diff --git a/display/generate_html.py b/display/generate_html.py
index 72880da..416b845 100644
--- a/display/generate_html.py
+++ b/display/generate_html.py
@@ -1,30 +1,84 @@
+#!/usr/bin/env python3
+
+import argparse
+import logging
+import os
 import sqlite3
+from pathlib import Path
+
 import pandas as pd
 import plotly.express as px
 
-TABLE_NAME = "stats"
+log = logging.getLogger(__name__)
 
-INTERVALS = [50, 100, 1000]  # on cron interval is 10min
+HERE = Path(os.path.dirname(os.path.realpath(__file__)))
+
+TABLE_NAME = "dc_stats"
+INTERVALS = [1]  # on cron interval is 10min
 
 
-# Create your connection.
-cnx = sqlite3.connect('data.sqlite')
+def parse_args():
+    parser = argparse.ArgumentParser(description="Extract docker stats in a sqlite db")
 
-df = pd.read_sql_query(f"SELECT * FROM {TABLE_NAME}", cnx)
-df = df.set_index("date")
-print(f"Find {len(df)} items")
+    parser.add_argument(
+        "sqlite",
+        nargs="?",
+        type=Path,
+        help="Path to sqlite file",
+        default=HERE / "stats.sqlite",
+    )
+    parser.add_argument(
+        "html",
+        nargs="?",
+        type=Path,
+        help="Path to sqlite file",
+        default=HERE / "stats.html",
+    )
+    parser.add_argument("--debug", "-d", action="store_true", help="Run in debug mode")
+    args = parser.parse_args()
+    return args.sqlite, args.html, args.debug
 
-df["granu"] = 1
 
-dfs = pd.DataFrame()
-for i in INTERVALS:
-    dfi = df[::i].copy()
-    dfi["granu"] = i
-    dfs = dfs.append(dfi)
+def generate_html_report(sqlite_fn: Path, html_fn: Path):
+    # Create your connection.
+    cnx = sqlite3.connect(sqlite_fn)
 
-print(f"Find {len(dfs)} items")
-fig = px.area(dfs, title="Wide-Form Input", animation_frame="granu")
-fig.for_each_trace(lambda trace: trace.update(fillcolor = trace.line.color))
-fig["layout"].pop("updatemenus") # optional, drop animation buttons
-fig.update_layout(transition = {'duration': 1e12})
-fig.write_html("stats.html", include_plotlyjs="cdn")
+    df = pd.read_sql_query(f"SELECT * FROM {TABLE_NAME}", cnx)
+    df = df.set_index("date")
+    log.info(f"Find {len(df)} items")
+
+    # df["granu"] = 1
+
+    dfs = pd.DataFrame()
+    for i in INTERVALS:
+        dfi = df[::i].copy()
+        breakpoint()
+        # dfi["granu"] = i
+        dfs = dfs.append(dfi)
+
+    log.info(f"Find {len(dfs)} items")
+    fig = px.area(dfs)
+    fig.for_each_trace(lambda trace: trace.update(fillcolor=trace.line.color))
+    fig["layout"].pop("updatemenus")  # optional, drop animation buttons
+    fig.update_layout(transition={"duration": 1e12})
+    fig.update_layout(
+        title="Utilisation de RAM pour les docker-compose de l'eunuque"
+              " (pour voir une stat, mettre la sourie sur le haut des courbes,"
+              " vers les points)",
+        xaxis_title="Temps",
+        yaxis_title="RAM",
+    )
+    fig.write_html(html_fn, include_plotlyjs="cdn")
+
+
+def main():
+    sqlite_fn, html_fn, debug = parse_args()
+    if debug:
+        logging.basicConfig(level=logging.DEBUG)
+    else:
+        logging.basicConfig(level=logging.INFO)
+    generate_html_report(sqlite_fn, html_fn)
+
+
+if __name__ == "__main__":
+    main()