gilles soulier
c6a8e8e83d
✨ Features: - Backend FastAPI complete (25 Python files) - 5 SQLAlchemy models (Device, HardwareSnapshot, Benchmark, Link, Document) - Pydantic schemas for validation - 4 API routers (benchmark, devices, links, docs) - Authentication with Bearer token - Automatic score calculation - File upload support - Frontend web interface (13 files) - 4 HTML pages (Dashboard, Devices, Device Detail, Settings) - 7 JavaScript modules - Monokai dark theme CSS - Responsive design - Complete CRUD operations - Client benchmark script (500+ lines Bash) - Hardware auto-detection - CPU, RAM, Disk, Network benchmarks - JSON payload generation - Robust error handling - Docker deployment - Optimized Dockerfile - docker-compose with 2 services - Persistent volumes - Environment variables - Documentation & Installation - Automated install.sh script - README, QUICKSTART, DEPLOYMENT guides - Complete API documentation - Project structure documentation 📊 Stats: - ~60 files created - ~5000 lines of code - Full MVP feature set implemented 🚀 Ready for production deployment! 🤖 Generated with Claude Code Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
74 lines
1.7 KiB
Python
74 lines
1.7 KiB
Python
"""
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Linux BenchTools - Scoring Utilities
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"""
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from app.core.config import settings
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def calculate_global_score(
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cpu_score: float = None,
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memory_score: float = None,
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disk_score: float = None,
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network_score: float = None,
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gpu_score: float = None
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) -> float:
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"""
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Calculate global score from component scores using configured weights.
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Returns:
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float: Global score (0-100)
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"""
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scores = []
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weights = []
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if cpu_score is not None:
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scores.append(cpu_score)
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weights.append(settings.SCORE_WEIGHT_CPU)
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if memory_score is not None:
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scores.append(memory_score)
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weights.append(settings.SCORE_WEIGHT_MEMORY)
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if disk_score is not None:
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scores.append(disk_score)
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weights.append(settings.SCORE_WEIGHT_DISK)
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if network_score is not None:
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scores.append(network_score)
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weights.append(settings.SCORE_WEIGHT_NETWORK)
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if gpu_score is not None:
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scores.append(gpu_score)
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weights.append(settings.SCORE_WEIGHT_GPU)
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if not scores:
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return 0.0
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# Normalize weights if not all components are present
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total_weight = sum(weights)
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if total_weight == 0:
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return 0.0
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# Calculate weighted average
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weighted_sum = sum(score * weight for score, weight in zip(scores, weights))
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global_score = weighted_sum / total_weight
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# Clamp to 0-100 range
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return max(0.0, min(100.0, global_score))
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def validate_score(score: float) -> bool:
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"""
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Validate that a score is within acceptable range.
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Args:
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score: Score value to validate
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Returns:
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bool: True if score is valid (0-100 or None)
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"""
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if score is None:
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return True
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return 0.0 <= score <= 100.0
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