nebula_x_deployment_files.txt

# =============================================================================
# NEBULA-X CONFIGURATION FILES
# Francisco Angulo de Lafuente - Agnuxo
# =============================================================================

# requirements.txt
# Core dependencies for NEBULA-X
torch>=2.0.0
transformers>=4.30.0
datasets>=2.14.0
huggingface_hub>=0.16.0
accelerate>=0.21.0

# Scientific computing
numpy>=1.24.0
scipy>=1.10.0
pandas>=2.0.0
scikit-learn>=1.3.0

# Quantum computing
pennylane>=0.32.0
pennylane-lightning>=0.32.0

# GPU acceleration
cupy-cuda12x>=12.0.0  # For CUDA 12.x
pycuda>=2022.2

# Optical and raytracing
pillow>=10.0.0
opencv-python>=4.8.0

# Evolutionary algorithms
deap>=1.4.1

# Networking and P2P
websockets>=11.0
aiohttp>=3.8.0

# Visualization
matplotlib>=3.7.0
seaborn>=0.12.0
plotly>=5.15.0

# Development and testing
pytest>=7.4.0
pytest-asyncio>=0.21.0
black>=23.0.0
flake8>=6.0.0
mypy>=1.5.0

# Documentation
sphinx>=7.1.0
sphinx-rtd-theme>=1.3.0

# Deployment
docker>=6.0.0
gradio>=3.39.0
streamlit>=1.25.0

---

# config.yaml
# Main configuration file for NEBULA-X

model:
  name: "NEBULA-X"
  version: "1.0.0"
  author: "Francisco Angulo de Lafuente (Agnuxo)"
  license: "Apache 2.0"
  
  # Architecture parameters
  architecture:
    hidden_size: 768
    num_hidden_layers: 12
    num_attention_heads: 12
    intermediate_size: 3072
    max_position_embeddings: 2048
    vocab_size: 50000
    dropout: 0.1
    layer_norm_eps: 1e-12
  
  # NEBULA-X specific features
  nebula_features:
    holographic_memory:
      enabled: true
      resolution: [256, 256]
      coherence_length: 1000
      interference_threshold: 0.1
      storage_planes: 10
    
    quantum_processing:
      enabled: true
      qubits_per_neuron: 4
      decoherence_time: 1e-6
      quantum_noise_level: 0.01
      error_correction: "basic"
    
    optical_raytracing:
      enabled: true
      rays_per_neuron: 1000
      max_bounces: 10
      monte_carlo_samples: 10000
      wavelength: 632.8e-9
      use_gpu_acceleration: true
    
    evolutionary_optimization:
      enabled: true
      population_size: 100
      mutation_rate: 0.1
      crossover_rate: 0.8
      generations: 1000
      selection_method: "tournament"
    
    p2p_networking:
      enabled: false  # Disabled by default for security
      port: 8080
      max_peers: 50
      sync_interval: 10.0
      encryption: true

training:
  # Training hyperparameters
  learning_rate: 1e-4
  batch_size: 32
  gradient_accumulation_steps: 4
  max_epochs: 10
  warmup_steps: 1000
  weight_decay: 0.01
  adam_epsilon: 1e-8
  max_grad_norm: 1.0
  
  # Holographic training specific
  holographic_learning_rate: 5e-5
  quantum_adaptation_rate: 1e-5
  optical_convergence_threshold: 1e-6
  
  # Checkpointing
  save_steps: 1000
  eval_steps: 500
  logging_steps: 100
  save_total_limit: 3
  
  # Data
  train_dataset: null
  eval_dataset: null
  max_seq_length: 2048
  preprocessing_num_workers: 4

evaluation:
  # Benchmark configurations
  benchmarks:
    mmlu:
      enabled: true
      num_samples: 1000
      batch_size: 8
      subjects: ["all"]
    
    gsm8k:
      enabled: true
      num_samples: 500
      batch_size: 4
      chain_of_thought: true
    
    hellaswag:
      enabled: true
      num_samples: 1000
      batch_size: 8
    
    arc:
      enabled: true
      num_samples: 500
      batch_size: 8
      challenge_set: true
    
    humaneval:
      enabled: false  # Resource intensive
      num_samples: 164
      batch_size: 1
      temperature: 0.2
  
  # Evaluation metrics
  metrics:
    standard: ["accuracy", "f1", "precision", "recall"]
    holographic: ["coherence", "interference_score", "pattern_stability"]
    quantum: ["entanglement_depth", "superposition_utilization", "decoherence_rate"]
    optical: ["raytracing_efficiency", "coherence_length", "photon_utilization"]

hardware:
  # GPU configuration
  gpu:
    device: "cuda"
    mixed_precision: true
    compile_model: true
    memory_fraction: 0.8
    
  # CPU configuration  
  cpu:
    num_workers: 8
    pin_memory: true
    
  # Specialized hardware
  quantum_simulator:
    backend: "pennylane"
    device: "default.qubit"
    shots: 1024
  
  raytracing:
    use_rt_cores: true
    use_tensor_cores: true
    cuda_kernels: true

deployment:
  # Hugging Face Hub
  hub:
    model_name: "Agnuxo/NEBULA-X"
    organization: "Agnuxo"
    private: false
    push_to_hub: true
    create_model_card: true
    
  # API deployment
  api:
    host: "0.0.0.0"
    port: 8000
    workers: 4
    timeout: 300
    max_batch_size: 16
    
  # Container deployment
  container:
    base_image: "nvidia/cuda:12.2-devel-ubuntu22.04"
    python_version: "3.11"
    expose_port: 8000

logging:
  level: "INFO"
  format: "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
  file: "nebula_x.log"
  max_bytes: 10485760  # 10MB
  backup_count: 5
  
  # Weights & Biases integration
  wandb:
    enabled: false
    project: "nebula-x"
    entity: "agnuxo"
    tags: ["holographic", "quantum", "optical"]

---

# docker-compose.yml
# Docker Compose configuration for NEBULA-X deployment

version: '3.8'

services:
  nebula-x:
    build:
      context: .
      dockerfile: Dockerfile
      args:
        PYTHON_VERSION: 3.11
        CUDA_VERSION: 12.2
    
    container_name: nebula-x-model
    
    ports:
      - "8000:8000"
      - "8080:8080"  # P2P networking
    
    volumes:
      - ./models:/app/models
      - ./data:/app/data
      - ./logs:/app/logs
      - ./checkpoints:/app/checkpoints
    
    environment:
      - CUDA_VISIBLE_DEVICES=0
      - TOKENIZERS_PARALLELISM=false
      - PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:512
      - NEBULA_X_CONFIG_PATH=/app/config.yaml
      - NEBULA_X_LOG_LEVEL=INFO
    
    runtime: nvidia
    
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]
    
    depends_on:
      - redis
      - monitoring
    
    restart: unless-stopped
    
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 40s

  redis:
    image: redis:7-alpine
    container_name: nebula-x-redis
    ports:
      - "6379:6379"
    volumes:
      - redis_data:/data
    restart: unless-stopped

  monitoring:
    image: prom/prometheus:latest
    container_name: nebula-x-monitoring
    ports:
      - "9090:9090"
    volumes:
      - ./monitoring/prometheus.yml:/etc/prometheus/prometheus.yml
      - prometheus_data:/prometheus
    restart: unless-stopped

  gradio-demo:
    build:
      context: .
      dockerfile: Dockerfile.demo
    container_name: nebula-x-demo
    ports:
      - "7860:7860"
    environment:
      - NEBULA_X_API_URL=http://nebula-x:8000
    depends_on:
      - nebula-x
    restart: unless-stopped

volumes:
  redis_data:
  prometheus_data:

networks:
  default:
    name: nebula-x-network

---

# Dockerfile
# Multi-stage Dockerfile for NEBULA-X deployment

ARG PYTHON_VERSION=3.11
ARG CUDA_VERSION=12.2

# Base stage with CUDA support
FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04 AS base

# Install system dependencies
RUN apt-get update && apt-get install -y \
    python${PYTHON_VERSION} \
    python${PYTHON_VERSION}-dev \
    python3-pip \
    git \
    curl \
    wget \
    build-essential \
    cmake \
    ninja-build \
    libopenblas-dev \
    liblapack-dev \
    libeigen3-dev \
    libfftw3-dev \
    && rm -rf /var/lib/apt/lists/*

# Set Python as default
RUN ln -s /usr/bin/python${PYTHON_VERSION} /usr/bin/python
RUN ln -s /usr/bin/python${PYTHON_VERSION} /usr/bin/python3

# Upgrade pip
RUN python -m pip install --upgrade pip setuptools wheel

# Development stage
FROM base AS development

WORKDIR /app

# Copy requirements first for better Docker layer caching
COPY requirements.txt .
COPY requirements-dev.txt .

# Install Python dependencies
RUN pip install --no-cache-dir -r requirements.txt
RUN pip install --no-cache-dir -r requirements-dev.txt

# Copy source code
COPY . .

# Install NEBULA-X in development mode
RUN pip install -e .

# Production stage
FROM base AS production

WORKDIR /app

# Create non-root user for security
RUN groupadd -r nebulax && useradd -r -g nebulax nebulax

# Copy only production requirements
COPY requirements.txt .

# Install production dependencies
RUN pip install --no-cache-dir -r requirements.txt

# Copy application code
COPY --chown=nebulax:nebulax . .

# Install NEBULA-X
RUN pip install --no-cache-dir .

# Create necessary directories
RUN mkdir -p /app/models /app/data /app/logs /app/checkpoints && \
    chown -R nebulax:nebulax /app

# Switch to non-root user
USER nebulax

# Expose ports
EXPOSE 8000 8080

# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
    CMD curl -f http://localhost:8000/health || exit 1

# Default command
CMD ["python", "-m", "nebula_x.api.server", "--host", "0.0.0.0", "--port", "8000"]

---

# Dockerfile.demo
# Dockerfile for Gradio demo interface

FROM python:3.11-slim

WORKDIR /app

# Install system dependencies
RUN apt-get update && apt-get install -y \
    curl \
    && rm -rf /var/lib/apt/lists/*

# Copy requirements
COPY requirements-demo.txt .

# Install dependencies
RUN pip install --no-cache-dir -r requirements-demo.txt

# Copy demo files
COPY demos/ ./demos/
COPY config.yaml .

# Create non-root user
RUN groupadd -r demo && useradd -r -g demo demo
RUN chown -R demo:demo /app
USER demo

# Expose Gradio port
EXPOSE 7860

# Run demo
CMD ["python", "demos/gradio_interface.py"]

---

# .github/workflows/ci.yml
# GitHub Actions CI/CD pipeline

name: NEBULA-X CI/CD

on:
  push:
    branches: [ main, develop ]
  pull_request:
    branches: [ main ]
  release:
    types: [ published ]

env:
  PYTHON_VERSION: 3.11
  CUDA_VERSION: 12.2

jobs:
  test:
    runs-on: ubuntu-latest
    strategy:
      matrix:
        python-version: [3.9, 3.10, 3.11]
    
    steps:
    - uses: actions/checkout@v4
    
    - name: Set up Python ${{ matrix.python-version }}
      uses: actions/setup-python@v4
      with:
        python-version: ${{ matrix.python-version }}
    
    - name: Cache pip dependencies
      uses: actions/cache@v3
      with:
        path: ~/.cache/pip
        key: ${{ runner.os }}-pip-${{ hashFiles('requirements*.txt') }}
        restore-keys: |
          ${{ runner.os }}-pip-
    
    - name: Install dependencies
      run: |
        python -m pip install --upgrade pip
        pip install -r requirements.txt
        pip install -r requirements-test.txt
    
    - name: Lint with flake8
      run: |
        flake8 nebula_x/ --count --select=E9,F63,F7,F82 --show-source --statistics
        flake8 nebula_x/ --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
    
    - name: Type check with mypy
      run: |
        mypy nebula_x/
    
    - name: Test with pytest
      run: |
        pytest tests/ -v --cov=nebula_x --cov-report=xml
    
    - name: Upload coverage to Codecov
      uses: codecov/codecov-action@v3
      with:
        file: ./coverage.xml
        flags: unittests
        name: codecov-umbrella

  test-gpu:
    runs-on: [self-hosted, gpu]
    if: github.event_name == 'push' && github.ref == 'refs/heads/main'
    
    steps:
    - uses: actions/checkout@v4
    
    - name: Set up Python
      uses: actions/setup-python@v4
      with:
        python-version: ${{ env.PYTHON_VERSION }}
    
    - name: Install dependencies
      run: |
        python -m pip install --upgrade pip
        pip install -r requirements.txt
        pip install -r requirements-test.txt
    
    - name: Test GPU functionality
      run: |
        pytest tests/test_gpu/ -v -m gpu
    
    - name: Run benchmarks
      run: |
        python -m nebula_x.benchmarks.run_benchmarks --quick

  build-docker:
    runs-on: ubuntu-latest
    needs: test
    
    steps:
    - uses: actions/checkout@v4
    
    - name: Set up Docker Buildx
      uses: docker/setup-buildx-action@v3
    
    - name: Login to DockerHub
      if: github.event_name != 'pull_request'
      uses: docker/login-action@v3
      with:
        username: ${{ secrets.DOCKERHUB_USERNAME }}
        password: ${{ secrets.DOCKERHUB_TOKEN }}
    
    - name: Extract metadata
      id: meta
      uses: docker/metadata-action@v5
      with:
        images: agnuxo/nebula-x
        tags: |
          type=ref,event=branch
          type=ref,event=pr
          type=semver,pattern={{version}}
          type=semver,pattern={{major}}.{{minor}}
    
    - name: Build and push Docker image
      uses: docker/build-push-action@v5
      with:
        context: .
        target: production
        push: ${{ github.event_name != 'pull_request' }}
        tags: ${{ steps.meta.outputs.tags }}
        labels: ${{ steps.meta.outputs.labels }}
        cache-from: type=gha
        cache-to: type=gha,mode=max

  deploy-hub:
    runs-on: ubuntu-latest
    needs: [test, test-gpu]
    if: github.event_name == 'release'
    
    steps:
    - uses: actions/checkout@v4
    
    - name: Set up Python
      uses: actions/setup-python@v4
      with:
        python-version: ${{ env.PYTHON_VERSION }}
    
    - name: Install dependencies
      run: |
        python -m pip install --upgrade pip
        pip install -r requirements.txt
        pip install huggingface_hub
    
    - name: Deploy to Hugging Face Hub
      env:
        HF_TOKEN: ${{ secrets.HF_TOKEN }}
      run: |
        python scripts/deploy_to_hub.py \
          --model-name Agnuxo/NEBULA-X \
          --version ${{ github.ref_name }}

---

# .gitignore
# Git ignore file for NEBULA-X project

# Python
__pycache__/
*.py[cod]
*$py.class
*.so
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST

# PyTorch
*.pth
*.pt
*.bin
*.safetensors

# Jupyter Notebook
.ipynb_checkpoints

# IPython
profile_default/
ipython_config.py

# Virtual environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/

# IDE
.vscode/
.idea/
*.swp
*.swo
*~

# OS
.DS_Store
.DS_Store?
._*
.Spotlight-V100
.Trashes
ehthumbs.db
Thumbs.db

# Project specific
models/
checkpoints/
data/
logs/
outputs/
cache/
wandb/
benchmark_reports/
*.log

# Docker
.dockerignore

# Secrets
.env.local
.env.production
secrets.yaml
api_keys.txt

# Large files
*.h5
*.hdf5
*.pickle
*.pkl
*.npy
*.npz

# Temporary files
tmp/
temp/
.tmp/

# Coverage
.coverage
.pytest_cache/
htmlcov/
.tox/
.nox/
.coverage.*

# Documentation builds
docs/_build/
docs/build/
site/

---

# requirements-dev.txt
# Development dependencies

# Testing
pytest>=7.4.0
pytest-asyncio>=0.21.0
pytest-cov>=4.1.0
pytest-mock>=3.11.0
pytest-xdist>=3.3.0

# Code quality
black>=23.0.0
isort>=5.12.0
flake8>=6.0.0
mypy>=1.5.0
pre-commit>=3.3.0

# Documentation
sphinx>=7.1.0
sphinx-rtd-theme>=1.3.0
myst-parser>=2.0.0

# Debugging
ipdb>=0.13.0
pdb++>=0.10.0

# Profiling
line_profiler>=4.1.0
memory_profiler>=0.61.0

# Jupyter
jupyter>=1.0.0
jupyterlab>=4.0.0
ipywidgets>=8.0.0

---

# requirements-demo.txt
# Dependencies for demo applications

gradio>=3.39.0
streamlit>=1.25.0
fastapi>=0.100.0
uvicorn[standard]>=0.23.0
requests>=2.31.0
pillow>=10.0.0
matplotlib>=3.7.0
plotly>=5.15.0

---

# setup.py
# Setup configuration for NEBULA-X package

from setuptools import setup, find_packages
import os

# Read long description from README
with open("README.md", "r", encoding="utf-8") as fh:
    long_description = fh.read()

# Read requirements from requirements.txt
with open("requirements.txt", "r", encoding="utf-8") as fh:
    requirements = [line.strip() for line in fh if line.strip() and not line.startswith("#")]

setup(
    name="nebula-x",
    version="1.0.0",
    author="Francisco Angulo de Lafuente",
    author_email="[email protected]",
    description="Enhanced Unified Holographic Neural Network with Quantum Processing",
    long_description=long_description,
    long_description_content_type="text/markdown",
    url="https://github.com/Agnuxo1/NEBULA-X",
    packages=find_packages(exclude=["tests*", "docs*"]),
    classifiers=[
        "Development Status :: 4 - Beta",
        "Intended Audience :: Science/Research",
        "Intended Audience :: Developers",
        "License :: OSI Approved :: Apache Software License",
        "Operating System :: OS Independent",
        "Programming Language :: Python :: 3",
        "Programming Language :: Python :: 3.9",
        "Programming Language :: Python :: 3.10",
        "Programming Language :: Python :: 3.11",
        "Topic :: Scientific/Engineering :: Artificial Intelligence",
        "Topic :: Scientific/Engineering :: Physics",
        "Topic :: Software Development :: Libraries :: Python Modules",
    ],
    python_requires=">=3.9",
    install_requires=requirements,
    extras_require={
        "dev": [
            "pytest>=7.4.0",
            "black>=23.0.0",
            "flake8>=6.0.0",
            "mypy>=1.5.0",
        ],
        "docs": [
            "sphinx>=7.1.0",
            "sphinx-rtd-theme>=1.3.0",
        ],
        "demo": [
            "gradio>=3.39.0",
            "streamlit>=1.25.0",
        ],
    },
    entry_points={
        "console_scripts": [
            "nebula-x=nebula_x.cli:main",
            "nebula-x-benchmark=nebula_x.benchmarks.cli:main",
            "nebula-x-train=nebula_x.training.cli:main",
            "nebula-x-serve=nebula_x.api.server:main",
        ],
    },
    include_package_data=True,
    package_data={
        "nebula_x": [
            "config/*.yaml",
            "data/*.json",
            "templates/*.html",
        ],
    },
    keywords=[
        "artificial intelligence",
        "holographic neural networks", 
        "quantum computing",
        "optical computing",
        "transformer",
        "deep learning",
        "machine learning",
        "neural networks",
        "raytracing",
        "photonic computing",
    ],
    project_urls={
        "Bug Reports": "https://github.com/Agnuxo1/NEBULA-X/issues",
        "Source": "https://github.com/Agnuxo1/NEBULA-X",
        "Documentation": "https://nebula-x.readthedocs.io/",
        "Hugging Face": "https://huggingface.co/Agnuxo/NEBULA-X",
    },
)

---

# pyproject.toml
# Modern Python project configuration

[build-system]
requires = ["setuptools>=61.0", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "nebula-x"
version = "1.0.0"
description = "Enhanced Unified Holographic Neural Network with Quantum Processing"
readme = "README.md"
license = {text = "Apache-2.0"}
authors = [
    {name = "Francisco Angulo de Lafuente", email = "[email protected]"}
]
maintainers = [
    {name = "Francisco Angulo de Lafuente", email = "[email protected]"}
]
keywords = [
    "artificial intelligence",
    "holographic neural networks", 
    "quantum computing",
    "optical computing",
    "transformer",
    "deep learning"
]
classifiers = [
    "Development Status :: 4 - Beta",
    "Intended Audience :: Science/Research",
    "License :: OSI Approved :: Apache Software License",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.9",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
]
requires-python = ">=3.9"
dependencies = [
    "torch>=2.0.0",
    "transformers>=4.30.0",
    "datasets>=2.14.0",
    "huggingface_hub>=0.16.0",
    "numpy>=1.24.0",
    "scipy>=1.10.0",
    "pandas>=2.0.0",
    "pillow>=10.0.0",
    "pyyaml>=6.0",
    "tqdm>=4.65.0",
]

[project.optional-dependencies]
quantum = ["pennylane>=0.32.0"]
gpu = ["cupy-cuda12x>=12.0.0", "pycuda>=2022.2"]
viz = ["matplotlib>=3.7.0", "seaborn>=0.12.0", "plotly>=5.15.0"]
dev = [
    "pytest>=7.4.0",
    "black>=23.0.0",
    "isort>=5.12.0",
    "flake8>=6.0.0",
    "mypy>=1.5.0",
    "pre-commit>=3.3.0",
]
docs = [
    "sphinx>=7.1.0",
    "sphinx-rtd-theme>=1.3.0",
    "myst-parser>=2.0.0",
]
demo = [
    "gradio>=3.39.0",
    "streamlit>=1.25.0",
    "fastapi>=0.100.0",
    "uvicorn[standard]>=0.23.0",
]

[project.scripts]
nebula-x = "nebula_x.cli:main"
nebula-x-benchmark = "nebula_x.benchmarks.cli:main"
nebula-x-train = "nebula_x.training.cli:main"
nebula-x-serve = "nebula_x.api.server:main"

[project.urls]
Homepage = "https://github.com/Agnuxo1/NEBULA-X"
Repository = "https://github.com/Agnuxo1/NEBULA-X"
Documentation = "https://nebula-x.readthedocs.io/"
"Bug Tracker" = "https://github.com/Agnuxo1/NEBULA-X/issues"
"Hugging Face" = "https://huggingface.co/Agnuxo/NEBULA-X"

[tool.setuptools]
package-dir = {"" = "."}

[tool.setuptools.packages.find]
exclude = ["tests*", "docs*", "examples*"]

[tool.black]
line-length = 88
target-version = ['py39', 'py310', 'py311']
include = '\.pyi?$'
extend-exclude = '''
/(
  # directories
  \.eggs
  | \.git
  | \.hg
  | \.mypy_cache
  | \.tox
  | \.venv
  | build
  | dist
)/
'''

[tool.isort]
profile = "black"
multi_line_output = 3
line_length = 88
known_first_party = ["nebula_x"]

[tool.mypy]
python_version = "3.9"
warn_return_any = true
warn_unused_configs = true
disallow_untyped_defs = false
disallow_incomplete_defs = false
check_untyped_defs = true
disallow_untyped_decorators = false
no_implicit_optional = true
warn_redundant_casts = true
warn_unused_ignores = true
warn_no_return = true
warn_unreachable = true
strict_equality = true

[[tool.mypy.overrides]]
module = [
    "cupy.*",
    "pycuda.*", 
    "pennylane.*",
    "deap.*",
    "cv2.*",
]
ignore_missing_imports = true

[tool.pytest.ini_options]
testpaths = ["tests"]
python_files = ["test_*.py", "*_test.py"]
python_functions = ["test_*"]
python_classes = ["Test*"]
addopts = [
    "--strict-markers",
    "--strict-config", 
    "--verbose",
    "--tb=short",
    "--cov=nebula_x",
    "--cov-report=term-missing",
    "--cov-report=html",
    "--cov-report=xml",
]
markers = [
    "slow: marks tests as slow (deselect with '-m \"not slow\"')",
    "gpu: marks tests that require GPU",
    "quantum: marks tests that require quantum simulation",
    "integration: marks tests as integration tests",
    "benchmark: marks tests as benchmark tests",
]
filterwarnings = [
    "ignore::UserWarning",
    "ignore::DeprecationWarning",
]

[tool.coverage.run]
source = ["nebula_x"]
omit = [
    "*/tests/*",
    "*/test_*",
    "setup.py",
    "*/venv/*",
    "*/.venv/*",
]

[tool.coverage.report]
exclude_lines = [
    "pragma: no cover",
    "def __repr__",
    "if self.debug:",
    "if settings.DEBUG",
    "raise AssertionError",
    "raise NotImplementedError",
    "if 0:",
    "if __name__ == .__main__.:",
    "class .*\\bProtocol\\):",
    "@(abc\\.)?abstractmethod",
]

[tool.flake8]
max-line-length = 88
extend-ignore = ["E203", "E501", "W503"]
max-complexity = 15
exclude = [
    ".git",
    "__pycache__",
    "build",
    "dist",
    ".eggs",
    "*.egg-info",
    ".venv",
    "venv",
]