semvec/pypi-packages huggingface dataset:
beylerXomg 1.1.0
Kolay kullanımlı OMG Python kütüphanesi, WAV dosyalarını oynatma ve örnekler içerir.
Requires Python: >=3.7

# OMG

OMG, kolay kullanımlı bir Python kütüphanesidir.  
WAV dosyalarını oynatma, fonksiyonlar ve örnekler içerir.

## Kurulum

```bash
pip install omg
localfiletransfer 0.1.0
A simple local network file transfer tool
Requires Python: >=3.6

# localfiletransfer

A lightweight, no-framework LAN/same WiFi file transfer server written in pure Python WSGI. No Flask, no Django — just fast, clean file sharing on your local network.

## 🔧 Features

- 📁 Upload files via browser
- 📥 Download files (inline or direct link)
- 🔐 Basic HTTP authentication (username/password)
- 🚫 Upload size limit (default: 2GB)
- ♻️ Automatic deletion of uploaded files after 1 hour
- ⚙️ No external web frameworks — pure WSGI
- 🔥 Gunicorn-ready

---

## 📦 Installation

```bash
pip install localfiletransfer
````

---

## ▶️ Usage

```bash
localfiletransfer --bind 0.0.0.0:5000
```

By default, this will start a file server on `http://<your-local-ip>:5000`.

### Access from any device on the same LAN

Just open the URL in a browser on any device connected to the same WiFi/network.

---

## 🔐 Authentication

Basic HTTP Authentication is enabled by default.

| Variable   | Default |
| ---------- | ------- |
| `LFS_USER` | `admin` |
| `LFS_PASS` | `admin` |

You can override credentials by setting environment variables before running:

```bash
LFS_USER=myuser LFS_PASS=mypass localfiletransfer --bind 0.0.0.0:5000
```

---

## 📤 File Upload

* Uploads are done via browser using a simple form.
* The **Upload** button is only enabled when a file is selected.
* Maximum upload size is **2GB** (configurable in code).
* All uploaded files are automatically **deleted after 1 hour**.

---

## 🧹 Cleanup Behavior

A background thread checks every 10 minutes and deletes files older than **1 hour** to keep the system clean.

No database or metadata is stored — pure file system handling.

---

## 🐍 Requirements

* Python 3.6+
* `gunicorn`

---

## 📦 Packaging

If you're installing from source:

```bash
git clone https://github.com/bivab0/localfiletransfer
cd localfiletransfer
pip install .
```

---

## 📄 License

MIT License © [Bivab Das](https://github.com/bivab0)

---

## 🤝 Contributing

PRs are welcome! Just keep it lightweight and dependency-free.
genitosdk 0.0.4
SDK Python pour accéder à l’API MovieLens (Data Analysts/Data Scientists friendly)
Requires Python: >=3.11

# MovieLens SDK - `genitosdk`

Un SDK Python simple pour interagir avec l’API REST MovieLens. Il est conçu pour les **Data Analysts** et **Data Scientists**, avec une prise en charge native de **Pydantic**, **dictionnaires** et **DataFrames Pandas**.

[![PyPI version](https://badge.fury.io/py/genitosdk.svg)](https://badge.fury.io/py/genitosdk)
[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)

---

## Installation

```bash
pip install genitosdk
```

---

## Configuration

```python
from genitosdk import MovieClient, MovieConfig

# Configuration avec l’URL de votre API (Render ou locale)
config = MovieConfig(movie_base_url="https://movies-api-backend-tcju.onrender.com")
client = MovieClient(config=config)
```

---

## Tester le SDK

### 1. Health check

```python
client.health_check()
# Retourne : {"status": "ok"}
```

### 2. Récupérer un film

```python
movie = client.get_movie(1)
print(movie.title)
```

### 3. Liste de films au format DataFrame

```python
df = client.list_movies(limit=5, output_format="pandas")
print(df.head())
```

---

## Modes de sortie disponibles

Toutes les méthodes de liste (`list_movies`, `list_ratings`, etc.) peuvent retourner :

- des objets **Pydantic** (défaut)
- des **dictionnaires**
- des **DataFrames Pandas**

Exemple :

```python
client.list_movies(limit=10, output_format="dict")
client.list_ratings(limit=10, output_format="pandas")
```

---

## Tester en local

Vous pouvez aussi utiliser une API locale :

```python
config = MovieConfig(movie_base_url="http://localhost:8000")
client = MovieClient(config=config)
```

---

## Public cible

- Data Analysts
- Data Scientists
- Étudiants et curieux en Data
- Développeurs Python

---

## Licence

MIT License

---

## Liens utiles

- API Render : [https://movies-api-backend-tcju.onrender.com](https://movies-api-backend-tcju.onrender.com)
- PyPI : [https://pypi.org/project/genitosdk](https://pypi.org/project/genitosdk)
humansignal 0.0.1
This is a template repository for Python projects that use uv for their dependency management.
Requires Python: <4.0,>=3.9
Keywords: python

# humansignal

[![Release](https://img.shields.io/github/v/release/niklub/humansignal)](https://img.shields.io/github/v/release/niklub/humansignal)
[![Build status](https://img.shields.io/github/actions/workflow/status/niklub/humansignal/main.yml?branch=main)](https://github.com/niklub/humansignal/actions/workflows/main.yml?query=branch%3Amain)
[![codecov](https://codecov.io/gh/niklub/humansignal/branch/main/graph/badge.svg)](https://codecov.io/gh/niklub/humansignal)
[![Commit activity](https://img.shields.io/github/commit-activity/m/niklub/humansignal)](https://img.shields.io/github/commit-activity/m/niklub/humansignal)
[![License](https://img.shields.io/github/license/niklub/humansignal)](https://img.shields.io/github/license/niklub/humansignal)

This is a template repository for Python projects that use uv for their dependency management.

- **Github repository**: <https://github.com/niklub/humansignal/>
- **Documentation** <https://niklub.github.io/humansignal/>

## Getting started with your project

### 1. Create a New Repository

First, create a repository on GitHub with the same name as this project, and then run the following commands:

```bash
git init -b main
git add .
git commit -m "init commit"
git remote add origin git@github.com:niklub/humansignal.git
git push -u origin main
```

### 2. Set Up Your Development Environment

Then, install the environment and the pre-commit hooks with

```bash
make install
```

This will also generate your `uv.lock` file

### 3. Run the pre-commit hooks

Initially, the CI/CD pipeline might be failing due to formatting issues. To resolve those run:

```bash
uv run pre-commit run -a
```

### 4. Commit the changes

Lastly, commit the changes made by the two steps above to your repository.

```bash
git add .
git commit -m 'Fix formatting issues'
git push origin main
```

You are now ready to start development on your project!
The CI/CD pipeline will be triggered when you open a pull request, merge to main, or when you create a new release.

To finalize the set-up for publishing to PyPI, see [here](https://fpgmaas.github.io/cookiecutter-uv/features/publishing/#set-up-for-pypi).
For activating the automatic documentation with MkDocs, see [here](https://fpgmaas.github.io/cookiecutter-uv/features/mkdocs/#enabling-the-documentation-on-github).
To enable the code coverage reports, see [here](https://fpgmaas.github.io/cookiecutter-uv/features/codecov/).

## Releasing a new version

- Create an API Token on [PyPI](https://pypi.org/).
- Add the API Token to your projects secrets with the name `PYPI_TOKEN` by visiting [this page](https://github.com/niklub/humansignal/settings/secrets/actions/new).
- Create a [new release](https://github.com/niklub/humansignal/releases/new) on Github.
- Create a new tag in the form `*.*.*`.

For more details, see [here](https://fpgmaas.github.io/cookiecutter-uv/features/cicd/#how-to-trigger-a-release).

---

Repository initiated with [fpgmaas/cookiecutter-uv](https://github.com/fpgmaas/cookiecutter-uv).
abnormal-hieratic-indexer 1.1.2
Index annotations from the Abnormal Hieratic Global Portal in Elasticsearch
Requires Python: >=3.9

# Abnormal Hieratic Indexer

Script that indexes annotations in the [Abnormal Hieratic Global Portal][ahgp].
This script is specifically tailored towards the annotations created for the AHGP.

Annotations in the AHGP are stored in a [Simple Annotation Server][sas],
but for search we use [Elasticsearch][es].

[ahgp]: https://lab.library.universiteitleiden.nl/abnormalhieratic/
[sas]: https://github.com/glenrobson/SimpleAnnotationServer
[es]: https://www.elastic.co/guide/en/elasticsearch/

## Installation

This script was developed with Python 3.9. It may run on other versions, but tests are very limited.

To install, run `pip install abnormal-hieratic-indexer` in your environment.

## Usage

```
$ abhier-indexer -h
usage: abhier-indexer [-h] [--canvas-uri-prefix CANVAS_URI_PREFIX] [--index INDEX] source target

positional arguments:
  source                Base URL for the Simple Annotation Server
  target                Base URL for ElasticSearch (default: http://localhost:9200)

optional arguments:
  -h, --help            show this help message and exit
  --canvas-uri-prefix CANVAS_URI_PREFIX
                        Index only annotations targeting canvases whose URIs start with this prefix (default:
                        https://lab.library.universiteitleiden.nl/manifests/external/louvre/)
  --index INDEX         URI path to the ElasticSearch index (default: /annotations/)
```

To enable periodic indexing, you can set up a cronjob or Systemd timer.

# Author and license

Abnormal Hieratic Indexer was created by Ben Companjen at the Centre for Digital Scholarship.

© 2024 Leiden University Libraries

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program.  If not, see <https://www.gnu.org/licenses/>.
omgXbeyler 1.1.0
Kolay kullanımlı OMG Python kütüphanesi, WAV dosyalarını oynatma ve örnekler içerir.
Requires Python: >=3.7

# OMG

OMG, kolay kullanımlı bir Python kütüphanesidir.  
WAV dosyalarını oynatma, fonksiyonlar ve örnekler içerir.

## Kurulum

```bash
pip install omg
omgxbeyler 1.0.0
Kolay kullanımlı OMG Python kütüphanesi, WAV dosyalarını oynatma ve örnekler içerir.
Requires Python: >=3.7

# OMG

OMG, kolay kullanımlı bir Python kütüphanesidir.  
WAV dosyalarını oynatma, fonksiyonlar ve örnekler içerir.

## Kurulum

```bash
pip install omg