semvec/pypi-packages huggingface dataset:
PyHTBcli 0.0.7
Command line interface for HackTheBox
Requires Python: >=3.8

# htbcli
HackTheBox Command Line Tool

![](images/htb-list-competitive.png)

# Requirements

## nmcli

VPN is controlled by the `nmcli` program. 

Is installed in most Debian-based Linux distributions by default.

Can be installed with:
```
$ apt-get install network-manager
```

## Fonts

To make the icons print nicely, need a [nerd font](https://www.nerdfonts.com/) installed.

Install instructions (Linux):

```
wget https://github.com/ryanoasis/nerd-fonts/releases/download/v2.1.0/Ubuntu.zip -O /tmp/Ubuntu.zip
mkdir -p ~/.local/share/fonts
unzip /tmp/Ubuntu.zip -d ~/.local/share/fonts
fc-cache -fv
```

# Installation

```bash
pip install PyHTBcli
```

# Shell Auto Complete

To get tab completion in the default linux shell.

## Bash

Add this line to `~/.bashrc`:

```bash
eval "$(_htb_COMPLETE=bash_source htb)"
```

## Zsh

Add this line to `~/.zshrc`:

```bash
eval "$(_HTB_COMPLETE=zsh_source htb)"
```

## Fish

Add this to `~/.config/fish/completions/htb.fish`:

```bash
eval (env _HTB_COMPLETE=fish_source htb)
```

## Full Documention

See [readthedocs](https://pyhtbcli.readthedocs.io/en/latest/) for full documentation.
pylorauna 0.1.0
API Wrapper for the Lorauna API. Lorauna refers to the 'Sauna Lorrainebad' in Bern, CH
Requires Python: >=3.10,<4.0

# Sauna Lorrainebad API Wrapper 🧖🏽‍♀️
In Bern, CH there's a super sweet sauna down at the Aare.  
Their current capacity can be seen on their [website](https://saunalorrainebad.ch) or through this little API wrapper.

## Example usage
```python
from pylorauna.lorauna import LoraunaClient

client = LoraunaClient()
data = client.get_data()
print(data.capacity_message)
# $ Mir hei no bis Endi Oktober Summerpouse.
```
model-loads 0.3
Loads GPU or CPU pytorch models

**model_loads** is an open-source Python package for pytorch load models easy.

[PyTorch](http://pytorch.org/) is a Python package that provides two high-level features:

- Tensor computation (like NumPy) with strong GPU acceleration
- Deep neural networks built on a tape-based autograd system

It's annoying to load cpu model to gpu devices or load multi-gpus trained model to single gpu devices sometimes, And this package try to simplify it.


## Table of Contents

- [Table of Contents](#table-of-contents) 
- [Installation](#installation)
- [Getting Started](#getting-started)
- [TODO list](#todo-list)

## Installation

To install load_models, you can do as follow:

```
    pip install model-loads
```

Or from source

```
    git clone https://github.com/cwh94/model_loads.git
    cd load_models
    python setup.py bdist_egg
    python setup.py install
```

## Getting Started


1. load pth model to GPU device
```
import model_loads as lo
import torchvision.models as models

model = models.MobileNetV2()
model_path = "../examples/models/pth/mobilenet_v2-b0353104.pth"
model, _ = lo.load_models(model_path, model, use_gpu=True)
print(model)
print(type(model))
```

2. load tar model(which contains state_dict and optimization info or accuracy) to CPU device

```
from models.tar.mobilenet_v2 import MobileNetV2

model = MobileNetV2()
model_path = "models/tar/checkpoint.pth.tar"

model, other_param = lo.load_models(model_path, model)
print(model)
print(other_param)

```

4. load model to CPU device
```
import os

os.environ["CUDA_VISIBLE_DEVICES"] = ""

model = models.MobileNetV2()
model_path = "models/pth/mobilenet_v2-b0353104.pth"
model, _ = lo.load_models(model_path, model, use_gpu=True)
print(model)
print(type(model))
```
limitys 2022.9.25
Overlap (Finnish: limitys) assesses sentences from constrained and overlapping vocabularies.
Requires Python: >=3.8
Keywords: developer-tools,surviving-process-bloat,requirements-engineering,validation,verification

# limitys

Overlap (Finnish: limitys) assesses sentences from constrained and overlapping vocabularies.

[License: MIT](https://git.sr.ht/~sthagen/limitys/tree/default/item/LICENSE)

[![version](https://img.shields.io/pypi/v/limitys.svg?style=flat)](https://pypi.python.org/pypi/limitys/)
[![downloads](https://pepy.tech/badge/limitys/month)](https://pepy.tech/project/limitys)
[![wheel](https://img.shields.io/pypi/wheel/limitys.svg?style=flat)](https://pypi.python.org/pypi/limitys/)
[![supported-versions](https://img.shields.io/pypi/pyversions/limitys.svg?style=flat)](https://pypi.python.org/pypi/limitys/)
[![supported-implementations](https://img.shields.io/pypi/implementation/limitys.svg?style=flat)](https://pypi.python.org/pypi/limitys/)

## Documentation

User and developer [documentation of limitys](https://codes.dilettant.life/docs/limitys).

## Bug Tracker

Feature requests and bug reports are best entered in the [todos of limitys](https://todo.sr.ht/~sthagen/limitys).

## Primary Source repository

The primary source of `limitys` lives somewhere on a mountain in Central Switzerland.
But, we use decentralized version control (git), so any clone can become the source to everyone's benefit, no central only code.
Anyway, the preferred public clones of `limitys` are:

* [on codeberg](https://codeberg.org/sthagen/limitys) - a democratic community-driven, non-profit software development platform operated by Codeberg e.V.
* [at sourcehut](https://git.sr.ht/~sthagen/limitys) - a collection of tools useful for software development.

# Status

Experimental.

**Note**: The default branch is `default`.