add pictures to statcounter

This commit is contained in:
2026-10-18 11:21:25 +02:00
parent ca5af75bbd
commit 3ebfeca7cc
5 changed files with 1225 additions and 32 deletions
+166 -31
View File
@@ -145,7 +145,7 @@ HTML = r"""
50% { opacity: 0.35; }
}
.ranges { display: flex; gap: 8px; margin-bottom: 18px; }
.ranges { display: flex; flex-wrap: wrap; gap: 8px; margin-bottom: 18px; }
.range-btn {
background: var(--card);
@@ -302,6 +302,7 @@ HTML = r"""
<button class="range-btn active" data-range="all">All</button>
<button class="range-btn" data-range="7d">Last 7 days</button>
<button class="range-btn" data-range="24h">Last 24 h</button>
<button class="range-btn" data-range="6h">Last 6 h</button>
</div>
<div class="grid">
@@ -315,6 +316,11 @@ HTML = r"""
<div class="value" id="stat-per-day">–</div>
<div class="hint">Average over full history</div>
</div>
<div class="card">
<div class="label">Growth 6 h</div>
<div class="value" id="stat-delta-6h">–</div>
<div class="hint" id="stat-delta-6h-hint">vs. measurement ~6 h ago</div>
</div>
<div class="card">
<div class="label">Growth 24 h</div>
<div class="value" id="stat-delta-24h">–</div>
@@ -400,6 +406,55 @@ HTML = r"""
<div id="heatmap"></div>
</div>
<div class="section-title">Images – all graphs</div>
<div class="chart-sub">Only exact measurements (counted every 2 h) are plotted – the estimates in between are excluded.</div>
<div class="chart-sub" id="images-empty" style="display:none">
No image counts yet – they appear after the next collector run with the image migration in place.
</div>
<div class="chart-container">
<div class="chart-title">Images over time</div>
<div class="chart-sub">Image URLs found while crawling · exact count every 2 h · only exact measurements are plotted (no estimates) · dashed line = trend &amp; 24 h forecast</div>
<div class="chart-box"><canvas id="imagesMainChart"></canvas></div>
</div>
<div class="chart-container">
<div class="chart-title">Change per 5 minutes</div>
<div class="chart-sub">Normalized to a 5-minute interval · spans between two exact counts (2 h) · grey = raw · colored = smoothed (moving average over 5 measurements)</div>
<div class="chart-box small"><canvas id="imagesDeltaChart"></canvas></div>
</div>
<div class="chart-container">
<div class="chart-title">Cumulative net growth</div>
<div class="chart-sub">Total images gained/lost since the start of the selected range · linear time axis</div>
<div class="chart-box small"><canvas id="imagesCumChart"></canvas></div>
</div>
<div class="chart-container">
<div class="chart-title">Images per hour (last 48 h)</div>
<div class="chart-sub">Sum of changes per hour bucket · green = growth, red = loss</div>
<div class="chart-box small"><canvas id="imagesHourlyChart"></canvas></div>
</div>
<div class="chart-row">
<div class="chart-container">
<div class="chart-title">Image growth by hour of day</div>
<div class="chart-sub">Average gain per 5 min, grouped by hour of day (whole history)</div>
<div class="chart-box small"><canvas id="imagesHodChart"></canvas></div>
</div>
<div class="chart-container">
<div class="chart-title">Records – biggest image changes</div>
<div class="chart-sub">Largest gains and losses between two consecutive measurements (selected range)</div>
<div id="records-images"></div>
</div>
</div>
<div class="section-title">Activity heatmap – image gain per hour of day</div>
<div class="chart-container heatmap">
<div class="chart-sub">Rows = days · columns = hours (0–23) · green = growth, red = loss, grey = no data</div>
<div id="heatmap-images"></div>
</div>
<div class="footer" id="footer"></div>
</div>
@@ -559,10 +614,26 @@ function parsePoints(values) {
.sort(function (a, b) { return a.x - b.x; });
}
function filterRange(points) {
// Nur exakte Bildzählungen (alle 2 h). Die dazwischen geschätzten Werte
// werden in keinem Diagramm dargestellt, damit alle Graphen ausschließlich
// echte Messpunkte zeigen.
function toImagePoints(points) {
return (points || [])
.filter(function (p) { return p.images !== null && p.images !== undefined; })
.filter(function (p) { return p.imagesExact; })
.map(function (p) { return { x: p.x, y: p.images }; });
}
const RANGE_SPANS = {
'6h': 6 * 3600000,
'24h': 24 * 3600000,
'7d': 7 * 24 * 3600000
};
function filterRange(points, anchorX) {
if (range === 'all' || !points.length) return points;
const last = points[points.length - 1].x;
const span = range === '24h' ? 24 * 3600000 : 7 * 24 * 3600000;
const last = anchorX === undefined ? points[points.length - 1].x : anchorX;
const span = RANGE_SPANS[range] || RANGE_SPANS['24h'];
return points.filter(function (p) { return p.x >= last - span; });
}
@@ -675,6 +746,12 @@ function baseScales(yFmt) {
function tooltipTitle(items) { return fmtDateFull(items[0].parsed.x); }
// Pages keep the existing camelCase ids (mainChart); other metrics get a prefix
// (imagesMainChart).
function chartId(prefix, suffix) {
return prefix ? prefix + suffix : suffix.charAt(0).toLowerCase() + suffix.slice(1);
}
function gradientFill(colorTop, colorBottom) {
return function (context) {
const chart = context.chart;
@@ -689,8 +766,14 @@ function gradientFill(colorTop, colorBottom) {
/* ---------- charts ---------- */
function renderCharts(points, deltas, smoothedDeltas) {
destroyCharts();
function renderCharts(cfg) {
const prefix = cfg.prefix;
const points = cfg.points;
const deltas = cfg.deltas;
const smoothedDeltas = cfg.smoothedDeltas;
const unit = cfg.unit;
const accent = cfg.accent;
const accentBar = cfg.accentBar;
const grid = 'rgba(128,128,128,0.15)';
/* 1. main chart + trend */
@@ -710,21 +793,21 @@ function renderCharts(points, deltas, smoothedDeltas) {
];
}
charts.main = new Chart(document.getElementById('mainChart'), {
charts[prefix + 'main'] = new Chart(document.getElementById(chartId(prefix, 'MainChart')), {
type: 'line',
data: {
datasets: [
{
label: 'Pages',
label: unit,
data: points,
parsing: false,
borderColor: ACCENT,
borderColor: accent,
borderWidth: 2,
pointRadius: 2.5,
pointHoverRadius: 5,
tension: 0.25,
fill: true,
backgroundColor: gradientFill('rgba(79,140,255,0.28)', 'rgba(79,140,255,0.02)'),
backgroundColor: gradientFill(cfg.gradTop, cfg.gradBottom),
spanGaps: false
},
{
@@ -753,8 +836,8 @@ function renderCharts(points, deltas, smoothedDeltas) {
title: tooltipTitle,
label: function (item) {
return item.datasetIndex === 0
? (fmt(item.parsed.y) + ' Pages')
: ('Trend: ' + fmt(item.parsed.y) + ' Pages');
? (fmt(item.parsed.y) + ' ' + unit)
: ('Trend: ' + fmt(item.parsed.y) + ' ' + unit);
}
}
}
@@ -763,7 +846,7 @@ function renderCharts(points, deltas, smoothedDeltas) {
});
/* 2. delta chart */
charts.delta = new Chart(document.getElementById('deltaChart'), {
charts[prefix + 'delta'] = new Chart(document.getElementById(chartId(prefix, 'DeltaChart')), {
type: 'line',
data: {
datasets: [
@@ -781,7 +864,7 @@ function renderCharts(points, deltas, smoothedDeltas) {
label: 'Change per 5 min',
data: smoothedDeltas,
parsing: false,
borderColor: ACCENT,
borderColor: accent,
borderWidth: 2.5,
pointRadius: 0,
pointHoverRadius: 4,
@@ -824,7 +907,7 @@ function renderCharts(points, deltas, smoothedDeltas) {
label: function (item) {
const raw = item.raw;
return [
'Smoothed: ' + fmtSigned(raw.y) + ' Pages per 5 min',
'Smoothed: ' + fmtSigned(raw.y) + ' ' + unit + ' per 5 min',
'Raw: ' + fmtSigned(raw.raw) + ' per 5 min (change ' + fmtSigned(raw.diff) + ' in ' + fmtDur(raw.dt) + ')'
];
}
@@ -839,7 +922,7 @@ function renderCharts(points, deltas, smoothedDeltas) {
return { x: p.x, y: p.y - points[0].y };
});
charts.cum = new Chart(document.getElementById('cumChart'), {
charts[prefix + 'cum'] = new Chart(document.getElementById(chartId(prefix, 'CumChart')), {
type: 'line',
data: {
datasets: [{
@@ -874,7 +957,7 @@ function renderCharts(points, deltas, smoothedDeltas) {
tooltip: {
callbacks: {
title: tooltipTitle,
label: function (item) { return fmtSigned(item.parsed.y) + ' Pages since range start'; }
label: function (item) { return fmtSigned(item.parsed.y) + ' ' + unit + ' since range start'; }
}
}
}
@@ -891,7 +974,7 @@ function renderCharts(points, deltas, smoothedDeltas) {
const hourlyLabels = hours.map(function (h) { return fmtDate(h); });
const hourlyValues = hours.map(function (h) { return Math.round(buckets[h]); });
charts.hourly = new Chart(document.getElementById('hourlyChart'), {
charts[prefix + 'hourly'] = new Chart(document.getElementById(chartId(prefix, 'HourlyChart')), {
type: 'bar',
data: {
labels: hourlyLabels,
@@ -917,7 +1000,7 @@ function renderCharts(points, deltas, smoothedDeltas) {
},
plugins: {
legend: { labels: { usePointStyle: true, boxWidth: 8, color: mutedColor() } },
tooltip: { callbacks: { label: function (item) { return fmtSigned(item.parsed.y) + ' Pages in this hour'; } } }
tooltip: { callbacks: { label: function (item) { return fmtSigned(item.parsed.y) + ' ' + unit + ' in this hour'; } } }
}
}
});
@@ -934,14 +1017,14 @@ function renderCharts(points, deltas, smoothedDeltas) {
return hodCount[i] ? Math.round(s / hodCount[i] * 10) / 10 : 0;
});
charts.hod = new Chart(document.getElementById('hodChart'), {
charts[prefix + 'hod'] = new Chart(document.getElementById(chartId(prefix, 'HodChart')), {
type: 'bar',
data: {
labels: hodValues.map(function (_, i) { return (i < 10 ? '0' : '') + i + ':00'; }),
datasets: [{
label: 'Avg gain per 5 min',
data: hodValues,
backgroundColor: hodValues.map(function (v) { return v >= 0 ? 'rgba(79,140,255,0.65)' : 'rgba(255,107,107,0.65)'; }),
backgroundColor: hodValues.map(function (v) { return v >= 0 ? accentBar : 'rgba(255,107,107,0.65)'; }),
borderRadius: 4
}]
},
@@ -959,7 +1042,7 @@ function renderCharts(points, deltas, smoothedDeltas) {
},
plugins: {
legend: { labels: { usePointStyle: true, boxWidth: 8, color: mutedColor() } },
tooltip: { callbacks: { label: function (item) { return fmtSigned(item.parsed.y) + ' Pages per 5 min (avg of ' + hodCount[item.dataIndex] + ' measurements)'; } } }
tooltip: { callbacks: { label: function (item) { return fmtSigned(item.parsed.y) + ' ' + unit + ' per 5 min (avg of ' + hodCount[item.dataIndex] + ' measurements)'; } } }
}
}
});
@@ -967,8 +1050,8 @@ function renderCharts(points, deltas, smoothedDeltas) {
/* ---------- records table ---------- */
function renderRecords(deltas) {
const el = document.getElementById('records');
function renderRecords(deltas, id, unit) {
const el = document.getElementById(id);
if (deltas.length < 2) {
el.innerHTML = '<div class="chart-sub">Not enough data yet.</div>';
return;
@@ -985,7 +1068,7 @@ function renderRecords(deltas) {
el.innerHTML =
'<table class="records">' +
'<tr><th>Time</th><th style="text-align:right">Change</th><th style="text-align:right">Span</th></tr>' +
'<tr><th>Time</th><th style="text-align:right">Change (' + unit + ')</th><th style="text-align:right">Span</th></tr>' +
rows(gains, 'pos') +
rows(losses, 'neg') +
'</table>';
@@ -993,8 +1076,8 @@ function renderRecords(deltas) {
/* ---------- heatmap ---------- */
function renderHeatmap(points) {
const el = document.getElementById('heatmap');
function renderHeatmap(points, id, unit) {
const el = document.getElementById(id);
if (!points.length) { el.innerHTML = ''; return; }
function localDayKey(d) {
@@ -1044,7 +1127,7 @@ function renderHeatmap(points) {
const op = maxAbs ? Math.min(0.85, 0.15 + 0.7 * Math.abs(dv) / maxAbs) : 0.3;
const color = dv >= 0 ? '46,204,113' : '255,107,107';
style = ' style="background:rgba(' + color + ',' + op.toFixed(2) + ')"';
title = fmtDay(new Date(day + 'T12:00:00').getTime()) + ' ' + h + ':00 – ' + fmtSigned(dv) + ' Pages (' + fmt(val) + ' total)';
title = fmtDay(new Date(day + 'T12:00:00').getTime()) + ' ' + h + ':00 – ' + fmtSigned(dv) + ' ' + unit + ' (' + fmt(val) + ' total)';
}
html += '<td><div class="cell"' + style + ' title="' + title + '"></div></td>';
}
@@ -1123,6 +1206,12 @@ function renderAll() {
setSigned('stat-per-day', perHour * 24);
}
const span6h = closestBefore(all, last.x - 6 * 3600000, Math.max(3 * intervalMs, 3600000));
setDeltaCard('stat-delta-6h', 'stat-delta-6h-hint',
span6h ? last.y - span6h.y : null,
span6h ? last.x - span6h.x : 0,
span6h ? (last.y - span6h.y) * (3600000 / Math.max(1, last.x - span6h.x)) * (5 / 60) : 0);
const span24h = closestBefore(all, last.x - 24 * 3600000, Math.max(6 * intervalMs, 3 * 3600000));
setDeltaCard('stat-delta-24h', 'stat-delta-24h-hint',
span24h ? last.y - span24h.y : null,
@@ -1217,9 +1306,55 @@ function renderAll() {
document.getElementById('footer').textContent = 'Forecast available once there are at least 2 measurements.';
}
renderCharts(fpoints, deltas, smoothedDeltas);
renderRecords(deltas);
renderHeatmap(all);
/* images: same graphs, but only exact measurements (every 2 h) */
const imageAll = toImagePoints(all);
const imageFpoints = filterRange(imageAll, last.x);
const imageDeltas = computeDeltas(imageFpoints).deltas;
const imageSmoothY = movingAverage(imageDeltas.map(function (d) { return d.y; }), DELTA_SMOOTH_WINDOW);
const imageSmoothedDeltas = imageDeltas.map(function (d, i) {
return { x: d.x, y: imageSmoothY[i], raw: d.y, dt: d.dt, diff: d.diff };
});
const imagesEmpty = document.getElementById('images-empty');
const hasImageValues = all.some(function (p) { return p.images !== null; });
if (!imageAll.length) {
imagesEmpty.textContent = hasImageValues
? 'Only estimated image counts so far – the graphs show exact counts only (every 2 h).'
: 'No image counts yet – they appear after the next collector run with the image migration in place.';
imagesEmpty.style.display = '';
} else if (!imageFpoints.length) {
imagesEmpty.textContent = 'No exact image counts in the selected range (counted every 2 h).';
imagesEmpty.style.display = '';
} else {
imagesEmpty.style.display = 'none';
}
destroyCharts();
renderCharts({
prefix: '',
points: fpoints,
deltas: deltas,
smoothedDeltas: smoothedDeltas,
unit: 'Pages',
accent: ACCENT,
accentBar: 'rgba(79,140,255,0.65)',
gradTop: 'rgba(79,140,255,0.28)',
gradBottom: 'rgba(79,140,255,0.02)'
});
renderCharts({
prefix: 'images',
points: imageFpoints,
deltas: imageDeltas,
smoothedDeltas: imageSmoothedDeltas,
unit: 'Images',
accent: ACCENT2,
accentBar: 'rgba(180,122,255,0.65)',
gradTop: 'rgba(180,122,255,0.28)',
gradBottom: 'rgba(180,122,255,0.02)'
});
renderRecords(deltas, 'records', 'Pages');
renderRecords(imageDeltas, 'records-images', 'Images');
renderHeatmap(all, 'heatmap', 'Pages');
renderHeatmap(imageAll, 'heatmap-images', 'Images');
}
async function update() {
+53
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@@ -129,6 +129,59 @@ class StatsPageTest(unittest.TestCase):
self.assertIn("Estimated · exact every 2 h", html)
self.assertIn("imagesExact", html)
def test_page_contains_6h_range_and_card(self):
client = stats_app.app.test_client()
response = client.get("/")
self.assertEqual(response.status_code, 200)
html = response.get_data(as_text=True)
self.assertIn('data-range="6h"', html)
self.assertIn('id="stat-delta-6h"', html)
self.assertIn('id="stat-delta-6h-hint"', html)
self.assertIn("'6h': 6 * 3600000", html)
self.assertIn("closestBefore(all, last.x - 6 * 3600000", html)
def test_page_contains_all_image_graphs(self):
client = stats_app.app.test_client()
response = client.get("/")
self.assertEqual(response.status_code, 200)
html = response.get_data(as_text=True)
self.assertIn("Images – all graphs", html)
for canvas in (
"imagesMainChart",
"imagesDeltaChart",
"imagesCumChart",
"imagesHourlyChart",
"imagesHodChart",
):
self.assertIn('id="' + canvas + '"', html)
self.assertIn('id="records-images"', html)
self.assertIn('id="heatmap-images"', html)
self.assertIn('id="images-empty"', html)
# the image series skips entries without an image count (old data)
# and only plots exact measurements - no estimates between the 2 h counts
self.assertIn("function toImagePoints(points)", html)
self.assertIn("p.images !== null && p.images !== undefined", html)
self.assertIn(".filter(function (p) { return p.imagesExact; })", html)
self.assertIn("only exact measurements are plotted (no estimates)", html)
self.assertIn("Only exact measurements (counted every 2 h) are plotted", html)
self.assertIn("Only estimated image counts so far", html)
self.assertIn("No exact image counts in the selected range", html)
# existing page chart ids must stay lowercase (mainChart, not MainChart)
self.assertIn("function chartId(prefix, suffix)", html)
self.assertIn("chartId(prefix, 'MainChart')", html)
# both series use the same time window (anchored to the latest page sample)
self.assertIn("filterRange(imageAll, last.x)", html)
# both metrics go through the same renderers, with the right units
self.assertIn("unit: 'Images'", html)
self.assertIn("unit: 'Pages'", html)
self.assertIn("renderRecords(deltas, 'records', 'Pages')", html)
self.assertIn("renderRecords(imageDeltas, 'records-images', 'Images')", html)
self.assertIn("renderHeatmap(all, 'heatmap', 'Pages')", html)
self.assertIn("renderHeatmap(imageAll, 'heatmap-images', 'Images')", html)
if __name__ == "__main__":
unittest.main(verbosity=2)
+341
View File
@@ -0,0 +1,341 @@
#!/usr/bin/env python3
"""
Tests für das Terminal-Dashboard (web/tui.py), ohne Terminal und ohne DB.
Geprüft werden Datei-Lesen, Zeitfenster, Sparkline, die Textdarstellung
und der Aufruf über die Kommandozeile (`--once`).
"""
import importlib.util
import json
import os
import subprocess
import sys
import tempfile
import unittest
from datetime import datetime, timedelta
HERE = os.path.dirname(os.path.abspath(__file__))
ROOT = os.path.dirname(HERE)
_spec = importlib.util.spec_from_file_location(
"jonassearch_stats_tui", os.path.join(HERE, "tui.py")
)
tui = importlib.util.module_from_spec(_spec)
_spec.loader.exec_module(tui)
try:
_stats_spec = importlib.util.spec_from_file_location(
"jonassearch_stats_app_for_tui", os.path.join(HERE, "app.py")
)
stats_app = importlib.util.module_from_spec(_stats_spec)
_stats_spec.loader.exec_module(stats_app)
except Exception: # z. B. Flask nicht installiert
stats_app = None
NOW = datetime(2026, 10, 17, 12, 0, 0)
def entry(timestamp, count, images=None, exact=None):
data = {"timestamp": timestamp.isoformat(), "count": count}
if images is not None:
data["images"] = images
if exact is not None:
data["images_exact"] = exact
return data
def sample_entries():
return [
entry(NOW - timedelta(hours=2), 980_000, images=100, exact=True),
entry(NOW - timedelta(hours=1), 981_000),
entry(NOW - timedelta(minutes=30), 981_950, images=120, exact=False),
]
def normalized(entries):
"""Rohdaten so aufbereiten, wie load_entries() sie liefert."""
result = []
for item in entries:
copy = dict(item)
copy["timestamp"] = tui.parse_timestamp(copy["timestamp"])
result.append(copy)
return result
class FormatTest(unittest.TestCase):
def test_fmt_int_uses_dots(self):
self.assertEqual(tui.fmt_int(987832), "987.832")
self.assertEqual(tui.fmt_int(None), "-")
def test_fmt_delta(self):
self.assertEqual(tui.fmt_delta(950), "+950")
self.assertEqual(tui.fmt_delta(-12), "-12")
self.assertEqual(tui.fmt_delta(0), "0")
self.assertEqual(tui.fmt_delta(None), "-")
def test_fmt_duration(self):
self.assertEqual(tui.fmt_duration(30), "30 s")
self.assertEqual(tui.fmt_duration(90), "1 min")
self.assertEqual(tui.fmt_duration(5400), "1 h 30 min")
self.assertEqual(tui.fmt_duration(90000), "1 d 1 h")
def test_samples_label(self):
self.assertEqual(tui._samples_label(1), "1 sample")
self.assertEqual(tui._samples_label(2), "2 samples")
def test_relative_time(self):
self.assertEqual(tui.relative_time(NOW, NOW), "just now")
self.assertEqual(
tui.relative_time(NOW - timedelta(minutes=3), NOW), "3 min ago"
)
class ParseTimestampTest(unittest.TestCase):
def test_iso_and_z(self):
self.assertEqual(
tui.parse_timestamp("2026-10-17T20:44:20.187761"),
datetime(2026, 10, 17, 20, 44, 20, 187761),
)
parsed = tui.parse_timestamp("2026-10-17T20:44:20Z")
self.assertIsNone(parsed.tzinfo)
self.assertEqual(
parsed,
datetime.fromisoformat("2026-10-17T20:44:20+00:00")
.astimezone().replace(tzinfo=None),
)
def test_invalid(self):
self.assertIsNone(tui.parse_timestamp("kaputt"))
self.assertIsNone(tui.parse_timestamp(""))
self.assertIsNone(tui.parse_timestamp(None))
class LoadEntriesTest(unittest.TestCase):
def setUp(self):
self.tmp = tempfile.TemporaryDirectory()
self.path = os.path.join(self.tmp.name, "page_counts.json")
def tearDown(self):
self.tmp.cleanup()
def _write(self, data):
with open(self.path, "w", encoding="utf-8") as handle:
if isinstance(data, str):
handle.write(data)
else:
json.dump(data, handle)
def test_missing_file_is_empty(self):
self.assertEqual(tui.load_entries(self.path), [])
def test_sorts_and_skips_bad_rows(self):
self._write([
entry(NOW, 20),
"kaputt",
{"timestamp": "kaputt", "count": 1},
{"timestamp": NOW.isoformat(), "count": "x"},
entry(NOW - timedelta(minutes=30), 10),
])
entries = tui.load_entries(self.path)
self.assertEqual([e["count"] for e in entries], [10, 20])
self.assertIsInstance(entries[0]["timestamp"], datetime)
def test_api_format_is_accepted(self):
self._write({"values": [entry(NOW, 5, images=7, exact=True)]})
entries = tui.load_entries(self.path)
self.assertEqual(len(entries), 1)
self.assertEqual(entries[0]["images"], 7)
self.assertTrue(entries[0]["images_exact"])
def test_invalid_images_becomes_none(self):
self._write([{"timestamp": NOW.isoformat(), "count": 1,
"images": "viele"}])
self.assertIsNone(tui.load_entries(self.path)[0]["images"])
def test_corrupt_json_raises(self):
self._write("{not json")
with self.assertRaises(tui.StatsDataError):
tui.load_entries(self.path)
def test_wrong_toplevel_type_raises(self):
self._write(42)
with self.assertRaises(tui.StatsDataError):
tui.load_entries(self.path)
class SharedScheduleTest(unittest.TestCase):
def test_exact_interval_matches_statserver(self):
if stats_app is None:
self.skipTest("web/app.py nicht importierbar (Flask fehlt)")
self.assertEqual(
tui.EXACT_IMAGE_INTERVAL, stats_app.EXACT_IMAGE_INTERVAL
)
class WindowTest(unittest.TestCase):
def test_window_filters_old_entries(self):
entries = normalized([
entry(NOW - timedelta(days=3), 1),
entry(NOW - timedelta(hours=1), 2),
])
self.assertEqual(
[e["count"] for e in tui.select_window(entries, "24h", NOW)], [2]
)
self.assertEqual(len(tui.select_window(entries, "all", NOW)), 2)
def test_latest_images_falls_back(self):
entries = normalized([
entry(NOW - timedelta(hours=1), 1, images=10, exact=True),
entry(NOW, 2),
])
images, exact, timestamp = tui.latest_images(entries)
self.assertEqual(images, 10)
self.assertTrue(exact)
self.assertEqual(timestamp, entries[0]["timestamp"])
def test_next_exact_text(self):
recent = normalized([
entry(NOW - timedelta(minutes=30), 1, images=1, exact=True)
])
self.assertEqual(
tui.next_exact_text(recent, NOW), "next exact in 1 h 30 min"
)
overdue = normalized([
entry(NOW - timedelta(hours=3), 1, images=1, exact=True)
])
self.assertEqual(
tui.next_exact_text(overdue, NOW), "exact count due now"
)
self.assertEqual(
tui.next_exact_text(normalized([entry(NOW, 1)]), NOW),
"no exact count yet",
)
class SparklineTest(unittest.TestCase):
def test_width_and_padding(self):
line = tui.sparkline([1, 2, 3], 10)
self.assertEqual(len(line), 10)
self.assertTrue(line.startswith(" "))
def test_single_sample(self):
self.assertEqual(tui.sparkline([5], 1), tui.SPARK_BLOCKS[4])
def test_increasing_values_use_increasing_blocks(self):
line = tui.sparkline([1, 2, 3, 4], 4)
indices = [tui.SPARK_BLOCKS.index(char) for char in line]
self.assertEqual(indices, sorted(indices))
def test_constant_values_do_not_crash(self):
self.assertEqual(tui.sparkline([7, 7, 7], 3), tui.SPARK_BLOCKS[4] * 3)
def test_empty(self):
self.assertEqual(tui.sparkline([], 10), "")
class RenderTest(unittest.TestCase):
def test_shows_numbers_and_hints(self):
lines = tui.render_dashboard(
normalized(sample_entries()), now=NOW, width=100
)
text = "\n".join(lines)
self.assertIn("Pages 981.950", text)
self.assertIn("Images 120", text)
self.assertIn("estimated", text)
self.assertIn("exact count due now", text)
self.assertIn("+950 since previous", text)
self.assertIn("q quit", text)
self.assertIn("t window (24h)", text)
self.assertIn("Recent samples", text)
def test_lines_fit_width(self):
for width in (32, 48, 60, 80):
lines = tui.render_dashboard(
normalized(sample_entries()), now=NOW, width=width, rows=24
)
for line in lines:
self.assertLessEqual(len(line), width, repr(line))
def test_row_budget_keeps_footer(self):
lines = tui.render_dashboard(
normalized(sample_entries()), now=NOW, width=80, rows=12
)
self.assertLessEqual(len(lines), 12)
self.assertIn("q quit", lines[-1])
def test_unreadable_file_error(self):
temp = tempfile.TemporaryDirectory()
self.addCleanup(temp.cleanup)
path = os.path.join(temp.name, "page_counts.json")
with open(path, "w", encoding="utf-8") as handle:
handle.write("{kaputt")
try:
tui.load_entries(path)
except tui.StatsDataError as exc:
lines = tui.render_dashboard([], now=NOW, width=90, error=str(exc))
else:
self.fail("StatsDataError erwartet")
self.assertIn("invalid JSON", "\n".join(lines))
self.assertIn("q quit", "\n".join(lines))
def test_empty_data(self):
text = "\n".join(tui.render_dashboard([], now=NOW, width=80))
self.assertIn("No samples yet", text)
class OnceModeTest(unittest.TestCase):
def setUp(self):
self.tmp = tempfile.TemporaryDirectory()
self.addCleanup(self.tmp.cleanup)
self.path = os.path.join(self.tmp.name, "page_counts.json")
with open(self.path, "w", encoding="utf-8") as handle:
json.dump(sample_entries(), handle)
def _run(self, *extra):
return subprocess.run(
[sys.executable, os.path.join(HERE, "tui.py"), "--once",
"--file", self.path, "--width", "100"] + list(extra),
capture_output=True,
text=True,
cwd=ROOT,
)
def test_once_prints_dashboard(self):
result = self._run()
self.assertEqual(result.returncode, 0, result.stderr)
self.assertIn("Pages", result.stdout)
self.assertIn("981.950", result.stdout)
self.assertIn("q quit", result.stdout)
def test_once_window_flag(self):
result = self._run("--window", "all", "--ascii")
self.assertEqual(result.returncode, 0, result.stderr)
self.assertIn("all data", result.stdout)
def test_once_corrupt_file_exits_nonzero(self):
with open(self.path, "w", encoding="utf-8") as handle:
handle.write("{kaputt")
result = self._run()
self.assertEqual(result.returncode, 1)
self.assertIn("error:", result.stderr)
def test_once_missing_file_is_empty_state(self):
os.unlink(self.path)
result = self._run()
self.assertEqual(result.returncode, 0, result.stderr)
self.assertIn("No samples yet", result.stdout)
if __name__ == "__main__":
unittest.main()
+640
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@@ -0,0 +1,640 @@
#!/usr/bin/env python3
"""
Terminal-Dashboard für den Statserver.
Liest dieselbe Datei wie `web/app.py` (`page_counts.json`) und zeigt
Seitenzahl, Bildanzahl, Wachstum, einen Sparkline-Verlauf und die
letzten Messwerte direkt im Terminal. Startet keinen Webserver und
benötigt keine zusätzlichen Pakete (nur curses aus der Standardlib).
Aufruf:
python3 web/tui.py # interaktiv (q beendet)
python3 web/tui.py --once # Momentaufnahme für Skripte/Logs
python3 web/tui.py --window 7d # 24h (Default) | 7d | 30d | all
"""
from __future__ import annotations
import argparse
import curses
import json
import locale
import shutil
import sys
import time
from datetime import datetime, timedelta
from pathlib import Path
DB_DATA = Path(__file__).parent / "page_counts.json"
# Muss zu EXACT_IMAGE_INTERVAL in web/app.py passen (dort per Test
# abgesichert): Bilder werden nur alle 2 Stunden exakt gezählt.
EXACT_IMAGE_INTERVAL = 2 * 60 * 60 # Sekunden
REFRESH_SECONDS = 2.0
DEFAULT_WINDOW = "24h"
WINDOWS = {
"24h": timedelta(hours=24),
"7d": timedelta(days=7),
"30d": timedelta(days=30),
"all": None,
}
WINDOW_ORDER = ("24h", "7d", "30d", "all")
WINDOW_LABELS = {
"24h": "last 24 h",
"7d": "last 7 days",
"30d": "last 30 days",
"all": "all data",
}
SPARK_BLOCKS = "▁▂▃▄▅▆▇█"
ASCII_BLOCKS = ".:-=+*#%"
TABLE_ROWS_ONCE = 15
class StatsDataError(Exception):
"""Die Statistikdatei fehlt nicht, ist aber nicht lesbar/parsebar."""
# --------------------------------------------------------------------------
# Daten
# --------------------------------------------------------------------------
def parse_timestamp(value):
"""ISO-Zeitstempel -> naive lokale datetime (oder None)."""
if not isinstance(value, str) or not value.strip():
return None
text = value.strip()
if text.endswith("Z"):
text = text[:-1] + "+00:00"
try:
timestamp = datetime.fromisoformat(text)
except ValueError:
return None
if timestamp.tzinfo is not None:
timestamp = timestamp.astimezone().replace(tzinfo=None)
return timestamp
def load_entries(path=DB_DATA):
"""
Messwerte laden, sortiert nach Zeitstempel.
Akzeptiert sowohl die Liste aus `page_counts.json` als auch das
Format der API (`{"values": [...]}`). Einträge ohne gültigen
Zeitstempel oder ohne Seitenzahl werden übersprungen.
"""
path = Path(path)
try:
raw = json.loads(path.read_text(encoding="utf-8"))
except FileNotFoundError:
return []
except OSError as exc:
raise StatsDataError(f"{path}: {exc}") from exc
except json.JSONDecodeError as exc:
raise StatsDataError(
f"{path}: invalid JSON (line {exc.lineno}: {exc.msg})"
) from exc
if isinstance(raw, dict):
raw = raw.get("values", [])
if not isinstance(raw, list):
raise StatsDataError(f"{path}: expected a JSON list of samples")
entries = []
for item in raw:
if not isinstance(item, dict):
continue
timestamp = parse_timestamp(item.get("timestamp"))
if timestamp is None:
continue
try:
count = int(item.get("count"))
except (TypeError, ValueError):
continue
entry = dict(item)
entry["timestamp"] = timestamp
entry["count"] = count
images = item.get("images")
if images is None:
entry["images"] = None
else:
try:
entry["images"] = int(images)
except (TypeError, ValueError):
entry["images"] = None
entries.append(entry)
entries.sort(key=lambda entry: entry["timestamp"])
return entries
def select_window(entries, window, now=None):
"""Nur Messwerte innerhalb des gewählten Zeitfensters."""
delta = WINDOWS.get(window, WINDOWS[DEFAULT_WINDOW])
if delta is None:
return list(entries)
now = now or datetime.now()
cutoff = now - delta
return [entry for entry in entries if entry["timestamp"] >= cutoff]
def latest_images(entries):
"""
(images, images_exact, timestamp) des neuesten Eintrags mit
Bildanzahl. Ältere Dateien haben kein `images`-Feld -> None.
"""
for entry in reversed(entries):
if entry.get("images") is not None:
return (
entry["images"],
entry.get("images_exact") is True,
entry["timestamp"],
)
return None, False, None
def next_exact_text(entries, now):
"""Wann die nächste exakte Bildzählung fällig ist."""
last_exact = None
for entry in reversed(entries):
if entry.get("images_exact") is True:
last_exact = entry["timestamp"]
break
if last_exact is None:
return "no exact count yet"
remaining = EXACT_IMAGE_INTERVAL - (now - last_exact).total_seconds()
if remaining <= 0:
return "exact count due now"
return f"next exact in {fmt_duration(remaining)}"
# --------------------------------------------------------------------------
# Formatierung
# --------------------------------------------------------------------------
def fmt_int(value):
if value is None:
return "-"
return f"{int(value):,}".replace(",", ".")
def fmt_delta(value):
if value is None:
return "-"
value = int(value)
if value == 0:
return "0"
if value > 0:
return "+" + fmt_int(value)
return "-" + fmt_int(abs(value))
def fmt_duration(seconds):
seconds = max(0, int(round(seconds)))
if seconds < 60:
return f"{seconds} s"
minutes = seconds // 60
if minutes < 60:
return f"{minutes} min"
hours, minutes = divmod(minutes, 60)
if hours < 24:
return f"{hours} h {minutes} min"
days, hours = divmod(hours, 24)
return f"{days} d {hours} h"
def relative_time(timestamp, now):
seconds = (now - timestamp).total_seconds()
if seconds < 5:
return "just now"
return f"{fmt_duration(seconds)} ago"
def sparkline(values, width, blocks=SPARK_BLOCKS):
"""Sparkline aus Zahlen; links mit Leerzeichen auf `width` aufgefüllt."""
if width <= 0 or not values:
return ""
values = list(values)[-width:]
low, high = min(values), max(values)
if high == low:
chars = [blocks[len(blocks) // 2]] * len(values)
else:
span = high - low
last = len(blocks) - 1
chars = [
blocks[min(last, int((value - low) / span * last + 0.5))]
for value in values
]
return " " * (width - len(values)) + "".join(chars)
def _fit(text, width):
return text[:max(0, width)]
def _samples_label(count):
return f"{count} sample" if count == 1 else f"{count} samples"
def _rate(window_entries):
"""Wachstum in Seiten pro Stunde (None bei < 2 Messwerten)."""
if len(window_entries) < 2:
return None
first, last = window_entries[0], window_entries[-1]
hours = (last["timestamp"] - first["timestamp"]).total_seconds() / 3600
if hours <= 0:
return None
return (last["count"] - first["count"]) / hours
def _deltas(entries):
"""Änderung der Seitenzahl gegenüber dem vorherigen Messwert."""
result = {}
previous = None
for entry in entries:
result[id(entry)] = (
None if previous is None else entry["count"] - previous
)
previous = entry["count"]
return result
def _time_label(timestamp, now, compact):
if compact:
return timestamp.strftime("%H:%M")
if timestamp.date() == now.date():
return timestamp.strftime("%H:%M")
return timestamp.strftime("%d.%m. %H:%M")
def _table_line(time_text, pages, delta, images, flag, compact):
if compact:
return (
f" {time_text:<6} {pages:>10} {delta:>8}"
f" {images:>6} {flag}"
)
return (
f" {time_text:<13} {pages:>12} {delta:>9}"
f" {images:>10} {flag}"
)
def _build_table(window_entries, delta_by_id, now, width, limit):
"""Neueste Messwerte zuerst; Kopfzeile als erste Zeile."""
compact = width < 62
header = _table_line(
"Time",
"Pages",
"Chg" if compact else "Change",
"Images",
"",
compact,
)
rows = []
newest_first = list(reversed(window_entries))
for entry in newest_first[:limit]:
flag = ""
if entry.get("images") is not None:
flag = "exact" if entry.get("images_exact") is True else "est."
rows.append(_table_line(
_time_label(entry["timestamp"], now, compact),
fmt_int(entry["count"]),
fmt_delta(delta_by_id.get(id(entry))),
fmt_int(entry.get("images")),
flag,
compact,
))
return header, rows
# --------------------------------------------------------------------------
# Darstellung
# --------------------------------------------------------------------------
def render_dashboard(entries, window=DEFAULT_WINDOW, now=None, width=80,
rows=None, source=None, error=None,
blocks=SPARK_BLOCKS):
"""
Dashboard als Liste von Textzeilen.
Reine Funktion ohne curses: dadurch testbar und auch für `--once`
bzw. Umleitungen nutzbar. `rows` begrenzt die Höhe (Terminal);
ohne Angabe werden bis zu 15 Messwerte angezeigt.
"""
now = now or datetime.now()
width = max(24, int(width))
source = str(source or DB_DATA)
lines = [_fit(" JonasSearch stats", width)]
if error:
lines.append("")
lines.append(_fit(f" ! {error}", width))
lines.append("")
lines.append(_fit(" q quit | r retry", width))
return lines[:rows] if rows else lines
if not entries:
lines.append("")
lines.append(_fit(" No samples yet.", width))
lines.append(_fit(f" Waiting for the collector to write {source}", width))
lines.append("")
lines.append(_fit(" q quit | r reload", width))
return lines[:rows] if rows else lines
latest = entries[-1]
previous = entries[-2] if len(entries) > 1 else None
delta = None if previous is None else latest["count"] - previous["count"]
window_entries = select_window(entries, window, now)
window_note = ""
if not window_entries:
window_entries = [latest]
window_note = " (no recent samples)"
rate = _rate(window_entries)
images, images_exact, images_ts = latest_images(entries)
lines.append(_fit(
f" updated {latest['timestamp']:%d.%m.%Y %H:%M:%S}"
f" ({relative_time(latest['timestamp'], now)})",
width,
))
lines.append("")
lines.append(_fit(f" Pages {fmt_int(latest['count'])}", width))
growth = [fmt_delta(delta) + " since previous" if delta is not None
else "first sample"]
if rate is not None:
growth.append(
f"{fmt_delta(round(rate))}/h over {WINDOW_LABELS[window]}"
f" ({_samples_label(len(window_entries))})"
)
lines.append(_fit(" " + " | ".join(growth), width))
lines.append("")
lines.append(_fit(f" Images {fmt_int(images)}", width))
if images is None:
images_detail = "not counted yet"
else:
kind = "exact" if images_exact else "estimated"
images_detail = (
f"{kind} | counted {images_ts:%H:%M} | exact every 2 h"
f" | {next_exact_text(entries, now)}"
)
lines.append(_fit(" " + images_detail, width))
lines.append("")
values = [entry["count"] for entry in window_entries]
low, high = min(values), max(values)
lines.append(_fit(
f" Pages | {WINDOW_LABELS[window]}{window_note}"
f" | {_samples_label(len(window_entries))}",
width,
))
range_text = f" ({fmt_int(low)} - {fmt_int(high)})"
spark_width = max(8, min(64, width - len(range_text) - 2))
spark = sparkline(values, spark_width, blocks)
lines.append(_fit(" " + spark + range_text, width))
delta_by_id = _deltas(entries)
footer = ["", _fit(
f" q quit | r reload | t window ({window}) | file: {source}",
width,
)]
if rows is None:
limit = TABLE_ROWS_ONCE
else:
# 3 Zeilen Overhead: Leerzeile, "Recent samples", Tabellenkopf
limit = max(0, rows - len(lines) - len(footer) - 3)
if limit > 0:
header, table = _build_table(
window_entries, delta_by_id, now, width, limit
)
lines += ["", _fit(" Recent samples", width), _fit(header, width)]
lines += [_fit(row, width) for row in table]
lines += footer
if rows is not None and len(lines) > rows:
# Sehr kleines Terminal: Kerninfo kürzen, Footer unten halten.
lines = lines[:max(0, rows - 1)] + [lines[-1]]
return lines
# --------------------------------------------------------------------------
# Interaktiv / einmalig
# --------------------------------------------------------------------------
def _blocks_for(args):
if args.ascii:
return ASCII_BLOCKS
encoding = (getattr(sys.stdout, "encoding", None) or "").lower()
return SPARK_BLOCKS if "utf" in encoding else ASCII_BLOCKS
def _render(args, entries, now, width, rows=None):
return render_dashboard(
entries,
window=args.window,
now=now,
width=width,
rows=rows,
source=args.file,
blocks=_blocks_for(args),
)
def emit_once(args, stream=None, errors=None):
"""Momentaufnahme ausgeben (kein curses). Rückgabe: Exit-Code."""
stream = stream or sys.stdout
errors = errors or sys.stderr
try:
entries = load_entries(args.file)
except StatsDataError as exc:
errors.write(f"error: {exc}\n")
return 1
width = args.width or shutil.get_terminal_size((80, 24)).columns
lines = _render(args, entries, datetime.now(), width)
stream.write("\n".join(lines) + "\n")
return 0
def next_window(window):
try:
index = WINDOW_ORDER.index(window)
except ValueError:
index = 0
return WINDOW_ORDER[(index + 1) % len(WINDOW_ORDER)]
def run_interactive(args):
try:
curses.wrapper(_interactive_loop, args)
except KeyboardInterrupt:
pass
except curses.error as exc:
print(
f"Terminal-Dashboard nicht möglich ({exc}); "
f"gebe Momentaufnahme aus.",
file=sys.stderr,
)
return emit_once(args)
return 0
def _interactive_loop(stdscr, args):
try:
curses.curs_set(0)
except curses.error:
pass
stdscr.timeout(max(50, int(args.interval * 1000)))
entries = []
error = None
loaded_at = 0.0
window = args.window
while True:
monotonic_now = time.monotonic()
if monotonic_now - loaded_at >= args.interval:
try:
entries = load_entries(args.file)
error = None
except StatsDataError as exc:
error = str(exc)
loaded_at = monotonic_now
height, width = stdscr.getmaxyx()
lines = render_dashboard(
entries,
window=window,
now=datetime.now(),
width=width,
rows=height,
source=args.file,
error=error,
blocks=_blocks_for(args),
)
stdscr.erase()
for index, line in enumerate(lines[:height]):
attributes = curses.A_BOLD if index == 0 else 0
try:
stdscr.addnstr(index, 0, line, max(0, width - 1), attributes)
except curses.error:
pass
stdscr.refresh()
key = stdscr.getch()
if key in (ord("q"), 27):
return
if key == ord("r"):
loaded_at = 0.0
elif key == ord("t"):
window = next_window(window)
def main(argv=None):
parser = argparse.ArgumentParser(
description=(
"Terminal-Dashboard für den Statserver "
"(liest web/page_counts.json)."
),
)
parser.add_argument(
"--file",
default=str(DB_DATA),
help=f"Statistikdatei (Default: {DB_DATA})",
)
parser.add_argument(
"--window",
choices=WINDOW_ORDER,
default=DEFAULT_WINDOW,
help="Zeitfenster für Verlauf und Tabelle (Default: 24h)",
)
parser.add_argument(
"--once",
action="store_true",
help="nur einmal ausgeben und beenden",
)
parser.add_argument(
"--width",
type=int,
default=None,
help="Breite für --once (Default: Terminalbreite)",
)
parser.add_argument(
"--interval",
type=float,
default=REFRESH_SECONDS,
help=f"Reload-Intervall in Sekunden (Default: {REFRESH_SECONDS})",
)
parser.add_argument(
"--ascii",
action="store_true",
help="ASCII-Sparkline statt Unicode-Blöcke",
)
args = parser.parse_args(argv)
try:
locale.setlocale(locale.LC_ALL, "")
except locale.Error:
pass
if args.once or not (sys.stdin.isatty() and sys.stdout.isatty()):
return emit_once(args)
return run_interactive(args)
if __name__ == "__main__":
sys.exit(main())