purbb 0.1.0

Python Utility for Rapid Data Science - Print common ML/DS library imports

PURBB

Python Utility for Rapid Data Science and Machine Learning

A simple utility package that helps you quickly print all common machine learning and data science library imports with detailed comments.

Installation

pip install purbb

Usage

After installing, simply import and use the print_all_lib function:

from purbb import print_all_lib

# Print all common ML/DS imports with descriptions
print_all_lib()

What it does

The print_all_lib() function prints a comprehensive list of commonly used Python imports for machine learning and data science, including:

• Core Python utilities (warnings, random, collections, io)
• Numerical libraries (NumPy, Pandas)
• Visualization libraries (Matplotlib, Seaborn)
• Scikit-learn modules (datasets, preprocessing, metrics, models)
• Machine learning algorithms (SVM, KNN, Decision Trees, etc.)
• Clustering algorithms (K-Means, Gaussian Mixture)
• Ensemble methods (Random Forest, Bagging, AdaBoost)
• Dimensionality reduction (PCA)
• Bayesian networks (pgmpy)
• Graph visualization (NetworkX, pydotplus)

Each import includes helpful comments explaining its purpose.

Example Output

from purbb import print_all_lib
print_all_lib()

# Output:
# -------- Core Python Utilities --------
# import warnings              # To ignore warnings during execution
# import random                # Used for random actions (e.g., Tic Tac Toe opponent)
# ...

Requirements

• Python 3.7 or higher

License

MIT License

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Author

Your Name

Version

0.1.0