semvec/pypi-packages huggingface dataset:
logninja-guardian 0.1.0
Interactive CLI tool for system optimization and monitoring using psutil (LOGGIE infrastructure)
License: MIT
Requires Python: >=3.7

# 🧰 logninja-system-optimizer

A secure, interactive CLI utility for optimizing system performance, including CPU, memory, disk, and network usage, built for the **LOGGIE** decentralized infrastructure stack.

> 🔐 Part of the LogNinja Ecosystem  
> 👤 Maintained by: [loggie.eth](https://sepolia.etherscan.io/address/0x8FF60880d97b1E088a3c480e727fa3CefF044712)  
> 🪙 Powered by: [LOGGIE Token](https://sepolia.etherscan.io/token/0x0bDB1e28D64b080892c5A7f9D56b1F98E5Cbf576)

---

## 🚀 What is this?

This tool helps optimize system resources by managing CPU, memory, disk, and network usage. It's perfect for:
- Enhancing system performance in real-time
- Managing server resources effectively
- Automating resource optimization for Linux-based systems

---

## ⚙️ Features

- ✅ Real-time monitoring of CPU, memory, disk, and network usage
- ✅ Dynamic adjustment of system resources (e.g., lowering CPU process priority)
- ✅ Soft throttle of network usage to avoid congestion
- ✅ Logging to both terminal and `optimization.log`
- ✅ Customizable DefCon levels for prioritizing system alerts
- ✅ Configurable optimization intervals via CLI

---

## 📦 Installation

```bash
pip install logninja-system-optimizer
sktimeutils 2.0.9
Array based, Universal Time conversion functions and classes  used by usask-arg software
License: MIT
Requires Python: >=3.7

# sktimeutils
This package provides Universal Time conversion functions used by the usask-arg group. The
code tries to be friendly for arrays, sequences and scalars. This package currently supports UT time expressed as strings,
modified julian dates expressed as floats, Python DateTime and numpy Datetime64. We typically use the package to process  
arrays of measurement times read in from data records stored in netcdf files or similar. The code is focussed on Universal Time 
and has no provision for handling time zone conversions etc.  Nor do we attempt to rigorously manage leap-seconds and 
other earth-rotation issues. 

## Installation
    
    pip install sktimeutils

We recommend running the unit tests, see below, after installation to download Earth rotation data files.

### Building a wheel
The python wheel can also be built from source code,

    conda install setuptools build
    python -m build --wheel

## Usage
Documentation can be found at ReadTheDocs [sktimeutils](https://sktimeutils.readthedocs.io/en/latest/index.html)

## Unit Tests
It is useful to run the unit tests as the tests will automatically download leap-second files and earth rotation 
information. Needless to say you must have an internet connection to successfully run the unit tests 

    python -m unittest discover -s sktimeutils.tests

## License
This project is licensed under the MIT license.
octoface 0.3.0
CLI tool for managing LLM models on IPFS and GitHub Pages
License: MIT
Requires Python: >=3.7

# OctoFace CLI

A command-line tool for managing LLM models on IPFS and GitHub Pages.

## Installation

```bash
pip install octoface
```

## Usage

### Set up credentials

```bash
# Set GitHub API token
export GITHUB_API_TOKEN="your-github-api-token"

# Set up web3.storage
npm i --global @web3-storage/w3cli
w3 login  # Follow prompts to authenticate
w3 space create my-space-name  # Create a storage space
w3 space use my-space-name     # Select the space for uploads
```

### Test GitHub API access

```bash
octoface test-github
```

### Download models from HuggingFace

```bash
octoface download "hf-username/cool-model"
```

### Upload models to IPFS and GitHub

```bash
# Upload local model
octoface upload . --name "gemma-3-4b-it"

# Upload with description
octoface upload "./path/to/model/gemma-3-4b-it" --description "State-of-the-art open models from Google"

# Upload with tags
octoface upload "./path/to/model" --name "My Model" --description "A cool model" --tags "cool,awesome"

# Download from HF and upload in one step
octoface upload "hf-username/cool-model"
```

### Generate files for manual submission

If you don't have push access to the OctoFaceHub repository, you can generate the necessary files and submit them manually:

```bash
# Generate files using a local model directory
octoface generate-files --path "./path/to/model" --name "My Model" --description "A cool model" --tags "cool,awesome"

# Generate files using an existing IPFS CID
octoface generate-files --cid "bafybeih2qqh6rfmgrrggvkwsve7yuru72tm66vmp2cc5q7nmhytnovq7dm" --name "My Model" --description "A cool model" --tags "cool,awesome"

# Specify custom output directory
octoface generate-files --path "./path/to/model" --name "My Model" --description "A cool model" --tags "cool,awesome" --output "./my-files"
```

After generating the files, follow the instructions in the GUIDE.md file to submit your model to OctoFaceHub.

## License

MIT