semvec/pypi-packages huggingface dataset:
tkinter-gl 1.1
A base class for GL rendering surfaces in tkinter.
Requires Python: >=3.8
Keywords: OpenGL, tkinter, rendering

tkinter_gl
==========

This Python package provides the tkinter widget class GLCanvas which
can serve as a rendering surface for an OpenGL client.

The responsibility of this class is only to manage an OpenGL context.

Clients need some other library such as PyOpenGL to make the OpenGL
calls from python.
amarantos 0.1.2
Tips and tools for personal wellness and longevity
Requires Python: >=3.13

# Amarantos

Tips and tools for personal wellness and longevity. *Amarantos* (ἀμάραντος) is Greek for "unfading" or "immortal" and is the root of *amaranth*—a flower known for retaining its color even dried.

> **Warning: AI-Generated Content**
>
> This repository was generated with AI assistance and has not been thoroughly vetted by a human. References, claims, and code may contain errors or inaccuracies. Please double-check all information against primary sources and exercise critical judgment. Treat this as a starting point for careful research, not a definitive resource.

## CLI Commands

```bash
# Rank all choices by 30th percentile lifespan impact
amarantos

# Filter by domain
amarantos --domain exercise

# Show only top/bottom 5
amarantos -n 5

# Show top 3 from each domain
amarantos --maxd 3

# Describe a specific choice
amarantos describe cycling
```

### Example

```
$ amarantos --maxd 1

Choice                                    P30 (years)       $/year   hours/year
------------------------------------------------------------------------------
Moderate Cardio                                 +1.63          200          120
Caloric Restriction                             +1.08         -500            0
Strong Social Connections                       +1.08          500          350
Finnish Sauna                                   +1.08         1200          150
Almonds                                         +0.98          100          100
Rapamycin                                       +0.87          500            2
Optimal Sleep Duration                          +0.69            0            0
Cognitive Training                              +0.19          200          100
Nature Exposure                                 +0.14          100          100
Alcohol Abstinence or Minimal Intake            +0.04         -500            0

P30: conservative (30th percentile) estimate of the *average* years of life extension
$/year, hours/year: annual cost of the intervention
```

See also: [External Resources](resources/README.md)

## Installation

```bash
uv add amarantos
```
lmfetch 0.3.6
Build intelligent context from codebases and URLs for LLMs
Requires Python: >=3.13

# lmfetch

**Effortlessly turn codebase into context for your LLMs.**

`lmfetch` is a lightning-fast CLI tool that fetches, chunks, supports local files and remote GitHub repositories, and ranks code context. It's designed to fit the most relevant code into your token budget, so your LLM can understand the implementation details without the noise.

## Install

**Mac & Linux**
```bash
curl -fsSL https://raw.githubusercontent.com/Abdulmumin1/lmfetch/main/install.sh | bash
```

**Windows** (PowerShell)
Coming soon.

## Usage

**Fetch local code**
```bash
lmfetch . "how does authentication work"
```

**Fetch from GitHub**
```bash
lmfetch https://github.com/vercel/ai "explain tool calling"
```

**Common Options**
```bash
# Set a token budget (default: 50k)
lmfetch . "query" -b 10k

# Force processing of large files
lmfetch . "query" --force-large

# Clear cache
lmfetch --clean-cache

# Output context to file
lmfetch . "query" -o context.md
```

## How It Works

1.  **Smart Chunking**: Understands AST (classes, functions) for Python, TS, Go, Rust, and more.
2.  **Hybrid Ranking**: Combines keyword matching, vector embeddings, and dependency graph centrality.
3.  **HyDE Reasoning**: Generates hypothetical code to match your *intent*, not just your keywords.
4.  **Privacy**: Runs locally. Embeddings use your own API keys (OpenAI/Google).

## Architecture

See [ARCHITECTURE.md](ARCHITECTURE.md) for a deep dive into the pipeline.

## License

MIT