🌟 Overview

NeuraPython is a unified powerhouse module that merges Artificial Intelligence, Machine Learning, Web Development, Data Science, Physics, Chemistry, and Mathematics into a single framework. It’s designed for developers, engineers, students, and researchers who want to explore intelligence, computation, and science without juggling multiple libraries.

This package consolidates commonly used tools — including TensorFlow, PyTorch, Flask, Scikit-learn, OpenCV, Matplotlib, and more — under one unified namespace.

🔍 Philosophy

“One Import. Infinite Possibilities.”

NeuraPython aims to make scientific, AI, and data workflows faster, simpler, and smarter — no boilerplate code, no repetitive setup.

🧩 Core Functionalities

🤖 Artificial Intelligence

• Connect to Google Gemini API and OpenAI ChatGPT API
• Universal Neural Network Engine supporting both TensorFlow and PyTorch
• Dynamic model building with sequential layer architecture
• Unified training, compilation, and prediction interface

🧠 Machine Learning

• NeuraPython_ML simplifies model creation, training, evaluation, and saving.
• Preprocessing tools: normalization, encoding, standardization, and scaling
• Prebuilt datasets: Iris, Wine, Digits, Breast Cancer
• Built-in models:
  • Linear & Logistic Regression
  • SVM, KNN, Decision Tree, Random Forest
  • Gradient Boosting, PCA, KMeans, Naive Bayes
• Automatic train-test split, cross-validation, and grid search

🌐 Web Development

• Flask-based WebServer class with:
  • Custom route handling
  • File upload and JSON endpoints
  • SQLite integration
  • Health-check routes
  • Vector plotting endpoints

🧮 Advanced Mathematics & Calculus

• Derivatives, Integrals, Limits, Partial Derivatives
• Gradient, Curl, Divergence
• Taylor Series, Summation, Jacobian, Hessian
• Symbolic computation powered by Sympy

⚛️ Physics

• Classical mechanics, Relativity, and Quantum mechanics equations
• Functions for velocity, acceleration, energy, force, momentum
• Relativistic mass, Lorentz factor, time dilation
• Quantum equations (Planck, De Broglie, Heisenberg)

⚗️ Chemistry

• Periodic Table data for 50+ elements
• Molar, atomic, and gas constant utilities
• Planck’s relation, photon energy, and quantum constants

📊 Data Visualization

• 2D & 3D visualization using Matplotlib
• Line, Bar, Scatter, Pie, Polar, and 3D vector plots
• Built-in Vector2D & Vector3D classes with geometry operations

🧾 File Readers & Converters

• Read: .pdf, .docx, .json, .xml, .csv, .xlsx, .html, .md, .txt
• Convert between formats:
  • PDF ↔ DOCX
  • CSV ↔ Excel ↔ JSON
  • Markdown → HTML
  • Text → PDF/DOCX
• Supports direct string-to-file conversion

🎤 Speech & Audio

• Text-to-Speech via pyttsx3
• Voice input recognition using SpeechRecognition
• Audio and video playback through pygame and OpenCV

🧰 Utility Tools

• QR Code Generator and Reader
• Calendar printer
• Google, YouTube, WhatsApp search helpers
• System utilities for file handling, OS detection, and device info

⚙️ Installation

From PyPI

pip install neurapython

Manual Installation

git clone https://github.com/IbrahimShahid7767/neurapython.git
cd neurapython
pip install -r requirements.txt

Dependencies

pip install numpy pandas scikit-learn flask pyttsx3 pygame pillow opencv-python pdfplumber pdf2docx docx2pdf fpdf markdown beautifulsoup4 sympy tensorflow torch joblib qrcode requests

💻 Usage Examples

Example 1 — Quick Math

from neurapython import Advanced_Maths

calc = Advanced_Maths()
print(calc.factorial(6))

Example 2 — Machine Learning Workflow

from neurapython import NeuraPython_ML

ml = NeuraPython_ML()
X, y = ml.load_builtin_dataset("iris")
X_train, X_test, y_train, y_test = ml.split(X, y)

model = ml.create_model("svm")
ml.train("svm", X_train, y_train)
y_pred = ml.predict("svm", X_test)

print(ml.evaluate(y_test, y_pred))

Example 3 — Neural Network with Torch

from neurapython import NeuralNetwork

nn = NeuralNetwork(backend="torch")
nn.Sequential([4, 8, 3])
nn.compile(optimizer="adam", loss="mse")
nn.fit([[1, 2, 3, 4]], [[0, 1, 0]], epochs=5)

Example 4 — Web Server

from neurapython import WebServer

app = WebServer()
app.simple_route("/", code="Welcome to NeuraPython Web")
app.health("/health")
app.run(port=5200)

Example 5 — Physics

from neurapython import Physics

p = Physics()
print(p.kinetic_energy(5, 10))
print(p.mass_energy_equivalence(0.1))

Example 6 — QR Code

from neurapython import QR_Code

QR_Code.generator("https://github.com/IbrahimShahid7767", "neura_qr.png")
print(QR_Code.reader("neura_qr.png"))

🧩 Module Summary

🧠 Vision

“NeuraPython isn’t just a library — it’s a platform for computational intelligence.”
It simplifies AI, math, and science workflows into a unified Pythonic experience.

📂 Project Structure

neurapython/
├── __init__.py
├── ai/
│   ├── neural.py
│   ├── ml.py
│   └── api_clients.py
├── core/
│   ├── physics.py
│   ├── chemistry.py
│   ├── calculus.py
│   ├── maths.py
│   └── matrices.py
├── utils/
│   ├── converter.py
│   ├── reader.py
│   ├── media.py
│   ├── webserver.py
│   └── qrcode_tool.py

🧾 License

MIT License © 2025 Ibrahim Shahid

Permission is hereby granted, free of charge, to any person obtaining a copy of this software to use, modify, and distribute copies without restriction.