Complete pipelines and helper tools for data science and machine learning projects.
Project description
dragon-ml-toolbox
A collection of machine learning pipelines and utilities, structured as modular packages for easy reuse and installation. This package has no base dependencies, allowing for lightweight and customized virtual environments.
Features:
- Modular scripts for data science workflows, including data exploration, ETL, model training, evaluation, and inference.
- Support for PyTorch-based models, ensemble learning (XGBoost, LightGBM), and MICE imputation.
Installation
Python 3.12
Via PyPI
Install the latest stable release from PyPI:
Using pip:
pip install dragon-ml-toolbox
Using UV:
uv add dragon-ml-toolbox
Via conda-forge
Install from the conda-forge channel:
conda install -c conda-forge dragon-ml-toolbox
Modular Installation
This toolbox is designed as a collection of mutually exclusive environments due to conflicting core dependencies.
- Rule: Create a fresh virtual environment for each module to use.
📦 Core Machine Learning Toolbox [ML]
Installs a comprehensive set of tools for typical data science workflows, including data manipulation, modeling, and evaluation using PyTorch.
➡️ On Windows, the default installation includes the CPU version of PyTorch. Follow the official instructions to install the CUDA version: PyTorch website
pip install "dragon-ml-toolbox[ML]"
Modules:
data_exploration
ETL_cleaning
ETL_engineering
IO_tools
keys
math_utilities
ML_callbacks
ML_chain
ML_configuration
ML_datasetmaster
ML_evaluation
ML_evaluation_captum
ML_finalize_handler
ML_inference
ML_inference_sequence
ML_inference_vision
ML_models
ML_models_diffusion
ML_models_sequence
ML_models_vision
ML_optimization
ML_scaler
ML_trainer
ML_utilities
ML_vision_transformers
optimization_tools
outlier_detection
path_manager
plot_fonts
resampling
schema
serde
SQL
utilities
constants
🌳 Ensemble Learning [ensemble]
Comprehensive set of tools for typical data science workflows focused on XGBoost and LightGBM.
pip install "dragon-ml-toolbox[ensemble]"
Modules:
data_exploration
ensemble_evaluation
ensemble_inference
ensemble_learning
ETL_cleaning
ETL_engineering
IO_tools
math_utilities
optimization_tools
outlier_detection
path_manager
plot_fonts
PSO_optimization
resampling
schema
serde
SQL
utilities
constants
🔬 MICE Imputation and Variance Inflation Factor [mice]
Utilities for advanced data cleaning and statistical checks. Features Multiple Imputation by Chained Equations (MICE) for handling missing data and Variance Inflation Factor (VIF) analysis to detect multicollinearity in features.
pip install "dragon-ml-toolbox[mice]"
Modules:
IO_tools
math_utilities
MICE
path_manager
plot_fonts
serde
utilities
VIF
📋 Excel File Handling [excel]
Installs dependencies required to process and handle .xlsx or .xls files.
pip install "dragon-ml-toolbox[excel]"
Modules:
IO_tools
excel_handler
path_manager
🎰 GUI for Boosting Algorithms (XGBoost, LightGBM) [gui-boost]
GUI tools compatible with XGBoost and LightGBM models used for inference.
pip install "dragon-ml-toolbox[gui-boost]"
Modules:
ensemble_inference
GUI_tools
IO_tools
path_manager
schema
serde
constants
🤖 GUI for PyTorch Models [gui-torch]
GUI tools compatible with PyTorch models used for inference.
pip install "dragon-ml-toolbox[gui-torch]"
Modules:
GUI_tools
IO_tools
keys
ML_models
ML_models_sequence
ML_models_vision # Requires: torchvision and Pillow
ML_inference
ML_inference_sequence
ML_inference_vision # Requires: torchvision and Pillow
ML_vision_transformers # Requires: torchvision and Pillow
ML_scaler
path_manager
schema
constants
Usage
After installation, import modules like this:
from ml_tools.serde import serialize_object, deserialize_object
from ml_tools.IO_tools import train_logger
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