semvec/pypi-packages huggingface dataset:
webnetwork 1.2.3
Automatic web server monitoring and defensive DoS/DDoS detection with blocking
License: MIT
Requires Python: >=3.8

# webnetwork

**webnetwork** is a Python package that automatically monitors your web server traffic, detects DoS/DDoS attacks, and blocks malicious IPs in real-time. It supports Linux, Windows, and macOS servers.

## Features

- Automatic host IP detection
- Web server log monitoring (Nginx, Apache)
- Live packet sniffing for TCP/SYN floods
- Automatic IP blocking (iptables on Linux/macOS, Windows firewall)
- Cross-platform support
- Minimal configuration required

## Installation

```bash
pip install webnetwork
```

## Usage

### Fully Automatic

Automatically detects logs and interfaces:

```python
import webnetwork

webnetwork.start()
```

### Specify Logfile or Network Interface

```python
import webnetwork

# Only monitor log file
webnetwork.start(logfile="/var/log/nginx/access.log")

# Only monitor network interface
webnetwork.start(iface="eth0")

# Monitor both
webnetwork.start(logfile="/var/log/nginx/access.log", iface="eth0")
```

### Notes

* Local blocking requires admin/root privileges.
* Automatically tries to detect common log files (`/var/log/nginx/access.log`, `/var/log/apache2/access.log`, `/var/log/httpd/access_log`).
* Live packet sniffing requires `scapy` and may need root/admin privileges.
* Monitors traffic continuously and logs alerts to `alerts.csv`.

## Configuration

Thresholds for detection can be tuned by modifying `detector.py`:

```python
LOG_CHECK_INTERVAL = 1.0
WINDOW_SECONDS = 10
REQS_PER_IP_THRESHOLD = 50
TOTAL_RPS_THRESHOLD = 200
UNIQUE_IP_ENTROPY_THRESHOLD = 0.5
SYN_RATE_THRESHOLD = 100
SYN_TO_ACK_RATIO = 5.0
```

## License

MIT License

## Author

HackingLab | Email : [hackinglab](mailto:mrfidal@proton.me) | GitHub : [webnetwork](https://github.com/bytebreach/webnetwork)
lgapp 1.0.0
LGApp: GUI for Labgrid
License: MIT
Requires Python: >=3.10

# LGApp
A web app that lets you pick and run tests via Labgrid's pytest plugin and generate HTML/PDF reports for test results.

## Features
- Pick a pytest file and run it with Labgrid
- View pytest HTML reports in the browser
- Download PDF versions

## Requirements
- Python 3.10+
- macOS/Linux (Not tested on Windows)

## Install
Open Terminal and run:
```bash
git clone https://github.com/danteppc/lgapp.git
cd lgapp
python3 -m venv .venv
source .venv/bin/activate
pip install -e .
```

## Run
Once installed, simply run:
```bash
lgapp
```
Then open http://localhost:8080

## Use
- Run tab: choose a `.py` test (defaults to `~/lgtest`, but you can browse anywhere)
- Tests run automatically; you'll be redirected to its report
- Reports tab: see all runs, view, download PDF, or delete

## Data & config locations
LGApp uses platform-appropriate user folders:
- Reports and DB are stored user data dir
- Labgrid environment config file: a default `lgconfig.yaml` is created in the user config dir on first run

## Screenshots

| Run Tests | Config Labgrid | Manage Reports |
| --- | --- | --- |
| ![Run page](imgs/1.png) | ![Config page](imgs/2.png) | ![Reports page](imgs/3.png) |
dash-ketcher 0.1
Dash Ketcher is a component allowing to use Ketcher molecules drawer in Dash.
License: MIT

# Dash Ketcher

### About Ketcher
Ketcher is an open-source web-based chemical structure editor available on https://lifescience.opensource.epam.com/ketcher/

### About Dash Ketcher
Dash Ketcher is a Dash component library, allowing to use Ketcher in Dash.

Currently, interactions include:
* output the current drawn structure as a SMILES string, 
* draw the structure corresponding to a provided SMILES string.

Other functionalities will be implemented later.



## Get started
All the commands below are given for a regular python installation on Linux-based systems,
and can be adapted to other systems or conda-based installation.

1. Create a local environment

   This step is optional but highly recommended to avoid conflicts with the base environment.
    ```
    $ virtualenv venv
    $ . venv/bin/activate
    ```
    _Note: venv\Scripts\activate for windows_

2. Install dash_ketcher

   Dash Ketcher can be installed from PyPI or Github repository.

   * From PyPi
      ```
      $ pip install dash_ketcher
      ```

   * From GitHub
      ```
      $ pip install git+https://dash_ketcher
      ```

3. Download Ketcher

   Download Ketcher's standalone version >= 3.2 and add it to your Dash project, e.g. in assets/

4. Adapt & use the code

   * Using the provided exemple
   
     1. Adapt `usage.py` with your local settings, notably with the path to your local Ketcher standalone
     2. Run `python usage.py`
     3. Visit http://localhost:8050 in your web browser to test it

   * Using your own code or Dash app

      Import dash_ketcher and use it as shown in `usage.py`

  

## Contributing
Everyone is welcome to contribute and send pull requests. 
This package was initially generated using the [dash-component-boilerplate](https://github.com/plotly/dash-component-boilerplate)



## Copyright
2025-present Philippe Gantzer