NeuraPython 2.0.0

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

🧠 NeuraPython — Unified AI, Science & System Framework (v1.2.4 Hybrid Edition)

Author: Ibrahim Shahid
Version: 2.0.0 (Hybrid Edition)
License: MIT

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📘 Overview

NeuraPython 1.2.4 is a cutting-edge, unified Python framework that bridges the realms of Artificial Intelligence, Machine Learning, Quantum Mechanics, Advanced Mathematics, Physics, Chemistry, Statistics, and Assembly-level System Programming — all in one coherent ecosystem.

The Hybrid Edition intelligently activates advanced analytical and visualization capabilities (via SciPy, Pandas, Statsmodels, Seaborn) when available, while maintaining a lightweight NumPy–Matplotlib core for high performance and portability.

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🚀 Key Highlights

Category	Description
🧠 Artificial Intelligence	Unified integration layer for ChatGPT, Gemini, and custom reasoning agents.
🤖 Machine Learning	Scikit-learn wrapper for streamlined dataset handling, model creation, and evaluation.
🧩 Neural Networks	PyTorch & TensorFlow compatible interface for deep learning workflows.
⚛️ Quantum Engine	Handles teleportation, tunneling, and quantum probability simulations.
📊 Statistics (Hybrid v3.0)	Enterprise-grade analytics: means, dispersions, tests, regressions, correlations, and dynamic graphing.
🧮 Advanced Mathematics	Algebra, calculus, probability, combinatorics, sequences, and matrix operations.
🔬 Physics Engine	Includes classical, relativistic, and quantum models with energy and field calculations.
⚗️ Chemistry Tools	Periodic table, molecular constants, and formula-based computations.
🧱 Assembly Layer	Custom interpretable assembly instructions for logical and arithmetic control.
🌐 Web Server	Flask-powered REST API and visualization hosting system.
🧾 Converters	PDF, DOCX, TXT, JSON, CSV, and HTML file transformation tools.
💾 Database Manager	SQLite wrapper with automatic schema creation and querying.
🧠 Sensors & System	PhysicalSensors class for temperature, motion, and light readings.
📈 Visualization	Matplotlib + Seaborn-based graphing engine with single and multi-frame plotting.
Translator	Translation from any language to other desired language

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⚙️ Installation

🔹 Core Installation

pip install neurapython

🔸 Upgrade Existing Version

pip install --upgrade neurapython

🔹 Full Analytical Stack

To unlock all Hybrid Edition features:

pip install numpy scipy pandas seaborn statsmodels matplotlib

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⚡ Quick Examples

🧠 Artificial Intelligence

from neurapython import AI
ai = AI()
print(ai.ask("Explain quantum tunneling simply."))

🤖 Machine Learning

from neurapython import NeuraPython_ML
ml = NeuraPython_ML()
X, y = ml.load_builtin_dataset("iris")
ml.create_model("random_forest")
ml.train("random_forest", X, y)
print(ml.evaluate(y, ml.predict("random_forest", X)))

⚛️ Quantum Calculations

from neurapython import QuantumCalculation
qc = QuantumCalculation()
qc.teleportation_simulation(qubits=3)
qc.quantum_tunneling(potential=5.0, energy=3.5)

📊 Statistics

from neurapython import Statistics
import numpy as np

data = np.random.normal(10, 2, 100)
S = Statistics(data)
print("Arithmetic Mean:", S.arithmetic_mean())
print("Geometric Mean:", S.geometric_mean())
S.plot_histogram(kde=True)

⚗️ Chemistry

from neurapython import Chemistry
chem = Chemistry()
print(chem.atomic_mass("Oxygen"))

⚙️ Assembly Execution

from neurapython import Assembly
asm = Assembly()
asm.load_code("""MOV AX, 5\nMOV BX, 3\nADD AX, BX\nOUT AX""")
asm.run()

🌐 Web Server

from neurapython import WebServer
app = WebServer()
app.simple_route('/', code='NeuraPython Web Active')
app.run()

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🧩 Module Architecture

neurapython/
│
├── AI                     # ChatGPT / Gemini integration layer
├── Assembly               # Assembly-level interpreter
├── Advanced_Maths         # Calculus, algebra, probability
├── Chemistry              # Elemental data & formulas
├── Database               # SQLite wrapper
├── Physics                # Mechanics, relativity, quantum
├── QuantumCalculation     # Quantum computation class
├── Statistics             # Full analytics + graphing engine
├── Sensors                # Physical sensor simulations
├── Visualizer2D / 3D      # Matplotlib-based plotting tools
├── WebServer              # Flask REST API and web interface
├── NeuralNetwork          # Deep learning backend manager
└── Converter, Reader, Media, Utilities

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🧠 Author

Ibrahim Shahid
📧 [e-mail]

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⚖️ License

MIT License — 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 · NumPy · SciPy · Pandas · Statsmodels · Seaborn · OpenCV · Matplotlib · P