semvec/pypi-packages huggingface dataset:
pyomnix 0.2
Integrated Tools for Scientific Computing, Data Analysis, and AI Development
Requires Python: >=3.12
Keywords: data-analysis, scientific-computing, ai, machine-learning, visualization

# PyOmnix

[![Python Version](https://img.shields.io/badge/python-3.12+-blue.svg)](https://www.python.org/downloads/)
[![License](https://img.shields.io/badge/license-MIT-green.svg)](LICENSE)
[![Code style: ruff](https://img.shields.io/badge/code%20style-ruff-000000.svg)](https://github.com/astral-sh/ruff)

PyOmnix is a Python toolkit for scientific data workflows, plotting, and AI-oriented utilities.
It is built as a modular library so you can use only the components you need.

## Overview

PyOmnix currently provides:

- Data processing helpers for experimental/scientific tabular data.
- Plotting utilities built around Matplotlib and Plotly.
- GUI tools for fast data inspection and manipulation.
- Agent-related modules for model/tool orchestration.
- Logging, environment, file, and math utility helpers.

## Installation

### Base

```bash
pip install pyomnix
```

### Optional extras

```bash
# GUI support (PyQt6 + WebEngine)
pip install "pyomnix[gui]"

# Web-related tools
pip install "pyomnix[web]"

# Development toolchain
pip install -e ".[dev]"
```

## Quick Start

### Logging

```python
from pyomnix import setup_logger, get_logger

setup_logger()
logger = get_logger(__name__)
logger.info("PyOmnix is ready.")
```

### Data Manipulator

```python
from pyomnix.data_process import DataManipulator

dm = DataManipulator(1)
# Example:
# dm.load_dfs(loc=0, data_in="data.csv")
# dfs = dm.get_datas(loc=0)
```

## CLI Entry Points

After installation, these commands are available:

- `gui_pan_color`: Launch the color palette selector.
- `gui_easy_data`: Launch the PyQt-based data GUI.

## Project Structure

- `src/pyomnix/data_process/`: data loading, splitting, plotting, GUI tools.
- `src/pyomnix/utils/`: reusable data/math/plot/environment/file utilities.
- `src/pyomnix/agents/`: graph, node, tool, prompt, storage, and settings modules.
- `src/pyomnix/omnix_logger.py`: logging framework used across the project.
- `src/pyomnix/pltconfig/`: plotting and color configuration assets.

## Development

```bash
# Lint
ruff check .

# Format (if you use black in your workflow)
black .

# Run tests
pytest
```

## Requirements

- Python `>=3.12`

See `pyproject.toml` for the complete dependency list.

## License

This project is licensed under the MIT License. See `LICENSE` for details.
qrkey 0.12.1
Swarm robotics deployments made easy.
Requires Python: >=3.11
Keywords: robotics, swarm, ux

# Qrkey

[![PyPI - Version](https://img.shields.io/pypi/v/qrkey.svg)](https://pypi.org/project/qrkey)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/qrkey.svg)](https://pypi.org/project/qrkey)
[![NPM - Version](https://img.shields.io/npm/v/qrkey.svg)](https://npmjs.org/package/qrkey)

<p align="center">
  <img src="qrkey.png" width="328"/>
</p>

## Summary

Qrkey is a library implementing a protocol designed to facilitate the
deployment of robots swarm.
The protocol relies on [MQTT](https://en.wikipedia.org/wiki/MQTT) so that a
Qrkey server is reachable even with a private IP address.
Access to the swarm is managed by a QR code based authentication scheme.

## Installation

- Python server library:

```console
pip install qrkey
```

- Node client library:

```console
npm i qrkey
```

## License

`qrkey` is distributed under the terms of the [BSD-3-Clause](https://spdx.org/licenses/BSD-3-Clause.html) license.
libABCD 2.2.1
the Autonomous Bariloche Central DAQ, a centralized DAQ system for scientific experiments
Requires Python: >=3.8
Keywords: logging, mqtt

Avalos-Bertou Central DAQ (libABCD) v2.2.0
==========================================
(Formerly: Autonomous Bariloche Central DAQ)

This library handles two crucial aspects of any experiment that consists 
of multiple clients taking data: the communication between clients and 
the log information.

The main concept for the DAQ is that it orbits around a central server. 
Control and information run through this server allowing a permanent 
follow-up of what is happening. The raw data is handled by the clients 
themselves and is not seen by the DAQ. The central server is a MQTT 
broker. We recommend using [`mosquitto`](https://mosquitto.org/).

Logs are handled by each client, but the `ABCDHandler` logging handler 
sends the relevant information through MQTT, allowing for a centralized 
monitoring.

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

### Requirements:
Starting from libABCD v2.2.0: `paho.mqtt>=2`.
v2.1 and less: `paho.mqtt<2`

The latest version can be installed from pip:
```bash
python3 -m pip install libabcd
```

Usage
-----

`libABCD` is a singleton object (i.e. a single instance runs per python
process). Start it by running:
```python
import libABCD
libABCD.init('my_daq')  # see documentation in the docstring
```
You can then `publish`, `subscribe`, `unsubscribe` and `add_callback` 
using the same object. Documentation can be found in the docstrings.  

Best practice for handling your application log:
```python
import logging
logger = logging.getLogger('your_app_name')
logger.addHandler(logging.NullHandler()) # remove all other handlers
logger.info('I am an INFO message') # or warning, error, critical
```

Don't forget to close the connection at the end of the session
```python
libABCD.disconnect()
```

A full documentation of the available features is under way.

Questions, requests, feedback
-----------------------------

If you find a bug, want to know more about specific features or have feedback
of any kind, do not hesitate to email me at nicolaseavalos AT gmail DOT com.

License
-------

This project is licensed under the MIT license.
httpie-salesforce 0.0.12
HTTPie Authorization plugin for Salesforce API
Requires Python: >=3.10

# HTTPie Salesforce Plugin

Salesforce REST API authorization with HTTPie.

## Install Plugin

```shell
httpie cli plugins install httpie-salesforce
```

## Use OAuth Flows

https://help.salesforce.com/s/articleView?id=xcloud.remoteaccess_authenticate.htm