semvec/pypi-packages huggingface dataset:
mtanvil 0.3.1
Parser and editor for Luanti worlds
Requires Python: >=3.9
Keywords: Luanti, Minetest

# mtanvil

<img alt="GitHub License" src="https://img.shields.io/github/license/fancyfinn9/mtanvil?color=darkgreen"> <a href="https://pypi.org/project/mtanvil/" target="_blank"><img alt="PyPI - Version" src="https://img.shields.io/pypi/v/mtanvil?logo=python&logoColor=white&color=blue"></a>

A Python library for parsing and editing Luanti worlds.

The name comes from Luanti’s former name (‘MT’ for Minetest) and the Minecraft world parsing library ‘anvil’

> mtanvil is in alpha, so if you decide to use it then be aware of the following:
>
> Future updates _will_ have breaking changes.
>
> Testing is welcome, please do open an issue if you find any bugs or problems.
>
> Features that are not supported (yet):
> * Some node inventories fail to load, such as the furnace in Minetest Game. I am researching this constantly and will have a solution to this very soon.
> * Older MapBlock formats (<29) may not load and/or serialize correctly (due to the lack of documentation of the specifics of their zlib compression). This will be fixed soon.
> * Older MapBlock formats (<23) will lose node metadata due to the old and new formats not being directly compatible. The conversion will be figured out in the future.

mtanvil fully supports MapBlock format version 29 (latest). Other versions may not be fully supported right now but should receive full support in the future.

It is recommended that you familiarize yourself with the [Map File Format and MapBlock Serialization Format](https://github.com/luanti-org/luanti/blob/master/doc/world_format.md#map-file-format) so that you fully understand what data mtanvil provides.

## Installation

Install mtanvil by running

`pip install mtanvil`

in your terminal.

## Docs

You can find the comprehensive mtanvil docs [here](https://github.com/fancyfinn9/mtanvil/wiki).

Please do open an issue if you find that something has not been documented properly.
scale-align 0.1.1
Standard Classification Alignment & Local Enrichment - Automate audit and enrichment of industrial classifications
Requires Python: >=3.9
Keywords: alignment, classification, embeddings, isic, nace, retrieval

# SCALE: Standard Classification Alignment & Local Enrichment

Automate the audit and enrichment of national classifications (e.g., KBLI) using international standards (e.g., ISIC, NACE), or other national standard classifications.

## Features

- **Bidirectional Asymmetric Retrieval**: Captures hierarchical "entailment" relationships common in classifications
- **Competitive Selection**: Max-score + margin algorithm for controlled mapping while minimizing noise
- **Multilingual E5-Large-Instruct Model**: Instruction-tuned model optimized for asymmetric retrieval tasks

## Installation

```bash
pip install scale-align
```

## Google Colab

Using in Google Colab? Try our [**Colab Notebook**](examples/colab_quickstart.ipynb).

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mdmahendri/scale-align/blob/main/examples/colab_quickstart.ipynb)


## Quick Start

```bash
scale-align \
    --source-dir /path/to/isic5 \
    --target-dir /path/to/nace21 \
    --correspondence correspondence.json \
    --output-dir ./output
```

## Input Format

### Classification Files
Text files with sentences separated by newlines:
```
/path/to/isic5/A.txt
/path/to/isic5/A0111.txt
```

### Correspondence JSON
```json
[["A","A"],["A0111","A01.11"],["A0112","A01.12"]]
```

## Output Format

Each output file `{source_code}_{target_code}.txt` contains:
```
[0]:[0,1]:0.87439287
[1,2]:[2]:0.92
[3]:[]:0
[4]:[3]:0.9999999
```

- `[source_indices]:[target_indices]:score`
- Empty brackets `[]` indicate no alignment (gap detected)

## CLI Options

| Option | Default | Description |
|--------|---------|-------------|
| `--threshold` | 0.7 | Minimum similarity score |
| `--margin` | 0.05 | Margin from champion score |
| `--batch-size` | 32 | Embedding batch size |
| `--device` | auto | Device (cuda/cpu/auto) |

## License

MIT
htmlcmp 1.1.1
Compare HTML files by rendered output
Requires Python: >=3.7

# htmlcmp

Tool to compare (generated) HTML files visually and automatically using Selenium.

Provides various entry points to run:
- `compare-html` is a CLI tool to compare two directory structures containing HTML files
- `compare-html-server` starts a webserver and allows to inspect differences manually
- `html-render-diff` renders two HTML files and produces images
- `html-tidy` allows to run HTML tidy on a directory

Used for regression testing in https://github.com/opendocument-app/OpenDocument.core.

## Install via PyPI

```bash
pip install htmlcmp
```

## Download and run the docker image

```bash
docker pull ghcr.io/opendocument-app/odr_core_test
```

```bash
docker run -ti \
  -v $(pwd):/repo \
  -p 8000:8000 \
  ghcr.io/opendocument-app/odr_core_test \
  compare-html-server /repo/REFERENCE /repo/MONITORED --compare --driver firefox --port 8000
```

## Manually build the docker image

```bash
docker build --tag odr_core_test test/docker
```

## Run locally

```bash
PYTHONPATH=$(pwd)/src:$PYTHONPATH python ./src/htmlcmp/compare_output_server.py \
  /path/to/REFERENCE \
  /path/to/MONITORED \
  --compare \
  --driver firefox \
  --port 8000 \
  -vv
```