semvec/pypi-packages huggingface dataset:
st-copy-button 0.1.2
A simple Streamlit component for copying text to the user's clipboard with one click.
License: MIT
Requires Python: <4.0,>=3.9.8
Keywords: streamlit, component, clipboard

# st-copy-button

A simple Streamlit component for copying text to the user's clipboard with one click.

Contains portions derived from mmz-001's st-copy-to-clipboard component.

## Installation instructions

```sh
pip install st-copy-button
```

## Usage instructions

> Note: The clipboard API is only available in secure contexts (HTTPS)

```python
import streamlit as st
from st_copy_button import st_copy_button

# Basic usage
st_copy_button("Copy this to clipboard")

# With custom labels
st_copy_button(
    text="Custom text",
    before_copy_label="📋 Push to copy",
    after_copy_label="✅ Text copied!",
    show_text=True
)
```
python-sn2 0.4.0
Python library for SystemNexa2 device integration
License: MIT
Requires Python: >=3.12
Keywords: systemnexa, home automation, iot

# python-sn2

Python library for SystemNexa2 device integration.

This package provides a client library for communicating with SystemNexa2 smart home
devices over WebSocket and REST APIs. It supports device discovery, real-time state
updates, brightness control, and configuration management.

Supported Devices
-----------------
- Switches: WBR-01
- Plugs: WPR-01, WPO-01
- Lights: WBD-01, WPD-01

Key Features
------------
- Asynchronous communication via WebSocket and REST
- Real-time device state updates
- Brightness control for dimmable devices
- Device settings management (433MHz, LED, DIY mode, etc.)
- Automatic reconnection handling
- Error handling and logging

## Installation

```bash
pip install python-sn2
```

## Usage

```python
"""Example usage of the python-sn2 library."""

import asyncio
import logging

from sn2.device import Device

logger = logging.getLogger(__name__)


async def main() -> None:
    """Demonstrate device usage."""
    # Create a device instance
    device = await Device.initiate_device(host="192.168.1.144")

    # Connect to the device
    await device.connect()

    # Set brightness
    await device.set_brightness(0.75)

    # Get device information
    info = await device.get_info()
    logger.info("Device: %s", info.information.name)

    # Disconnect
    await device.disconnect()

    await device.close()


if __name__ == "__main__":
    logging.basicConfig(level=logging.INFO)
    asyncio.run(main())
```

## Development

This project uses [uv](https://docs.astral.sh/uv/) for dependency management.

Setup the development environment:

```bash
./scripts/test-setup
```

Or manually:

```bash
# Create virtual environment and install package
uv venv
uv pip install -e ".[dev]"
```

Run tests:

```bash
uv run pytest
```

Run linting:

```bash
uv run ruff check .
uv run ruff format .
```

## Release Process

This project uses automated versioning and releases. To create a new release:

### Automated (Recommended)

```bash
# Bump patch version (0.1.0 -> 0.1.1)
./scripts/release.sh patch

# Bump minor version (0.1.0 -> 0.2.0)
./scripts/release.sh minor

# Bump major version (0.1.0 -> 1.0.0)
./scripts/release.sh major
```

This will:
1. Run tests and linting
2. Bump version in `pyproject.toml` and `sn2/__init__.py`
3. Create a git commit and tag
4. Push to GitHub
5. Trigger GitHub Actions to build and publish to PyPI

### Manual

```bash
# Install bump-my-version
uv pip install bump-my-version

# Bump version
bump-my-version bump patch  # or minor/major

# Push changes and tags
git push origin main --tags
```

The GitHub Actions workflow will automatically:
- Create a GitHub release with release notes
- Build the package
- Publish to PyPI (via Trusted Publishing)

## License

MIT License
qfinlib 2025.1229.1200
A comprehensive quantitative finance library
License: MIT
Requires Python: <4.0,>=3.9

# qfinlib

A comprehensive quantitative finance library for Python.

## Disclaimer

This repository contains personal, educational research only. It is not related to any professional role, employer, or investment activity. All material is based on public information.

## Overview

qfinlib provides a complete toolkit for quantitative finance, including:

- **Date handling**: Serial dates, tenors, schedules, holiday calendars, day count fractions
- **Mathematical utilities**: Interpolation, solvers, statistics, auto-differentiation
- **Market data**: Curves, FX, rates, volatility, credit, inflation, bonds
- **Financial instruments**: Swaps, bonds, FRA, futures, options, CDS, FX forwards, deposits, ZCIS
- **Valuation**: Pricing engines for all instrument types
- **Risk analytics**: PV, DV01, gamma, theta, carry/roll, scenario analysis
- **Calibration**: Curve and volatility model calibration
- **Models**: Interest rate models (LGM, Hull-White)

## Installation

```bash
pip install qfinlib
```

## Quick Start

```python
import qfinlib as qf

# Example usage coming soon
```

## Documentation

See the `docs/` directory for detailed documentation and tutorials.

## Development

See [CONTRIBUTING.md](.github/CONTRIBUTING.md) for development guidelines.

## CI/CD

This project uses GitHub Actions for continuous integration and deployment:
- Tests run automatically on pull requests
- Package is automatically published to PyPI when merged to `main`

See [.github/CI_SETUP.md](.github/CI_SETUP.md) for CI/CD setup instructions.

## License

MIT License