cherrypick-ml: A Machine Learning Orchestration and Pipeline Toolkit
| Testing | Structured validation of preprocessing, orchestration, and explainability components |
| Package | PyPI distribution |
| License | |
| downloads | |
| docs |
What is it?
cherrypick-ml is a Python package that provides a unified interface for building, managing, and evaluating machine learning workflows. It integrates preprocessing, anomaly detection, model orchestration, and explainability into a single, modular framework.
The library is designed to simplify real-world machine learning development by reducing repetitive code while maintaining flexibility and transparency in model pipelines.
Contributors and Contributions
Table of Contents
Main Features
cherrypick-ml provides the following core capabilities:
- Automated model orchestration for classification and regression tasks
- Integrated preprocessing utilities including encoding and missing value handling
- Outlier detection using statistical method such as Inter quartile range(IQR), Z-score, modified Z-score, Isolation Forest and Local Outlier Factor based outlier pruning
- SHAP-based explainability for feature importance and model interpretation
- Flexible train-test splitting utilities
- Modular design allowing independent usage of components
- Designed for practical, real-world machine learning workflows
Core Components
The library is structured into the following modules:
-
Orchestrator
High-level interface for training, evaluating, and selecting models with explainable visualisation -
preprocessing
Tools for encoding, imputation, and feature preparation -
anomaly
Outlier detection and data pruning utilities -
explain
Model explainability using SHAP-based analysis -
splits
Utilities for dataset partitioning
Documentation
Explore the full documentation for cherrypick-ml
Where to get it
The source code is currently hosted on GitHub at:
https://github.com/Sujal-G-Sanyasi/Cherrypick
Binary installers for the latest released version are available at the Python Package Index (PyPI):
pip install cherrypick-ml
Metadata
Release files for cherrypick-ml 0.1.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| cherrypick_ml-0.1.4.tar.gz | 18.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| cherrypick_ml-0.1.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 36.6 kB
Release files / cherrypick_ml-0.1.4.tar.gz
| Download URL | cherrypick_ml-0.1.4.tar.gz |
|---|---|
| Size | 18.4 kB |
| Tags | Source |
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Release files / cherrypick_ml-0.1.4-py3-none-any.whl
| Download URL | cherrypick_ml-0.1.4-py3-none-any.whl |
|---|---|
| Size | 18.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.14.0
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