semvec/pypi-packages huggingface dataset:
wikicleaner 0.1.7
Bindings to a rust library that can help process wikipedia's data dumps.
Requires Python: >=3.8

# Wikicleaner

Wikipedia provides a series of [dumps](https://dumps.wikimedia.org/backup-index.html) in XML format. While developing this project, I personally used the [simple wiki](https://dumps.wikimedia.org/simplewiki/20240201/) dumps.

## Purpose

The intent of this project is to provide some low-level routines that allow us to manipulate the content of XML dumps. One such routine removes all of the annotations like `[[File:*]]` and `{{some metadata}}` in order to make our input more digestible for an AI application that uses embeddings.

## Example Usage

```py
>>> import wikicleaner as wc
>>> article_raw_text = "[[File:Colorful spring garden.jpg|thumb|180px|right|[[Spring]] flowers in April in the [[Northern Hemisphere]].]] April comes between [[March]] and [[May]]"
>>> wc.clean_article_text(article_raw_text)
' April comes between March and May'
```
pointcloud-extraction-toolkit 0.0.3
scripts for allowing user to load and preprocess data from the lidar / image data in order to convert into raw attributed point cloud dataset
Requires Python: >=3.8

## @geospatial-pipelines/data_preparation:

This package provides the tools and utils for the first stage of the operation after fetching data: allowing users to do operations of the current raw dataset of pointcloud (.las, .laz, .pcd) for operations like: 
    - Cropping (2D/3D cropping)
    - conversion of the coordinates 
    - combination of point clouds
    - conversion across various formats.

## installation and setup:
- Install from the pip directory: `pip install -r requirements.txt`
- Or via the source by cloning the whole [geospatial-pipeline]() and then installing the file via the `pip install -r requirements.txt`.


## Various packages:
--------------- ------------
| package_file | usecases |