semvec/pypi-packages huggingface dataset:
simple-project-generator 0.1.3
my pypi project generator
Requires Python: >=3.8
Keywords: writing, translate

# simple-project-generator

my pypi project generator

![logo](https://raw.githubusercontent.com/trucomanx/SimpleProjectGenerator/main/screenshot.png)

## 1. Installing

To install the package from [PyPI](https://pypi.org/project/simple_project_generator/), follow the instructions below:


```bash
pip install --upgrade simple_project_generator
```

Execute `which simple-project-generator` to see where it was installed, probably in `/home/USERNAME/.local/bin/simple-project-generator`.

### Using

To start, use the command below:

```bash
simple-project-generator
```
## 2. More information

If you want more information go to [doc](https://github.com/trucomanx/SimpleProjectGenerator/blob/main/doc) directory.

## 3. Buy me a coffee

If you find this tool useful and would like to support its development, you can buy me a coffee!  
Your donations help keep the project running and improve future updates.  

[☕ Buy me a coffee](https://ko-fi.com/trucomanx) 

## 4. License

This project is licensed under the GPL license. See the `LICENSE` file for more details.
coderecon 0.1.6
Engineering-first repository reconnaissance and architectural auditing.
Requires Python: >=3.10


# 🔍 CodeRecon

![CodeRecon Logo](https://raw.githubusercontent.com/mvrkarthik07/coderecon/main/assets/coderecon_logo.png)


**Engineering-first repository reconnaissance and architectural auditing.**

CodeRecon is a pragmatic CLI tool designed to bridge the gap between documentation and reality. It performs deep static analysis of codebases to identify functional mapping, architectural risks, and implementation gaps using local intelligence.

---

**[Architecture Guide](https://github.com/mvrkarthik07/coderecon/blob/main/ARCHITECTURE.md)** – Deep dive into the system design and AST parsing logic.



**[CodeRecon Demo](https://www.youtube.com/watch?v=84yY41UJoqQ)** - *Click to watch the engineering-first reconnaissance workflow in action.*

## 🚀 Installation

### 1. From PyPI
Install the core tool directly via pip:
```bash
pip install coderecon
```
### 2. Local LLM Setup
CodeRecon requires Ollama for its reasoning capabilities.

Download Ollama from ollama.com.

Pull the required model:

```Bash
ollama pull llama3
```
### 🛠️ Usage
Quick Start
Analyze your current directory and get a structural breakdown:

```Bash
coderecon explain .
```
Architectural Mapping
Generate a topology map to see functional roles and risk density:

```Bash
coderecon topology .
```
### Formal Audit
Generate a persistent RECON_REPORT.md with technical specs and Mermaid diagrams:

```Bash
coderecon report .
```
### Remote Audit
Analyze a GitHub repository without cloning it manually:

```Bash
coderecon explain [https://github.com/user/project](https://github.com/user/project)
```
### Help Menu
Gives an entire menu of the available commands and functions and their purposes:

```Bash
coderecon help
```

### 🏗️ Architectural Bucketing
The tool automatically classifies files into functional roles:

Entry Points: System dispatchers and main hooks.

Core: High-logic modules with central dependencies.

Data Layer: Schemas, models, and database logic.

External Integrations: API clients and LLM wrappers.

Utilities: Helper modules and reporting logic.

## 🔌 Architecture & Extensibility (MCP)

CodeRecon is built on the **Model Context Protocol (MCP)**. While primarily a CLI tool, its internal engine functions as an MCP server.

* **Standardized Context**: Uses `fastmcp` to bridge local AST analysis with LLM reasoning.
* **Tool-Agnostic**: Because it follows the MCP standard, CodeRecon’s analysis logic can be plugged into any MCP-compliant host (like Claude Desktop or IDE agents) in the future.
* **Local-First Protocol**: MCP ensures that the communication between the scanner and the LLM happens entirely on your machine.

### 🛡️ Privacy & Philosophy
100% Local: Your code never leaves your machine. Analysis is performed via local AST parsing and local LLM inference.

No-Cap: Prioritizes hard file data over AI "guesses."

Ephemeral: Remote clones are stored in temp directories and aggressively deleted after use.

### Generated by CodeRecon — Local & Private Intelligence.

---
pybalboa 1.1.4
Module to communicate with a Balboa spa wifi adapter.
Requires Python: >=3.10
Keywords: Balboa, asynchronous, hot tub, spa

# pybalboa

[![PyPI - Version](https://img.shields.io/pypi/v/pybalboa?style=for-the-badge)](https://pypi.org/project/pybalboa/)
[![Buy Me A Coffee/Beer](https://img.shields.io/badge/Buy_Me_A_☕/🍺-F16061?style=for-the-badge&logo=ko-fi&logoColor=white&labelColor=grey)](https://ko-fi.com/natekspencer)
[![Sponsor on GitHub](https://img.shields.io/badge/Sponsor_💜-6f42c1?style=for-the-badge&logo=github&logoColor=white&labelColor=grey)](https://github.com/sponsors/natekspencer)

[![GitHub License](https://img.shields.io/github/license/natekspencer/pybalboa?style=flat-square)](LICENSE)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/pybalboa?style=flat-square)](https://pypi.org/project/pybalboa/)
![Pepy Total Downloads](https://img.shields.io/pepy/dt/pybalboa?style=flat-square)
![PyPI - Downloads](https://img.shields.io/pypi/dm/pybalboa?style=flat-square)

Python Module to interface with a balboa spa

Requires Python 3 with asyncio.

To Install:

```
pip install pybalboa
```

To test:

```
python3 pybalboa <ip-of-spa-wifi> <debug-flag>
```

## To Use

See `__main__.py` for usage examples.

Minimal example:

```python
  import asyncio
  import pybalboa

  async with pybalboa.SpaClient(spa_host) as spa:
    # read/run spa commands
```

## Related

- https://github.com/ccutrer/balboa_worldwide_app/wiki - invaluable wiki for Balboa module protocol

## ❤️ Support Me

I maintain this python project in my spare time. If you find it useful, consider supporting development:

- 💜 [Sponsor me on GitHub](https://github.com/sponsors/natekspencer)
- ☕ [Buy me a coffee / beer](https://ko-fi.com/natekspencer)
- 💸 [PayPal (direct support)](https://www.paypal.com/paypalme/natekspencer)
- ⭐ [Star this project](https://github.com/natekspencer/pybalboa)
- 📦 If you’d like to support in other ways, such as donating hardware for testing, feel free to [reach out to me](https://github.com/natekspencer)

## 📈 Star History

[![Star History Chart](https://api.star-history.com/svg?repos=natekspencer/pybalboa)](https://www.star-history.com/#natekspencer/pybalboa)
ludos 0.2.0
Pygame abstraction framework for rapid game development
Requires Python: >=3.12

# Ludos

Pygame-ce abstraction framework that eliminates boilerplate for rapid game development. Clean separation between input, state, and rendering with extensibility at every layer.

## Install

```bash
pip install ludos
```

## Quick Start

```python
from dataclasses import dataclass
import pygame
from ludos import (
    BaseGameState, BaseScene, EngineConfig, GameEngine,
    KeyBindings, SceneManager, StateManager,
)

@dataclass
class MyState(BaseGameState):
    score: int = 0

class PlayScene(BaseScene):
    def handle_input(self, events, state_manager):
        pass

    def update(self, dt, state_manager):
        pass

    def render(self, surface, state_manager):
        surface.fill((0, 0, 0))

config = EngineConfig(title="My Game", width=800, height=600)
state_manager = StateManager(MyState())
scene_manager = SceneManager()
scene_manager.push(PlayScene())

engine = GameEngine(config)
engine.run(scene_manager, state_manager)
```

## Features

- **State management** — Subclass `BaseGameState` as a dataclass, mutate through `StateManager.update()`
- **Scene stack** — Push/pop/replace scenes with `on_enter`/`on_exit` lifecycle hooks
- **Input mapping** — Map raw pygame keys to semantic actions via `KeyBindings`
- **Display wrapper** — `Window` handles pygame display init and surface management
- **Built-in menu** — `MenuScene` with configurable `MenuConfig` for quick prototyping
- **Error hierarchy** — All errors inherit `LudosError` for unified catching

## Documentation

See the [user guide](docs/guide.md) for full documentation.

## License

MIT