semvec/pypi-packages huggingface dataset:
telstra-smart-modem 1.0.1
Library to retrieve information from a Telstra Smart Modem.
License: MIT
Requires Python: >=3.6

# Telstra Smart Modem - Python library

This library provides a Python 3 interface to query information from a Telstra Smart Modem (Gen 2).

## Tested with

* Telstra Smart Modem (Gen 2):
	* **Model**: Technicolor DJA0231
	* **Firmware**: 18.1.c.0443-950-RB

## Current features

* Retrieving online status (Online, Backup & Offline)
* Retrieving connected devices:
	* Checking if a device is connected
	* Retrieving information of seen device's
	(ipv4, ipv6, hostname, mac, connection type, ethernet port)

## Links

* [GitHub](https://github.com/hatdz/telstra-smart-modem/)
* [PyPI](https://pypi.org/project/telstra-smart-modem/)

## Installation

### Requirements

* [Requests](https://pypi.org/project/requests/)
* [Beautiful Soup](https://pypi.org/project/beautifulsoup4/)

### Methods

#### PIP

```
pip install telstra-smart-modem
```

## Usage

### Initialization

```python
import telstra_smart_modem

IP = '192.168.0.1'
USERNAME = 'admin'
PASSWORD = 'Telstra'

# Create tsm (Telstra Smart Modem) modem object:
tsm = telstra_smart_modem.Modem(IP, USERNAME, PASSWORD)
```

### Devices

```python
# Get current devices object from modem:
>>> clients = tsm.getDevices()

# Get list of seen devices:
>>> clients.devices
[
	{
		'online': False,
		'hostname': 'host1',
		'ipv4': None,
		'ipv6': [],
		'mac': '00:00:00:00:00:01',
		'connection': 'wireless - 5GHz',
		'eth-port': None
	},
	{
		'online': True,
		'hostname': 'host2',
		'ipv4': '192.168.0.3',
		'ipv6': [
			'2001:0db8:0000:0000:0000:8a2e:0370:7334'
		],
		'mac': '00:00:00:00:00:02',
		'connection': 'ethernet',
		'eth-port': 2
	}
]

# Get specific device by mac address:
>>> clients.getDevice("00:00:00:00:00:01")
{
	'online': False,
	'hostname': 'host1',
	'ipv4': None,
	'ipv6': [],
	'mac': '00:00:00:00:00:01',
	'connection': 'ethernet',
	'eth-port': 2
}

# Check if a device is currently connected:
>>> clients.isOnline("00:00:00:00:00:02")
True
>>> clients.isOnline("11:11:11:11:11:11")
False
```

### Online status

```python
# Returns 'online' if the modem is connected through the WAN port.
# Returns 'backup' if the WAN connection is down and the 4G backup is active.
# Returns 'offline' if both the WAN and 4G connections are down.

>>> tsm.getModemStatus()
online
```
EvaMap 2.0.6
A python library that can assess the quality of an RDF mapping
License: MIT
Keywords: rdf,mapping,semantic web,research

# LibraryEvaMap

A python library that can assess the quality of an RDF mapping.

### Installation

Installation in a `virtualenv` is recommended.

Assuming you already have `python 3` and `pip` installed

```bash
pip install EvaMap
```

### Initialize EvaMap

First, instantiation of an EvaMap object takes three parameters:

1) **rdf_ontology**: The ontology used in the yarrrml_mapping in RDF (turtle, xml or n3)
2) **yarrrml_mapping**: The RDF mapping of the json_data in YARRRML
3) **json_data**: The dataset in JSON format

```python
from EvaMap.EvaMap import EvaMap

evamap = EvaMap(rdf_ontology, yarrrml_mapping, json_data)
```

### Assess the mapping

You can assess the quality of the **yarrrml_mapping** by using the `evaluate_mapping` method:

```python
evamap.evaluate_mapping()
```

### Retrieve results

After evaluation, you can retrieve the total score of the **yarrrml_mapping** with _get_total_score()_ method:

```python
evamap.get_total_score() # e.g., 0.6805555555555557
```

or, a list of Dict representing score for each dimensions, metrics and feedbacks with _get_complet_result()_ method:

```python
evamap.get_complet_result()
```
django-pell 0.0.10
Django pell WYSIWYG widget
License: MIT
Keywords: django

# Django Pell

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)
[![coverage report](https://gitlab.com/BradleyKirton/django-pell/badges/master/coverage.svg?job=test)](https://gitlab.com/BradleyKirton/django-pell/)

Custom django widget built on [pell](https://github.com/jaredreich/pell).

![Django Pell in action](django_pell.png)


## Usage

```python
class EditorForm(forms.Form):
    """Simple form which exposes the Django Pell Widget."""

    editor = forms.CharField(
        widget=PellWidget(),
        help_text='Pell is "the simplest and smallest WYSIWYG text editor for web, with no dependencies"',
        label=False,
    )


def editor_view(request):
    """Simple view which renders the EditorForm."""

    return render(
        request,
        "editor.html",
        context={"form": EditorForm()},
    )
```

```html
<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <title>Document</title>
</head>
{{ form.media }}
<body>
  {{ form.as_p }}
</body>
</html>
```

For a complete example check out the `example` included in this repo.
Categorical-similarity-measures 0.4
Similarity Measures Utility Package
License: MIT
Keywords: Similarity,Distance,Categorical data

Determining similarity or distance between two objects is a key step for several data mining and knowledge discovery tasks. For quantitative data, Minkowski distance plays a major role in finding the distance between two entities. The prevalently known and used similarity measures are Manhattan distance which is the Minkowski distance of order 1 and the Euclidean distance which is the Minkowski distance of order 2. But, in the case of categorical data, we know that there does not exist an innate order and that makes it problematic to find the distance between two categorical points. This is a utility package for finding similarity measures such as Eskin, IOF, OF, Overlap (Simple Matching), Goodall1, Goodall2, Goodall3, Goodall4, Lin, Lin1, Morlini_Zani (S2), Variable Entropy and Variable Mutability. These similarity measures help in finding the distance between two or more objects or entities containing categorical data.
palmero 0.2.3
Easy and secure python encryption
License: MIT
Requires Python: >=3.4
Keywords: encryption decryption security tool

# Palmero
Palmero is a hyper-simplification of encryption in Python.

## Features

### Palmero features encryption key generation based on the identitiy of the machine you're encrypting on.
Meaning that unless you know the password and are on the machine the file was created on, the file won't be unlocked. That said, machine ID generation is possible, so you can give someone both the password and your machine's unique ID to bypass this if need be.

### Super easy encryption and decryption
Using Palmero is as easy as calling ```encrypt()``` or ```decrypt``` with your source file and password. Palmero has already been tuned to offer high levels of security, and allows for customizablity with some parameters.

### Uses Pycryptodome under the hood
Most of the fundementals of the encryption process are handled by Pycryptodome, which allows for many levels of customisability and fine tuning in the source code.