–Pages
Loading…
Loading…
Interval: –
First measurement: –
Measurements: –
Last update: –
Growth / hour
–
Average over full history
Growth / day
–
Average over full history
Last 5 min
–
Latest interval change
Last hour
–
vs. measurement ~1 h ago
Last 24 h
–
vs. measurement ~24 h ago
Forecast next hour
–
Linear trend extrapolation
Indexed pages over time
X-axis shows the real measurement timestamps · dashed line = linear-regression trend & 24 h forecast
Change per 5 minutes
Computed from the raw measurements: each change is normalized to a 5-minute interval
"""
def load_data():
if not DB_DATA.exists():
return []
try:
with DB_DATA.open("r", encoding="utf-8") as f:
return json.load(f)
except Exception:
return []
def save_data(data):
tmp = DB_DATA.with_suffix(".tmp")
with tmp.open("w", encoding="utf-8") as f:
json.dump(data, f, indent=2)
tmp.replace(DB_DATA)
def get_page_count():
command = [
"sudo",
"-u",
"postgres",
"psql",
"-p",
"25432",
"-d",
"jonassearch",
"-t",
"-A",
"-c",
"SELECT COUNT(*) FROM pages;"
]
result = subprocess.run(
command,
capture_output=True,
text=True,
check=True
)
return int(result.stdout.strip())
def collect():
while True:
try:
count = get_page_count()
entry = {
"timestamp": datetime.now().isoformat(),
"count": count
}
data = load_data()
data.append(entry)
save_data(data)
print(
f"[{entry['timestamp']}] "
f"Pages: {count}"
)
except Exception as e:
print(f"Fehler beim Abrufen der Seitenzahl: {e}")
time.sleep(INTERVAL)
@app.route("/")
def index():
return render_template_string(HTML)
@app.route("/api/data")
def api_data():
return jsonify({
"values": load_data()
})
if __name__ == "__main__":
# Collector im Hintergrund starten
thread = threading.Thread(target=collect, daemon=True)
thread.start()
# Webserver
app.run(
host="0.0.0.0",
port=8081,
threaded=True
)