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228 changed files with 278 additions and 2182 deletions

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@ -1,3 +0,0 @@
[flake8]
exclude = .git, .venv, output, static/icons
max-line-length = 160

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@ -1,151 +0,0 @@
name: CI
on:
push:
pull_request:
workflow_dispatch:
jobs:
ci:
name: Lint, test, and build
# This label must match your Forgejo runner's label
runs-on: docker
# Use a clean Debian container so tools are predictable
container: debian:stable-slim
env:
PYTHONDONTWRITEBYTECODE: "1"
PIP_DISABLE_PIP_VERSION_CHECK: "1"
UV_SYSTEM_PYTHON: "1"
steps:
- name: Install build tooling
run: |
set -euo pipefail
apt-get update
DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
git ca-certificates python3 python3-venv python3-pip python3-setuptools \
python3-wheel sqlite3
update-ca-certificates || true
- name: Checkout repository (manual)
run: |
set -euo pipefail
if [ -f Makefile ] || [ -d .git ]; then
echo "Repository present in workspace; skipping clone"
exit 0
fi
REMOTE_URL="${CI_REPOSITORY_URL:-}"
if [ -z "$REMOTE_URL" ]; then
if [ -n "${GITHUB_SERVER_URL:-}" ] && [ -n "${GITHUB_REPOSITORY:-}" ]; then
REMOTE_URL="${GITHUB_SERVER_URL%/}/${GITHUB_REPOSITORY}.git"
elif [ -n "${GITHUB_REPOSITORY:-}" ]; then
REMOTE_URL="https://git.jordanwages.com/${GITHUB_REPOSITORY}.git"
else
echo "Unable to determine repository URL from CI environment" >&2
exit 1
fi
fi
AUTH_URL="$REMOTE_URL"
if [ -n "${GITHUB_TOKEN:-}" ]; then
ACTOR="${GITHUB_ACTOR:-oauth2}"
AUTH_URL=$(printf '%s' "$REMOTE_URL" | sed -E "s#^https://#https://${ACTOR}:${GITHUB_TOKEN}@#")
fi
echo "Cloning from: $REMOTE_URL"
if ! git clone --depth 1 "$AUTH_URL" .; then
echo "Auth clone failed; trying anonymous clone..." >&2
git clone --depth 1 "$REMOTE_URL" .
fi
if [ -n "${GITHUB_SHA:-}" ]; then
git fetch --depth 1 origin "$GITHUB_SHA" || true
git checkout -q "$GITHUB_SHA" || true
elif [ -n "${GITHUB_REF_NAME:-}" ]; then
git fetch --depth 1 origin "$GITHUB_REF_NAME" || true
git checkout -q "$GITHUB_REF_NAME" || true
fi
- name: Set up venv and install deps
run: |
set -euo pipefail
# Prefer persistent cache if runner provides /cache
USE_CACHE=0
if [ -d /cache ] && [ -w /cache ]; then
export PIP_CACHE_DIR=/cache/pip
mkdir -p "$PIP_CACHE_DIR"
REQ_HASH=$(sha256sum requirements.txt | awk '{print $1}')
PYVER=$(python3 -c 'import sys;print(".".join(map(str, sys.version_info[:2])))')
CACHE_VENV="/cache/venv-${REQ_HASH}-py${PYVER}"
if [ ! -f "$CACHE_VENV/bin/activate" ]; then
echo "Preparing cached virtualenv: $CACHE_VENV"
rm -rf "$CACHE_VENV" || true
python3 -m venv "$CACHE_VENV"
fi
ln -sfn "$CACHE_VENV" .venv
USE_CACHE=1
else
# Fallback to local venv
python3 -m venv .venv
fi
# If the link didn't produce an activate file, fallback to local venv
if [ ! -f .venv/bin/activate ]; then
echo "Cached venv missing; creating local .venv"
rm -f .venv
python3 -m venv .venv
USE_CACHE=0
fi
. .venv/bin/activate
python -m pip install --upgrade pip
if [ "$USE_CACHE" = "1" ]; then
# Ensure required packages are present; pip will use cache
pip install -r requirements.txt pytest || pip install -r requirements.txt pytest
else
pip install -r requirements.txt pytest
fi
- name: Format check (black)
run: |
. .venv/bin/activate
black --check .
- name: Lint (flake8)
run: |
. .venv/bin/activate
flake8 .
- name: Run tests (pytest)
run: |
. .venv/bin/activate
export PYTHONPATH="$(pwd)${PYTHONPATH:+:$PYTHONPATH}"
pytest -q --maxfail=1
- name: Build sample reports (no artifact upload)
run: |
set -euo pipefail
. .venv/bin/activate
python - <<'PY'
import sqlite3, pathlib
db = pathlib.Path('database/ngxstat.db')
db.parent.mkdir(parents=True, exist_ok=True)
conn = sqlite3.connect(db)
cur = conn.cursor()
cur.execute('''CREATE TABLE IF NOT EXISTS logs (
id INTEGER PRIMARY KEY,
ip TEXT,
host TEXT,
time TEXT,
request TEXT,
status INTEGER,
bytes_sent INTEGER,
referer TEXT,
user_agent TEXT,
cache_status TEXT
)''')
cur.execute("INSERT INTO logs (ip, host, time, request, status, bytes_sent, referer, user_agent, cache_status) VALUES ('127.0.0.1','example.com','2024-01-01 10:00:00','GET / HTTP/1.1',200,100,'-','curl','MISS')")
cur.execute("INSERT INTO logs (ip, host, time, request, status, bytes_sent, referer, user_agent, cache_status) VALUES ('127.0.0.1','example.com','2024-01-01 10:05:00','GET /about HTTP/1.1',200,100,'-','curl','MISS')")
conn.commit(); conn.close()
PY
python scripts/generate_reports.py global
python scripts/generate_reports.py hourly
python scripts/generate_reports.py index
tar -czf ngxstat-reports.tar.gz -C output .
echo "Built sample reports archive: ngxstat-reports.tar.gz"

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@ -24,9 +24,6 @@ This document outlines general practices and expectations for AI agents assistin
The `run-import.sh` script can initialize this environment automatically.
Always activate the virtual environment before running scripts or tests.
* Before committing code run `black` for consistent formatting and execute
the test suite with `pytest`. All tests should pass.
* Dependency management: Use `requirements.txt` or `pip-tools`
* Use standard libraries where feasible (e.g., `sqlite3`, `argparse`, `datetime`)
* Adopt `typer` for CLI command interface (if CLI ergonomics matter)
@ -92,14 +89,6 @@ ngxstat/
If uncertain, the agent should prompt the human for clarification before making architectural assumptions.
## Testing
Use `pytest` for automated tests. Run the suite from an activated virtual environment and ensure all tests pass before committing:
```bash
pytest -q
```
---
## Future Capabilities
@ -117,4 +106,3 @@ As the project matures, agents may also:
* **2025-07-17**: Initial version by Jordan + ChatGPT
* **2025-07-17**: Expanded virtual environment usage guidance

148
README.md
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@ -1,16 +1,11 @@
# ngxstat
Per-domain Nginx log analytics with hybrid static reports and live insights.
`ngxstat` is a lightweight log analytics toolkit for Nginx. It imports access
logs into an SQLite database and renders static dashboards so you can explore
per-domain metrics without running a heavy backend service.
## Generating Reports
## Requirements
Use the `generate_reports.py` script to build aggregated JSON and HTML snippet files from `database/ngxstat.db`.
* Python 3.10+
* Access to the Nginx log files (default: `/var/log/nginx`)
The helper scripts create a virtual environment on first run, but you can also
set one up manually:
Create a virtual environment and install dependencies:
```bash
python3 -m venv .venv
@ -18,95 +13,118 @@ source .venv/bin/activate
pip install -r requirements.txt
```
Then run one or more of the interval commands:
```bash
python scripts/generate_reports.py hourly
python scripts/generate_reports.py daily
python scripts/generate_reports.py weekly
python scripts/generate_reports.py monthly
```
Each command accepts optional flags to generate per-domain reports. Use
`--domain <name>` to limit output to a specific domain or `--all-domains`
to generate a subdirectory for every domain found in the database:
```bash
# Hourly reports for example.com only
python scripts/generate_reports.py hourly --domain example.com
# Weekly reports for all domains individually
python scripts/generate_reports.py weekly --all-domains
```
Reports are written under the `output/` directory. Each command updates the corresponding `<interval>.json` file and writes one HTML snippet per report. These snippets are loaded dynamically by the main dashboard using Chart.js and DataTables.
### Configuring Reports
Report queries are defined in `reports.yml`. Each entry specifies the `name`,
optional `label` and `chart` type, and a SQL `query` that must return `bucket`
and `value` columns. The special token `{bucket}` is replaced with the
appropriate SQLite `strftime` expression for each interval (hourly, daily,
weekly or monthly) so that a single definition works across all durations.
When `generate_reports.py` runs, every definition is executed for the requested
interval and creates `output/<interval>/<name>.json` plus a small HTML snippet
`output/<interval>/<name>.html` used by the dashboard.
Example snippet:
```yaml
- name: hits
chart: bar
query: |
SELECT {bucket} AS bucket,
COUNT(*) AS value
FROM logs
GROUP BY bucket
ORDER BY bucket
```
Add or modify entries in `reports.yml` to tailor the generated metrics.
## Importing Logs
Run the importer to ingest new log entries into `database/ngxstat.db`:
Use the `run-import.sh` script to set up the Python environment if needed and import the latest Nginx log entries into `database/ngxstat.db`.
```bash
./run-import.sh
```
Rotated logs are processed in order and only entries newer than the last
imported timestamp are added.
This script is suitable for cron jobs as it creates the virtual environment on first run, installs dependencies and reuses the environment on subsequent runs.
## Generating Reports
The importer handles rotated logs in order from oldest to newest so entries are
processed exactly once. If you rerun the script, it only ingests records with a
timestamp newer than the latest one already stored in the database, preventing
duplicates.
To build the HTML dashboard and JSON data files use `run-reports.sh` which runs
all intervals in one go:
## Cron Report Generation
Use the `run-reports.sh` script to run all report intervals in one step. The script sets up the Python environment the same way as `run-import.sh`, making it convenient for automation via cron.
```bash
./run-reports.sh
```
The script calls `scripts/generate_reports.py` internally to create hourly,
daily, weekly and monthly reports, then writes analysis JSON files used by the
"Analysis" tab. Per-domain reports are written under `output/domains/<domain>`
alongside the aggregate data. Open `output/index.html` in a browser to view the
dashboard.
Running this script will create or update the hourly, daily, weekly and monthly reports under `output/`. It also detects all unique domains found in the database and writes per-domain reports to `output/domains/<domain>/<interval>` alongside the aggregate data. After generation, open `output/index.html` in your browser to browse the reports.
If you prefer to run individual commands you can invoke the generator directly:
```bash
python scripts/generate_reports.py hourly
python scripts/generate_reports.py daily --all-domains
```
## Log Analysis
## Analysis Helpers
`run-analysis.sh` executes additional utilities that examine the database for
missing domains, caching opportunities and potential threats. The JSON output is
saved under `output/analysis` and appears in the "Analysis" tab. The
`run-reports.sh` script also generates these JSON files as part of the build.
## UX Controls
The dashboard defaults to a 7day window for time series. Your view preferences
persist locally in the browser under the `ngxstat-state-v2` key. Use the
"Reset view" button to clear saved state and restore defaults.
The `run-analysis.sh` script runs helper routines that inspect the database. It
creates or reuses the virtual environment and then executes a set of analysis
commands to spot missing domains, suggest cache rules and detect potential
threats.
```bash
./run-analysis.sh
```
The JSON results are written under `output/analysis` and can be viewed from the
"Analysis" tab in the generated dashboard.
## Serving Reports with Nginx
## Serving the Reports
The generated files are static. You can serve them with a simple Nginx block:
To expose the generated HTML dashboards and JSON files over HTTP you can use a
simple Nginx server block. Point the `root` directive to the repository's
`output/` directory and optionally restrict access to your local network.
```nginx
server {
listen 80;
server_name example.com;
# Path to the generated reports
root /path/to/ngxstat/output;
location / {
try_files $uri $uri/ =404;
}
# Allow access only from private networks
allow 192.0.0.0/8;
allow 10.0.0.0/8;
deny all;
}
```
Restrict access if the reports should not be public.
With this configuration the generated static files are served directly by
Nginx while connections outside of `192.*` and `10.*` are denied.
## Running Tests
Install the development dependencies and execute the suite with `pytest`:
```bash
pip install -r requirements.txt
pytest -q
```
All tests must pass before submitting changes.
## Acknowledgements
ngxstat uses the following thirdparty resources:
* [Chart.js](https://www.chartjs.org/) for charts
* [DataTables](https://datatables.net/) and [jQuery](https://jquery.com/) for table views
* [Bulma CSS](https://bulma.io/) for styling
* Icons from [Free CC0 Icons](https://cc0-icons.jonh.eu/) by Jon Hicks (CC0 / MIT)
* [Typer](https://typer.tiangolo.com/) for the command-line interface
* [Jinja2](https://palletsprojects.com/p/jinja/) for templating
The project is licensed under the GPLv3. Icon assets remain in the public domain
via the CC0 license.

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@ -1,37 +1,28 @@
- name: hits
label: Hits
icon: pulse
chart: line
bucket: time_bucket
bucket_label: Time
query: |
SELECT {bucket} AS time_bucket,
SELECT {bucket} AS bucket,
COUNT(*) AS value
FROM logs
GROUP BY time_bucket
ORDER BY time_bucket
GROUP BY bucket
ORDER BY bucket
- name: error_rate
label: Error Rate (%)
icon: file-alert
chart: line
bucket: time_bucket
bucket_label: Time
query: |
SELECT {bucket} AS time_bucket,
SELECT {bucket} AS bucket,
SUM(CASE WHEN status BETWEEN 400 AND 599 THEN 1 ELSE 0 END) * 100.0 / COUNT(*) AS value
FROM logs
GROUP BY time_bucket
ORDER BY time_bucket
GROUP BY bucket
ORDER BY bucket
- name: cache_status_breakdown
label: Cache Status
icon: archive
chart: polarArea
bucket: cache_status
bucket_label: Cache Status
query: |
SELECT cache_status AS cache_status,
SELECT cache_status AS bucket,
COUNT(*) AS value
FROM logs
GROUP BY cache_status
@ -46,168 +37,78 @@
- name: domain_traffic
label: Top Domains
icon: globe
chart: table
top_n: 50
per_domain: false
bucket: domain
bucket_label: Domain
query: |
SELECT host AS domain,
SELECT host AS bucket,
COUNT(*) AS value
FROM logs
GROUP BY domain
GROUP BY host
ORDER BY value DESC
- name: bytes_sent
label: Bytes Sent
icon: upload
chart: line
bucket: time_bucket
bucket_label: Time
query: |
SELECT {bucket} AS time_bucket,
SELECT {bucket} AS bucket,
SUM(bytes_sent) AS value
FROM logs
GROUP BY time_bucket
ORDER BY time_bucket
GROUP BY bucket
ORDER BY bucket
- name: top_paths
label: Top Paths
icon: map
chart: table
top_n: 50
buckets:
- domain
- path
bucket_label:
- Domain
- Path
query: |
WITH paths AS (
SELECT host AS domain,
substr(substr(request, instr(request, ' ') + 1), 1,
SELECT path AS bucket,
COUNT(*) AS value
FROM (
SELECT substr(substr(request, instr(request, ' ') + 1), 1,
instr(substr(request, instr(request, ' ') + 1), ' ') - 1) AS path
FROM logs
), ranked AS (
SELECT domain, path, COUNT(*) AS value,
ROW_NUMBER() OVER (PARTITION BY domain ORDER BY COUNT(*) DESC) AS rn
FROM paths
GROUP BY domain, path
)
SELECT domain, path, value
FROM ranked
WHERE rn <= 20
ORDER BY domain, value DESC
GROUP BY path
ORDER BY value DESC
LIMIT 20
- name: user_agents
label: User Agents
icon: user
chart: table
top_n: 50
buckets:
- domain
- user_agent
bucket_label:
- Domain
- User Agent
query: |
WITH ua AS (
SELECT host AS domain, user_agent
FROM logs
), ranked AS (
SELECT domain, user_agent, COUNT(*) AS value,
ROW_NUMBER() OVER (PARTITION BY domain ORDER BY COUNT(*) DESC) AS rn
FROM ua
GROUP BY domain, user_agent
)
SELECT domain, user_agent, value
FROM ranked
WHERE rn <= 20
ORDER BY domain, value DESC
SELECT user_agent AS bucket,
COUNT(*) AS value
FROM logs
GROUP BY user_agent
ORDER BY value DESC
LIMIT 20
- name: referrers
label: Referrers
icon: link
chart: table
top_n: 50
buckets:
- domain
- referrer
bucket_label:
- Domain
- Referrer
query: |
WITH ref AS (
SELECT host AS domain, referer AS referrer
FROM logs
), ranked AS (
SELECT domain, referrer, COUNT(*) AS value,
ROW_NUMBER() OVER (PARTITION BY domain ORDER BY COUNT(*) DESC) AS rn
FROM ref
GROUP BY domain, referrer
)
SELECT domain, referrer, value
FROM ranked
WHERE rn <= 20
ORDER BY domain, value DESC
SELECT referer AS bucket,
COUNT(*) AS value
FROM logs
GROUP BY referer
ORDER BY value DESC
LIMIT 20
- name: status_distribution
label: HTTP Statuses
icon: server
chart: pie
bucket: status_group
bucket_label: Status
query: |
SELECT CASE
WHEN status BETWEEN 200 AND 299 THEN '2xx'
WHEN status BETWEEN 300 AND 399 THEN '3xx'
WHEN status BETWEEN 400 AND 499 THEN '4xx'
ELSE '5xx'
END AS status_group,
END AS bucket,
COUNT(*) AS value
FROM logs
GROUP BY status_group
ORDER BY status_group
GROUP BY bucket
ORDER BY bucket
colors:
- "#48c78e"
- "#209cee"
- "#ffdd57"
- "#f14668"
# New time-series: status classes over time (stacked)
- name: status_classes_timeseries
label: Status Classes Over Time
icon: server
chart: stackedBar
bucket: time_bucket
bucket_label: Time
stacked: true
query: |
SELECT {bucket} AS time_bucket,
SUM(CASE WHEN status BETWEEN 200 AND 299 THEN 1 ELSE 0 END) AS "2xx",
SUM(CASE WHEN status BETWEEN 300 AND 399 THEN 1 ELSE 0 END) AS "3xx",
SUM(CASE WHEN status BETWEEN 400 AND 499 THEN 1 ELSE 0 END) AS "4xx",
SUM(CASE WHEN status BETWEEN 500 AND 599 THEN 1 ELSE 0 END) AS "5xx",
COUNT(*) AS total
FROM logs
GROUP BY time_bucket
ORDER BY time_bucket
# New time-series: cache status over time (compact Hit/Miss; exclude '-' by default)
- name: cache_status_timeseries
label: Cache Status Over Time
icon: archive
chart: stackedBar
bucket: time_bucket
bucket_label: Time
stacked: true
exclude_values: ["-"]
query: |
SELECT {bucket} AS time_bucket,
SUM(CASE WHEN cache_status = 'HIT' THEN 1 ELSE 0 END) AS hit,
SUM(CASE WHEN cache_status = 'MISS' THEN 1 ELSE 0 END) AS miss,
COUNT(*) AS total
FROM logs
GROUP BY time_bucket
ORDER BY time_bucket

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@ -1,15 +1,6 @@
#!/usr/bin/env bash
set -e
# Prevent concurrent executions of this script.
LOCK_FILE="/tmp/$(basename "$0").lock"
if [ -e "$LOCK_FILE" ]; then
echo "[WARN] $(basename "$0") is already running (lock file present)." >&2
exit 0
fi
touch "$LOCK_FILE"
trap 'rm -f "$LOCK_FILE"' EXIT
# Ensure virtual environment exists
if [ ! -d ".venv" ]; then
echo "[INFO] Creating virtual environment..."

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@ -1,17 +1,6 @@
#!/usr/bin/env bash
set -e
# Prevent multiple simultaneous runs by using a lock file specific to this
# script. If the lock already exists, assume another instance is running and
# exit gracefully.
LOCK_FILE="/tmp/$(basename "$0").lock"
if [ -e "$LOCK_FILE" ]; then
echo "[WARN] $(basename "$0") is already running (lock file present)." >&2
exit 0
fi
touch "$LOCK_FILE"
trap 'rm -f "$LOCK_FILE"' EXIT
# Ensure virtual environment exists
if [ ! -d ".venv" ]; then
echo "[INFO] Creating virtual environment..."

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@ -1,15 +1,6 @@
#!/usr/bin/env bash
set -e
# Prevent concurrent executions of this script.
LOCK_FILE="/tmp/$(basename "$0").lock"
if [ -e "$LOCK_FILE" ]; then
echo "[WARN] $(basename "$0") is already running (lock file present)." >&2
exit 0
fi
touch "$LOCK_FILE"
trap 'rm -f "$LOCK_FILE"' EXIT
# Ensure virtual environment exists
if [ ! -d ".venv" ]; then
echo "[INFO] Creating virtual environment..."
@ -29,25 +20,21 @@ fi
# Generate reports for all domains combined
echo "[INFO] Generating aggregate reports..."
python -m scripts.generate_reports hourly
python -m scripts.generate_reports daily
python -m scripts.generate_reports weekly
python -m scripts.generate_reports monthly
python -m scripts.generate_reports global
python scripts/generate_reports.py hourly
python scripts/generate_reports.py daily
python scripts/generate_reports.py weekly
python scripts/generate_reports.py monthly
python scripts/generate_reports.py global
# Generate reports for each individual domain
echo "[INFO] Generating per-domain reports..."
python -m scripts.generate_reports hourly --all-domains
python -m scripts.generate_reports daily --all-domains
python -m scripts.generate_reports weekly --all-domains
python -m scripts.generate_reports monthly --all-domains
# Generate analysis JSON
echo "[INFO] Generating analysis files..."
python -m scripts.generate_reports analysis
python scripts/generate_reports.py hourly --all-domains
python scripts/generate_reports.py daily --all-domains
python scripts/generate_reports.py weekly --all-domains
python scripts/generate_reports.py monthly --all-domains
# Generate root index
python -m scripts.generate_reports index
python scripts/generate_reports.py index
# Deactivate to keep cron environment clean
if type deactivate >/dev/null 2>&1; then

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@ -18,7 +18,7 @@ from __future__ import annotations
import sqlite3
from pathlib import Path
from typing import List, Optional, Set
from typing import Dict, List, Optional, Set
from datetime import datetime, timedelta
import json
@ -105,9 +105,7 @@ def hits(domain: Optional[str] = typer.Option(None, help="Filter by domain")) ->
@app.command("cache-ratio")
def cache_ratio_cmd(
domain: Optional[str] = typer.Option(None, help="Filter by domain")
) -> None:
def cache_ratio_cmd(domain: Optional[str] = typer.Option(None, help="Filter by domain")) -> None:
"""Display cache hit ratio as a percentage."""
ratio = get_cache_ratio(domain) * 100
if domain:
@ -117,11 +115,7 @@ def cache_ratio_cmd(
@app.command("check-missing-domains")
def check_missing_domains(
json_output: bool = typer.Option(
False, "--json", help="Output missing domains as JSON"
)
) -> None:
def check_missing_domains(json_output: bool = typer.Option(False, "--json", help="Output missing domains as JSON")) -> None:
"""Show domains present in the database but absent from Nginx config."""
try:
from scripts.generate_reports import _get_domains as _db_domains
@ -155,9 +149,12 @@ def check_missing_domains(
typer.echo(d)
@app.command("suggest-cache")
def suggest_cache(
threshold: int = 10,
json_output: bool = False,
threshold: int = typer.Option(
10, help="Minimum number of MISS entries to report"
),
json_output: bool = typer.Option(False, "--json", help="Output results as JSON"),
) -> None:
"""Suggest domain/path pairs that could benefit from caching.
@ -190,7 +187,7 @@ def suggest_cache(
HAVING miss_count >= ?
ORDER BY miss_count DESC
""",
(int(threshold),),
(threshold,),
)
rows = [r for r in cur.fetchall() if r[0] in no_cache]
@ -210,18 +207,13 @@ def suggest_cache(
for item in result:
typer.echo(f"{item['host']} {item['path']} {item['misses']}")
@app.command("suggest-cache")
def suggest_cache_cli(
threshold: int = typer.Option(10, help="Minimum number of MISS entries to report"),
json_output: bool = typer.Option(False, "--json", help="Output results as JSON"),
) -> None:
"""CLI wrapper for suggest_cache."""
suggest_cache(threshold=threshold, json_output=json_output)
@app.command("detect-threats")
def detect_threats(
hours: int = 1,
ip_threshold: int = 100,
hours: int = typer.Option(1, help="Number of recent hours to analyze"),
ip_threshold: int = typer.Option(
100, help="Requests from a single IP to flag"
),
) -> None:
"""Detect potential security threats from recent logs."""
@ -237,8 +229,8 @@ def detect_threats(
max_dt = datetime.strptime(row[0], "%Y-%m-%d %H:%M:%S")
recent_end = max_dt
recent_start = recent_end - timedelta(hours=int(hours))
prev_start = recent_start - timedelta(hours=int(hours))
recent_start = recent_end - timedelta(hours=hours)
prev_start = recent_start - timedelta(hours=hours)
prev_end = recent_start
fmt = "%Y-%m-%d %H:%M:%S"
@ -324,7 +316,9 @@ def detect_threats(
""",
(recent_start_s, recent_end_s, ip_threshold),
)
high_ip_requests = [{"ip": ip, "requests": cnt} for ip, cnt in cur.fetchall()]
high_ip_requests = [
{"ip": ip, "requests": cnt} for ip, cnt in cur.fetchall()
]
conn.close()
@ -345,14 +339,6 @@ def detect_threats(
out_path.write_text(json.dumps(report, indent=2))
typer.echo(json.dumps(report))
@app.command("detect-threats")
def detect_threats_cli(
hours: int = typer.Option(1, help="Number of recent hours to analyze"),
ip_threshold: int = typer.Option(100, help="Requests from a single IP to flag"),
) -> None:
"""CLI wrapper for detect_threats."""
detect_threats(hours=hours, ip_threshold=ip_threshold)
if __name__ == "__main__":
app()

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@ -1,28 +0,0 @@
import json
from urllib.request import urlopen, Request
from pathlib import Path
ICON_LIST_URL = "https://cc0-icons.jonh.eu/icons.json"
BASE_URL = "https://cc0-icons.jonh.eu/"
OUTPUT_DIR = Path(__file__).resolve().parent.parent / "static" / "icons"
def main() -> None:
OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
req = Request(ICON_LIST_URL, headers={"User-Agent": "Mozilla/5.0"})
with urlopen(req) as resp:
data = json.load(resp)
icons = data.get("icons", [])
for icon in icons:
slug = icon.get("slug")
url = BASE_URL + icon.get("url")
path = OUTPUT_DIR / f"{slug}.svg"
req = Request(url, headers={"User-Agent": "Mozilla/5.0"})
with urlopen(req) as resp:
path.write_bytes(resp.read())
print(f"Downloaded {len(icons)} icons to {OUTPUT_DIR}")
if __name__ == "__main__":
main()

View file

@ -1,27 +1,17 @@
import json
import sys
import sqlite3
from pathlib import Path
import shutil
from typing import List, Dict, Optional
from datetime import datetime, timezone
import time
import yaml
import typer
from jinja2 import Environment, FileSystemLoader
# Ensure project root is importable when running as a script (python scripts/generate_reports.py)
PROJECT_ROOT = Path(__file__).resolve().parent.parent
if str(PROJECT_ROOT) not in sys.path:
sys.path.insert(0, str(PROJECT_ROOT))
DB_PATH = Path("database/ngxstat.db")
OUTPUT_DIR = Path("output")
TEMPLATE_DIR = Path("templates")
REPORT_CONFIG = Path("reports.yml")
GENERATED_MARKER = OUTPUT_DIR / "generated.txt"
# Mapping of interval names to SQLite strftime formats. These strings are
# substituted into report queries whenever the special ``{bucket}`` token is
@ -37,19 +27,6 @@ INTERVAL_FORMATS = {
app = typer.Typer(help="Generate aggregated log reports")
@app.callback()
def _cli_callback(ctx: typer.Context) -> None:
"""Register post-command hook to note generation time."""
def _write_marker() -> None:
OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
# Use timezone-aware UTC to avoid deprecation warnings and ambiguity
timestamp = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S")
GENERATED_MARKER.write_text(f"{timestamp}\n")
ctx.call_on_close(_write_marker)
def _get_domains() -> List[str]:
"""Return a sorted list of unique domains from the logs table."""
conn = sqlite3.connect(DB_PATH)
@ -77,20 +54,6 @@ def _save_json(path: Path, data: List[Dict]) -> None:
path.write_text(json.dumps(data, indent=2))
def _copy_icons() -> None:
"""Copy vendored icons and scripts to the output directory."""
src_dir = Path("static/icons")
dst_dir = OUTPUT_DIR / "icons"
if src_dir.is_dir():
dst_dir.mkdir(parents=True, exist_ok=True)
for icon in src_dir.glob("*.svg"):
shutil.copy(icon, dst_dir / icon.name)
js_src = Path("static/chartManager.js")
if js_src.is_file():
shutil.copy(js_src, OUTPUT_DIR / js_src.name)
def _render_snippet(report: Dict, out_dir: Path) -> None:
"""Render a single report snippet to ``<name>.html`` inside ``out_dir``."""
env = Environment(loader=FileSystemLoader(TEMPLATE_DIR))
@ -99,9 +62,7 @@ def _render_snippet(report: Dict, out_dir: Path) -> None:
snippet_path.write_text(template.render(report=report))
def _write_stats(
generated_at: Optional[str] = None, generation_seconds: Optional[float] = None
) -> None:
def _write_stats() -> None:
"""Query basic dataset stats and write them to ``output/global/stats.json``."""
conn = sqlite3.connect(DB_PATH)
cur = conn.cursor()
@ -125,10 +86,6 @@ def _write_stats(
"end_date": end_date,
"unique_domains": unique_domains,
}
if generated_at:
stats["generated_at"] = generated_at
if generation_seconds is not None:
stats["generation_seconds"] = generation_seconds
out_path = OUTPUT_DIR / "global" / "stats.json"
_save_json(out_path, stats)
@ -149,8 +106,6 @@ def _generate_interval(interval: str, domain: Optional[str] = None) -> None:
typer.echo("No report definitions found")
return
_copy_icons()
bucket = _bucket_expr(interval)
conn = sqlite3.connect(DB_PATH)
@ -185,16 +140,6 @@ def _generate_interval(interval: str, domain: Optional[str] = None) -> None:
name = definition["name"]
query = definition["query"].replace("{bucket}", bucket)
query = query.replace("FROM logs", "FROM logs_view")
# Apply top_n limit for tables (performance-friendly), if configured
top_n = definition.get("top_n")
chart_type = definition.get("chart", "line")
if top_n and chart_type == "table":
try:
n = int(top_n)
if "LIMIT" not in query.upper():
query = f"{query}\nLIMIT {n}"
except Exception:
pass
cur.execute(query)
rows = cur.fetchall()
headers = [c[0] for c in cur.description]
@ -208,38 +153,15 @@ def _generate_interval(interval: str, domain: Optional[str] = None) -> None:
"json": f"{name}.json",
"html": f"{name}.html",
}
if "icon" in definition:
entry["icon"] = definition["icon"]
if "bucket" in definition:
entry["bucket"] = definition["bucket"]
if "buckets" in definition:
entry["buckets"] = definition["buckets"]
if "bucket_label" in definition:
entry["bucket_label"] = definition["bucket_label"]
if "color" in definition:
entry["color"] = definition["color"]
if "colors" in definition:
entry["colors"] = definition["colors"]
# Optional UX metadata passthrough for frontend-only transforms
for key in (
"windows_supported",
"window_default",
"group_others_threshold",
"exclude_values",
"top_n",
"stacked",
"palette",
):
if key in definition:
entry[key] = definition[key]
_render_snippet(entry, out_dir)
report_list.append(entry)
_save_json(out_dir / "reports.json", report_list)
if domain:
typer.echo(f"Generated {interval} reports for {domain}")
else:
typer.echo(f"Generated {interval} reports")
typer.echo(f"Generated {interval} reports")
def _generate_all_domains(interval: str) -> None:
@ -250,10 +172,12 @@ def _generate_all_domains(interval: str) -> None:
def _generate_root_index() -> None:
"""Render the top-level index listing all intervals and domains."""
_copy_icons()
intervals = sorted(
[name for name in INTERVAL_FORMATS if (OUTPUT_DIR / name).is_dir()]
)
intervals = [
p.name
for p in OUTPUT_DIR.iterdir()
if p.is_dir() and p.name.lower() not in {"domains", "global"}
]
intervals.sort()
domains_dir = OUTPUT_DIR / "domains"
domains: List[str] = []
@ -277,12 +201,6 @@ def _generate_global() -> None:
typer.echo("No report definitions found")
return
start_time = time.time()
# Use timezone-aware UTC for generated_at (string remains unchanged format)
generated_at = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S")
_copy_icons()
conn = sqlite3.connect(DB_PATH)
cur = conn.cursor()
@ -296,16 +214,6 @@ def _generate_global() -> None:
name = definition["name"]
query = definition["query"]
# Apply top_n limit for tables (performance-friendly), if configured
top_n = definition.get("top_n")
chart_type = definition.get("chart", "line")
if top_n and chart_type == "table":
try:
n = int(top_n)
if "LIMIT" not in query.upper():
query = f"{query}\nLIMIT {n}"
except Exception:
pass
cur.execute(query)
rows = cur.fetchall()
headers = [c[0] for c in cur.description]
@ -319,67 +227,18 @@ def _generate_global() -> None:
"json": f"{name}.json",
"html": f"{name}.html",
}
if "icon" in definition:
entry["icon"] = definition["icon"]
if "bucket" in definition:
entry["bucket"] = definition["bucket"]
if "buckets" in definition:
entry["buckets"] = definition["buckets"]
if "bucket_label" in definition:
entry["bucket_label"] = definition["bucket_label"]
if "color" in definition:
entry["color"] = definition["color"]
if "colors" in definition:
entry["colors"] = definition["colors"]
# Optional UX metadata passthrough for frontend-only transforms
for key in (
"windows_supported",
"window_default",
"group_others_threshold",
"exclude_values",
"top_n",
"stacked",
"palette",
):
if key in definition:
entry[key] = definition[key]
_render_snippet(entry, out_dir)
report_list.append(entry)
_save_json(out_dir / "reports.json", report_list)
elapsed = round(time.time() - start_time, 2)
_write_stats(generated_at, elapsed)
_write_stats()
typer.echo("Generated global reports")
def _generate_analysis() -> None:
"""Generate analysis JSON files consumed by the Analysis tab."""
try:
# Import lazily to avoid circulars and keep dependencies optional
from scripts import analyze
except Exception as exc: # pragma: no cover - defensive
typer.echo(f"Failed to import analysis module: {exc}")
return
# Ensure output root and icons present for parity
_copy_icons()
# These commands write JSON files under output/analysis/
try:
analyze.check_missing_domains(json_output=True)
except Exception as exc: # pragma: no cover - continue best-effort
typer.echo(f"check_missing_domains failed: {exc}")
try:
analyze.suggest_cache(json_output=True)
except Exception as exc: # pragma: no cover
typer.echo(f"suggest_cache failed: {exc}")
try:
analyze.detect_threats()
except Exception as exc: # pragma: no cover
typer.echo(f"detect_threats failed: {exc}")
typer.echo("Generated analysis JSON files")
@app.command()
def hourly(
domain: Optional[str] = typer.Option(
@ -450,12 +309,6 @@ def global_reports() -> None:
_generate_global()
@app.command()
def analysis() -> None:
"""Generate analysis JSON files for the Analysis tab."""
_generate_analysis()
@app.command()
def index() -> None:
"""Generate the root index page linking all reports."""

View file

@ -61,9 +61,7 @@ try:
suffix = match.group(1)
number = int(suffix.lstrip(".")) if suffix else 0
log_files.append((number, os.path.join(LOG_DIR, f)))
log_files = [
path for _, path in sorted(log_files, key=lambda x: x[0], reverse=True)
]
log_files = [path for _, path in sorted(log_files, key=lambda x: x[0], reverse=True)]
except FileNotFoundError:
print(f"[ERROR] Log directory not found: {LOG_DIR}")
exit(1)

View file

@ -49,15 +49,7 @@ def discover_configs() -> Set[Path]:
found.add(path)
for pattern in INCLUDE_RE.findall(text):
pattern = os.path.expanduser(pattern.strip())
if os.path.isabs(pattern):
# ``Path.glob`` does not allow absolute patterns, so we
# anchor at the filesystem root and remove the leading
# separator.
base = Path(os.sep)
glob_iter = base.glob(pattern.lstrip(os.sep))
else:
glob_iter = path.parent.glob(pattern)
for included in glob_iter:
for included in path.parent.glob(pattern):
if included.is_file() and included not in found:
queue.append(included)
return found
@ -93,3 +85,4 @@ def parse_servers(paths: Set[Path]) -> List[Dict[str, str]]:
entry["root"] = " ".join(directives["root"])
servers.append(entry)
return servers

View file

@ -1,46 +0,0 @@
#!/usr/bin/env bash
set -e
# Default schedules
import_sched="*/5 * * * *"
report_sched="0 * * * *"
analysis_sched="0 0 * * *"
remove=false
usage() {
echo "Usage: $0 [--import CRON] [--reports CRON] [--analysis CRON] [--remove]"
}
while [ $# -gt 0 ]; do
case "$1" in
--import)
import_sched="$2"; shift 2;;
--reports)
report_sched="$2"; shift 2;;
--analysis)
analysis_sched="$2"; shift 2;;
--remove)
remove=true; shift;;
-h|--help)
usage; exit 0;;
*)
usage; exit 1;;
esac
done
repo_dir="$(cd "$(dirname "$0")" && pwd)"
if [ "$remove" = true ]; then
tmp=$(mktemp)
sudo crontab -l 2>/dev/null | grep -v "# ngxstat import" | grep -v "# ngxstat reports" | grep -v "# ngxstat analysis" > "$tmp" || true
sudo crontab "$tmp"
rm -f "$tmp"
echo "[INFO] Removed ngxstat cron entries"
exit 0
fi
cron_entries="${import_sched} cd ${repo_dir} && ./run-import.sh # ngxstat import\n${report_sched} cd ${repo_dir} && ./run-reports.sh # ngxstat reports\n${analysis_sched} cd ${repo_dir} && ./run-analysis.sh # ngxstat analysis"
( sudo crontab -l 2>/dev/null; echo -e "$cron_entries" ) | sudo crontab -
echo "[INFO] Installed ngxstat cron entries"

View file

@ -1,109 +0,0 @@
export let currentLoad = null;
const loadInfo = new Map();
export function newLoad(container) {
if (currentLoad) {
abortLoad(currentLoad);
}
reset(container);
const controller = new AbortController();
const token = { controller, charts: new Map() };
loadInfo.set(token, token);
currentLoad = token;
return token;
}
export function abortLoad(token) {
const info = loadInfo.get(token);
if (!info) return;
info.controller.abort();
info.charts.forEach(chart => {
try {
chart.destroy();
} catch (e) {}
});
loadInfo.delete(token);
if (currentLoad === token) {
currentLoad = null;
}
}
export function registerChart(token, id, chart) {
const info = loadInfo.get(token);
if (info) {
info.charts.set(id, chart);
} else {
chart.destroy();
}
}
export function reset(container) {
if (!container) return;
container.querySelectorAll('canvas').forEach(c => {
const chart = Chart.getChart(c);
if (chart) {
chart.destroy();
}
});
container.innerHTML = '';
}
// ---- Lightweight client-side data helpers ----
// Slice last N rows from a time-ordered array
export function sliceWindow(data, n) {
if (!Array.isArray(data) || n === undefined || n === null) return data;
if (n === 'all') return data;
const count = Number(n);
if (!Number.isFinite(count) || count <= 0) return data;
return data.slice(-count);
}
// Exclude rows whose value in key is in excluded list
export function excludeValues(data, key, excluded = []) {
if (!excluded || excluded.length === 0) return data;
const set = new Set(excluded);
return data.filter(row => !set.has(row[key]));
}
// Compute percentages for categorical distributions (valueKey default 'value')
export function toPercent(data, valueKey = 'value') {
const total = data.reduce((s, r) => s + (Number(r[valueKey]) || 0), 0);
if (total <= 0) return data.map(r => ({ ...r }));
return data.map(r => ({ ...r, [valueKey]: (Number(r[valueKey]) || 0) * 100 / total }));
}
// Group categories with share < threshold into an 'Other' bucket.
export function groupOthers(data, bucketKey, valueKey = 'value', threshold = 0.03, otherLabel = 'Other') {
if (!Array.isArray(data) || data.length === 0) return data;
const total = data.reduce((s, r) => s + (Number(r[valueKey]) || 0), 0);
if (total <= 0) return data;
const major = [];
let other = 0;
for (const r of data) {
const v = Number(r[valueKey]) || 0;
if (total && v / total < threshold) {
other += v;
} else {
major.push({ ...r });
}
}
if (other > 0) major.push({ [bucketKey]: otherLabel, [valueKey]: other });
return major;
}
// Simple moving average over numeric array
export function movingAverage(series, span = 3) {
const n = Math.max(1, Number(span) || 1);
const out = [];
for (let i = 0; i < series.length; i++) {
const start = Math.max(0, i - n + 1);
let sum = 0, cnt = 0;
for (let j = start; j <= i; j++) {
const v = Number(series[j]);
if (Number.isFinite(v)) { sum += v; cnt++; }
}
out.push(cnt ? sum / cnt : null);
}
return out;
}

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@ -1,4 +0,0 @@
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<path d="M8.5 12 6 22l6-2 6 2-2.5-10"/>
</svg>

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