Soft Computing Library (numpyyy)

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 numpyyy

To update to the latest version:

pip install --upgrade numpyyy

Requires Python 3.6 or newer.

Step 2: View the programs

Option A: From the terminal

Show all practicals:

numpysc
# or
numpyyy

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 numpysc_lib

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

Option C: In Google Colab or Jupyter

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

Publishing a new version (for maintainers)

1. Make any additions or updates in the numpysc_lib/ 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.