sol-ai-core 0.1.0

A professional Python Library for automated data cleaning, model selection, and visualization.

sol-ai-core

SOL Engine is now sol-ai-core, a professional, environment-agnostic Python library for automated data cleaning, machine learning model selection, and visualization.

Features

• Logic Separated: Works seamlessly in any Python environment (Jupyter, VS Code, CI/CD) without requiring Streamlit.
• Class-Based Design: Easy to use object-oriented approach.
• End-to-End Automation: Pass a DataFrame, auto-clean it, train models, and generate insights in just a few lines of code.

Installation

You can install the package via pip once published to PyPI:

pip install sol-ai-core

For local development:

git clone https://github.com/yourusername/sol-ai-core.git
cd sol-ai-core
pip install -e .

Usage

import pandas as pd
from sol_core.engine import SolEngine

# 1. Load your data
df = pd.read_csv("data.csv")

# 2. Initialize the engine
engine = SolEngine(df)

# 3. Clean the data automatically
clean_df = engine.auto_clean()

# 4. Train a model automatically (Classification or Regression)
report = engine.select_and_train_model(target_column="target")
print(report)

# 5. Generate Visualizations (Returns Matplotlib figure objects)
figures = engine.generate_visualizations(target_column="target")
figures['target_distribution'].show()

Publishing to PyPI

To build and publish this library to PyPI, use the following commands:

# Install build tools and twine
pip install build twine

# Build the package (creates dist/ directory)
python -m build

# Upload to PyPI (will prompt for username and password/token)
python -m twine upload dist/*