semvec/pypi-packages huggingface dataset:
ac-library-python-stubs 0.1.0.20250812
Type stubs for not522/ac-library-python
Requires Python: >=3.9

# ac-library-python-stubs

[日本語のREADME](README_ja.md)

A package that adds type stubs for static analysis to [not522/ac-library-python](https://github.com/not522/ac-library-python).

Mainly adds Generic types to SegTree, LazySegmentTree, and FenwickTree.

Specifically, this allows you to specify types in places where `typing.Any` was previously used:

```python
Mono = tuple[int, int]
def op(x: Mono, y: Mono) -> Mono:
    return (x[0] + y[0], x[1] + y[1])
seg = SegTree(op, (0, 0), 10)
# > seg.prod(l: int, r: int) -> Mono

fen = FenwickTree[float](10)
# > fen.add(x: int, v: float) -> None
```

## Installation
```bash
pip install ac-library-python-stubs
```

## Requirement
- python 3.9+
- [ac-library-python v0.1.0](https://github.com/not522/ac-library-python/releases/tag/v0.1.0)

> [!NOTE]
> As of 2025-07-21, https://atcoder.jp judge uses [ac-library-python@58f324e](https://github.com/not522/ac-library-python@58f324ec020d57191e7b9e4957b0c5feb5ed3aff), which shows package version `0.0.1`, but the code has no differences from `0.1.0`.
react-django 0.1.2
CLI to scaffold fullstack React + Django + Tailwind projects
Requires Python: >=3.7

# Full-Stack Django + Vite + React + TailwindCSS Scaffold

- **Start Project:**
  - Creating it Globally for Windows ----> 
    - py -m pip install react-django

  - Creating it Globally for Linux/macOS: ----> 
    - python3 -m pip install react-django


  - run this in your terminal
   - py -m react_django
   - pytho3 -m react_django (Linux/macOS)


  

This project is a **one-command scaffold** for creating a fully integrated **Django backend** and **Vite + React + TailwindCSS frontend** inside a single repository.  
It automatically configures **development** and **production** environments, including database settings, static files, and environment-based React/Django integration.

---

## 📦 Features

- **Frontend:**
  - [Vite](https://vitejs.dev/) with [React](https://reactjs.org/)
  - [TailwindCSS](https://tailwindcss.com/) styling
  - Auto-generated `vite.config.js` and `index.css`
  - Environment-aware server settings from `config.json`
  - Fonts and theme variables preconfigured

- **Backend:**
  - [Django](https://www.djangoproject.com/) REST API
  - [Django REST Framework](https://www.django-rest-framework.org/)
  - CORS support via `django-cors-headers`
  - Token-based authentication
  - Whitenoise for static file serving
  - Environment-aware settings from `config.json`
  - SQLite (dev) / PostgreSQL (production)

- **Extras:**
  - Single root directory for both frontend and backend
  - Auto-creation of `config.json` for easy environment switching
  - Django templates configured to serve Vite in dev and built static files in production

---

## 🛠 Requirements

Before running the script, make sure you have:

- **Python 3.8+**  
- **Node.js 18+ & npm**  
- **pip** (comes with Python)  
- **PostgreSQL** (only needed in production)

---

## 🚀 Usage

### 1️⃣ Clone or Download
```bash
git clone https://github.com/ISAAC-EDZORDZI-FIAVOR/Django_React_Template
cd yourrepo


After running the script, you'll get a structure like:

    your-project/
    │── account/                  # Django app
    │── core/                     # Django project
    │── dist/                     # Built React files (production)
    │── env/                      # Python virtual environment
    │── media/                    # User-uploaded files
    │── node_modules/             # Frontend dependencies
    │── src/                      # React source code
    │── static/                   # Django static files (collected)
    │── template/                 # Django templates
    │── config.json               # Environment configuration
    │── requirements.txt          # Python dependencies
    │── vite.config.js            # Vite config linked to config.json
    │── manage.py
    │── package.json
    │── index.css
khmereasytools 0.3.8
A simple, self-contained library for Khmer text processing, with optional OCR and POS tagging support.
Requires Python: >=3.6


# Khmer Easy Tools

A simple, user-friendly, and self-contained Python library for common Khmer Natural Language Processing (NLP) tasks. This package provides easy-to-use functions for keyword extraction and segmentation without requiring complex external dependencies for its core features.

## Installation

Install the base package:
```bash
pip install khmereasytools
```

### Installing Optional Features

You can install the features you need.

```bash
# To install support for POS tagging (khpos)
pip install khmereasytools[khmernltk]

# To install support for OCR (khocr)
pip install khmereasytools[ocr]

# To install all optional features
pip install khmereasytools[all]
```

**For OCR functionality**, you must also install Google's Tesseract OCR engine on your system.
-   [Tesseract Installation Guide](https://github.com/tesseract-ocr/tesseract/wiki)
-   Make sure to install the Khmer (`khm`) language data.

## How to Use

### Keyword Extraction (`khfilter`)
Uses a built-in segmentation algorithm to find words and remove stop words by using Khmer Stop Word and Segmentaion Dictionary.
```python
import khmereasytools as ket
text = "នេះគឺជាប្រាសាទអង្គរវត្តស្ថិតនៅក្នុងខេត្តសៀមរាប"
keywords = ket.khfilter(text)
print(f"Keywords: '{keywords}'")
```

### Text Segmentation (`khseg`)
Uses a built-in segmentation algorithm to split text into words.
```python
import khmereasytools as ket
text = "នេះគឺជាប្រាសាទអង្គរវត្ត"
words = ket.khseg(text)
print(f"Segmented Words: {words}")
```

### Syllable Segmentation (`khsyllable`)
Uses a built-in rule-based method to split text into syllables.
```python
import khmereasytools as ket
text = "សាលារៀន"
syllables = ket.khsyllable(text)
print(f"Syllables: {syllables}")
```

### Part-of-Speech Tagging (`khpos`)
*Requires `khmernltk` to be installed.*
```python
import khmereasytools as ket
# pip install khmereasytools[khmernltk]
text = "ខ្ញុំស្រឡាញ់ភាសាខ្មែរ"
tags = ket.khpos(text)
print(f"POS Tags: {tags}")
```

### OCR from Image (`khocr`)
*Requires `ocr` dependencies to be installed.*
```python
import khmereasytools as ket
# pip install khmereasytools[ocr]
# text_from_image = ket.khocr('khmer_text.png')
# print(f"Text from OCR: {text_from_image}")
```