_html_report(sqlite_fn, html_fn)
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if __name__ == "__main__":
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main()
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