make dashboard

This commit is contained in:
lelo 2025-03-18 17:26:48 +00:00
parent e380ae25cb
commit 3fa915a9ce
8 changed files with 346 additions and 58 deletions

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app.py
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@ -9,9 +9,12 @@ from datetime import datetime, date, timedelta
from urllib.parse import unquote
import diskcache
import json
import geoip2.database
from werkzeug.middleware.proxy_fix import ProxyFix
cache = diskcache.Cache('./filecache', size_limit= 32 * 1024**3) # 32 GB limit
app = Flask(__name__)
app.wsgi_app = ProxyFix(app.wsgi_app, x_for=1, x_proto=1)
# Use a raw string for the default FILE_ROOT path.
app.config['FILE_ROOT'] = r'/mp3_root'
@ -199,16 +202,22 @@ def api_browse(subpath):
'files': files
})
@app.route("/access-log")
def lookup_location(ip, reader):
try:
response = reader.city(ip)
country = response.country.name if response.country.name else "Unknown"
city = response.city.name if response.city.name else "Unknown"
return country, city
except Exception:
return "Unknown", "Unknown"
@app.route("/dashboard")
@require_secret
def access_log():
# Get timeframe filter from query parameter; default to "today"
def dashboard():
timeframe = request.args.get('timeframe', 'today')
now = datetime.now()
# Determine the start time based on the requested timeframe
if timeframe == 'today':
# Beginning of today
start = now.replace(hour=0, minute=0, second=0, microsecond=0)
elif timeframe == '7days':
start = now - timedelta(days=7)
@ -217,12 +226,12 @@ def access_log():
elif timeframe == '365days':
start = now - timedelta(days=365)
else:
# Default to today if an unknown timeframe is passed
start = now.replace(hour=0, minute=0, second=0, microsecond=0)
# Query the access log database for file access counts since the 'start' time
conn = sqlite3.connect('access_log.db')
cursor = conn.cursor()
# Raw file access counts for the table (top files)
cursor.execute('''
SELECT full_path, COUNT(*) as access_count
FROM file_access_log
@ -231,9 +240,86 @@ def access_log():
ORDER BY access_count DESC
''', (start.isoformat(),))
rows = cursor.fetchall()
# Daily access trend for a line chart
cursor.execute('''
SELECT date(timestamp) as date, COUNT(*) as count
FROM file_access_log
WHERE timestamp >= ?
GROUP BY date
ORDER BY date
''', (start.isoformat(),))
daily_access_data = [dict(date=row[0], count=row[1]) for row in cursor.fetchall()]
# Top files for bar chart (limit to 10)
cursor.execute('''
SELECT full_path, COUNT(*) as access_count
FROM file_access_log
WHERE timestamp >= ?
GROUP BY full_path
ORDER BY access_count DESC
LIMIT 10
''', (start.isoformat(),))
top_files_data = [dict(full_path=row[0], access_count=row[1]) for row in cursor.fetchall()]
# User agent distribution (limit to 10)
cursor.execute('''
SELECT user_agent, COUNT(*) as count
FROM file_access_log
WHERE timestamp >= ?
GROUP BY user_agent
ORDER BY count DESC
LIMIT 10
''', (start.isoformat(),))
user_agent_data = [dict(user_agent=row[0], count=row[1]) for row in cursor.fetchall()]
# Referrer distribution (limit to 10)
cursor.execute('''
SELECT referrer, COUNT(*) as count
FROM file_access_log
WHERE timestamp >= ?
GROUP BY referrer
ORDER BY count DESC
LIMIT 10
''', (start.isoformat(),))
referrer_data = [dict(referrer=row[0] if row[0] else "Direct/None", count=row[1]) for row in cursor.fetchall()]
# Aggregate IP addresses with counts
cursor.execute('''
SELECT ip_address, COUNT(*) as count
FROM file_access_log
WHERE timestamp >= ?
GROUP BY ip_address
ORDER BY count DESC
''', (start.isoformat(),))
ip_rows = cursor.fetchall()
# Initialize GeoIP2 reader once for efficiency
reader = geoip2.database.Reader('GeoLite2-City.mmdb')
ip_data = []
for ip, count in ip_rows:
country, city = lookup_location(ip, reader)
ip_data.append(dict(ip=ip, count=count, country=country, city=city))
reader.close()
# Summary stats
total_accesses = sum([row[1] for row in rows])
unique_files = len(rows)
cursor.execute('SELECT COUNT(DISTINCT ip_address) FROM file_access_log WHERE timestamp >= ?', (start.isoformat(),))
unique_ips = cursor.fetchone()[0]
conn.close()
return render_template("access_log.html", rows=rows, timeframe=timeframe)
return render_template("dashboard.html",
timeframe=timeframe,
rows=rows,
daily_access_data=daily_access_data,
top_files_data=top_files_data,
user_agent_data=user_agent_data,
referrer_data=referrer_data,
ip_data=ip_data,
total_accesses=total_accesses,
unique_files=unique_files,
unique_ips=unique_ips)
def log_file_access(full_path):
"""
@ -278,8 +364,10 @@ def serve_file(filename):
app.logger.error(f"File not found: {full_path}")
return "File not found", 404
# Exclude HEAD requests from logging
if request.method != 'HEAD':
# HEAD request are coming in to initiate server caching.
# only log initial hits and not the reload of further file parts
range_header = request.headers.get('Range')
if request.method != 'HEAD' and (not range_header or range_header.startswith("bytes=0-")):
log_file_access(full_path)
mime, _ = mimetypes.guess_type(full_path)

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@ -8,7 +8,12 @@ services:
- ./:/app
- ./filecache:/app/filecache
- ./templates:/app/templates
- /mnt/app.bethaus:/mp3_root:ro
- ./GeoLite2-City.mmdb:/app/GeoLite2-City.mmdb:ro
- type: bind
source: /mnt/app.bethaus
target: /mp3_root
bind:
propagation: rshared
environment:
- FLASK_APP=app.py
- FLASK_RUN_HOST=0.0.0.0

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@ -1,3 +1,4 @@
flask
pillow
diskcache
geoip2

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@ -119,6 +119,8 @@ function attachEventListeners() {
const newPath = this.getAttribute('data-path');
loadDirectory(newPath);
history.pushState({ subpath: newPath }, '', newPath ? '/path/' + newPath : '/');
// Scroll to the top of the page after click:
window.scrollTo({ top: 0, behavior: 'smooth' });
});
});

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@ -15,12 +15,12 @@ body {
display: grid;
grid-template-rows: auto 1fr auto;
min-height: 100%;
padding-bottom: 200px;
}
.container {
width: 90%;
max-width: 900px;
margin: 0 auto;
padding-bottom: 200px;
}
.container a {

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@ -1,46 +0,0 @@
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>File Access Log</title>
<style>
body { font-family: Arial, sans-serif; margin: 20px; }
table, th, td { border: 1px solid #ccc; border-collapse: collapse; padding: 8px; }
th { background-color: #f2f2f2; }
.btn { margin: 5px; padding: 8px 12px; text-decoration: none; background-color: #4CAF50; color: white; border-radius: 4px; }
.btn:hover { background-color: #45a049; }
.box { margin: 15px 0; }
</style>
</head>
<body>
<h1>File Access Log ({{ timeframe }})</h1>
<div class="box">
<a href="{{ url_for('access_log', timeframe='today') }}" class="btn">Today</a>
<a href="{{ url_for('access_log', timeframe='7days') }}" class="btn">Last 7 Days</a>
<a href="{{ url_for('access_log', timeframe='30days') }}" class="btn">Last 30 Days</a>
<a href="{{ url_for('access_log', timeframe='365days') }}" class="btn">Last 365 Days</a>
</div>
<div class="box">
<table>
<thead>
<tr>
<th>File Path</th>
<th>Access Count</th>
</tr>
</thead>
<tbody>
{% for row in rows %}
<tr>
<td>{{ row[0] }}</td>
<td>{{ row[1] }}</td>
</tr>
{% else %}
<tr>
<td colspan="2">No data available for the selected timeframe.</td>
</tr>
{% endfor %}
</tbody>
</table>
</div>
</body>
</html>

238
templates/dashboard.html Normal file
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@ -0,0 +1,238 @@
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Web Analytics Dashboard</title>
<!-- Using Bootstrap for responsive layout -->
<link href="https://cdn.jsdelivr.net/npm/bootstrap@5.0.2/dist/css/bootstrap.min.css" rel="stylesheet">
<style>
body { margin: 20px; }
.card { margin-bottom: 20px; }
canvas { max-width: 100%; }
</style>
</head>
<body>
<div class="container">
<h1 class="mb-4">Web Analytics Dashboard ({{ timeframe }})</h1>
<!-- Timeframe selection buttons -->
<div class="mb-3">
<a href="{{ url_for('index') }}" class="btn btn-primary">Home</a>
<a href="{{ url_for('dashboard', timeframe='today') }}" class="btn btn-primary">Today</a>
<a href="{{ url_for('dashboard', timeframe='7days') }}" class="btn btn-primary">Last 7 Days</a>
<a href="{{ url_for('dashboard', timeframe='30days') }}" class="btn btn-primary">Last 30 Days</a>
<a href="{{ url_for('dashboard', timeframe='365days') }}" class="btn btn-primary">Last 365 Days</a>
</div>
<!-- Summary Cards -->
<div class="row mb-4">
<div class="col-md-4">
<div class="card text-white bg-info">
<div class="card-body">
<h5 class="card-title">Total Accesses</h5>
<p class="card-text">{{ total_accesses }}</p>
</div>
</div>
</div>
<div class="col-md-4">
<div class="card text-white bg-success">
<div class="card-body">
<h5 class="card-title">Unique Files</h5>
<p class="card-text">{{ unique_files }}</p>
</div>
</div>
</div>
<div class="col-md-4">
<div class="card text-white bg-warning">
<div class="card-body">
<h5 class="card-title">Unique IPs</h5>
<p class="card-text">{{ unique_ips }}</p>
</div>
</div>
</div>
</div>
<!-- Charts Section -->
<div class="row">
<!-- Access Trend Chart -->
<div class="col-md-6 mb-4">
<div class="card">
<div class="card-body">
<h5 class="card-title">Access Trend</h5>
<canvas id="accessTrendChart"></canvas>
</div>
</div>
</div>
<!-- Top Files Accessed Chart -->
<div class="col-md-6 mb-4">
<div class="card">
<div class="card-body">
<h5 class="card-title">Top Files Accessed</h5>
<canvas id="topFilesChart"></canvas>
</div>
</div>
</div>
<!-- User Agent Distribution Chart -->
<div class="col-md-6 mb-4">
<div class="card">
<div class="card-body">
<h5 class="card-title">User Agent Distribution</h5>
<canvas id="userAgentChart"></canvas>
</div>
</div>
</div>
<!-- Referrer Distribution Chart -->
<div class="col-md-6 mb-4">
<div class="card">
<div class="card-body">
<h5 class="card-title">Referrer Distribution</h5>
<canvas id="referrerChart"></canvas>
</div>
</div>
</div>
</div>
<!-- Detailed Table of Top File Accesses -->
<div class="card mb-4">
<div class="card-header">
Detailed File Access Data
</div>
<div class="card-body">
<table class="table table-striped">
<thead>
<tr>
<th>File Path</th>
<th>Access Count</th>
</tr>
</thead>
<tbody>
{% for row in rows %}
<tr>
<td>{{ row[0] }}</td>
<td>{{ row[1] }}</td>
</tr>
{% else %}
<tr>
<td colspan="2">No data available for the selected timeframe.</td>
</tr>
{% endfor %}
</tbody>
</table>
</div>
</div>
<!-- New Section: IP Address Access Data -->
<div class="card">
<div class="card-header">
IP Address Access Distribution
</div>
<div class="card-body">
<table class="table table-bordered">
<thead>
<tr>
<th>IP Address</th>
<th>Access Count</th>
<th>City</th>
<th>Country</th>
</tr>
</thead>
<tbody>
{% for ip in ip_data %}
<tr>
<td>{{ ip.ip }}</td>
<td>{{ ip.count }}</td>
<td>{{ ip.city }}</td>
<td>{{ ip.country }}</td>
</tr>
{% else %}
<tr>
<td colspan="4">No IP access data available for the selected timeframe.</td>
</tr>
{% endfor %}
</tbody>
</table>
</div>
</div>
</div>
<!-- Load Chart.js from CDN -->
<script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
<script>
// Data passed from the backend as JSON
const dailyAccessData = {{ daily_access_data|tojson }};
const topFilesData = {{ top_files_data|tojson }};
const userAgentData = {{ user_agent_data|tojson }};
const referrerData = {{ referrer_data|tojson }};
// Access Trend Chart - Line Chart
const ctxTrend = document.getElementById('accessTrendChart').getContext('2d');
new Chart(ctxTrend, {
type: 'line',
data: {
labels: dailyAccessData.map(item => item.date),
datasets: [{
label: 'Access Count',
data: dailyAccessData.map(item => item.count),
borderWidth: 2,
fill: true
}]
},
options: {
responsive: true,
plugins: { legend: { position: 'top' } },
scales: {
x: { title: { display: true, text: 'Date' } },
y: { title: { display: true, text: 'Access Count' } }
}
}
});
// Top Files Chart - Horizontal Bar Chart
const ctxTopFiles = document.getElementById('topFilesChart').getContext('2d');
new Chart(ctxTopFiles, {
type: 'bar',
data: {
labels: topFilesData.map(item => item.full_path),
datasets: [{
label: 'Access Count',
data: topFilesData.map(item => item.access_count),
borderWidth: 1
}]
},
options: {
indexAxis: 'y',
responsive: true,
plugins: { legend: { display: false } },
scales: {
x: { title: { display: true, text: 'Access Count' } },
y: { title: { display: true, text: 'File Path' } }
}
}
});
// User Agent Distribution - Pie Chart
const ctxUserAgent = document.getElementById('userAgentChart').getContext('2d');
new Chart(ctxUserAgent, {
type: 'pie',
data: {
labels: userAgentData.map(item => item.user_agent),
datasets: [{
data: userAgentData.map(item => item.count)
}]
},
options: { responsive: true }
});
// Referrer Distribution - Pie Chart
const ctxReferrer = document.getElementById('referrerChart').getContext('2d');
new Chart(ctxReferrer, {
type: 'pie',
data: {
labels: referrerData.map(item => item.referrer),
datasets: [{
data: referrerData.map(item => item.count)
}]
},
options: { responsive: true }
});
</script>
</body>
</html>