semvec/pypi-packages huggingface dataset:
SpaMV 1.0.28
The Python package for a spatial multi-omics integration algorithm called SpaMV.
Requires Python: >=3.10

# SpaMV: An interpretable spatial multi-omics data integration and dimension reduction algorithm

# Installation

1) Create and activate a conda environment with python 3.12

```
conda env create spamv python==3.12
conda activate spamv
```

2) (Optional) If you want to apply our algorithm to large datasets (with more than 10,000 spots), please make sure you have
   installed the pyg-lib package.

```
pip install pyg-lib -f https://data.pyg.org/whl/torch-${TORCH}+${CUDA}.html
```

where

- `${TORCH}` should be replaced by either `1.13.0`, `2.0.0`, `2.1.0`, `2.2.0`, `2.3.0`, `2.4.0`, `2.5.0`, `2.6.0`, or
  `2.7.0`
- `${CUDA}` should be replaced by either `cpu`, `cu102`, `cu117`, `cu118`, `cu121`, `cu124`, `cu126`, or `cu128`

3) Then you can install our package as follows:

```
pip install spamv
```

# Tutorial

We provide two jupyter notebooks (Tutorial_simulation.ipynb and Tutorial_realworld.ipynb) to reproduce the results in
our paper. Before you run them, please make sure that you have downloaded the simulated data and/or real-world data from
our Zenodo repositoy.
infuse-iot 0.6.0
Infuse-IoT Platform python package
Requires Python: >=3.10

# Infuse-IoT Python Tools

## Installation

Install from PyPI with ``pip`` or ``pipx``:

```
pip install infuse-iot
```

## Register Autocomplete

To register for autocompletion (tab complete).

```
autoload -Uz compinit
compinit
eval "$(register-python-argcomplete infuse)"
```

## Usage

```
> infuse --help
usage: infuse [-h] [--version] <command> ...

options:
  -h, --help         show this help message and exit
  --version          show program's version number and exit

commands:
  <command>
    bt_log           Connect to remote Bluetooth device serial logs
    cloud            Infuse-IoT cloud interaction
    credentials      Manage Infuse-IoT credentials
    csv_annotate     Annotate CSV data
    csv_plot         Plot CSV data
    data_logger_sync
                     Synchronise data logger state from remote devices
    gateway          Connect to a local gateway device
    localhost        Run a local server for TDF viewing
    native_bt        Native Bluetooth gateway
    ota_upgrade      Automatically OTA upgrade observed devices
    provision        Provision device on Infuse Cloud
    rpc              Run remote procedure calls on devices
    rpc_cloud        Manage remote procedure calls through Infuse-IoT cloud
    serial_throughput
                     Test serial throughput to local gateway
    tdf_csv          Save received TDFs in CSV files
    tdf_list         Display received TDFs in a list
```

## Credential Storage

Under linux, the preferred credential storage provider for the python ``keyring``
package is provided by ``gnome-keyring``. The available backends can be listed with
``keyring --list-backends``.

```
sudo apt install gnome-keyring
```

### WSL Issues

Under WSL, they keyring has been observed to consistently raise
``secretstorage.exceptions.PromptDismissedException: Prompt dismissed``.
This can be resolved by adding the following to ``~/.bashrc`` and reloading
the terminal.
```
dbus-update-activation-environment --all > /dev/null 2>&1
```
wittiot 1.0.33
WSView Plus support
Requires Python: >=3.8

# Wittiot

Python library for accessing Wittiot / WSView Plus weather station data via local LAN API.

## Installation

```bash
pip install wittiot
```

## Usage

```python
import asyncio
import logging
from aiohttp import ClientSession
from wittiot import API

async def main():
    # Replace with your device IP
    HOST = "192.168.1.110"
    
    async with ClientSession() as session:
        api = API(HOST, session=session)
        
        try:
            # Get all sensor data
            data = await api._request_loc_allinfo()
            print(f"Data from {HOST}:")
            print(data)
        except Exception as e:
            print(f"Error: {e}")

if __name__ == "__main__":
    logging.basicConfig(level=logging.INFO)
    asyncio.run(main())
```

## Supported Devices

- GW1100
- GW2000
- WN1900
- And other Ecowitt/Wittiot devices supporting local API
stixpy 0.2.0
An open-source Python analysis library for the Spectrometer Telescope for Imaging X-rays (STIX) instrument on Solar Obriter.
Requires Python: >=3.11
Keywords: solar physics, solar, sun, x-rays

stixpy Analysis Software
========================

|Powered By| |Build Status| |Doc Status| |Python Versions|

.. |Powered By| image:: https://img.shields.io/badge/powered%20by-SunPy-orange.svg?style=flat
    :target: http://www.sunpy.org
    :alt: Powered by SunPy Badge

.. |Build Status| image:: https://github.com/TCDSolar/stixpy/actions/workflows/ci.yaml/badge.svg
    :target: https://github.com/TCDSolar/stixpy/actions/workflows/ci.yaml
    :alt: Build Status

.. |Doc Status| image:: https://readthedocs.org/projects/stixpy/badge/?version=stable
    :target: http://stixpy.readthedocs.io/en/latest/?badge=stable
    :alt: Documentation Status

.. |Python Versions| image:: https://img.shields.io/pypi/pyversions/stixpy
    :target: https://pypi.python.org/pypi/stixpy
    :alt: Python Versions

stixpy is an open source Python library for analysis of Spectrometer Telescope for Imaging X-rays (STIX) onboard Solar Orbiter (SO)
data

Installation
------------

It is strongly advised that you use and isolated environment through python's venv, virturalenv, anaconda or similar.

.. code-block::

   pip install stixpy

To install the developer version and set up a development environment, follow the instructions in our [Developer Guide](https://stixpy.readthedocs.io/en/latest/how_to_guides/dev_guide.html).


Usage
-----

Getting Help
------------


Contributing
------------
When you are interacting with the community you are asked to
follow the `Code of Conduct`_.

.. _Code of Conduct: http://docs.sunpy.org/en/stable/coc.html
ralphy 4.0.1
Autonomous AI Coding Loop
Requires Python: >=3.10
Keywords: ai, coding, automation, claude

# Ralphy

A ralphy-implemented ralphy. This project was built using the original [ralphy](https://github.com/anthropics/ralphy) autonomous coding loop.

Autonomous AI Coding Loop that orchestrates AI coding assistants to implement tasks until completion.

## Installation

```bash
pip install ralphy
```

## Quick Start

```bash
# Initialize project config
ralphy --init

# Run a single task
ralphy "add user authentication"

# Run PRD until complete
ralphy --prd PRD.md
```

## Features

- **Multiple AI Engines**: Claude Code, OpenCode, Cursor, Codex, Qwen-Code, Factory Droid
- **PRD Mode**: Loop through tasks from Markdown, YAML, or GitHub Issues
- **Single Task Mode**: Execute one task in an existing project
- **Parallel Execution**: Run tasks concurrently with git worktrees
- **Auto PR Creation**: Create pull requests automatically
- **Cost Tracking**: Monitor token usage and costs

## Supported AI Engines

| Engine | Flag | CLI |
|--------|------|-----|
| Claude Code | `--claude` (default) | `claude` |
| OpenCode | `--opencode` | `opencode` |
| Cursor Agent | `--cursor` | `agent` |
| Codex CLI | `--codex` | `codex` |
| Qwen-Code | `--qwen` | `qwen` |
| Factory Droid | `--droid` | `droid` |

## Configuration

Initialize a `.ralphy/` directory with project config:

```bash
ralphy --init
```

This auto-detects:
- Project name, language, framework
- Test, lint, and build commands

Add rules the AI must follow:

```bash
ralphy --add-rule "Always use TypeScript strict mode"
```

## PRD Formats

**Markdown:**
```markdown
- [ ] Implement user authentication
- [ ] Add payment processing
- [x] Set up database (completed)
```

**YAML:**
```yaml
tasks:
  - title: "Implement auth"
    parallel_group: 1
  - title: "Add payments"
    parallel_group: 1
```

**GitHub Issues:**
```bash
ralphy --github owner/repo --github-label enhancement
```

## Options

```bash
ralphy --parallel              # Run tasks in parallel
ralphy --max-parallel 5        # Concurrent agents (default: 3)
ralphy --branch-per-task       # Create branch per task
ralphy --create-pr             # Create PRs automatically
ralphy --no-tests              # Skip tests
ralphy --no-lint               # Skip linting
ralphy --fast                  # Skip tests and linting
ralphy --max-iterations 10     # Stop after N tasks
ralphy --dry-run               # Preview without executing
ralphy --verbose               # Debug output
```

## Requirements

- Python 3.10+
- git
- At least one AI CLI installed (claude, opencode, etc.)

## License

MIT