NeuraPython 1.2.0

A multi-purpose AI and utility module for Python — includes GUI, file handling, math, media, and OS integration.

🧠 NeuraPython — Unified Scientific and AI Python Framework

Author: Ibrahim Shahid
Version: 1.2.0
License: MIT

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📘 Overview

NeuraPython is a powerful, all-in-one Python module that integrates Artificial Intelligence, Machine Learning, Physics, Chemistry, Mathematics, Databases, Media Handling, Web Servers, Speech Recognition, and much more — all inside one unified framework.
It is designed for developers, data scientists, educators, and researchers who want a single tool for advanced computation, visualization, automation, and AI integration.

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🚀 Key Features

Category	Description
Artificial Intelligence	Access Google Gemini and OpenAI GPT APIs directly.
Machine Learning	Unified wrapper over Scikit-Learn: data preprocessing, model training, evaluation, and persistence.
Neural Networks	Dual backend (PyTorch & TensorFlow) with a universal API for model creation and training.
Mathematics	Advanced arithmetic, algebra, probability, and calculus using symbolic math.
Physics	Complete suite for classical, relativistic, and quantum physics equations and constants.
Chemistry	Periodic table, atomic data lookup, and molecular computation.
Database	Simplified SQLite3 interface with auto schema creation and CRUD support.
Web Development	Built-in Flask-powered server for quick web apps and JSON APIs.
Speech & Media	Text-to-speech, voice recognition, and media (image, audio, video) handling.
Visualization	2D and 3D graphing powered by Matplotlib.
File Conversion	Convert between PDF, DOCX, Excel, JSON, CSV, and Markdown/HTML seamlessly.
QR Codes	Generate and decode QR codes easily.
Readers	Built-in file readers for multiple formats: PDF, DOCX, JSON, HTML, XML, CSV, etc.

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🧩 Installation

Requires Python 3.9+

Install from PyPI:

pip install neurapython

Upgrade if already installed:

pip install --upgrade neurapython

Then import the module:

from neurapython import *

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🧠 Example Usage

🧩 Machine Learning

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

ml.create_model("random_forest")
ml.train("random_forest", X_train, y_train)
pred = ml.predict("random_forest", X_test)
print(ml.evaluate(y_test, pred))

🔬 Neural Network

nn = NeuralNetwork(backend='torch')
nn.Sequential([4, 8, 3])
nn.compile()
nn.fit([[0.1, 0.2, 0.3, 0.4]], [[1, 0, 0]], epochs=3)

⚛️ Physics

phy = Physics()
print(phy.mass_energy_equivalence(0.001))  # E = mc²

⚗️ Chemistry

chem = Chemistry()
print(chem._elements[0])  # Hydrogen info

📊 Visualization

viz = Visualizer2D(["A","B","C"], [10,20,15], title="Example Bar Graph")
viz.bar_graph()
viz.show()

🔈 Speech & Media

speak("Hello, this is NeuraPython in action!")
text = voice_input("Say something:")
print("You said:", text)

🧮 Calculus

calc = Calculus()
print(calc.derivative("x**2 + 3*x", "x"))

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🧱 Module Structure

neurapython/
│
├── AI                    # API access (ChatGPT, Gemini)
├── Advanced_Maths        # Arithmetic, algebra, statistics
├── Calculus              # Symbolic calculus and differentiation
├── Chemistry             # Periodic table and constants
├── Converter             # File format converters
├── Database              # SQLite handler
├── Media                 # Audio, video, and image tools
├── Matrices, Vectors     # Linear algebra utilities
├── NeuraPython_ML        # Scikit-learn unified wrapper
├── NeuralNetwork         # TensorFlow / PyTorch integration
├── Physics               # Mechanics, relativity, quantum
├── Reader                # File readers (txt, pdf, json, etc.)
├── Visualizer2D / 3D     # Graph plotting
├── WebServer             # Flask API server
└── QR_Code               # Generate and read QR codes

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⚙️ Requirements

• torch
• tensorflow
• scikit-learn
• flask
• pyttsx3
• speechrecognition
• pygame
• opencv-python
• pandas
• numpy
• matplotlib
• sympy
• pdfplumber
• docx2pdf
• pdf2docx
• markdown
• fpdf
• joblib
• requests
• bs4

Install dependencies manually (if needed):

pip install neurapython

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📚 Additional Information

• Fully modular — import only what you need.
• Cross-platform (Windows, macOS, Linux).
• Integrated TensorFlow and PyTorch support.
• Built-in physics constants and quantum utilities.
• File conversion utilities for automation workflows.
• Speech and multimedia integration for interactive projects.
• Database and web utilities for backend development.

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🧠 Author

Ibrahim Shahid
📧 Email: [e-mail]

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⚖️ License

This project is licensed under the MIT License.
You are free to use, modify, and distribute with proper credit.

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🌟 Contribution

Contributions are welcome!

1. Fork this repository
2. Create your branch (git checkout -b feature/YourFeature)
3. Commit changes (git commit -m "Add new feature")
4. Push (git push origin feature/YourFeature)
5. Open a Pull Request

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🧩 Future Enhancements

• Web-based dashboard for AI/ML models
• Extended NLP and Vision utilities
• Integrated scientific simulator

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💬 Credits

Developed with ❤️ by Ibrahim Shahid
Powered by: TensorFlow · PyTorch · Flask · Scikit-learn · SymPy · Pandas · NumPy · OpenCV · Matplotlib and more.

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