semvec/pypi-packages huggingface dataset:
eclipsenodeeditor 0.12
A python module
Requires Python: >=3.10

# eclipsenodeeditor

[![PyPI version](https://badge.fury.io/py/eclipsenodeeditor.svg)](https://badge.fury.io/py/eclipsenodeeditor)

**eclipsenodeeditor** description text

## Features

- **Feature1**: brief description

## Examples

```python

```
firebase-admin-stubs 0.1.0
Type stubs for firebase-admin package
Requires Python: >=3.7
Keywords: admin, firebase, stubs, types, typing

# firebase-admin-stubs

Type stubs for the `firebase-admin` Python package.

## Installation

```bash
pip install firebase-admin-stubs
```

## Usage

These stubs provide type information for the `firebase-admin` package. They will be automatically used by type checkers like mypy when you import `firebase-admin`.

```python
from firebase_admin import credentials, initialize_app

cred = credentials.Certificate('path/to/serviceAccount.json')
app = initialize_app(cred)
```

## Development

This package contains type stubs for the `firebase-admin` package. The stubs are manually curated to provide accurate type information for the Firebase Admin SDK.

## License

MIT
youtube-search-sdk 0.1.0
SDK for interacting with YouTube Search API
Requires Python: >=3.8

# YouTube Search SDK

A Python SDK for interacting with the YouTube Search API. This SDK provides a simple and intuitive interface to search for YouTube videos with various parameters.

## Features

- Simple and intuitive API
- Type hints and documentation
- Pydantic models for response validation
- Context manager support for proper resource cleanup
- Configurable API endpoint

## Installation

```bash
pip install youtube-search-sdk
```

## Quick Start

```python
from youtube_search_sdk import YouTubeSearchClient

# Create a client
client = YouTubeSearchClient(base_url="http://your-api-url:8000")

# Basic search
results = client.search("Python programming")

# Search with parameters
results = client.search(
    query="Python programming",
    limit=10,  # results per page (1-50)
    pages=2    # number of pages (1-10)
)

# Using context manager (recommended)
with YouTubeSearchClient() as client:
    results = client.search("Python programming")
    for video in results:
        print(f"Title: {video.title}")
        print(f"Channel: {video.channel_name}")
        print(f"Link: {video.link}")
        print("---")
```

## Response Structure

Each search result includes:

```python
class VideoResult:
    title: str
    channel_name: str
    duration: str
    views: str
    publish_date: Optional[datetime]
    link: str
    description: Optional[str]
    keywords: Optional[List[str]]
    page_number: int
```

## Error Handling

The SDK provides clear error messages for common issues:

```python
try:
    results = client.search("", limit=100)
except ValueError as e:
    print(f"Invalid parameters: {e}")
except httpx.HTTPError as e:
    print(f"API request failed: {e}")
```

## Development

To set up the development environment:

```bash
# Clone the repository
git clone https://github.com/yourusername/youtube-search-sdk
cd youtube-search-sdk

# Install development dependencies
pip install -e ".[dev]"

# Run tests
pytest
```

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## License

This project is licensed under the MIT License - see the LICENSE file for details.
webp-imagefield 0.2.2
A custom Django ImageField that automatically converts images to WebP format.
Requires Python: >=3.6

# 🌐 WebP Image Field

[![PyPI version](https://badge.fury.io/py/webp-image-field.svg)](https://badge.fury.io/py/webp-image-field)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Django Version](https://img.shields.io/badge/Django-%3E%3D3.0-blue.svg)](https://www.djangoproject.com/)
[![Python Version](https://img.shields.io/badge/Python-%3E%3D3.6-blue.svg)](https://www.python.org/)

**WebP Image Field** is a Django package that provides a custom ImageField which automatically converts uploaded images to the WebP format. This helps optimize image loading times on the web, as WebP images are often significantly smaller than JPEG or PNG files.

## ✨ Features

- 🚀 **Automatic Conversion**: Seamlessly converts images to WebP during upload.
- 🔧 **Customizable Quality**: Adjust WebP quality to balance between size and image fidelity.
- 🔌 **Easy Integration**: Drop-in replacement for Django's ImageField.

## 📋 Requirements

Before using WebP Image Field, ensure you have the following dependencies installed:

- **Python**: >= 3.6
- **Django**: >= 3.0
- **Pillow**: >= 8.0.0

## 🛠 Installation

Install the package using pip:

bash
pip install webp-image-field


## 🚀 How to Use
1. Add to Your Django Project
First, make sure that webp-image-field is installed in your environment .

2. Update Your Models if you have been using ImageField
Replace Django’s built-in ImageField with WebPImageField in your models.
if you have been migrated you don't have to make new migrations.

Here’s a basic example:

bash
from django.db import models
from webp_image_field import WebPImageField

class MyModel(models.Model):
    image = WebPImageField(upload_to='images/', quality=85)

    def __str__(self):
        return f"Image: {self.image.url}"

        
upload_to: Specifies the directory within your MEDIA_ROOT where the images will be saved.

quality: Sets the quality of the WebP images (default is 90). You can adjust this value to balance between image quality and file size.
easyaipy 0.1.3
EasyAIPy allows extracting precise variables from AI API responses.
Requires Python: >=3.6

# easyaipy

EasyAIPy allows extracting precise variables from AI API responses. It is designed to interact with 
OpenAI and Gemini developer APIs. It allows programmers to specify the amount and the datatypes of variables
they want to receive in their API response. 

## Installation

```bash
pip install easyaipy
```

## A Simple Example with OpenAI API

```python
from easyaipy import openai_easy_prompt

# Define or import your API key
api_key = "YOUR_API_KEY"

# Define the input prompt
prompt = "Generate a brief summary of the importance of AI in education."

# Specify an output schema (optional)
output_schema = {
    "summary": str,
    "word_count": int
}


response = openai_easy_prompt(
    prompt=prompt,
    model="gpt-4o-mini",
    output_schema=output_schema,
    max_retries=3,
    api_key=api_key
)

# Print the validated response
print("Response:", response)
```

## Expected Output
If the OpenAI API responds correctly and matches the schema, the output will look like this:


```json
{
    "summary": "AI in education enhances personalized learning, streamlines administrative tasks, and fosters innovation in teaching.",
    "word_count": 15
}
```
pycoffer 0.1.4
A python xxxFile like ( ie GzipFile, BZ2File, ...) for manipulating coffer encrypted files.
Requires Python: >=3.9

[![CircleCI](https://dl.circleci.com/status-badge/img/gh/bibi21000/PyCoffer/tree/main.svg?style=svg)](https://dl.circleci.com/status-badge/redirect/gh/bibi21000/PyCoffer/tree/main)
[![codecov](https://codecov.io/gh/bibi21000/PyCoffer/graph/badge.svg?token=4124GIOJAK)](https://codecov.io/gh/bibi21000/PyCoffer)
![PyPI - Downloads](https://img.shields.io/pypi/dm/pycoffer)

# PyCoffer

A python coffer.

Store your confidential data in a secure coffer.

User doc : https://bibi21000.github.io/PyCoffer/usage/install.html

Developer doc : https://bibi21000.github.io/PyCoffer/dev/coffer.html
dicom-exporter 1.0.0
Program to export dicom files to .vti or .vtkjs
Keywords: dicom exporter medical

# DICOM-exporter

The DICOM-exporter is used to export DICOM files into VTK.JS or VTI files.

## Install

```sh
pip install .
```

## Usage

```sh
dicom-exporter <path/to/dicom/folder> <path/to/output.vti>
```

or for faster loading in VTK.JS:

```sh
dicom-exporter <path/to/dicom/folder> <path/to/output.vtkjs>
```

Setting the `--convert-12-bits`-flag will convert the resulting VTK file using 12 bits instead of 16 bits per block. This is only applied if the input DICOM files are encoded in 12 bits instead of 16 bits (i.e. BitsStored is 12 in the DICOM metadata).

The output file is compressed using gzip for VTK.JS files and ZLib for VTI files, unless the `--no-compress` flag is set.

Use `--resample` flag to resample the volume using the closest axis aligned direction matrix. This resampling will set the direction matrix to identity (legacy behavior).
appcraft 0.5.3
Appcraft is a modular framework designed to simplify software development by providing a structured and extensible architecture. It enables developers to create and manage complex applications with ease, ensuring scalability and maintainability.
Requires Python: >=3.6

# Appcraft

## Introduction

Welcome to the Appcraft!

Appcraft is a modular framework designed to simplify software development by providing a structured and extensible architecture. It enables developers to create and manage complex applications with ease, ensuring scalability and maintainability.

## Overview
- [Documentation](https://duxtec.github.io/appcraft/latest/index.html)
- [Getting Started](https://duxtec.github.io/appcraft/latest/getting_started.html)
- [Templates](https://duxtec.github.io/appcraft/latest/templates/index.html)
- [Architecture](https://duxtec.github.io/appcraft/latest/architecture/index.html)
- [Contribute](https://duxtec.github.io/appcraft/latest/contribute.html)
- [Contact](https://duxtec.github.io/appcraft/latest/contact.html)
byuhbll-configuro 1.0.0
A configuration library for Python applications.
Requires Python: >=3.8

# Configuro

`byuhbll-configuro` is a configuration tool for Python projects.

## Contributing to this project

### Project development setup

Follow these steps to setup your development environment:

1. Clone the repository. Run `git clone git@gitlab.com:byuhbll/lib/python/configuro.git`.
2. Open the project in Visual Studio Code.
3. Open the project in a devcontainer with the [Dev Containers](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers) extension.
4. Contribute!

This project uses [uv](https://docs.astral.sh/uv/) to manage dependencies.

### Project documentation

The [project's documentation](docs/index.md) can be found in the `docs` directory and is in markdown format.

### Testing this project

Running `pytest` will run all unit tests.

Unit tests can also be run using `tox`. Simply run `tox` on the command line and the unit tests should run for all supported versions of Python.
typer-common-functions 0.1.2
Commonly used Functions around the Typer CLI Library
Requires Python: >=3.8
Keywords: cli, typer

# 🎯 Typer Common Functions

Helper functions for [Typer](https://typer.tiangolo.com/) CLI applications.

[![PyPI version](https://badge.fury.io/py/typer-common-functions.svg)](https://pypi.org/project/typer-common-functions/)
[![License: LGPL v3](https://img.shields.io/badge/License-LGPL_v3-blue.svg)](https://www.gnu.org/licenses/lgpl-3.0)
[![Python Versions](https://img.shields.io/pypi/pyversions/typer-common-functions.svg)](https://pypi.org/project/typer-common-functions/)

## ✨ Features

- 📝 Rich-based logging configuration
- ⚡ Typer helper functions and utilities

## 📦 Installation

Available on [PyPI](https://pypi.org/project/typer-common-functions/):

```bash
pip install typer-common-functions
```

## 🚀 Usage

```python
from typer_common_functions import set_logging, typer_unpacker

# Configure logging with Rich
set_logging(verbose=True)

# Create CLI commands with type hints
@typer_unpacker
def hello(name: str) -> str:
    return f"Hello {name}!"
```

## 🛠️ Development

### 📋 Requirements

- 🐍 Python 3.8+
- 🏗️ [Hatch](https://hatch.pypa.io/) for project management
- ⚡ [UV](https://github.com/astral-sh/uv) for dependency management
- 🐳 [Dev Container](https://containers.dev/) support (optional)

### ⚙️ Setup

```bash
# Install tools
uv pip install hatch pre-commit
pre-commit install

# Create dev environment
hatch shell

# Run tests
hatch run dev:test

# Run linting
hatch run dev:lint

# Run formatters
hatch run dev:format
```

### 🔍 Code Quality

- ✅ Testing: pytest with coverage
- 🔬 Linting: flake8, pylint, mypy
- 🎨 Formatting: black, isort
- 🛡️ Security: bandit
- 🔄 Git hooks: pre-commit

### 📦 Release Process

1. 🔖 Run "Version Bump" workflow in GitHub Actions
2. 🎯 Choose version bump type
3. 👀 Review and merge the created PR
4. 🚀 Automated release and PyPI publish on merge

## 📄 License

LGPL-3.0-or-later - see [LICENSE](LICENSE)
breadcrumbsaddressbar 0.1.0.dev0
Address bar Qt widget with breadcrumb navigation
Requires Python: >=3.12

Address bar Qt widget with breadcrumb navigation
![](preview.gif)

Depends on [QtPy](https://github.com/spyder-ide/qtpy) abstraction layer library.

Tested in Windows 10 only.


## Assets
* [Right Arrow](https://www.iconfinder.com/icons/211607/right_arrow_icon), MIT
* [Left Arrow](https://www.iconfinder.com/icons/211689/left_arrow_icon), MIT
create-base-project 0.0.3
This libraly i`am created just for self using if u want u can use it with me
Requires Python: >=3.12

0.1.0

A simple CLI tool to help you create base projects for different Python frameworks. Currently, it supports creating projects for:

- **PyQt** (for GUI applications)
- **Aiogram** (for Telegram bots)

This tool helps automate the setup of projects, virtual environments, and dependency management.

## Features

- **Project Initialization**: Create a new project with predefined templates for PyQt or Aiogram.
- **Virtual Environment Management**: Create, activate, and manage virtual environments with ease.
- **Dependency Management**: Install and uninstall required dependencies for your project.
metafind 1.0.1
Metadata analysis tool written for CSEC-473 - Penetration Testing
Requires Python: >=3.13

# Metafind

![Python Version from PEP 621 TOML](https://img.shields.io/python/required-version-toml?tomlFilePath=https%3A%2F%2Fraw.githubusercontent.com%2Fsapph2c%2Fmetafind%2Fmain%2Fpyproject.toml&style=for-the-badge&logo=python&logoSize=auto)
![GitHub Actions Workflow Status](https://img.shields.io/github/actions/workflow/status/sapph2c/metafind/ci.yml?style=for-the-badge&logo=github&logoSize=auto)
![GitHub deployments](https://img.shields.io/github/deployments/sapph2c/metafind/pypi?style=for-the-badge&logo=pypi&logoColor=white&logoSize=auto)

**Metafind** is a metadata analysis tool written for CSEC-473 - Penetration Testing.

## Features

- Ability to retrieve and scrub file metadata.
- Lists unique discovered metadata tags.

## Install

Metafind is available as a Python package on PyPI and can be installed using `uv` (recommended), `pipx`, or `pip`.

**Note**: python 3.13+ is required

Install using uv:

```bash
uv install tool metafind@latest
```

Install using pipx:

```bash
pipx install metafind
```

Install using pip:

```bash
pip install metafind
```

## Usage

> [!IMPORTANT]  
> Metafind requires a metadata backend to be available within your system path.
>
> This can be specified in the CLI via `--backend`, which defaults to `exiftool`.
>
> For a full list of supported backends, see [Supported Backends](#Supported-Backends)

CLI options:

```bash
> metafind --help

Usage: metafind [OPTIONS] COMMAND [ARGS]...

  Metadata analysis tool created for CSEC-473 - Penetration Testing.

  Authored by sapph2c

Options:
  --help  Show this message and exit.

Commands:
  fetch   get file(s) metadata
  scrub   scrub file(s) metadata
  unique  get unique tags from file(s)
```

Retrieving file metadata:

```bash
metafind fetch <path-to-file>
```

Scrubbing metadata: (It's recommended to make a backup of the specified file(s), as this operation is non-reversible)

```bash
metafind scrub <path-to-file>
```

Listing all unique metadata tags:

```bash
metafind unique <path-to-file>
```

## Supported Backends

- [Exiftool](https://exiftool.org)