semvec/pypi-packages huggingface dataset:
prjct-harpy 2020.9.17
Harpy who is using ARP
Requires Python: >=3.6

# hARPy

Active/passive ARP discovery tool.

---

# Features

- Suspicious packet detection.
- Active or passive scan option.
- Ability to send packets from a fake IP address.
- Option to determine the amount of ARP requests to be sent.
- Option to determine the sleep time between each ARP request.

---

# Supported Platforms

Linux only.

---

# Preparation (APT)

```shell script
# apt update
# apt install python3 python3-pip
```

---

# Installation

```shell script
# pip3 install project-harpy
```

---

# Upgrade

```shell script
# pip3 install --upgrade project-harpy
```

---

# Usage

```shell script
# harpy -h
```
```
usage: harpy [-h] [-c count] [-i interface] [-n node] [-p] -r range [-s sleep] [-v]

Written by Serhat Celik <prjctsrht@gmail.com>

optional arguments:
  -h, --help    show this help message and exit
  -c count      number of times to send each arp request (default: 1)
  -i interface  the network device to send/sniff packets (default: first available)
  -n node       last ip octet to be used to send packets (default: 43)
  -p            enable passive mode, do not send any packets
  -s sleep      time to sleep between each arp request in ms (default: 3)
  -v            show program version and exit

required arguments:
  -r range      scan a given range, e.g. 192.168.2.1/24 (valid: /8, /16, /24)

Use at your own risk!
```

---

# Examples

```shell script
# harpy -r 192.168.2.1/24
```
```
|_  _  _ _      | TOTAL HOST: 3
| |(_|| |_)\/   | TOTAL REQ.: 2
        |  /    | TOTAL REP.: 2
-----------------------------------------------------------------------------------------------------
IP ADDRESS      | ETH MAC ADDRESS   | ARP MAC ADDRESS   | REQ.   | REP.   | VENDOR
-----------------------------------------------------------------------------------------------------
192.168.2.1     | 18:28:61:xx:xx:xx | 18:28:61:xx:xx:xx | 0      | 1      | airties wireless networks
192.168.2.80    | 18:28:61:xx:xx:xx | 18:28:61:xx:xx:xx | 1      | 1      | airties wireless networks
192.168.2.240   | c8:60:00:xx:xx:xx | 18:28:61:xx:xx:xx | 1      | 0      | asustek computer inc.
```

---

# Uninstallation

```shell script
# pip3 uninstall project-harpy
```

---

# Contact

If you find a bug or have a suggestion, please consider [creating an issue](https://github.com/serhatcelik/hARPy/issues) to contact with me.
django-updown-ratings 1.0.1
Reusable Django application for youtube like up and down voting.

# django-updown-ratings

> Simple Django application for adding Youtube like up and down voting. \
> This [`django-updown-ratings`][1] is forked from [`django-updown`][2] to support the newest django version.

[![build status][3]][4]
[![django version][5]][6]
[![python version][7]][8]

## Install

```
pip install django-updown-ratings
```

## Usage

Add `"updown"` to your `INSTALLED_APPS`. Then just add a `RatingField` to your existing model:

```
from django.db import models
from updown.fields import RatingField

class Post(models.Model):
    # ...other fields...
    rating = RatingField()
```

You can also allow the user to change his vote:

```
class Post(models.Model):
    # ...other fields...
    rating = RatingField(can_change_vote=True)
```

Now you can write your own view to submit ratings or use the predefined:

```
from updown.views import AddRatingFromModel

urlpatterns = [
    ....

    path('<int:object_id>/rate/<str:score>', AddRatingFromModel(), {
        'app_label': 'blogapp',
        'model': 'Post',
        'field_name': 'rating'
    }, name='post_rating'),
]
```

To submit a vote just go to `post/<id>/rate/(1|-1)`. If you allowed users to
change they're vote, they can do it with the same url.


[1]: https://github.com/agusmakmun/django-updown-ratings
[2]: https://github.com/weluse/django-updown

[3]: https://secure.travis-ci.org/agusmakmun/django-updown-ratings.png?branch=master
[4]: http://travis-ci.org/agusmakmun/django-updown-ratings

[5]: https://img.shields.io/badge/Django-2.0%20%3E=%203.1-green.svg
[6]: https://www.djangoproject.com

[7]: https://img.shields.io/pypi/pyversions/django-updown-ratings.svg
[8]: https://pypi.python.org/pypi/django-updown-ratings
python-Wappalyzer 0.3.1
Python implementation of the Wappalyzer web application detection utility

python-Wappalyzer
=================

[![Build Status](https://travis-ci.org/chorsley/python-Wappalyzer.svg?branch=master)](https://travis-ci.org/chorsley/python-Wappalyzer)
[![PyPI version](https://badge.fury.io/py/python-Wappalyzer.svg)](https://badge.fury.io/py/python-Wappalyzer)
[![Coverage Status](https://coveralls.io/repos/github/chorsley/python-Wappalyzer/badge.svg?branch=master)](https://coveralls.io/github/chorsley/python-Wappalyzer?branch=master)

Python implementation of the [Wappalyzer](https://github.com/AliasIO/wappalyzer) web application detection utility.  


### Install

```
$ python3 -m pip install python-Wappalyzer
```

### Usage

```python
from Wappalyzer import Wappalyzer, WebPage
wappalyzer = Wappalyzer.latest()
webpage = WebPage.new_from_url('http://example.com')
wappalyzer.analyze(webpage)
```

> `
{'Docker', 'Azure CDN', 'Amazon Web Services', 'Amazon ECS'}
`

```python
wappalyzer.analyze_with_categories(webpage)
```

> `
{'Amazon ECS': {'categories': ['IaaS']},
 'Amazon Web Services': {'categories': ['PaaS']},
 'Azure CDN': {'categories': ['CDN']},
 'Docker': {'categories': ['Containers']}}
`

```python
webpage = WebPage.new_from_url('http://wordpress-example.com')
wappalyzer.analyze_with_versions_and_categories(webpage)
```


> `
{'Font Awesome': {'categories': ['Font scripts'], 'versions': ['5.4.2']},
 'Google Font API': {'categories': ['Font scripts'], 'versions': []},
 'MySQL': {'categories': ['Databases'], 'versions': []},
 'Nginx': {'categories': ['Web servers', 'Reverse proxies'], 'versions': []},
 'PHP': {'categories': ['Programming languages'], 'versions': ['5.6.40']},
 'WordPress': {'categories': ['CMS', 'Blogs'], 'versions': ['5.4.2']},
 'Yoast SEO': {'categories': ['SEO'], 'versions': ['14.6.1']}}
`

***

Last version to support Python2 was `0.2.2`.
avato-training 0.2.0
Python client library for the logistic regression instance of the avato platform
Requires Python: >=3.6.1,<4.0.0

# Confidential ML Training :weight_lifting:
Python client library for Training instance of the decentriq platform.

# What is Confidential ML Training?
By using Confidential Computing, Confidential ML Training enables you to train machine learning models based on data that nobody ever can access; not you, not us, not the infrastructure provider, nobody. This removes the risk for data breaches or data misuse.

# Demo features :sparkles:
1. Logistic Regression training with hyperparameter tuning.
2. Remote attestation service to validate security guarantees.
3. Model conversion to Scikit-learn for easy offline inference.

## Prerequisites
You need to have Python >=3.7 installed (check using `python --version`) and internet access.

## Installation

Execute the following steps in the `avato-python-client-training` folder.

1. Create a new Python environment to install into using
`python -m venv .env`
2. Activate the environment using
`source .env/bin/activate`
3. Install dependencies using `.env/bin/pip install .`
ansible-playbook-runner 0.1.2
simple ansible playbook runner

# ansible-playbook-runner

ansible-playbook-runner is a simple wrapper for ansible

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install ansible-playbook-runner.

```bash
pip install foobar
```
## Usage

```python
from ansible_playbook_runner import Runner

Runner(['inventory_path'], 'playbook_path').run()
```

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.