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This commit is contained in:
Simon Bußmann
2025-08-26 13:40:45 +02:00
parent e41833a996
commit 8fdb21c2c8
14 changed files with 414 additions and 616 deletions
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213
app.py
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@@ -1,64 +1,171 @@
from flask import Flask, render_template, request
import sqlite3
import pandas as pd
from config import DB_PATH
#!/usr/bin/env python3
"""
Flask app to visualize a large SQLite database of speed tests.
- Plots time series for down_90th and up_90th
- Serves a lazily loaded table (server-side pagination)
- Designed for ~1GB DB: efficient SQLite pragmas + timestamp cursor pagination
Run:
export DB_PATH="/path/to/your/speedtests.sqlite3"
python3 app.py
Then open http://127.0.0.1:5000
Optional: create an index (speeds up range scans by timestamp):
sqlite3 "$DB_PATH" "CREATE INDEX IF NOT EXISTS idx_speed_tests_ts ON speed_tests(timestamp);"
"""
from __future__ import annotations
import os
import math
import sqlite3
from datetime import datetime
import pytz
app = Flask(__name__)
from flask import Flask, jsonify, request, render_template
def load_data():
# 1) grab raw
conn = sqlite3.connect(DB_PATH)
df = pd.read_sql("SELECT * FROM speed_tests", conn)
conn.close()
DB_PATH = os.environ.get("DB_PATH", "./speed_tests.sqlite3")
PAGE_SIZE_DEFAULT = 200
PAGE_SIZE_MAX = 1000
SERIES_MAX_POINTS_DEFAULT = 5000
SERIES_MAX_POINTS_HARD = 20000
# 2) parse epoch→UTC datetimes, then shift to Europe/Berlin
df['datetime'] = (
pd.to_datetime(df['timestamp'], unit='s', utc=True)
.dt.tz_convert('Europe/Berlin')
app = Flask(__name__, template_folder="templates")
# ---------------------- SQLite Helpers ----------------------
def get_conn() -> sqlite3.Connection:
uri = f"file:{os.path.abspath(DB_PATH)}?cache=shared"
conn = sqlite3.connect(uri, uri=True, check_same_thread=False)
conn.row_factory = sqlite3.Row
conn.execute("PRAGMA journal_mode=WAL;")
conn.execute("PRAGMA synchronous=NORMAL;")
conn.execute("PRAGMA temp_store=MEMORY;")
conn.execute("PRAGMA cache_size=-20000;") # ~20MB cache
return conn
CONN = get_conn()
# ---------------------- Utilities ----------------------
def ts_to_iso(ts: float | int | str) -> str:
try:
t = float(ts)
except Exception:
return str(ts)
return datetime.fromtimestamp(t, tz=pytz.timezone("Europe/Berlin")).isoformat()
# ---------------------- API Endpoints ----------------------
@app.get("/api/series")
def api_series():
q_from = request.args.get("from", type=float)
q_to = request.args.get("to", type=float)
max_points = request.args.get("max_points", type=int) or SERIES_MAX_POINTS_DEFAULT
max_points = max(100, min(max_points, SERIES_MAX_POINTS_HARD))
params = []
where = []
if q_from is not None:
where.append("timestamp >= ?")
params.append(q_from)
if q_to is not None:
where.append("timestamp <= ?")
params.append(q_to)
where_sql = ("WHERE " + " AND ".join(where)) if where else ""
cnt_sql = f"SELECT COUNT(*) AS n FROM speed_tests {where_sql};"
n_rows = CONN.execute(cnt_sql, params).fetchone()[0]
stride = 1 if n_rows <= max_points else math.ceil(n_rows / max_points)
sql = (
f"SELECT timestamp, down_90th, up_90th FROM speed_tests {where_sql} "
"ORDER BY timestamp ASC;"
)
# 3) for your table display, format as naive strings
df['recorded_at'] = df['datetime'].dt.strftime('%Y-%m-%d %H:%M:%S')
return df
def get_aggregated_data(df: pd.DataFrame, interval: str = '5min'):
# ensure 'datetime' is the index
df = df.set_index('datetime')
# 1) resample into N-minute bins, mean
agg = (
df
.resample(interval)
.agg({
'down_90th': 'mean',
'up_90th': 'mean'
rows = []
kept = 0
for i, r in enumerate(CONN.execute(sql, params)):
if (i % stride) == 0:
rows.append({
"t": float(r["timestamp"]),
"t_iso": ts_to_iso(r["timestamp"]),
"down_90th": None if r["down_90th"] is None else float(r["down_90th"]),
"up_90th": None if r["up_90th"] is None else float(r["up_90th"]),
})
.reset_index()
kept += 1
if kept >= max_points:
break
return jsonify({
"count_total": n_rows,
"stride": stride,
"returned": len(rows),
"points": rows,
})
@app.get("/api/table")
def api_table():
limit = request.args.get("limit", type=int) or PAGE_SIZE_DEFAULT
limit = max(1, min(limit, PAGE_SIZE_MAX))
order = request.args.get("order", default="desc")
order = "ASC" if str(order).lower().startswith("asc") else "DESC"
cursor = request.args.get("cursor", type=float)
params = []
where = []
if cursor is not None:
if order == "ASC":
where.append("timestamp > ?")
else:
where.append("timestamp < ?")
params.append(cursor)
where_sql = ("WHERE " + " AND ".join(where)) if where else ""
sql = (
"SELECT id, timestamp, failed, isp, ip, location_code, location_city, location_region, "
"latency, jitter, down_100kB, down_1MB, down_10MB, down_25MB, down_90th, "
"up_100kB, up_1MB, up_10MB, up_90th "
f"FROM speed_tests {where_sql} ORDER BY timestamp {order} LIMIT ?;"
)
params2 = params + [limit]
rows = [dict(r) for r in CONN.execute(sql, params2).fetchall()]
next_cursor = None
if rows:
last_ts = rows[-1]["timestamp"]
try:
next_cursor = float(last_ts)
except Exception:
next_cursor = last_ts
for r in rows:
r["timestamp_iso"] = ts_to_iso(r["timestamp"])
return jsonify({
"limit": limit,
"order": order.lower(),
"count": len(rows),
"next_cursor": next_cursor,
"rows": rows,
})
@app.get("/")
def index():
return render_template(
"index.html",
db_name=os.path.basename(DB_PATH),
SERIES_MAX_POINTS_DEFAULT=SERIES_MAX_POINTS_DEFAULT,
SERIES_MAX_POINTS_HARD=SERIES_MAX_POINTS_HARD,
PAGE_SIZE_DEFAULT=PAGE_SIZE_DEFAULT,
PAGE_SIZE_MAX=PAGE_SIZE_MAX,
)
# 3) output for Chart.js
return {
"times": agg['datetime'].tolist(),
"down_90th": agg['down_90th'].round(2).tolist(),
"up_90th": agg['up_90th'].round(2).tolist()
}
if __name__ == "__main__":
port = int(os.environ.get("PORT", 5000))
app.run(host="0.0.0.0", port=port, debug=True)
@app.route('/')
def index():
df = load_data()
agg = request.args.get("agg", "5min")
chart_data = get_aggregated_data(df, agg)
#if math.isnan(chart_data['down_90th'][-1]) or math.isnan(chart_data['up_90th'][-1]):
#return render_template('local.html', data=df.to_dict(orient='records'), chart_data=chart_data)
return render_template('index.html', aggregation=agg, data=df.to_dict(orient='records'), chart_data=chart_data)
if __name__ == '__main__':
app.run(host='0.0.0.0', port=5001)

33
com.user.speedtest.plist
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@@ -1,33 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN"
"http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>Label</key>
<string>com.user.speedtest</string>
<key>WorkingDirectory</key>
<string>/Users/cato/Code/Cato447/speed-logger</string>
<key>ProgramArguments</key>
<array>
<string>/opt/homebrew/bin/uv</string>
<string>run</string>
<string>--script</string>
<string>/Users/cato/Code/Cato447/speed-logger/run_speedtest.py</string>
</array>
<key>StartInterval</key>
<integer>30</integer>
<key>RunAtLoad</key>
<true/>
<key>StandardOutPath</key>
<string>/tmp/speedtest.out</string>
<key>StandardErrorPath</key>
<string>/tmp/speedtest.err</string>
</dict>
</plist>

2
config.py.example
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DB_PATH =
ROUTER_MAC =

89
db.py
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import sqlite3
from config import DB_PATH
def init_db(db_path=DB_PATH):
conn = sqlite3.connect(db_path)
c = conn.cursor()
c.execute('''
CREATE TABLE IF NOT EXISTS speed_tests (
id INTEGER PRIMARY KEY AUTOINCREMENT,
timestamp REAL NOT NULL,
failed BOOLEAN NOT NULL,
isp TEXT,
ip TEXT,
location_code TEXT,
location_city TEXT,
location_region TEXT,
latency REAL,
jitter REAL,
down_100kB REAL,
down_1MB REAL,
down_10MB REAL,
down_25MB REAL,
down_90th REAL,
up_100kB REAL,
up_1MB REAL,
up_10MB REAL,
up_90th REAL
)
''')
conn.commit()
conn.close()
def insert_result(results: dict|None, db_path=DB_PATH):
conn = sqlite3.connect(db_path)
c = conn.cursor()
# If the test failed entirely, store it as a failure with timestamp now
if results is None or "tests" not in results:
from time import time
c.execute("INSERT INTO speed_tests (timestamp, failed) VALUES (?, ?)", (time(), True))
conn.commit()
conn.close()
return
tests = results.get("tests", {})
meta = results.get("meta", {})
# Get a consistent timestamp from any TestResult (or fallback to now)
from time import time as now
sample_test = next(iter(tests.values()), None)
timestamp = sample_test.time if sample_test else now()
print(tests)
print(meta)
def get(tests, key):
return tests[key].value if key in tests else None
c.execute('''
INSERT INTO speed_tests (
timestamp, failed, isp, ip, location_code, location_city, location_region,
latency, jitter,
down_100kB, down_1MB, down_10MB, down_25MB, down_90th,
up_100kB, up_1MB, up_10MB, up_90th
) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
''', (
timestamp, False,
get(tests, "isp"),
get(meta, "ip"),
get(meta, "location_code"),
get(meta, "location_city"),
get(meta, "location_region"),
get(tests, "latency"),
get(tests, "jitter"),
get(tests, "100kB_down_mbps"),
get(tests, "1MB_down_mbps"),
get(tests, "10MB_down_mbps"),
get(tests, "25MB_down_mbps"),
get(tests, "90th_percentile_down_mbps"),
get(tests, "100kB_up_mbps"),
get(tests, "1MB_up_mbps"),
get(tests, "10MB_up_mbps"),
get(tests, "90th_percentile_up_mbps")
))
conn.commit()
conn.close()

6
main.py
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def main():
print("Hello from speed-logger!")
if __name__ == "__main__":
main()

17
prometheus_test.py
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from prometheus_client import CollectorRegistry, Gauge, push_to_gateway
# Config
PUSHGATEWAY_URL = "https://pushgateway.cato447.de"
JOB_NAME = "test_push"
# Create a new registry for the job
registry = CollectorRegistry()
test_metric = Gauge('test_metric_value', 'Just a test metric', registry=registry)
# Set the metric value (e.g., random or fixed)
test_metric.set(42)
# Push to the gateway
push_to_gateway(PUSHGATEWAY_URL, job=JOB_NAME, registry=registry)
print("Pushed test metric to Pushgateway.")

1
pyproject.toml
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@@ -11,4 +11,5 @@ dependencies = [
"gunicorn>=23.0.0",
"pandas>=2.2.3",
"prometheus-client>=0.21.1",
"pytz>=2025.2",
]

30
show_data.py
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import sqlite3
import pandas as pd
from config import DB_PATH
from datetime import datetime
def load_data():
# Connect to SQLite database
conn = sqlite3.connect(DB_PATH)
query = "SELECT * FROM speed_tests"
df = pd.read_sql(query, conn)
conn.close()
return df
df = load_data()
# Convert timestamps to human-readable format
df['datetime'] = pd.to_datetime(df['timestamp'], unit='s')
# Suppose your DataFrame is called `df`
df["timestamp"] = df["timestamp"].apply(lambda ts: datetime.fromtimestamp(ts).strftime("%Y-%m-%d %H:%M:%S"))
# Collect the data for charts
chart_data = {
"times": df['datetime'].dt.strftime('%Y-%m-%d %H:%M:%S').tolist(),
"down_90th": df['down_90th'].tolist(),
"up_90th": df['up_90th'].tolist()
}
print(df[-60:])

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static/css/style.css
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body {
font-family: Arial, sans-serif;
padding: 20px;
background-color: #f4f4f4;
}
header h1 {
text-align: center;
color: #333;
}
table {
width: 100%;
margin-top: 20px;
border-collapse: collapse;
}
th, td {
padding: 10px;
text-align: center;
border: 1px solid #ddd;
}
th {
background-color: #f2f2f2;
}

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static/js/chart.js
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static/js/chartjs-plugin-annotation
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357
templates/index.html
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<!DOCTYPE html>
<!doctype html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Internet Speed Dashboard</title>
<!-- DataTables CSS -->
<link
rel="stylesheet"
href="https://cdn.datatables.net/1.13.4/css/jquery.dataTables.min.css"
/>
<!-- jQuery + DataTables JS -->
<script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
<script src="https://cdn.datatables.net/1.13.4/js/jquery.dataTables.min.js"></script>
<!-- Chart.js core (umd build) -->
<script src="https://cdn.jsdelivr.net/npm/chart.js/dist/chart.umd.min.js"></script>
<!-- date adapter (Moment.js + Chart.js adapter) -->
<script src="https://cdn.jsdelivr.net/npm/moment/min/moment.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/chartjs-adapter-moment/dist/chartjs-adapter-moment.min.js"></script>
<!-- zoom & pan plugin -->
<script src="https://cdn.jsdelivr.net/npm/chartjs-plugin-zoom/dist/chartjs-plugin-zoom.min.js"></script>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1" />
<title>Speed Tests</title>
<style>
body { font-family: sans-serif; margin: 2rem; }
#speedChart { max-width: 100%; margin-bottom: 2rem; }
table.dataTable { width: 100% !important; }
body { font-family: system-ui, -apple-system, Segoe UI, Roboto, Ubuntu, Cantarell, 'Helvetica Neue', Arial, 'Noto Sans', 'Liberation Sans', sans-serif; margin: 0; background: #0b0b10; color: #e8e8f0; }
header { padding: 1rem 1.25rem; position: sticky; top: 0; background: #0b0b10; border-bottom: 1px solid #23232b; z-index: 2; }
.wrap { max-width: 1200px; margin: 0 auto; padding: 1rem; }
.card { background: #12121a; border: 1px solid #23232b; border-radius: 16px; padding: 1rem; box-shadow: 0 4px 16px rgba(0,0,0,.25); }
h1 { font-size: 1.25rem; margin: 0; }
#chart { height: 420px; }
table { width: 100%; border-collapse: collapse; font-size: 0.95rem; }
th, td { padding: 8px 10px; border-bottom: 1px solid #23232b; white-space: nowrap; }
thead th { position: sticky; top: 0; background: #12121a; z-index: 1; }
tr:hover td { background: #171723; }
.muted { color: #a0a0b8; font-size: 0.9rem; }
.controls { display: flex; gap: .5rem; align-items: center; flex-wrap: wrap; margin-bottom: .5rem; }
input, select, button { background: #0b0b10; color: #e8e8f0; border: 1px solid #23232b; border-radius: 10px; padding: .4rem .6rem; }
button { cursor: pointer; }
#sentinel { height: 24px; }
.badge { display:inline-block; padding:.15rem .5rem; border-radius: 999px; background:#1e293b; color:#d1e7ff; font-size: .75rem; margin-left: .5rem; }
</style>
<script src="https://cdn.plot.ly/plotly-2.35.2.min.js" defer></script>
</head>
<body>
<h1>90th-Percentile Speeds (Aggregated every {{ aggregation }})</h1>
<header>
<div class="wrap">
<h1>Speed Tests <span class="badge">DB: {{ db_name }}</span></h1>
<div class="muted">down_90th vs up_90th · lazy table below</div>
</div>
</header>
<!-- Chart -->
<canvas id="speedChart" width="800" height="300"></canvas>
<main class="wrap" style="display:grid; gap: 1rem;">
<section class="card">
<div class="controls">
<label>Max points <input id="maxPoints" type="number" value="{{ SERIES_MAX_POINTS_DEFAULT }}" min="200" max="{{ SERIES_MAX_POINTS_HARD }}" step="200"></label>
<button id="reloadSeries">Reload series</button>
<span class="muted" id="seriesMeta"></span>
</div>
<div id="chart"></div>
</section>
<script>
var chartData = {{ chart_data | tojson }};
const acceptableDownloadRange = {
min: 600,
max: 1000
};
const acceptableUploadRange = {
min: 15,
max: 50
};
const times = chartData.times;
const downloadMinBand = times.map(() => acceptableDownloadRange.min);
const downloadMaxBand = times.map(() => acceptableDownloadRange.max);
const uploadMinBand = times.map(() => acceptableUploadRange.min);
const uploadMaxBand = times.map(() => acceptableUploadRange.max);
// --- Build annotation boxes for NaN spans ---
const annotations = [];
let inGap = false;
let gapStart = null;
for (let i = 0; i < times.length; i++) {
const down = chartData.down_90th[i];
const up = chartData.up_90th[i];
const isNan = isNaN(down) || isNaN(up);
if (!inGap && isNan) {
inGap = true;
gapStart = times[i];
}
if (inGap && !isNan) {
const gapEnd = times[i];
annotations.push({
type: 'box',
xMin: gapStart,
xMax: gapEnd,
backgroundColor: 'rgba(255, 0, 0, 0.15)',
borderWidth: 0
});
inGap = false;
}
}
// Close trailing gap if it reaches the end
if (inGap) {
annotations.push({
type: 'box',
xMin: gapStart,
xMax: times[times.length - 1],
backgroundColor: 'rgba(255, 0, 0, 0.15)',
borderWidth: 0
});
}
var ctx = document.getElementById('speedChart').getContext('2d');
var speedChart = new Chart(ctx, {
type: 'line',
data: {
labels: times,
datasets: [
{
label: 'Download Speed',
data: chartData.down_90th,
borderColor: 'rgba(75, 192, 192, 1)',
fill: false
},
{
label: 'Upload Speed',
data: chartData.up_90th,
borderColor: 'rgba(153, 102, 255, 1)',
fill: false
},
{
label: 'Acceptable Download Range',
data: downloadMinBand,
borderColor: 'rgba(0, 200, 0, 0.1)',
backgroundColor: 'rgba(0, 200, 0, 0.1)',
fill: '+1',
pointRadius: 0,
borderWidth: 0
},
{
data: downloadMaxBand,
borderColor: 'rgba(0, 200, 0, 0.1)',
backgroundColor: 'rgba(0, 200, 0, 0.1)',
fill: false,
pointRadius: 0,
borderWidth: 0
},
{
label: 'Acceptable Upload Range',
data: uploadMinBand,
borderColor: 'rgba(255, 165, 0, 0.1)',
backgroundColor: 'rgba(255, 165, 0, 0.1)',
fill: '+1',
pointRadius: 0,
borderWidth: 0
},
{
data: uploadMaxBand,
borderColor: 'rgba(255, 165, 0, 0.1)',
backgroundColor: 'rgba(255, 165, 0, 0.1)',
fill: false,
pointRadius: 0,
borderWidth: 0
}
]
},
options: {
responsive: true,
plugins: {
legend: {
labels: {
filter: function(item) {
return item.text !== undefined;
}
}
},
annotation: {
annotations: annotations
}
},
scales: {
x: {
type: 'category',
title: {
display: true,
text: 'Time'
}
},
y: {
title: {
display: true,
text: 'Speed (Mbps)'
},
min: 0
}
}
}
});
</script>
<!-- Data table -->
<h2>Raw Data</h2>
<table id="speedTable" class="display">
<thead>
<tr>
<th>Recorded At</th>
<th>Download (90th)</th>
<th>Upload (90th)</th>
</tr>
</thead>
<tbody>
{% for row in data %}
<tr>
<td>{{ row.datetime }}</td>
<td>{{ row.down_90th }}</td>
<td>{{ row.up_90th }}</td>
</tr>
{% endfor %}
</tbody>
<section class="card">
<div class="controls">
<strong>Table</strong>
<label>Page size <input id="pageSize" type="number" value="{{ PAGE_SIZE_DEFAULT }}" min="10" max="{{ PAGE_SIZE_MAX }}" step="50"></label>
<select id="orderSel">
<option value="desc" selected>Newest first</option>
<option value="asc">Oldest first</option>
</select>
<button id="resetTable">Reset</button>
<span class="muted" id="tableMeta"></span>
</div>
<div style="overflow:auto; max-height: 420px; border:1px solid #23232b; border-radius: 12px;">
<table id="tbl">
<thead><tr>
<th>timestamp</th>
<th>down_90th</th>
<th>up_90th</th>
<th>latency</th>
<th>jitter</th>
<th>failed</th>
<th>isp</th>
<th>ip</th>
<th>location</th>
</tr></thead>
<tbody></tbody>
</table>
</div>
<div id="sentinel"></div>
</section>
</main>
<script>
$(document).ready(function() {
$('#speedTable').DataTable({
pageLength: 50,
order: [[0, 'desc']]
});
async function loadSeries() {
const maxPoints = Math.max(200, Math.min({{ SERIES_MAX_POINTS_HARD }}, Number(document.getElementById('maxPoints').value||{{ SERIES_MAX_POINTS_DEFAULT }})));
const url = new URL('/api/series', window.location.origin);
url.searchParams.set('max_points', maxPoints);
const res = await fetch(url);
const js = await res.json();
const t = js.points.map(p => new Date(p.t * 1000));
const down = js.points.map(p => p.down_90th);
const up = js.points.map(p => p.up_90th);
const layout = {
margin: {l: 50, r: 20, t: 10, b: 40},
paper_bgcolor: '#12121a',
plot_bgcolor: '#12121a',
xaxis: {title: 'Time', gridcolor: '#23232b'},
yaxis: {title: 'Mbit/s (approx)', gridcolor: '#23232b'},
showlegend: true,
legend: {orientation: 'h'}
};
const traces = [
{x: t, y: down, name: 'down_90th', mode: 'lines', type: 'scatter'},
{x: t, y: up, name: 'up_90th', mode: 'lines', type: 'scatter'}
];
Plotly.react('chart', traces, layout, {displayModeBar: true, responsive: true});
document.getElementById('seriesMeta').textContent = `returned ${js.returned} / total ${js.count_total} (stride ${js.stride})`;
}
document.getElementById('reloadSeries').addEventListener('click', loadSeries);
window.addEventListener('load', loadSeries);
let nextCursor = null;
let loading = false;
function formatRow(r) {
const loc = `${r.location_code||''} · ${r.location_city||''} · ${r.location_region||''}`;
return `<tr>
<td title="${r.timestamp}">${r.timestamp_iso}</td>
<td>${r.down_90th ?? ''}</td>
<td>${r.up_90th ?? ''}</td>
<td>${r.latency ?? ''}</td>
<td>${r.jitter ?? ''}</td>
<td>${r.failed}</td>
<td>${r.isp ?? ''}</td>
<td style="max-width:220px; overflow:hidden; text-overflow:ellipsis;">${r.ip ?? ''}</td>
<td>${loc}</td>
</tr>`;
}
async function loadMore() {
if (loading) return;
loading = true;
const limit = Math.max(10, Math.min({{ PAGE_SIZE_MAX }}, Number(document.getElementById('pageSize').value||{{ PAGE_SIZE_DEFAULT }})));
const order = document.getElementById('orderSel').value;
const url = new URL('/api/table', window.location.origin);
url.searchParams.set('limit', limit);
url.searchParams.set('order', order);
if (nextCursor !== null) url.searchParams.set('cursor', nextCursor);
const res = await fetch(url);
const js = await res.json();
const tbody = document.querySelector('#tbl tbody');
tbody.insertAdjacentHTML('beforeend', js.rows.map(formatRow).join(''));
nextCursor = js.next_cursor;
document.getElementById('tableMeta').textContent = `loaded ${js.count} rows · next cursor: ${nextCursor ?? '—'}`;
loading = false;
}
function resetTable() {
document.querySelector('#tbl tbody').innerHTML = '';
nextCursor = null;
loadMore();
}
document.getElementById('resetTable').addEventListener('click', resetTable);
window.addEventListener('load', resetTable);
const sentinel = document.getElementById('sentinel');
const io = new IntersectionObserver((entries) => {
entries.forEach(e => {
if (e.isIntersecting) loadMore();
});
}, {root: null, rootMargin: '200px', threshold: 0});
io.observe(sentinel);
</script>
</body>
</html>

34
templates/local.html
View File

@@ -1,34 +0,0 @@
{% extends 'layout.html' %}
{% block content %}
<h2>Graph: Download vs. Upload Speeds</h2>
<canvas id="speedChart"></canvas>
<h2>Test Results</h2>
<table border="1">
<thead>
<tr>
<th>Timestamp</th>
<th>ISP</th>
<th>Latency</th>
<th>Jitter</th>
<th>Download (90th Percentile)</th>
<th>Upload (90th Percentile)</th>
</tr>
</thead>
<tbody>
{% for row in data|reverse %}
<tr>
<td>{{ row.timestamp }}</td>
<td>{{ row.isp }}</td>
<td>{{ row.latency }}</td>
<td>{{ row.jitter }}</td>
<td>{{ row.down_90th }}</td>
<td>{{ row.up_90th }}</td>
</tr>
{% endfor %}
</tbody>
</table>
{% endblock %}

226
uv.lock generated
View File

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