semvec/pypi-packages huggingface dataset:
palmerpenguins 0.1.6
A python package for the palmer penguins dataset
License: MIT
Requires Python: >=3.9


palmerpenguins
~~~~~~~~~~~~~~~~~~~~~~
The Palmer penguins dataset by Allison Horst, Alison Hill, and Kristen Gorman was first made publicly available as an R package. The goal of the Palmer Penguins dataset is to replace the highly overused Iris dataset for data exploration & visualization.
Using this python package you can easily load the Palmer penguins into your python environment.


Overview
~~~~~~~~~~~~~~~~~~~~~~
Size measurements, clutch observations, and blood isotope ratios for 344 adult foraging Adelie, Chinstrap, and Gentoo penguins observed on islands in the Palmer Archipelago near Palmer Station, Antarctica. Data were collected and made available by Dr. Kristen Gorman and the Palmer Station Long Term Ecological Research (LTER) Program.

Examples
~~~~~~~~~~~~~~~~~~~~~~
```
from palmerpenguins import load_penguins
```

```
penguins = load_penguins()
```



License
~~~~~~~~~~~~~~~~~~~~~~
Data are available by
[CC-0](https://creativecommons.org/share-your-work/public-domain/cc0/) license in
accordance with the [Palmer Station LTER Data Policy](http://pal.lternet.edu/data/policies)
and the
[LTER Data Access Policy for Type I data](https://lternet.edu/data-access-policy/).




Bibliography
~~~~~~~~~~~~~~~~~~~~~~
Gorman KB, Williams TD, Fraser WR (2014) Ecological Sexual Dimorphism and Environmental
Variability within a Community of Antarctic Penguins (Genus Pygoscelis). PLoS ONE 9(3):
e90081. https://doi.org/10.1371/journal.pone.0090081

See also
~~~~~~~~~~~~~~~~~~~~~~
More information about the dataset is available in
[its official documentation](https://allisonhorst.github.io/palmerpenguins/).

The Palmer penguins dataset in Julia:
https://github.com/devmotion/PalmerPenguins.jl
localsets 0.1.72
Local Pokemon random battle sets (auto-updating) and Smogon competitive sets
License: MIT
Requires Python: >=3.8
Keywords: pokemon, battle, data, random, showdown, smogon, competitive

# localsets

**Fully offline Pokémon battle data. All data is bundled with the package and never downloaded at install or runtime. Updates are handled automatically by GitHub Actions and published with each new release.**

Offline Pokemon battle data with auto-updates from official sources.

## What it does

- **Random Battle Data**: Access Pokemon Showdown's RandBats data offline
- **Competitive Sets**: Get Smogon competitive Pokemon sets
- **Auto-Updates**: Automatically syncs with official repositories every 24 hours (via CI, not by end user)
- **Multiple Formats**: Supports all generations (Gen 1-9) and battle formats

## Quick Start

```python
from localsets import PokemonData

data = PokemonData(
    randbats_formats=['gen9randombattle'],
    smogon_formats=['gen9ou']
)

pikachu = data.get_randbats('pikachu', 'gen9randombattle')
sets = data.get_smogon_sets('pikachu', 'gen9ou')
```

## Installation

```bash
pip install localsets
```

## CLI Usage

```bash
# Get random battle Pokemon
localsets randbats get pikachu --format gen9randombattle

# Get competitive sets
localsets smogon get pikachu gen9ou
```

## Data Sources

- **RandBats**: [pkmn/randbats](https://github.com/pkmn/randbats) - Pokemon Showdown random battle data
- **Smogon**: [smogon/pokemon-showdown](https://github.com/smogon/pokemon-showdown) - Competitive Pokemon sets

## Features

- Offline-first with bundled data
- Automatic updates via GitHub Actions (not by end user)
- Support for all Pokemon generations
- Both random battle and competitive formats
- Simple Python API and CLI interface
- Graceful fallbacks and error handling
mermkit 0.2.6
Python bindings for mermkit (Mermaid rendering toolkit)
License: MIT
Requires Python: >=3.8
Keywords: cli, diagram, mermaid, render

# mermkit (Python)

Minimal wrapper around the `mermkit` CLI.

## Install

```
pip install mermkit
```

## Usage

```python
from mermkit import render

svg = render("graph TD; A-->B", format="svg")
```

## Serve mode
For repeated renders, use the JSON IPC server:

```python
from mermkit import MermkitClient

client = MermkitClient()
client.start()
result = client.render("graph TD; A-->B")
client.close()
```

## Requirements
- `mermkit` CLI available on PATH, or set `MERMKIT_BIN`:

```
export MERMKIT_BIN=/path/to/mermkit
```