semvec/pypi-packages huggingface dataset:
HaulEnc 0.1
A Python-based file encryption and decryption toolkit.
Requires Python: >=3.6

# Haul - File Encryption Toolkit 🔐

<p>Haul is a Python-based file encryption and decryption toolkit designed to secure your sensitive files. It uses strong AES encryption in CBC mode along with PBKDF2 for key derivation. The toolkit is simple to use and provides a command-line interface (CLI) to encrypt and decrypt files or directories.</p>

### With Haul, you can:

<ul>
	<li>Encrypt and decrypt files or entire directories with ease.</li>
	<li>Initialize a key file and password protection for encryption and decryption.</li>
	<li>Work with AES-256 encryption and secure password hashing.</li>
</ul>

## Features:-

<ul>
	<li><b>Encrypt files:</b> Secure sensitive data by encrypting files using AES-256.</li>
	<li><b>Decrypt files:</b> Decrypt encrypted files with the correct password.</li>
	<li><b>Key management:</b> Generate and store encryption keys securely.</li>
	<li><b>Directory-based operations:</b> Encrypt and decrypt multiple files within a directory.</li>
	<li><b>Easy-to-use CLI:</b> Simple commands to perform actions like initializing, encrypting, and decrypting.</li>
</ul>

## Installation:-

To install Haul, you can either clone the repository or install it directly using pip from PyPI. 

```
pip install HaulEnc
```

## Use Case Example

### 1. Initializing the Key

Run the following command to initialize the key:

```bash
haul --action init
```

*Initializing with a specified directory:*

```bash
haul --action init --directory /usr/local/bin
```

**🗒️ Note:** Initialization will make changes only within user-privileged directories. It will initialize in every privileged directory and create a `key.key` file in the specified location.

#### Additional Tips:
- Ensure you have the necessary permissions for the target directory.
- Keep the generated `key.key` file secure, as it is critical for encryption and decryption processes.

---

### 2. Encryption

Encrypt files securely using the following command:

```bash
haul --action encrypt
```

*Encryption with a specified directory:*

```bash
haul --action encrypt --directory /usr/local/bin
```
skylog-sdk 0.1.15
skylog python sdk
Requires Python: >=3.8.12

# skylog-sdk

[![Release](https://img.shields.io/github/v/release/vahidtwo/skylog-sdk)](https://img.shields.io/github/v/release/vahidtwo/skylog-sdk)
[![Build status](https://img.shields.io/github/actions/workflow/status/vahidtwo/skylog-sdk/main.yml?branch=main)](https://github.com/vahidtwo/skylog-sdk/actions/workflows/main.yml?query=branch%3Amain)
[![Commit activity](https://img.shields.io/github/commit-activity/m/vahidtwo/skylog-sdk)](https://img.shields.io/github/commit-activity/m/vahidtwo/skylog-sdk)
[![License](https://img.shields.io/github/license/vahidtwo/skylog-sdk)](https://img.shields.io/github/license/vahidtwo/skylog-sdk)

- **Github repository**: <https://github.com/vahidtwo/skylog-sdk/>
- **Documentation** <https://vahidtwo.github.io/skylog-sdk/>
- **PIPY Package** <https://pypi.org/project/skylog-sdk/>

# Python SDK for Skylog Integration

Skylog is a robust service designed for seamless integration with various platforms like Sentry, Telegram,
and more, enabling the efficient transmission of logs and rapid identification of issues.

This Python SDK facilitates easy interaction with Skylog services, allowing users to:

- fire alert
- stop alert
- notify

# How to install

install from gitlab

```bash
pip install skylog-sdk
```

## Setup and Configuration

- **Environment Variables**: Configure the following variables in your project environment:

  - `DEFAULT_SKY_LOG_ALERTING_TELEGRAM_ALERT_NAME`: Default alert name for Telegram
  - `DEFAULT_SKY_LOG_ALERTING_PHONE_CALL_ALERT_NAME`: Default alert name for phone calls
  - `DEFAULT_SKY_LOG_ALERTING_SMS_ALERT_NAME`: Default alert name for SMS
  - `SKY_LOG_ALERTING_BASE_URL`: Base URL for Skylog API calls
  - `SKY_LOG_ALERTING_TOKEN`: Your Skylog authentication token

- **Proxy Configuration**: If using a proxy, include the following additional variables:
  - `PROXY_USERNAME`
  - `PROXY_PASSWORD`
  - `PROXY_IP`
  - `PROXY_PORT`

## Usage Example

```python
from skylog import AlertingSkyLogClient, AlertingProvider

# Initialize the Skylog client with the desired provider (e.g., Telegram)
client = AlertingSkyLogClient(provider=AlertingProvider.telegram)

# Example Operations:
client.fire_alert(description='Issue detected', instance_name='unique_key', provider=AlertingProvider.sms)
client.stop_alert(description='Issue resolved', instance_name='unique_key', provider=AlertingProvider.sms)
client.notify(description='Alert notification', instance_name='unique_key', provider=AlertingProvider.telegram)
```

## Concepts to Understand

### Alertname and Instance

- **Alertname**: Represents the provider or service. It identifies where Skylog sends alerts.
- **Instance**: A unique identifier within a group alert, specifying a particular part of a universal alert.

### Alerts Management

- **Firing an Alert**: Triggering an alert, resulting in immediate notifications sent to relevant endpoints.
- **Stopping an Alert**: Removing a fired alert, resolving it and stopping further notifications.
- **Notifying an Alert**: Sending messages to endpoints without adding records to the triggered list.
pymadoc 0.1.1
Python package to download and combine parts of MADOC dataset
Requires Python: >=3.6

# pyMADOC

Python package to download and combine parts of MADOC dataset from Zenodo (record: 14637314). The MADOC dataset contains social media posts from multiple platforms (Reddit, Voat, Bluesky, and Koo), making it easy to study cross-platform content and community dynamics.

## Features

- Easy download of platform-specific data files
- Automatic pairing of Reddit-Voat community data
- Both Python API and Command Line Interface
- Support for direct DataFrame loading
- Progress bars for downloads
- Efficient parquet file format

## Installation

```bash
pip install pymadoc
```

## Usage

### As a Python Package

```python
from pymadoc import list_available_data, download_file, download_community_pair

# List available platforms and communities
data_info = list_available_data()
print(data_info["platforms"])  # ['reddit', 'voat', 'bluesky', 'koo']
print(data_info["communities"])  # ['CringeAnarchy', 'fatpeoplehate', ...]

# Download a specific file
# For Reddit/Voat, specify both platform and community
file_path = download_file("reddit", community="funny", output_dir="data")
# For Bluesky/Koo, specify only platform
file_path = download_file("bluesky", output_dir="data")

# Load directly as DataFrame
df = download_file("reddit", community="funny", as_dataframe=True)

# Download and combine Reddit-Voat community pair
# As files
reddit_file, voat_file = download_community_pair("funny", output_dir="data")
# As combined DataFrame
combined_df = download_community_pair("funny", as_dataframe=True)
```

### Command Line Interface

List available platforms and communities:
```bash
pymadoc list
```

Download a specific file:
```bash
# Reddit/Voat (requires community)
pymadoc download reddit --community funny --output-dir data
# Bluesky/Koo
pymadoc download bluesky --output-dir data
```

Download Reddit-Voat community pair:
```bash
pymadoc pair funny --output-dir data
```

## Available Data

### Platforms
- Reddit: Community-specific posts and comments
- Voat: Community-specific posts and comments
- Bluesky: Platform-wide posts
- Koo: Platform-wide posts

### Communities (Reddit/Voat only)
- CringeAnarchy
- fatpeoplehate
- funny
- gaming
- gifs
- greatawakening
- KotakuInAction
- MensRights
- milliondollarextreme
- pics
- technology
- videos

## Data Format

All files are stored in parquet format for efficient storage and fast loading. Each file contains the following columns:
- Platform-specific post/comment IDs
- Content text
- Timestamps
- User information
- Engagement metrics

## Requirements

- Python 3.6 or higher
- pandas
- requests
- tqdm

## Citation

If you use this package or the MADOC dataset in your research, please cite:
```
@dataset{madoc_dataset,
    title = {MADOC: Multi-platform Archive of Digital Online Content},
    author = {Tomašević, Aleksandar},
    year = {2024},
    publisher = {Zenodo},
    doi = {10.5281/zenodo.14637314}
}
```

## License

MIT License

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.
bread-engine 0.1.1
A python game engine using PyGame
Requires Python: >=3.8

# [Bread Engine](https://pypi.org/project/bread-engine/)
The bread engine is a basic "game engine" made using PyGame.
The engine allows you to create games much easier and is fully compatible with PyGame.

## Example usage:
```python
import bread_engine

engine = bread_engine.Engine()

engine.run()
```

## Installation
```shell
pip install pygame
pip install bread_engine
```

## More examples:
```python
import bread_engine

class Player(bread_engine.Rect):
    def __init__(self):
        super().__init__(100, 100, 50, 50, bread_engine.Color.GREEN, has_physics="gravity")
        self.ground_level = engine.window_height - self.rect.height
        self.gravity = 0.4
        self.velocity_y = 0

    def update(self):
        keys = bread_engine.KeyHandler.get_pressed_keys()

        if keys[bread_engine.KeyHandler.Key.A] or keys[bread_engine.KeyHandler.Key.LEFT]:
            self.rect.x -= 4
        if keys[bread_engine.KeyHandler.Key.D] or keys[bread_engine.KeyHandler.Key.RIGHT]:
            self.rect.x += 4

        if keys[bread_engine.KeyHandler.Key.SPACE] and self.rect.y == self.ground_level:
            self.velocity_y = -10

def cube_update(cube):
    cube.rect.x += 1

def different_cube_update(cube):
    cube.rect.x += 2

engine = bread_engine.Engine(debug=True, window_vsync=True, exit_bind=bread_engine.KeyHandler.Key.ESCAPE)

cube = bread_engine.Rect(200, 100, 50, 50, bread_engine.Color.RED, update_function=cube_update)

player = Player()

engine.add_object(player)
engine.add_object(cube)

engine.run()
```

I recommend taking a look at the source code for a better understanding of the engine!