semvec/pypi-packages huggingface dataset:
WINRPCexploit 1.3.7
A package to exploit windows RPC Vulnerability
Requires Python: >=3.6

CVE-2022-26809 - weakness in a core Windows component (RPC) earned a CVSS score of 9.8 not without a reason, as the attack does not require authentication and can be executed remotely over a network, and can result in remote code execution (RCE) with the privileges of the RPC service, which depends on the process hosting the RPC runtime. That critcal bug, with a bit of luck, allows to gain access to unpatched Windows host running SMB. The vulnerability can be exploited both from outside the network in order to breach it as well as between machines in the network.
actor-loader 0.1.3
Console application to load the required C-Actors into any mod.
Requires Python: >=3.7

# Actor Loader - Vanilla Actors with Collision

An automation tool for quickly putting the right Collision Actors (C-Actors, Vanilla Actors with Collision) in your mod.

## What is ActorLoader for?

To understand this, you must first be familiar with C-Actors.

C-Actors was originally a mod including every applicable actor in the game with attached collision.
These actors could be used in Ice-Spear to make landscape scenes quickly without having to worry about manually adding collision to them. A timely process that was easy to mess up.

The original C-Actors mod would be required as a prerequisite in every mod using it.
This wasn't terrible, but because it had almost every actor in it, it slowed down merging times in BCML quite a lot. There was no real need for all 2044 actors to be loaded when only 5 were used in the mod.

My alternative at the time was to take the actors used and put them into my mod.
This was an okay solution, but it got difficult to keep track of which actors were used as the mod expanded.

So this is what ActorLoader is for, it gets every C-Actor used by reading the mods smubin files, then copies them into the mods content folder.

If you have any questions, feel free to ask them in the comments or on my [Discord server]("https://discord.gg/cbA3AWwfJj").

## Usage

In the root folder of your mod (the folder containing aoc, content, etc . . .)  type actor-loader.exe in the file path.

_Note: in previous versions it was required to append 'C' to new actors, this is no longer required._
cachier-common-library 0.2.0
A python library for common classes and functions used to build cachier applications
Requires Python: >=3.10.4

# Cachier Common Library

A python library for common classes and functions used to build cachier applications

## Table of Contents

- [Installation](#installation)
- [Usage](#usage)
- [Support](#support)
- [Contributing](#contributing)

## Installation

Install the package from pypi:

```sh
pip install cachier-common-library
```

## Usage

```python
from cachier_common_library import DriverType

# Using the DriverType enum
print(DriverType.RAM)
print(DriverType.JSON)
print(DriverType.SQLITE)
print(DriverType.PICKLE)
```

## Support

Please [open an issue](https://github.com/apinanyogaratnam/cachier-common-library/issues/new) for support.

## Contributing

Please contribute using [Github Flow](https://guides.github.com/introduction/flow/). Create a branch, add commits, and [open a pull request](https://github.com/apinanyogaratnam/cachier-common-library/compare/). -->

<!--
TODO comments:
TODO: create InvalidDriverError
-->
chlengmo 0.0.4
A fast Character-Level N-Gram Model
Requires Python: >=3.6

# Character-Level N-Gram Model

[![tests](https://github.com/VictorDavis/chlengmo/actions/workflows/tests.yml/badge.svg)](https://github.com/VictorDavis/chlengmo/actions/workflows/tests.yml)

**Chlengmo**: ("Kling-mo") A lean, simple, _fast_ character-level n-gram model. Faster than [NLTK](https://www.nltk.org/api/nltk.lm.html). Zero dependencies.

## Sample Usage

```python

# retrieve corpus from NLTK
# NOTE: NLTK is not a dependency, only using it to fetch a training corpus.
filename = "melville-moby_dick.txt"
text = gutenberg.raw(filename)
start = "Call me Ishmael"
start_idx = text.index(start)
text = text[start_idx:]

# 15-gram model
model = Chlengmo(n=15).fit(text)
model.generate(length=981, prompt="Call me ", seed=42)
```

> Call me Ishmael . Some years ago -- never mind how long precisely -- who knows ? Certain I am , however , the sperm whale \' s food ; and , also , calling to mind the regular , ascertained seasons for hunting him in particular that , in the internal parts of the vessel ; the becharmed crew maintaining the profoundest homage ; yea , an all - abounding adoration ! for almost all the tapers , lamps , and candles that burn round the globe , by girdling it with guineas , one to every three parts of an inch ; stabbing him in the ventricles of his heart . He was in Radney the chief mate , said ,--" Take the rope , sir -- I give it into thy hands , Starbuck watched the Pequod \' s jaw - bone tiller had several times descended from heaven by the way of this fire - ship on the sea . A short space elapsed , and up into this noiselessness came Ahab alone from his cabin . He was a small , short , youngish man , sprinkled all over his face with freckles , and wearing redundant yellow hair .

## Unit Tests

```bash
# from inside the tests/ subfolder
cd tests/

# create virtual environment
virtualenv .venv
. .venv/bin/activate

# install unit test dependencies
python3 -m pip install -r requirements.txt

# run unit tests
pytest

# run coverage report
coverage run -m pytest
coverage report
coverage html
open htmlcov/index.html

# cleanup
deactivate
rm -rf .venv
```

## Notebooks

REF: https://janakiev.com/blog/jupyter-virtual-envs/

```bash
# from inside the notebooks/ subfolder
cd notebooks/

# create virtual environment
virtualenv .venv
. .venv/bin/activate

# install notebook dependencies
python3 -m pip install -r requirements.txt

# create jupyter kernel
python3 -m pip install ipykernel
python3 -m ipykernel install --user --name=.venv

# exit virtual environment & run jupyter
deactivate
PYTHONPATH=../ jupyter notebook

# cleanup
rm -rf .venv
```
reskin-sensor 2.0.2
Data acquisition library for a ReSkin sensor
Requires Python: >=3.6

# Reskin Sensor Library
This is a python library to interface with [ReSkin](https://openreview.net/forum?id=87_OJU4sw3V) sensors. We provide two classes for interfacing with [ReSkin](https://openreview.net/forum?id=87_OJU4sw3V). The `ReSkinBase` class is good for standalone data collection: it blocks code execution while data is being collected. The `ReSkinProcess` class can be used for non-blocking background data collection. Data can be buffered in the background while you run the rest of your code.

Latest stable release is v2.0.0

## Installation

This package can be installed using pip:
```
pip install reskin_sensor
```
Alternatively, if you would like the latest (potentially unstable) version, 
1. Clone this repository using 
```
$ git clone https://github.com/raunaqbhirangi/reskin_sensor.git --recursive
```
2. Install this package using
```
$ pip install -e .
```
## Usage

1. Connect the 5X board to the microcontroller. 

2. Connect the microcontroller (we recommend the Adafruit Trinket M0 or the Adafruit QT PY) to the computer using a suitable USB cable

3. Use the [Arduino IDE](https://www.arduino.cc/en/software) to upload code to a microcontroller. The code as well as upload instructions can be found in the [arduino](./arduino) folder.
If you get a `can't open device "<port-name>": Permission denied` error, modify permissions to allow read and write on that port. On Linux, this would look like 
```
$ sudo chmod a+rw <port-name>
```

4. Run test code on the computer
```
$ python tests/sensor_proc_test.py -p <port-name>
```
## Credits
This package is maintained by [Raunaq Bhirangi](https://www.cs.cmu.edu/~rbhirang/). We would also like to cite the [pyForceDAQ](https://github.com/lindemann09/pyForceDAQ) library which was used as a reference in structuring this package.