PiHoleLongTermStats

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PiHoleLongTermStats

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A dashboard to visualize DNS query data from a Pi-hole v.6 FTL database file.

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# Pi Hole Long Term Statistics v.0.2.7

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</div>

A dashboard built with **Dash** and **Plotly** to explore long-term DNS query data from **Pi-hole v.6** FTL database files. Visualize allowed vs blocked domains, top clients, and query trends over time. I originally made this for my own use, but if you find it useful, a ⭐ would be awesome!

**Disclaimer : This is an unofficial, third-party project. The Pi Hole team and the development of [PiHole](https://pi-hole.net/) software is not related to this project.**

See more [screenshots](https://github.com/davistdaniel/PiHoleLongTermStats/blob/main/screenshots/screenshots.md). (The screenshots use a mock database.)

## 🧰 Features
- ➕ Combine multiple databases and visualize consolidated stats.
- 🗂️ Info cards : Query stats, Activity stats, Day and Night stats. See [all supported metrics](https://github.com/davistdaniel/PiHoleLongTermStats?tab=readme-ov-file#supported-metrics).
- 📈 Interactive charts for query trends and client behavior, heatmaps showing day-hour stats, reply-times visualisation and more.
- 🔍 Filter queries by client.
- 🌐 View any number of top blocked/allowed domains, top clients.
- 📅 Analyze queries and compute stats over a custom date range and visualize them.
- ❌ Exclude domains using regex patterns before computing stats.

## 📦 Dependencies

- Python (>=3.11). See `requirements.txt` for dependencies.
- Pi-hole (> v.6) FTL database file (pihole-FTL.db)

## 🚀 Getting Started

> [!WARNING]
> Using your actual Pi-hole FTL db file for querying is **not** recommended and it is advised to use a copy. Place the copy in the project root or specify its path using the `--db_path` argument or `PIHOLE_LT_STATS_DB_PATH` environment variable. In any case, PiHoleLongTermStats does not monitor for changes in the Pi-hole FTL db file even if you mount it.

> [!TIP]
> There are multiple ways to run the dashboard: using Python or Docker.

<details>
<summary>Some more tips and notes. Click to expand.</summary>

* You can set up a cron job to periodically copy the FTL database to the `db_path` `PIHOLE_LT_STATS_DB_PATH` location. Use the reload button in the dashboard to refresh the stats.
  * Set your timezone (e.g "Europe/Berlin") using `--timezone` or `PIHOLE_LT_STATS_TIMEZONE`.
  * PiHoleLongTermStats reloads the Pi-hole FTL database and recalculates stats whenever the the reload button is clicked.
  * Refreshing the page uing the browser's refresh button, will always serve cached dashboard and data.
  * To update the dashboard with newer data from the database, you have to **manually** click the reload button (🔄) in the dashboard. Alternatively, you can restart the script or the docker container (using a cron job, for instance).
  * If no date range is selected during refresh, it uses the default period set by `--days` or `PIHOLE_LT_STATS_DAYS`. Large date ranges may lead to increased memory usage.
  * When multiple database files are provided, PiHoleLongTermStats concatenates them into a single dataframe and sorts the combined data by timestamp. Duplicate entries are **not** removed for calculating stats. Consolidating multiple databases can lead to increased memory usage.

</details>

## Installation

### Using Docker

<details>
<summary>Click to expand.</summary>

An example of docker compose file can be found [here](https://github.com/davistdaniel/PiHoleLongTermStats/blob/main/docker-compose.yml). 
See details about configurations options [here](https://github.com/davistdaniel/PiHoleLongTermStats/blob/main/docs/configuration_guide.md).

1. Make a directory for PiHoleLongtermStats:
    ```bash
    mkdir PiHoleLongTermStats
    cd PiHoleLongTermStats
    ```

2. Make a copy/backup of your `pihole-FTL.db` (**Important!**) and place it in the PiHoleLongTermStats directory:

```bash
   # Example: Copy from the default Pi-hole location
   sudo sqlite3 /etc/pihole/pihole-FTL.db ".backup ./pihole-FTL.db" 
   # Ensure the user running the app has read permissions
   sudo chown $USER:$USER pihole-FTL.db
   ```
3. Make a docker-compose.yml file in the same directory:
    
    ```docker
    services:
    pihole-long-term-stats:
        image: ghcr.io/davistdaniel/piholelongtermstats:latest
        container_name: pihole-lt-stats
        ports:
        - "9292:9292"  # Map host port to container port
        volumes:
        - ./:/db_dir  # Mount the directory containing your DB files, for instance if the pihole-FTL.db is in the same folder as the docker-compose file.
        # To include additional Pi-hole databases from other folders, mount them similarly:
        #- /path/to/other/folder:/db_dir_2
        environment:

# Configuration guide can be found on the github repository.

- PIHOLE_LT_STATS_DB_PATH=/db_dir/pihole-FTL.db  # Path inside the container to the mounted DB file
        - PIHOLE_LT_STATS_DAYS=31                     # Number of days from now of data to analyze; change if desired
        - PIHOLE_LT_STATS_PORT=9292                   # Port the app listens to inside container; keep in sync with ports mapping
        - PIHOLE_LT_STATS_NCLIENTS=10                 # Number of clients to show in top clients plots
        - PIHOLE_LT_STATS_NDOMAINS=10                 # Number of domains to show in top domains plots
        - PIHOLE_LT_STATS_TIMEZONE=UTC                # timezone for display
        - PIHOLE_LT_STATS_CLIENT_ID=hostname          # Client grouping and display criterion
        #- PIHOLE_LT_STATS_IGNORE_DOMAINS=.*\.local   # regex patterns for excluding domains. Example: to exclude all .local domains use .*\.local

# Provide multiple databases by listing their container paths as a
        # comma-separated string (databases in the same directory do not need additional volume mounts), e.g.:
        #- PIHOLE_LT_STATS_DB_PATH=/db_dir/pihole-FTL.db,/db_dir/pihole-FTL-2.db

# To ignore multiple domain patterns, separate each regex with a comma.
        # example definition below ignores: anything ending in .local, anything starting with ads, exactly example.com
        #- PIHOLE_LT_STATS_IGNORE_DOMAINS=.*\.local,^ads\.,^example\.com$

restart: unless-stopped

```
    and run using :

```bash
    sudo docker compose up -d
    ```
4. Open your browser and visit [http://localhost:9292](http://localhost:9292)
</details>

### Using Python

If installing using python, you can install from this git repo or as a package from PyPi.

#### Install from PyPi :

<details>
<summary>Click to expand.</summary>

1. Install PiHoleLongTermStats from PyPi

```bash
    python -m pip install piholelongtermstats
    ````

2. Make a directory for PiHoleLongtermStats (optional):

```bash
    mkdir PiHoleLongTermStats
    cd PiHoleLongTermStats
    ```

3. Make a copy/backup of your `pihole-FTL.db` (**Important!**) and place it in the PiHoleLongTermStats directory:

```bash
    piholelongtermstats [OPTIONS]
    ```
5. Open your browser and visit [http://localhost:9292](http://localhost:9292)

<details>
    <summary><b>Examples for python (Click to expand.)</b></summary>

To start the dashboard and visualize a single pihole-FTL database file for the last 15 days, with top 20 clients and top 15 domains on port 9292 while ingoring all domains which end with ".local":

```bash
    piholelongtermstats --db_path pihole-FTL.db --days 15 --n_clients 20 --n_domains 15 --port 9292 --ignore-domains ".*\.local"
    ```
    To combine two databases, provide paths as comma-separated strings:

```bash
    piholelongtermstats --db_path pihole-FTL.db,pihole-FTL-2.db
    ```
    To exclude multiple domains, provide comma-separated regex patterns:

```bash
    piholelongtermstats --ignore-domains ".*\.local,.*\.apple.com"
    ```
    </details>

</details>

#### Install from source :

<details>
<summary>Click to expand.</summary>

1. Clone this repository and move into the project folder:

```bash
    git clone https://github.com/davistdaniel/PiHoleLongTermStats.git
    cd PiHoleLongTermStats
    ```

2. Install dependencies using pip:

```bash
    pip install -r requirements.txt
    ```

3. Make a copy/backup of your `pihole-FTL.db` (**Important!**) and place it in the PiHoleLongTermStats directory:
    ```bash
    # Example: Copy from the default Pi-hole location
    sudo sqlite3 /etc/pihole/pihole-FTL.db ".backup ./pihole-FTL.db"
    # Ensure the user running the app has read permissions
    sudo chown $USER:$USER pihole-FTL.db 
    ```

4. Run the app:

```bash
    python piholelongtermstats/app.py [OPTIONS]
    ```

See the Configuration section below for available options.

5. Open your browser and visit [http://localhost:9292](http://localhost:9292)

<details>
    <summary><b>Examples for python (Click to expand.)</b></summary>

To start the dashboard and visualize a single pihole-FTL database file for the last 15 days, with top 20 clients and top 15 domains on port 9292 while ingoring all domains which end with ".local":

```bash
    python piholelongtermstats/app.py --db_path pihole-FTL.db --days 15 --n_clients 20 --n_domains 15 --port 9292 --ignore-domains ".*\.local"
    ```
    To combine two databases, provide paths as comma-separated strings:

```bash
    python piholelongtermstats/app.py --db_path pihole-FTL.db,pihole-FTL-2.db
    ```
    To exclude multiple domains, provide comma-separated regex patterns:

```bash
    python piholelongtermstats/app.py --ignore-domains ".*\.local,.*\.apple.com"
    ```
    </details>
</details>

### Using `uvx`:

For this to work, `uv` must be installed. If you only want to run the dashboard once or rarely:

```bash
uvx piholelongtermstats --db_path "pihole-FTL.db" --days 91
```

## ⚙️ Configuration

You can configure the app using command-line arguments or environment variables. For a detailed reference on all settings and configurations, see the [Configuration Guide](https://github.com/davistdaniel/PiHoleLongTermStats/blob/main/docs/configuration_guide.md).

| Command-Line Argument | Environment Variable         | Default Value   | Description                                      |
|-----------------------|------------------------------|-----------------|--------------------------------------------------|
| `--db_path`      | `PIHOLE_LT_STATS_DB_PATH`    | `pihole-FTL.db` | Path to the copied Pi-hole database file. Multiple databases can be combined by providing paths as comma-separated strings.        |
| `--days`         | `PIHOLE_LT_STATS_DAYS`       | `31`           | Number of days back from today to analyze.          |
| `--port`         | `PIHOLE_LT_STATS_PORT`       | `9292`          | Port number to serve the Dash app on.            |
| `--n_clients`         | `PIHOLE_LT_STATS_NCLIENTS`       | `10`          | Number of top clients to show in top clients plots.            |
| `--n_domains`         | `PIHOLE_LT_STATS_NDOMAINS`       | `10`          | Number of top domains to show in top domains plots.            |
| `--timezone`         | `PIHOLE_LT_STATS_TIMEZONE`       | `UTC`          | Timezone for displaying times in the dashboard.            |
| `--ignore-domains` | `PIHOLE_LT_STATS_IGNORE_DOMAINS` | `""` | Comma-separated regex patterns to exclude domains from stats (e.g. to exclude all `.local` domains, use `.*\.local`). |
| `--client_id`      | `PIHOLE_LT_STATS_CLIENT_ID`      | `hostname`      | Client grouping criterion (e.g., `hostname`, `mac`, `ip`, `hostname_mac`, `hostname_ip`, `mac_ip`). |

## 🧑‍💻 Contributing

Any contribution, feature ideas, documentation improvements or bug fixes are always welcome.
In case of new features, opening an issue and discussion before implementation is recommended.
This project uses uv for dependency management.

### Development workflow
* Clone the repository.

```bash
    git clone https://github.com/davistdaniel/PiHoleLongTermStats.git
    cd PiHoleLongTermStats
    ```
    
* From the project directory (with uv already installed), install dependencies:

```bash
    uv sync --extra develop
    ```
* Run the test suite:

```bash
    uv run python -m pytest tests/ -v -s --cov=piholelongtermstats --cov-report term-missing
    ```
* Make your changes.
* Submit a pull request.

## Supported metrics
| Metric | Description |
|--------|-------------|
| Allowed Queries | Total number of queries that were allowed through the Pi-hole. |
| Blocked Queries | Total number of queries that were blocked by the Pi-hole. |
| Top Allowed Domain | The domain which was allowed the most |
| Top Blocked Domain | The domain which was blocked the most |
| Total Unique Clients | The total number of unique devices that made queries. |
| Total Queries | Total number of queries processed by the Pi-hole. |
| Highest number of queries were on | The date with the peak query count. |
| Lowest number of queries were on | The date with the lowest query count. |
| Average reply time | The average time it takes for the Pi-hole to respond to a query. |
| Most Active Hour | The hour with the highest number of queries. |
| Least Active Hour | The hour with the lowest number of queries. |
| Most Active Day of the Week | The day with the highest query activity. |
| Least Active Day of the Week | The day with the lowest query activity. |
| Longest Blocking Streak | The longest consecutive period where queries were blocked. |
| Longest Allowing Streak | The longest consecutive period where queries were allowed. |
| Total queries during the day | Total number of queries made during daytime hours (06:00 to 23:59). |
| Total queries during the night | Total number of queries made during nighttime hours. |
| Top allowed domain during the day | The most allowed domain during the day. |
| Top blocked domain during the day | The most blocked domain during the day. |
| Top allowed domain during the night | The most allowed domain during the night. |
| Top blocked domain during the night | The most blocked domain during the night. |
| Most Persistent Client | The client that made the highest number of queries. |
| Most Diverse Client | The client that queried a blocked domain the most times. |
| Longest Idle Period | The longest period without any queries. |
| Slowest Responding Domain | The domain with the highest average response time. |
| Average Time Between Blocked Queries | Average interval between consecutive blocked queries. |
| Average Time Between Allowed Queries | Average interval between consecutive allowed queries. |

## 📄 License
[MIT](LICENSE)

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