semvec/pypi-packages huggingface dataset:
topsis-simanta-102483083 1.0.1
A simple package for TOPSIS implementation
Requires Python: >=3.6

# Topsis-Simanta-102483083

This is a Python package to implement the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method for Multi-Criteria Decision Making (MCDM).

## Installation

You can install this package using pip:

```bash
pip install Topsis-Simanta-102483083
topsis-yash-102303766 1.0.0
A simple package for TOPSIS implementation
Requires Python: >=3.6

# Topsis-Yash-102303766

This is a Python package to implement the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method for Multi-Criteria Decision Making (MCDM).

## Installation

You can install this package using pip:

```bash
pip install Topsis-Yash-102303766
pycobello 0.1.1a0
A blazing fast, dependency-light static site generator
Requires Python: >=3.12

<div style="text-align: center">
    <img src="pycobello.png" width="200">
</div>

# pycobello

[![PyPI version](https://img.shields.io/pypi/v/pycobello?style=flat-square)](https://pypi.org/project/pycobello/)
[![Python 3.12+](https://img.shields.io/badge/python-3.12+-blue?style=flat-square)](https://www.python.org/downloads/)
[![License](https://img.shields.io/github/license/pycobello/pycobello?style=flat-square)](LICENSE)
[![CI](https://github.com/pycobello/pycobello/actions/workflows/ci.yml/badge.svg?style=flat-square)](https://github.com/pycobello/pycobello/actions/workflows/ci.yml)

A blazing fast, dependency-light static site generator (SSG) for Python 3.12+.

- **Markdown + YAML front matter** → HTML
- **Jinja2 themes** (`.html` templates)
- **CLI-first** (Typer): `init`, `new`, `build`, `preview`, `check`, `deploy`
- **Incremental builds** with a JSON cache and write-avoidance by content hash
- **Preview server** via stdlib `http.server`; optional `--watch` with `[watch]` extra
- **Diagnostics** (`check`): duplicate URLs, required front matter, internal links
- **Plugin system** via Python entry points (`pycobello.plugins`)

## Install

```bash
uv add pycobello
# or
pip install pycobello
```

Optional watch support (live rebuild on file changes):

```bash
uv add "pycobello[watch]"
```

## Quick start

```bash
# Create a new site
pycobello init

# Build
pycobello build

# Serve the built site
pycobello preview
```

## Commands

| Command | Description |
|--------|-------------|
| `pycobello init [DIR]` | Create scaffold: `pycobello.yml`, content, theme, static |
| `pycobello new post "Title"` | Create a new post (with date prefix) |
| `pycobello new page "Title"` | Create a new page |
| `pycobello build [--clean]` | Build site into `dist/` (default: incremental) |
| `pycobello preview [--port 8000] [--watch]` | Serve `dist/`; optional watch + rebuild |
| `pycobello check` | Run diagnostics (URLs, front matter, links) |
| `pycobello deploy github-pages` | Generate GitHub Actions workflow for GitHub Pages |

## Config

Config file: `pycobello.yml` in the project root (YAML only).

- **site**: `title`, `base_url`, `author`
- **build**: `content_dir`, `theme_dir`, `static_dir`, `output_dir`, `clean_urls`, `ignore`
- **collections**: `posts` and `pages` (each: `path`, `url_prefix`, `template`)
- **plugins**: `enabled` (list of plugin names)

## Theme contract

Templates live in `theme/templates/`. Required:

- `base.html` – base layout
- `page.html` – pages
- `post.html` – posts
- `index.html` – index (blog listing)

Context: `site`, `collections`, current `page` or `post`. Helpers: `url_for`, filter `datefmt`.

## Development

```bash
uv sync --all-groups
uv run pre-commit install
```

Linting (ruff check) and formatting (ruff format) run automatically before each commit. To run them manually: `uv run ruff check .`, `uv run ruff format .`, and `uv run pytest`.

## License

Apache License 2.0. See [LICENSE](LICENSE).
pycompound 0.1.11
Python package to perform compound identification in mass spectrometry via spectral library matching.
Requires Python: >=3.9

# PyCompound

A Python-based tool for spectral library matching, PyCompound is available as a Python package (pycompound) with a command-line interface (CLI) available and as a GUI application build with Python/Shiny. It performs spectral library matching to identify chemical compounds, offering a range of spectrum preprocessing transformations and similarity measures, including Cosine, three entropy-based similarity measures, and a plethora of binary similarity measures. PyCompound also includes functionality to tune parameters commonly used in a compound identification workflow given a query library of spectra with known ID. PyCompound supports both high-resolution mass spectrometry (HRMS) data (e.g., LC-MS/MS) and nominal-resolution mass spectrometry (NRMS) data (e.g., GC-MS). For the full documentation, see the GitHub repository https://github.com/hdlugas/pycompound.