semvec/pypi-packages huggingface dataset:
pymcsrvstatus 1.1.3
An async API wrapper for the mcsrvstat.us API.
Requires Python: >=3.9

# pymcsrvstatus

[<img alt="Discord" src="https://img.shields.io/discord/1070058354925383681?logo=discord&color=%235661f6&style=plastic">](https://discord.gg/eMUMe77Yb8)
[<img alt="Actions Status" src="https://c.csw.im/cswimr/pymcsrvstatus/badges/workflows/actions.yaml/badge.svg?style=plastic">](https://c.csw.im/cswimr/pymcsrvstatus/actions?workflow=actions.yaml)
[<img alt="PyPI - Version" src="https://img.shields.io/pypi/v/pymcsrvstatus?style=plastic">](https://pypi.org/project/pymcsrvstatus/)
[<img alt="PyPI - Python Version" src="https://img.shields.io/pypi/pyversions/pymcsrvstatus?style=plastic">](https://pypi.org/project/pymcsrvstatus/)
[<img alt="PyPI - License" src="https://img.shields.io/pypi/l/pymcsrvstatus?style=plastic">](https://c.csw.im/cswimr/pymcsrvstatus/src/tag/v1.1.3/LICENSE.md)  

A simple async API wrapper for the [mcsrvstat.us](https://api.mcsrvstat.us") API.

## Usage

```python
from pymcsrvstatus import check_if_online, fetch, get_icon_url
import asyncio

async def example(address: str) -> None:
    if await check_if_online(address, extra_user_agent="pymcsrvstatus example"):
        print("Hypixel is online!")
    else:
        print("Hypixel is offline!")

    status = await fetch(address, extra_user_agent="pymcsrvstatus example")
    assert status.online is True
    print(status.protocol) # Protocol(version=47, name="1.8.9")
    print(status.version) # "Requires MC 1.8 / 1.21"
    print(status.players) # Players(online=33812, max=200000, list=None)

    print(get_icon_url(address)) # https://api.mcsrvstat.us/icon/hypixel.net

asyncio.run(example(address="hypixel.net"))
```
mental-health-app 0.6
A mental health prediction app using facial analysis.
Requires Python: >=3.6

# Mental Health App
<img style="width: -webkit-fill-available" src="https://galihru.github.io/facemind/logofm.png" alt="logo facemind">

<p align="center" style="display: flex; justify-content: center; align-items: center; flex-wrap: wrap; gap: 0.5em;">
  <a href="https://pypi.org/project/mental_health_app/">
    <img src="https://img.shields.io/pypi/v/mental_health_app.svg" alt="PyPI version"/>
  </a>
  <a href="https://pypi.org/project/mental_health_app/">
    <img src="https://img.shields.io/pypi/dm/mental_health_app.svg" alt="PyPI downloads"/>
  </a>

</p>

This application uses computer vision and machine learning to analyze mental health based on facial expressions. The app includes login system, and real-time mental health analysis through facial landmarks, using OpenCV, Mediapipe, and PyQt5.

## Requirements

Before running the app, make sure you have the following Python packages installed:

- `opencv-python`
- `numpy`
- `mediapipe`
- `selenium`
- `PyQt5`
- `pandas`

You can install missing dependencies by running the following command:

```bash
docker pull ghcr.io/galihru/mental_health_app:latest
```

## Author by
1. Ana Maulida
2. GALIH RIDHO UTOMO

Delegation for competition paper
logfire-lsp 0.0.4
A Language Server Protocol implementation for Pydantic Logfire
Requires Python: >=3.9

# Logfire LSP

A [Language Server Protocol](https://microsoft.github.io/language-server-protocol/) implementation
for the [Logfire platform](https://logfire.pydantic.dev/docs/).

> [!WARNING]
>
> This project is in early development.

<div align="center">
    <picture>
      <img src="./assets/example.png" alt="LSP Example">
    </picture>
</div>
mitene-download 0.6.0
Download medias from https://mitene.us/ or https://family-album.com/
Requires Python: >=3.9

Download medias from https://mitene.us/ or https://family-album.com/ to keep a local backup.

## Usage

Install with `pip install mitene_download`.

From mitene app, invite a family member for the web version and copy the URL ( that should be something like `https://mitene.us/f/abcd123456` )

Run the script with `mitene_download https://mitene.us/f/abcd123456`, using the URL from previous step.
 
This will download all photos and video in `out` folder. Some text files will be created with the comments.

If the album is password-protected, you can specify the password using `--password` command line argument, similar to this: `mitene_download https://mitene.us/f/abcd123456 --password the_password`.

To exclude comments (MD files) use the `--nocomments` command line argument, similar to this: `mitene_download https://mitene.us/f/abcd123456 --nocomments`
selenia 0.2.0
Selenium wrapper to find XPath from natural language using LLMs
Requires Python: >=3.7

# Selenia

Selenium wrapper to find XPath from natural language using LLMs

---

## 🚀 Overview
Selenia lets you locate web elements using natural language queries, powered by LLMs (Large Language Models). It integrates with Selenium and supports local LLMs via Ollama.

## ✨ Features
- 🔍 Find elements by describing them in plain English
- 🤖 Pluggable LLM model clients (Ollama, OpenAI, etc.)
- 🧪 Easy integration with Selenium WebDriver
- 🧩 Extensible for custom model backends

## 📦 Installation
```bash
pip install selenia
```
Or from source:
```bash
pip install .
```

## 🛠️ Usage Example
```python
from selenium import webdriver
from selenia import Selenia, OllamaServerClient, OllamaClient

#for either remote or local ollama server
driver = webdriver.Chrome()
model_client = OllamaServerClient(model_name="llama3",base_url="http://localhost:11434/api/generate")

#for local ollama 
model_client = OllamaClient(model_name="llama3")

selenia = Selenia(driver, model_client)

# Find an element by description
element = selenia.find("the search input box at the top bar")

# Find all matching elements
elements = selenia.find_all("all buttons with the text 'Submit'")
```

## 🧩 Model Clients
- **OllamaServerClient**: Connects to a local Ollama server (defaults: [`model_name`:`llama3`,`base_url`=`http://localhost:11434/api/generate`])
- **OllamaClient**: Uses the Ollama Python package

## 🧪 Running Tests
```bash
pytest tests/
```

## 📄 License
MIT

---

Made with ❤️ by Penielny
hancsv 1.2
A utility for handling CSV files, supports Hancom Cell CSV file (for cybersecurity demo purposes only).
Requires Python: >=3.6

# hancsv

> **Warning:** This project is for **cybersecurity demonstration purposes only**. It may contain potential security vulnerabilities, and it should **not** be used in production environments.

## Features

- **Sniff CSV file structure**: Attempts to detect delimiters, quote characters, and more.
- **Read CSV as dictionaries**: Implements `DictReader` for reading CSV files as Python dictionaries.
- **Write CSV from dictionaries**: Implements `DictWriter` to write dictionaries as CSV files.

## Security Disclaimer

This package **may contain vulnerabilities** that could lead to unintended behavior or security issues.
Please **do not use this package** in real-world applications where security and data integrity are important.

## Installation

This package can be installed via pip:
```python
pip install hancsv
```

## Usage

```python
from hancsv import DictReader, DictWriter, Sniffer

# Reading CSV as dictionaries
with open('data.csv', 'r') as f:
    reader = DictReader(f)
    for row in reader:
        print(row)

# Writing CSV from dictionaries
with open('output.csv', 'w') as f:
    writer = DictWriter(f, fieldnames=["name", "age"])
    writer.writeheader()
    writer.writerow({"name": "Charlie", "age": 40})
```
turkle-review 0.2
Adds batch review capability to Turkle
Requires Python: >=3.8

# Turkle Review
Adds the ability to review completed task assignments in the admin UI.

This turkle plugin adds a button to the Batch listing page to view completed results.
It displays the username, input from the CSV, and the answers from the form.
It does its best to guess which columns have json and renders that as a tree.

## Install
Install the Python package using pip:
```
pip install turkle-review
```
Then add this as an app in local_settings.py:
```
INSTALLED_APPS.append('turkle_review')
```
Your IDE will complain about this line but it works.

Finally, you will need to restart the webserver.
pyeqx 0.7.17
Python library for interacting with Spark, Azure, Minio, and other data sources.
Requires Python: >=3.11

# esbm-dis-dfts-pyeqx-core

Spark: `3.5.3`

## pre-requisites

to setup virtual environment to execute unit tests, it has to setup virtual env and install dependencies

```bash
# setup virtual env
python3.12 -m venv .venv

# activate virtual env
source .venv/bin/activate

# install dependencies
pip install delta-spark pyspark pandas retrying minio requests

# install dependencies (If you want to publish)
pip install twine
```

## tests

to execute unit test run this command at root of the project

```bash
python3 -m unittest discover test -p "**.py"

# or

pytest
```

## build

```bash
python3 -m pip install --upgrade build
python3 -m build
```

## publish to testpypi

```bash
python3 -m twine upload --repository testpypi dist/*
```

## publish to pypi

```bash
python3 -m twine upload dist/*

# specific config for pypi
python3 -m twine upload --config-file .pypirc dist/*
```

## publish to gitlab

```bash
python3 -m twine upload --repository-url https://gitlab.com/api/v4/projects/<project_id>/packages/pypi/ --username gitlab-ci-token --password <access_token> dist/*

# Replace <project_id> with the ID of your GitLab project
```

## install from gitlab

```bash
#install from pypi
pip install pyeqx-core

#install from testpypi
pip install -i https://test.pypi.org/simple/ pyeqx-core

# install from gitlab
pip install datadriven-core --index-url https://__token__:<access_token>@gitlab.com/api/v4/projects/<project_id>/packages/pypi/simple
pip install pyeqx-core --index-url https://__token__:<access_token>@gitlab.com/api/v4/projects/<project_id>/packages/pypi/simple
# Replace <project_id> with the ID of your GitLab project
```
triodos_fund_analyzer 0.1.dev1
Tool to visualize Triodos fund histories
Requires Python: >=3.10

# triodos-fund-analyzer

This is a small tool to visualize the value of Triodos funds.

## Ethics

Holding shares usually is not ethical for a number of reasons. Triodos
funds are among the rare exceptions that have less unethical impact.

In general it is not ethical to make profits of other peoples work. Even
more so, because for the largest part the unequal distribution of wealth
requires the poor to borrow money for their causes.

It may be ethical if you give the profits of fund investments to
[objectively](https://www.britannica.com/topic/effective-altruism)
[good](https://plato.stanford.edu/entries/common-good/) projects.

## The tool

If you (plan to) own shares of funds, you may want to know how they do.
If that concerns Triodos funds, you can use this tool to visualize the
course history, including optional corrections.

### Check it out

Check it out online https://triodos-fund-analyzer.streamlit.app/

### Install it

`pip install triodos_fund_analyzer`

### Use it

For now, run `plot-funds <Triodos ... Fund>` from a shell. If you know
your stuff, feel free to use the implemented function to build a plot to
you liking - you're welcome to feed it back via Pull Requests.

-----
**That's it, have fun!**