semvec/pypi-packages huggingface dataset:
PassShield 0.1.0
Secure password handling for database connections
Requires Python: >=3.6
Keywords: password encryption security mysql database

# PassHash Library

A secure way to handle database passwords with encryption.

## Features

- 🔒 Encrypt/decrypt passwords using Fernet symmetric encryption
- 🛡️ Secure MySQL connection handling
- 🌐 Environment variable support for production
- ⌨️ CLI password prompt for development
- 🔄 Key rotation support
- ✅ Unit tested

## Installation

```bash
pip install passhash
bioib 0.1.3
Biological Information Bottleneck
Requires Python: <4,>=3.7

# bioIB
bioIB package for scRNA-seq analysis

This repository provides the code for bioIB, described in our article - 
"bioIB: Identifying informative metagenes in single-cell RNA-seq with the Information Bottleneck algorithm"

![intro_figure](https://github.com/user-attachments/assets/ffe67ad3-1ef0-4d14-aec0-7ae6184c0199)

bioIB is a novel method for scRNA-seq analysis, based on the Information Bottleneck algorithm. 
Given the cellular labels representing the signal of interest, such as cell type, bioIB generates probabilistic gene clusters, or metagenes, that capture the major biological processes differentially activated between the defined cellular populations.

# This repository

This repository contains:

1. The bioIB package code.
2. Jupyter notebook tutorial exemplifying the use of the bioIB package functions.

# Installation
The bioIB package can be installed through pip:
```
pip install bioib
```
macals 0.1.0
Access ambient light sensor on macOS
Requires Python: >=3.11

# macals
Python module for accessing the ambient light sensor on macOS

## Usage

### Command Line

```
python -m macals
```

This will iterate all ambient light sensors and their lux values.

### Python

```python
from macals import list_sensors

for sensor in list_sensors:
    print(f'{sensor.name}: {sensor.get_current_lux()} lux')
```

There is likely only ever to be a single sensor, so `macals.find_sensor()` is probably fine to use, which just returns the first.

```python
from macals import find_sensor

sensor = find_sensor()
print(f'{sensor.name}: {sensor.get_current_lux()} lux')
```

You can also just use the `LightSensor` class if you know the service name:

```python
from macals import LightSensor

sensor = LightSensor('AppleSPUVD6286')
print(f'{sensor.name}: {sensor.get_current_lux()} lux')
```
bounding-shape 0.2.1
Creates shapely shapes around given points.
Requires Python: >=3.10

This library creates [Shapely](https://shapely.readthedocs.io/en/stable/) shapes designed to fit closely around a set of given points, and provides functionality to create a grid of points inside those shapes. 
This simplifies the problem of trying to find a shape that fits around all points, whilst allowing for gaps/multiple shapes to accomodate for situations where points may be clustered around a few areas, or handling points far outside a cluster. 

For examples of how to use the library, see the github readme [here](https://github.com/IGILtd/bounding_shape/blob/main/README.md).
filmsdk-ibrahim 0.0.4
Python SDK to access API MovieLens
Requires Python: >=3.12

# MovieLens SDK - `filmsdk_ibrahim`

A simple Python SDK to interact with the MovieLens REST API. It is designed for Data Analysts and Data Scientists, with native support for Pydantic, dictionaries, and Pandas DataFrames.

---

## Installation

```bash
pip install filmsdk_ibrahim
```

---

## Configuration to test on local machine

```python
from filmsdk_ibrahim import MovieClient, MovieConfig

# Configuration with your API URL (local via docker)
config = MovieConfig(movie_base_url="http://localhost:5050")
client = MovieClient(config=config)
```

---

## Test SDK

### 1. Health check

```python
client.health_check()
# Retourn : {"status": "ok"}
```

### 2. Get a film

```python
movie = client.get_movie(1)
print(movie.title)
```

### 3. List of films in DataFrame format

```python
df = client.list_movies(limit=5, output_format="pandas")
print(df.head())
```

---

## Available output modes

All listing methods (list_movies, list_ratings, etc.) can return:

Pydantic objects (default)

Dictionaries

Pandas DataFrames

Example :

```python
client.list_movies(limit=10, output_format="dict")
client.list_ratings(limit=10, output_format="pandas")
```

---

## Liens utiles

- PyPI : [https://pypi.org/project/filmsdk-ibrahim/0.0.3/](https://pypi.org/project/filmsdk-ibrahim/0.0.3/)