Lars
c79cc9eafb
- Add data_layer/ module structure with utils.py + body_metrics.py - Migrate 3 functions: weight_trend, body_composition, circumference_summary - Refactor placeholders to use data layer - Add charts router with 3 Chart.js endpoints - Tests: Syntax ✅, Confidence logic ✅ Phase 0c PoC (3 functions): Foundation for 40+ remaining functions Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
52 lines
1.4 KiB
Python
52 lines
1.4 KiB
Python
"""
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Data Layer - Pure Data Retrieval & Calculation Logic
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This module provides structured data functions for all metrics.
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NO FORMATTING. NO STRINGS WITH UNITS. Only structured data.
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Usage:
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from data_layer.body_metrics import get_weight_trend_data
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data = get_weight_trend_data(profile_id="123", days=28)
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# Returns: {"slope_28d": 0.23, "confidence": "high", ...}
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Modules:
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- body_metrics: Weight, body fat, lean mass, circumferences
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- nutrition_metrics: Calories, protein, macros, adherence
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- activity_metrics: Training volume, quality, abilities
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- recovery_metrics: Sleep, RHR, HRV, recovery score
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- health_metrics: Blood pressure, VO2Max, health stability
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- goals: Active goals, progress, projections
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- correlations: Lag-analysis, plateau detection
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- utils: Shared functions (confidence, baseline, outliers)
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Phase 0c: Multi-Layer Architecture
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Version: 1.0
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Created: 2026-03-28
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"""
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# Core utilities
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from .utils import *
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# Metric modules
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from .body_metrics import *
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# Future imports (will be added as modules are created):
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# from .nutrition_metrics import *
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# from .activity_metrics import *
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# from .recovery_metrics import *
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# from .health_metrics import *
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# from .goals import *
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# from .correlations import *
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__all__ = [
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# Utils
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'calculate_confidence',
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'serialize_dates',
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# Body Metrics
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'get_weight_trend_data',
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'get_body_composition_data',
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'get_circumference_summary_data',
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]
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