📦 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
Using Poetry
# Add to your project
poetry add kdp
From Source
# Clone the repository
git clone https://github.com/piotrlaczkowski/keras-data-processor.git
cd keras-data-processor
# Install using pip
pip install -e .
# Or using poetry
poetry install
🧩 Dependencies
Core Dependencies
- 🐍 Python 3.7+
- 🔄 TensorFlow 2.5+
- 🔢 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!")