NeuraPython 1.2.2

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

🧠 NeuraPython — Unified AI, Science & Assembly Framework

Author: Ibrahim Shahid
Version: 1.2.2
License: MIT

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📘 Overview

NeuraPython is a next-generation, unified Python framework designed to bridge Artificial Intelligence, Machine Learning, Scientific Computation, and even Assembly-level execution — all inside one cohesive ecosystem.

It simplifies development for AI engineers, data scientists, educators, physicists, and automation enthusiasts by combining advanced computation, system control, and AI capabilities under one intuitive API.

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🚀 Key Highlights

Category	Description
🧠 Artificial Intelligence	Direct integration with Google Gemini and OpenAI ChatGPT APIs for text and reasoning tasks.
🤖 Machine Learning	Unified Scikit-Learn wrapper for dataset loading, preprocessing, model training, evaluation, and persistence.
🧩 Neural Networks	Supports both PyTorch and TensorFlow backends with a shared universal interface.
🧮 Mathematics & Calculus	Symbolic and numeric mathematics: differentiation, integration, gradients, Jacobians, Hessians, and more.
⚛️ Physics Engine	Covers mechanics, relativity, electricity, magnetism, and quantum physics (including Heisenberg uncertainty).
⚗️ Chemistry Tools	Built-in periodic table, molecular data, and atomic constants for chemical computations.
🗄️ Databases	Simplified SQLite manager with auto-schema creation, insertion, and query utilities.
🌐 Web Development	Built-in Flask server for APIs, websites, and JSON endpoints. Includes error handling and file upload endpoints.
🔊 Speech & Audio	Text-to-speech and voice recognition utilities for interactive AI apps.
📊 Visualization	Generate 2D, 3D, and polar plots using Matplotlib with minimal code.
🧩 Assembly Language Support	Built-in Assembly interpreter and hardware-level utilities for advanced system control and code execution.
🧾 Converters	Seamless conversion between PDF, DOCX, TXT, Excel, CSV, JSON, and Markdown/HTML.
🧱 Vectors & Matrices	Advanced matrix algebra and vector calculus engine.
🧮 Advanced Maths	Arithmetic, statistics, combinatorics, sequences, and probability utilities.
🖼️ Media Handling	Display images, play audio/video, and process multimedia via OpenCV and Pygame.
🧾 Readers	Universal file readers for PDF, DOCX, JSON, XML, CSV, and more.
🔐 QR Codes	Create and decode QR codes effortlessly.
🗓️ Calendar	Print system calendar data instantly via Python.
Sensors
class PhysicalSensors
Contain multiple Sensors

| |Web Scrapping class Web_Scrapper Used for Web Scrapping

🧩 Installation

Requires Python 3.9+

Install from PyPI:

pip install neurapython

Upgrade if already installed:

pip install --upgrade neurapython

Then import:

from neurapython import *

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⚙️ Quick Examples

🤖 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

💾 Database

db = Database()
db.create("data.db", "Users", [
    {"name": "ID", "datatype": "INTEGER"},
    {"name": "Name", "datatype": "TEXT"}
])
db.insert_data("data.db", "Users", {"ID": [1], "Name": ["Ibrahim"]})

🧮 Calculus

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

🧩 Assembly Support

from neurapython import Assembly

asm = Assembly()
asm.load_code("""
MOV AX, 5
MOV BX, 10
ADD AX, BX
OUT AX
""")
asm.run()

🔈 Speech & Voice

speak("Welcome to NeuraPython!")
text = voice_input("Say something:")
print("You said:", text)

🌐 Web Server

server = WebServer()
server.simple_route("/", code="Welcome to NeuraPython Web API!")
server.run()

📊 Visualization

viz = Visualizer2D(["A", "B", "C"], [5, 10, 15], title="Bar Graph Example")
viz.bar_graph()
viz.show()

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🧱 Module Structure

neurapython/
│
├── AI                   # GPT / Gemini integration
├── Assembly             # Assembly language interpreter & hardware control
├── Advanced_Maths       # Algebra, statistics, probability
├── Calculus             # Derivatives, limits, Jacobians, etc.
├── Chemistry            # Periodic table and constants
├── Converter            # File conversions
├── Database             # SQLite wrapper
├── Media                # Image, audio, video
├── Matrices, Vectors    # Linear algebra utilities
├── NeuraPython_ML       # Unified ML wrapper
├── NeuralNetwork        # TensorFlow / PyTorch backend
├── Physics              # Classical, relativistic, quantum
├── Reader               # File readers
├── Visualizer2D / 3D    # Graph plotting
└── WebServer            # Flask API/web server

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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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💬 Credits

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

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