dalla-data-processing 0.0.12

data processing pipeline with deduplication, stemming, quality checking, and readability scoring, used for the DALLA Models

Dalla Data Processing (dalla-dp)

A comprehensive Arabic data processing pipeline with deduplication, stemming, quality checking, and readability scoring, used for the DALLA Models.

Compatibility

• Linux: Fully supported
• macOS: Fully supported (Intel or through rosetta)
• Windows: Supported through WSL, for native windows: manual build from source works for deduplication.

Installation

Quick Start (All Features)

For most users, install with all features enabled:

Using uv

uv pip install "dalla-data-processing[all]"

Using pip

pip install "dalla-data-processing[all]"

Modular Installation (Advanced)

Install only the components you need to keep dependencies minimal:

# Base installation (no processing features, only core dependencies)
pip install dalla-data-processing

# Install specific features
pip install "dalla-data-processing[dedup]"        # Deduplication only
pip install "dalla-data-processing[stem]"         # Stemming only
pip install "dalla-data-processing[quality]"      # Quality checking only
pip install "dalla-data-processing[readability]"  # Readability scoring only
pip install "dalla-data-processing[pack]"         # Dataset packing only

# Combine multiple features
pip install "dalla-data-processing[dedup,stem,quality]"

Development Installation

From Source (with uv)

git clone https://github.com/U4RASD/dalla-data-processing.git
cd dalla-data-processing

# Install all features and dev dependencies
uv sync --all-extras

# Or install with specific extras only
uv sync --extra dedup --extra stem

From Source (with pip)

git clone https://github.com/U4RASD/dalla-data-processing.git
cd dalla-data-processing

# Install with all features for development
pip install -e ".[all,dev]"

Components

Note: Each component requires its corresponding extra to be installed. Install with [all] to enable all features, or see Modular Installation to install only what you need.

1. Deduplication

Detect and remove duplicate or near-duplicate documents from your datasets using the Onion algorithm.

• Requires: [dedup] extra

2. Stemming

Apply morphological analysis and stemming using CAMeL Tools.

• Requires: [stem] extra

3. Quality Checking

Check text quality using morphological analysis to detect errors and foreign words.

• Requires: [quality] extra

4. Readability Scoring

Calculate readability scores using Flesch Reading Ease and Osman methods. Contains also ranking according to both scores

• Requires: [readability] extra

5. Dataset Packing

Pack and prepare datasets for training.

• Requires: [pack] extra

Links

• Homepage: https://acrps.ai
• Documentation: https://github.com/U4RASD/dalla-data-processing#readme
• ACRPS: https://acr.ps