semvec/pypi-packages huggingface dataset:
test-genie-test 1.0.5
AI-powered CLI tool to auto-generate test cases for Python, C++, and Java code with both online and offline modes
Requires Python: >=3.8
Keywords: testing, test-generation, ai, cli, python, cpp, java, pytest, unittest, gtest, junit

# 🧪 TestGenie - Instantly Generate Test Cases from Your Terminal

**TestGenie** is a fast, intuitive CLI tool designed for developers who want to generate meaningful test cases from their source code - without ever leaving the terminal.

No more toggling between browser tabs, writing boilerplate, or wasting hours on trivial tests. TestGenie bridges your code with AI-powered suggestions tailored for your language and logic. 

*Currently, it uses online AI agents for test cases generation, but an offline mode is coming soon. Stay tuned!*

---

## ✨ Features

- 🔍 **Language-aware test generation** (Python, C++) [more coming soon]
- ⚡ **CLI-first experience** - stay in your flow
- 🧠 Powered by context-aware agents
- 🌐 Syncs with your online dashboard
- 🔐 Lightweight auth system
- 📊 Usage tracking (for you and your team)

---

## 🚀 Installation

TestGenie requires Python 3.8+

Install directly from PyPI:

```bash
pip install test-genie
```
---

## 🛠 Usage

Generate test cases from your CLI:

```bash
test-genie generate --path path/to/your_file.py
```

You can also specify the language explicitly:

```bash
test-genie generate -pt path/to/your_file.cpp -l cpp
```

Authenticate once:

```bash
test-genie login
```

If you don't have an account, register quickly on our website: https://thetestgenie.com

---

## 🌐 Dashboard

Visit our dashboard (https://thetestgenie.com/dashboard) to view your usage, premium status, recent generation history, and more.

---

## 💡 Use Cases

- Quickly bootstrap test coverage on legacy projects
- Generate starter tests for new logic
<!-- - Integrate with CI to flag untested critical paths -->
- Empower junior devs with example-driven TDD

---

## 📦 Publishing / Contributing

Want to contribute or self-host the backend? Instructions are coming soon. For now, feel free to mail me at wadhwakushagra01@gmail.com

---

## 📃 License

MIT © 2025 TestGenie Team
oxfordapi 0.1.1
Explore the Oxford dictionaries API.
Requires Python: >=3.11.0

> [!CAUTION]
> This project has moved to [pip install oxfordapi](https://pypi.org/project/oxfordapi/)

# Oxford Dictionary API Python Wrapper

This project offers a simple client for the [Oxford Dictionary API](https://developer.oxforddictionaries.com/).

## Getting your App Key and ID

To get your App Key and ID, please follow the [Getting Started](https://developer.oxforddictionaries.com/documentation/getting_started) guide.

## Installation

`pip install oxfordapi`

## Usage

```python
from oxfordapi import Client

async def main():
  oxford_api = Client("<app_id>", "<app_key>")
  print(await oxford_api.get_entries("word"))

if __name__ == "__main__":
    asyncio.run(main())
```
generalize 0.3.0
Machine learning tools for running repeated nested leave-one-dataset-out validation and more.
Requires Python: <4.0,>=3.9

# Generalize <a href='https://github.com/LudvigOlsen/generalize'><img src='https://raw.githubusercontent.com/LudvigOlsen/generalize/master/generalize_242x280_250dpi.png' align="right" height="140" /></a>

**Author:** [Ludvig R. Olsen](https://www.ludvigolsen.dk/) ( <r-pkgs@ludvigolsen.dk> )

The ultimate goal of training machine learning models is to generalize to new, unseen data. This package contains tools for measuring model performance across multiple datasets via cross-dataset-validation (aka. leave-one-dataset-out).

Under development!

 - Not generalized enough for general usage (ironic, I know)
 - Relies on an old version of scikit-learn, needs updating
 - Linear regression is not currently implemented
 - Help strings are likely not up-to-date

### Main functions and classes

| Function                       | Description                                                                        |
|:-------------------------------|:-----------------------------------------------------------------------------------|
| `nested_cross_validate()`      | Run (repeated) nested cross-validation.                                            |
| `train_full_model()`           | Train model on all data and save to disk.                                          |
| `evaluate_univariate_models()` | Evaluate prediction potential of every predictor separately.                       |
| `PipelineDesigner`             | Design a scikit-learn pipeline for use in cross-validation.                        |
| `ROCCurve`, `ROCCurves`        | ROC curve containers with various utility methods.                                 |
| `select_samples()`             | Utility for selecting samples based on (collapsed) labels.                         |
ceph-client 1.0.3
A Python client for Ceph S3-compatible storage
Requires Python: <4.0,>=3.12

# Ceph client

Ceph client

- [Prerequisites](#prerequisites)
- [Updating project template](#updating-project-template)

## Prerequisites

Make sure you have the following software installed:

- [python ^3.12](https://www.python.org/downloads/)
- [poetry ^2.1.3](https://python-poetry.org/docs/#installation)

Install python dependencies using poetry and activate the virtual environment:

```sh
poetry env use python3.12
poetry install
eval $(poetry env activate)
```

Lastly, install `pre-commit hooks` by running:

```sh
pre-commit install
```

## Updating project template

To update the project template, run `copier update` and answer template
questions:

```sh
copier update --trust
```

Review the changes Copier made to your project:

```sh
git diff
```

Resolve any merge conflicts, then stage and commit the changes:

```sh
git add .
git commit -m "Updated project template"
git push
```
apifoncier2 0.1.4
Utiliser l'API Données foncières du Cerema en python
Requires Python: >=3.11
Keywords: api, datafoncier, foncier

# apifoncier

Ce package est un client Python qui permet d'interroger facilement les différents jeux de données foncières interrogeables via l'API Données foncières du Cerema, notamment :

- les mutations foncières et immobilières issues de DVF+ (ouvert) et de DV3F (restriction d'accès)
- les données des Fichiers fonciers (parcelles, locaux, TUPs, propriétaires)
- les données sur les friches issues de Cartofriches
- les indicateurs territoriaux (consommation d'espace, marché immobilier, etc.)

## Installation

```bash
pip install apifoncier2
```

## Documentation

La documentation complète est disponible sur [https://cerema.github.io/apifoncier/](https://cerema.github.io/apifoncier/)

## Lien vers le dépôt GitHub

Le code source est disponible sur [https://github.com/cerema/apifoncier](https://github.com/cerema/apifoncier)
MIOFlow 0.1.9
MIOFlow is a Python package for modeling and analyzing single-cell RNA-seq data using optimal flows.
Requires Python: >=3.8
Keywords: neural ode, trajectory, emd, Optimal Transport, single cell RNA, mioflow

<a id="readme-top"></a>

<!-- PROJECT LOGO -->

<div align="center">

  <h1 align="center">MIOFlow</h1>

<!-- PROJECT SHIELDS -->
[![arXiv](https://img.shields.io/badge/arXiv-2206.14928-b31b1b.svg)](https://arxiv.org/abs/2206.14928)
[![Latest PyPI version](https://img.shields.io/pypi/v/mioflow.svg)](https://pypi.org/project/mioflow/)
[![Twitter](https://img.shields.io/twitter/follow/KrishnaswamyLab.svg?style=social&label=Follow)](https://twitter.com/KrishnaswamyLab)
[![GitHub Stars](https://img.shields.io/github/stars/KrishnaswamyLab/ImmunoStruct.svg?style=social\&label=Stars)](https://github.com/KrishnaswamyLab/ImmunoStruct)
</div>



**MIOFlow** is a Python package for modeling and analyzing single-cell RNA-seq data using **optimal flows**. It leverages **neural ordinary differential equations (neural ODEs)** and **optimal transport** to reconstruct trajectories, compare cell populations, and study dynamic biological processes.

## Features

- **Trajectory inference** using optimal transport and neural ODEs
- **Comparison across conditions** (e.g., control vs. perturbation)  
- **Visualization utilities** for single-cell dynamics
- **Flexible I/O** for AnnData and standard scRNA-seq formats

## Installation

### Install from PyPI

```bash
pip install MIOFlow
```

### Install from GitHub (Development Version)

```bash
pip install git+https://github.com/yourusername/MIOFlow.git
```

## Usage

### Basic Workflow

A basic workflow can be found on the tutorials. There is a Google Colab option as well.

tutorials/1_MIOFlow_Example.ipynb or tutorials/2_Colab_Training_MIOFlow


## Citation

If you use **MIOFlow** in your research, please cite:

```
@misc{https://doi.org/10.48550/arxiv.2206.14928,
  doi = {10.48550/ARXIV.2206.14928},
  url = {https://arxiv.org/abs/2206.14928},
  author = {Huguet,  Guillaume and Magruder,  D. S. and Tong,  Alexander and Fasina,  Oluwadamilola and Kuchroo,  Manik and Wolf,  Guy and Krishnaswamy,  Smita},
  keywords = {Machine Learning (cs.LG),  FOS: Computer and information sciences,  FOS: Computer and information sciences},
  title = {Manifold Interpolating Optimal-Transport Flows for Trajectory Inference},
  publisher = {arXiv},
  year = {2022},
  copyright = {arXiv.org perpetual,  non-exclusive license}
}
```

## License

MIOFlow is distributed under the terms of the Yale License.

## Support

- 🐛 Issues: [GitHub Issues](https://github.com/yourusername/MIOFlow/issues)
- 💬 Discussions: [GitHub Discussions](https://github.com/yourusername/MIOFlow/discussions)

## Acknowledgments

- Built with PyTorch for neural ODE implementations
- Integrates with scanpy ecosystem for single-cell analysis
- Optimal transport implementations based on POT library
jsonschema-to-typeddict 1.4.2
Generates a python file with a TypedDict definition that attempts to match what is in a given JsonSchema.
Requires Python: >=3.10

# jsonschema-to-typeddict
precommit hook for creating a TypedDict definition for your JsonSchema

## Usage

Add the following to your `.pre-commit-config.yaml`:

```yaml
-   repo: https://github.com/henriquegemignani/jsonschema-to-typeddict
    rev: v1.0.1
    hooks:
    -   id: jsonschema-to-typeddict
        files: src/my_package/files/schema.json
        args: [ --output-path, src/my_package/configuration.pyi, --root-name, Configuration ]
```
spyprof 0.0.2
Sampling Python Profiler
Requires Python: >=3.9

# SPyProf
Sampling line-by-line Python profiler.

# Installation
```bash
pip install https://github.com/yuriiz/spyprof
```

# Usage
Import `spyprof` module at startup:

```python
import spyprof
```

Profiling reports will be written to `spyprof` directory periodically every 10 seconds and at application exit.

Profiling report measured with `ITIMER_REAL` timer will be written to spyprof/real.html.

Profiling report measured with `ITIMER_PROF` timer will be written to spyprof/prof.html.

# Example

Running following code:
```python
import math
from time import sleep

import spyprof


def foo():
    """
    CPU time consuming code.
    """
    for i in range(10**8):
        math.sqrt(i)
        math.sqrt(i)
        pass


def bar():
    """
    Real time consuming code.
    """
    sleep(10)


if __name__ == "__main__":
    foo()
    bar()
```

Will result in the following reports:
| real.html | prof.html |
| --------- | --------- |
| <img width="1280" height="958" alt="Screenshot 2025-09-08 at 21-13-57 " src="https://github.com/user-attachments/assets/a801a750-9471-439b-85d0-3fce44c37cc6" /> | <img width="1280" height="958" alt="Screenshot 2025-09-08 at 21-14-04 " src="https://github.com/user-attachments/assets/5a1360cc-19e3-4571-b808-e415049e3d3b" /> |
educelab-imgproc 0.7.0a0
EduceLab image processing module
Requires Python: >=3.9

# EduceLab Image Processing

`educelab-imgproc` is a Python module for performing common image
processing tasks. This module is largely a collection of wrapper functions
around functionality provided by other toolkits (numpy, scikit-image, etc.) and
is meant to encourage consistent, predictable use across EduceLab projects.
It should not be considered a total replacement for those other, wonderful
toolkits.

## Requirements
- Python 3.9+

## Installation

This project is available on PyPI:

```shell
python3 -m pip install educelab-imgproc
```

### GUI (Work in progress)

This package comes with a basic image editor for testing the various processing 
functions. To run:

```shell
# Install this module with GUI dependencies
python -m pip install educelab-imgproc[gui]

# Run the GUI
el_imgproc
```

## API Documentation

Visit our API documentation [here](https://educelab.gitlab.io/educelab-imgproc/).
asciigenator 0.0.6
A Python library for generating ASCII art from text
Requires Python: >=3.6
Keywords: ascii art text generator cli

# asciigenator <!-- omit in toc -->

A lightweight Python library for generating ASCII art from text.

[![PyPI version](https://img.shields.io/pypi/v/asciigenator.svg?color=blue)](https://pypi.org/project/asciigenator/)
[![Python Versions](https://img.shields.io/pypi/pyversions/asciigenator.svg)](https://pypi.org/project/asciigenator/)
[![License](https://img.shields.io/github/license/bhatishan2003/asciigenator)](LICENSE)
[![Python application](https://github.com/bhatishan2003/asciigenator/actions/workflows/python-app.yml/badge.svg)](https://github.com/bhatishan2003/asciigenator/actions/workflows/python-app.yml)
[![Coverage](https://img.shields.io/codecov/c/github/bhatishan2003/asciigenator)](https://codecov.io/gh/bhatishan2003/asciigenator)

## Table of Contents <!-- omit in toc -->

-   [Installation](#installation)
-   [Usage](#usage)
    -   [Basic Python Usage](#basic-python-usage)
    -   [Command Line Usage](#command-line-usage)
-   [Testing](#testing)

---

## Installation

-   Clone the repository:

    ```bash
    git clone https://github.com/bhatishan2003/asciigenator.git
    cd asciigenator
    ```

-   Install the package:

    ```bash
    pip install .
    ```

-   For development (editable mode):

    ```bash
    pip install -e .
    ```

## Usage

### Basic Python Usage

```python
import asciigenator

# Test simple font
print("=== Simple Font ===")
print(asciigenator.generate("Hello", font="simple"))

# === Simple Font ===
#  *   **  ** *** ***  ** *** *   *
# * * *   *    *   *  *   *   **  *
# ***  *  *    *   *  * * **  * * *
# * *   * *    *   *  * * *   *  **
# * * **   ** *** ***  ** *** *   *

print("\n=== Block Font ===")
print(asciigenator.generate("Ishan", font="block"))

# === Block Font ===
#   █
#  █ █  ████  ████ █████ █████  ████ █████  █   █
#  █ █  █     █       █     █   █     █     ██  █
# █████  ███  █       █     █   █  ██ ████  █ █ █
# █   █     █ █       █     █   █   █ █     █  ██
# █   █ ████   ████ █████ █████  ████ █████ █   █

print("\n=== Available Fonts ===")
print(asciigenator.list_fonts())

# === Available Fonts ===
# ['block', 'simple']

```

### Command Line Usage

```bash
asciigenator "Hello World"
asciigenator "Hello World" --font block
asciigenator --list-fonts
asciigenator "Hello World" --font block  --border "#"
asciigenator "Hello World"  --font block --color magenta
```

## Testing

Run all tests:

```bash
pytest -v
```
buildwizard 1.0.0
Auto sync your itemsets, perks and spells with mobalytics.gg ones on champion selection.
Requires Python: >=3.13
Keywords: automation, builds, buildwizard, lcu, league, league of legends, lol, runes, simplerunes

# README.md

Auto sync your itemsets, perks and spells with mobalytics.gg ones on champion selection.
formtool 1.0.0
ffmpeg command shortcuts
Requires Python: >=3.10

# formtool

Easy ffmpeg shortcuts

- [x] Can batch convert files
- [x] Automatically use best settings
- [x] You can override params
- [x] Deletes original files if you want
- [x] Shortcuts that are actually short

## Install

```bash
pip install formtool
```

## Usage

```bash
# Compress everything to flac, save space without losing quality
fflac **/*.wav

# If you want to send some music but flac is too big: convert to mp3 v0
fmp3 song.flac

# If you want to archive videos
fav1 *.mp4

# If you want to send videos to telegram
fx264 video.mkv
```
my-clicker 0.0.1
Streamlit component that allows you to do X
Requires Python: >=3.7

# streamlit-custom-component

Streamlit component that allows you to do X

## Installation instructions

```sh
pip install streamlit-custom-component
```

## Usage instructions

```python
import streamlit as st

from my_component import my_component

value = my_component()

st.write(value)
```
ira-ev-api-wrapper 0.1.1
A simple HTTP library for handling device actions
Requires Python: >=3.6

# IRA.EV API Wrapper

This project is a Python library that provides methods for performing HTTP requests against the undocumented IRA.ev API from Tata Motors

## Features

- **Login**: Login using mobile
- **Refresh Access Token**
- **Get Vehicles Details**: Secure a specified device.

## Installation

To install the library, clone the repository and install the required dependencies:

## Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

## License

This project is licensed under the MIT License. See the LICENSE file for more details.
pr-pro 1.1.0
PRogramming PROgrams is a Python library for defining training programs.
Requires Python: >=3.12

# PRogramming PROgrams
---
[![cov](https://RolandStolz.github.io/pr_pro/badges/coverage.svg)](https://github.com/RolandStolz/pr_pro/actions)

`pr_pro` is a Python package for defining training programs. It's main features at a glance are:
1. Modular and extensible definition of different types of exercises
2. Export to and import from `json` files
3. Automatic computation of weights based on defined max values
3. Render as **plain text** or **pdf**
4. **Ready to deploy** `streamlit` app for each custom program that you define

## Simple example
```Python
program = get_simple_example_program()
program.compute_values(ComputeConfig(one_rm_calculator=Brzycki1RMCalculator()))
print(program)

# Export to pdf
program.export_to_pdf(Path('example.pdf'))
```
```
--- Workout Test program ---
Best exercise values
  Backsquat: 100
  Bench Press: 80

Workout sessions
--- W1D1 ---
notes: Easy on first day.
Backsquat with 2 sets:
  reps 5, weight 55.0, percentage 0.55, relative_percentage 0.619
  reps 5, weight 55.0, percentage 0.55, relative_percentage 0.619
Pendlay row + Pushup with 2 sets:
  reps 6, percentage 0.6 | reps 10
  reps 6, percentage 0.6 | reps 10
Bench Press with 2 sets:
  reps 8, weight 40.0, percentage 0.5, relative_percentage 0.621
  reps 8, weight 40.0, percentage 0.5, relative_percentage 0.621
```

`pr_pro` also allows defining progressions throughout the training block. Look into `pr_pro/examples.py` for an example of this.

## Installation
```bash
pip install pr_pro
```

## `streamlit` visualization
You need to install the visualization dependencies
```bash
pip install pr_pro[vis]
```

Simply define your program and create a file `streamlit_app.py` with
```python
from pr_pro.streamlit_vis.streamlit_app import run_streamlit_app

program = ...  # Your program
run_streamlit_app(program)
```

Then run the streamlit app as per usual
```bash
streamlit run streamlit_app.py
```

The app looks like this:
![Streamlit app example](https://RolandStolz.github.io/pr_pro/streamlit_app_example.png)

For a live demo go to [https://pr-pro-demo.streamlit.app/](https://pr-pro-demo.streamlit.app/)
azdex 0.1.1
Add your description here
Requires Python: >=3.12
Keywords: python dex libs, dex, Python Decentralized Crypto Exchange Libs

# Dex

- DEX = Cryptocurrency Decentralized Exchanges (加密货币去中心化交易所)

## Installation

```ruby

uv add azdex

```

## DEX Rankings

- ✅ [CoinMarketCap - DEX](https://coinmarketcap.com/rankings/exchanges/dex/)

## DEX Exchanges

### Hyperliquid

- ✅ [Hyperliquid](https://app.hyperliquid.xyz/trade)
- ✅ [Python SDK](https://github.com/hyperliquid-dex/hyperliquid-python-sdk)
yeswehack 0.8.11
yeswehack - YesWeHack API Wrapper
Requires Python: <3.13,>=3.7.0

SDK for yeswehack


# Build from source

`make build` (or `poetry build`)

# Installation

## Developer

### Requirements

- [`poetry`](https://python-poetry.org/) (`pip install poetry`)

### Installation

`make install` (or `poetry install`): creates a virtualenv and install dependencies

## From pip

```
pip install yeswehack
```

## From wheel

```
pip install path/to/yeswehack-wheel.whl
```

# Getting starting with YesWeHack Python SDK

## API Module

In this python module, we define object mapping to YesWeHack API Object.
ledger-app-clients.ethereum 0.6.0
Ledger Ethereum Python client
Requires Python: >=3.9

# Python client for the Ledger Ethereum application

This package allows to communicate with the Ledger Ethereum application, either on a
real device, or emulated on Speculos.

## Installation from pypi.org

You can install the client from `pypi.org`:

  ```bash
  pip install ledger_app_clients.ethereum
  ```

## Installation from sources

You can also install the client from this repo:

```bash
pip install .
```
DE-Lib 0.0.56.3.3
Biblioteca de funcionalidades

<h1>DAX_UTIL</h1>

## **Biblioteca de funcionalidades**

## Conteudo

Os pacotes que compoem esta biblioteca sao:<br>
- Cipher<br>
- DateUtils<br>
- Generic<br>
- SQL<br>
- System<br>
- WebHook<br>

<h3>Descricao dos pacotes...</h3>
<h2>Cipher:</h2>

Pacote responsavel por criptografar e descriptografar conteudos, composta 
por tres classes: RSA, AES e B64.
Peculiaridades de cada uma destas classes:<br>
- <b>RSA</b>: Criptografa textos curtos
- <b>AES</b>: Criptografa textos longos (faz uso tambem da RSA)
- <b>B64</b>: Criptografia mais vulneravel

<b><u>from Utils.Cipher import RSA, AES, B64</b></u>

Apesar de criptografar qualquer tipo de valor, nao e recomendada utilizar 
para senhas ou informacoes sensiveis pois sua vulnerabilidade e grande.<br>
***Em breve sera disponibilizadas funcionalidades para este fim neste pacote

<h2>DateUtils</h2> Pacote responsavel por manipulacao de datas e horas
<h2>Generic</h2>Funcionalidades de utilizacao generica. Principal foco e facilitar e 
diminuir aqueles codigos que ocupam varias linhas suprimindo-os em apenas uma linha,
quando possivel. Ex.:<br> 
- NVL() --> Equivalente ao NVL do ORACLE. nvl(None, "a")<br>
- IIF() --> If de uma linha so IF(value_boolean, value_True, value_False)<br>
- entre outras funconalidades<br>

<h2>SQL</h2>Ainda em desenvolvimento. Com objetivo de facilitar obtencao de valores de cursores, etc.
<h2>System</h2>Obtem informacoes do sistema operacional
<h2>WebHook</h2>Funcionalidades para conversar com TEAMS e SLACK