installation.md

📦 Installation Guide

Installation Guide

Get KDP up and running in your environment quickly and easily

📋 Overview

KDP can be installed through various methods, from simple pip installation to building from source. Choose the method that best fits your needs and environment.

🚀

Quick Installation

Simple pip install for most users

🛠️

Multiple Methods

pip, Poetry, or source installation

🧩

Optional Dependencies

Install only what you need

⚡

GPU Support

Leverage GPU acceleration

🚀 Quick Installation

pip install kdp

🛠️ Installation Methods

Using pip (Recommended)

# Basic installation
pip install kdp

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Using Poetry

# Add to your project
poetry add kdp

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From Source

# Clone the repository
git clone https://github.com/UnicoLab/keras-data-processor.git
cd keras-data-processor

# Install using pip
pip install -e .

# Or using poetry
poetry install

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🧩 Dependencies

Core Dependencies

• 🐍 Python 3.10+
• 🔄 TensorFlow 2.18+ (Keras 3)
• 🔢 NumPy 1.19+
• 📊 Pandas 1.2+

Optional Dependencies

Package	Purpose	Install Command
scipy	🧪 Scientific computing and statistical functions	pip install "kdp[dev]"
ipython	🔍 Interactive Python shell and notebook support	pip install "kdp[dev]"
pytest	✅ Testing framework and utilities	pip install "kdp[dev]"
pydot	📊 Graph visualization for model architecture	pip install "kdp[dev]"
Development Tools	🛠️ All development dependencies	pip install "kdp[dev]"
Documentation Tools	📚 Documentation generation tools	pip install "kdp[doc]"

🖥️ GPU Support

Enable GPU Acceleration

# Install TensorFlow with GPU support
pip install tensorflow-gpu

Ensure you have the appropriate CUDA and cuDNN versions installed.

✅ Verifying Your Installation

import kdp

# Check version
print(f"KDP version: {kdp.__version__}")

# Basic functionality test
from kdp import PreprocessingModel, FeatureType
features = {"test": FeatureType.FLOAT}
model = PreprocessingModel(features_specs=features)
print("Installation successful!")

👣 Next Steps

🏁

Quick Start Guide

Learn the basics of KDP

Get Started →

🏗️

Architecture Overview

Understand KDP's components

Learn More →

🔍

Feature Processing

Explore KDP's capabilities

Explore →

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