Soft Computing Library (nummpyyy)

A Python package that stores practical programs for Soft Computing & Neural Networks (Simple Neural Networks, Sigmoidal Functions, McCulloch-Pitts, Hebb Rule, Backpropagation, Fuzzy Sets, Perceptron) and prints their source code on demand, from Python or the terminal.

Install it once with pip, then view any practical code on any machine without copying files around.

Practicals Included

Step 1: Install

pip install nummpyyy

To update to the latest version:

pip install --upgrade nummpyyy

Requires Python 3.6 or newer.

Step 2: View the programs

Option A: From the terminal

Show all practicals:

numpysc
# or
nummpyyy

Show a single practical (type the name or partial name):

numpysc "1A-Simple-Neural-Network"
numpysc "7-Fuzzy"
numpysc "8-Perceptron"

Option B: From Python

import nummpyyy

nummpyyy.show_codes()                           # Show all practicals
nummpyyy.show_codes("7-Fuzzy")                  # Show specific practical
nummpyyy.show_codes("1A-Simple-Neural-Network") # Show specific practical

Option C: In Google Colab or Jupyter

!pip install nummpyyy
import nummpyyy
nummpyyy.show_codes("8-Perceptron")

Publishing a new version (for maintainers)

1. Make any additions or updates in the nummpyyy/ folder.
2. Increment version in setup.py (e.g. 1.1.2).
3. Clean old builds:

   rm -rf dist build *.egg-info
   

4. Build:

   python3 -m build
   

5. Check and Upload to PyPI:

   python3 -m twine upload dist/*
   

License

MIT. See LICENSE.