semvec/pypi-packages huggingface dataset:
types-pyperclip 1.11.0.20260216
Typing stubs for pyperclip
Requires Python: >=3.10

## Typing stubs for pyperclip

This is a [type stub package](https://typing.python.org/en/latest/tutorials/external_libraries.html)
for the [`pyperclip`](https://github.com/asweigart/pyperclip) package. It can be used by type checkers
to check code that uses `pyperclip`. This version of
`types-pyperclip` aims to provide accurate annotations for
`pyperclip==1.11.*`.

This package is part of the [typeshed project](https://github.com/python/typeshed).
All fixes for types and metadata should be contributed there.
See [the README](https://github.com/python/typeshed/blob/main/README.md)
for more details. The source for this package can be found in the
[`stubs/pyperclip`](https://github.com/python/typeshed/tree/main/stubs/pyperclip)
directory.

This package was tested with the following type checkers:
* [mypy](https://github.com/python/mypy/) 1.19.1
* [pyright](https://github.com/microsoft/pyright) 1.1.408

It was generated from typeshed commit
[`9c00c6e556cd864c044daffb07733f3a8c38b621`](https://github.com/python/typeshed/commit/9c00c6e556cd864c044daffb07733f3a8c38b621).
makoview 0.1.3
Visualise the results from Mako
Requires Python: <3.13,>=3.9

# makoview

Makoview is a visualisation tool intended to be used with the [Mako](https://github.com/shimlab/mako) pipeline for the differential analysis of RNA modifications using Oxford Nanopore data. For more information, see the repository at [shimlab/mako](https://github.com/shimlab/mako)

## Installation

Makoview is available through both PyPI (tagged/release builds) and TestPyPI (development builds). You can install it using `pip`, or execute it in an isolated environment with pipx/uvx:

```sh
pip install makoview

# for testing purposes: run latest commit from GitHub
uvx --from https://github.com/shimlab/makoview.git makoview
```
khmer-segmenter 0.1.0
The package is for segment khmer words (adding space between words) with two method: compound-based and morpheme-based.
Requires Python: >=3.10

# Khmer Segmenter

A lightweight Khmer word segmentation package for `Python ≥ 3.10`, designed for simple and efficient tokenization.

This project is adapted and simplified from the original [khnlp](https://pypi.org/project/khnlp/) package, with the following goals:

- Support modern Python versions (≥ 3.10)
- Simplified installation
- Focus on a single task: Khmer word segmentation
- Lightweight and easy to integrate into NLP pipelines

This package is intended as a small academic contribution to support Khmer NLP research and practical applications.

## Installation

```bash
pip install khmer-segmenter
```

Requires:
- Python >= 3.10

## Usage
```python
from khmer_segmenter import Tokenizer

tokenizer = Tokenizer(seg_type="com")

print(tokenizer.tokenize("សួស្ដីអ្នកទាំងអស់យើង"))
```

## Segmentation Modes

The tokenizer supports two segmentation strategies:

### 1. Compound-based (`seg_type="com"`)

- Segments text into compound words
- Suitable for general word-level NLP tasks
- Recommended for downstream applications such as:
    - Text classification
    - Named Entity Recognition
    - Information retrieval


### 2. Morpheme-based (`seg_type="mor"`)

- Performs finer-grained segmentation
- Splits text into smaller morphological units
- Useful for:
    - Linguistic analysis
    - Subword modeling
    - Research-focused NLP tasks


## Motivation

Khmer is a low-resource language with no explicit word boundary markers (spaces are not consistently used to separate words). This creates challenges for:
- Automatic Speech Recognition (ASR)
- Language Modeling
- Machine Translation
- Information Extraction

Existing tools for Khmer segmentation often have:
- Limited Python version support
- Heavy dependencies
- Broader NLP scope than necessary

This project provides a focused, minimal, and modern alternative dedicated solely to segmentation.