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https://github.com/sstent/FitTrack_GarminSync.git
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feat: Add files from examples/Garmin_Analyser
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156
examples/Garmin_Analyser/config/settings.py
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156
examples/Garmin_Analyser/config/settings.py
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"""Configuration settings for Garmin Analyser."""
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import os
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import logging
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from pathlib import Path
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from typing import Dict, Tuple
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from dotenv import load_dotenv
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# Load environment variables
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load_dotenv()
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# Logger for this module
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logger = logging.getLogger(__name__)
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# Base paths
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BASE_DIR = Path(__file__).parent.parent
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DATA_DIR = BASE_DIR / "data"
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REPORTS_DIR = BASE_DIR / "reports"
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# Database settings
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DB_PATH = BASE_DIR / "garmin_analyser.db"
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DATABASE_URL = f"sqlite:///{DB_PATH}"
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# Create directories if they don't exist
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DATA_DIR.mkdir(exist_ok=True)
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REPORTS_DIR.mkdir(exist_ok=True)
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# Garmin Connect credentials
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GARMIN_EMAIL = os.getenv("GARMIN_EMAIL")
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GARMIN_PASSWORD = os.getenv("GARMIN_PASSWORD")
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# Flag to ensure deprecation warning is logged only once per process
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_deprecation_warned = False
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def get_garmin_credentials() -> Tuple[str, str]:
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"""Get Garmin Connect credentials from environment variables.
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Prefers GARMIN_EMAIL and GARMIN_PASSWORD. If GARMIN_EMAIL is not set
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but GARMIN_USERNAME is present, uses GARMIN_USERNAME as email with a
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one-time deprecation warning.
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Returns:
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Tuple of (email, password)
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Raises:
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ValueError: If required credentials are not found
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"""
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global _deprecation_warned
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email = os.getenv("GARMIN_EMAIL")
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password = os.getenv("GARMIN_PASSWORD")
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if email and password:
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return email, password
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# Fallback to GARMIN_USERNAME
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username = os.getenv("GARMIN_USERNAME")
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if username and password:
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if not _deprecation_warned:
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logger.warning(
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"GARMIN_USERNAME is deprecated. Please use GARMIN_EMAIL instead. "
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"GARMIN_USERNAME will be removed in a future version."
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)
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_deprecation_warned = True
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return username, password
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raise ValueError(
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"Garmin credentials not found. Set GARMIN_EMAIL and GARMIN_PASSWORD "
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"environment variables."
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)
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# Bike specifications
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class BikeConfig:
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"""Bike configuration constants."""
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# Valid gear configurations
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VALID_CONFIGURATIONS: Dict[int, list] = {
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38: [14, 16, 18, 20],
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46: [16]
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}
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# Default bike specifications
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DEFAULT_CHAINRING_TEETH = 38
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BIKE_WEIGHT_LBS = 22
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BIKE_WEIGHT_KG = BIKE_WEIGHT_LBS * 0.453592
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# Wheel specifications (700x25c)
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WHEEL_CIRCUMFERENCE_MM = 2111 # 700x25c wheel circumference
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WHEEL_CIRCUMFERENCE_M = WHEEL_CIRCUMFERENCE_MM / 1000
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TIRE_CIRCUMFERENCE_M = WHEEL_CIRCUMFERENCE_M # Alias for gear estimation
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# Physics-based power estimation constants
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BIKE_MASS_KG = 75.0 # Total bike + rider mass in kg
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BIKE_CRR = 0.004 # Rolling resistance coefficient
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BIKE_CDA = 0.3 # Aerodynamic drag coefficient * frontal area (m²)
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AIR_DENSITY = 1.225 # Air density in kg/m³
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DRIVE_EFFICIENCY = 0.97 # Drive train efficiency
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# Analysis toggles and caps
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INDOOR_AERO_DISABLED = True # Disable aerodynamic term for indoor workouts
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INDOOR_BASELINE_WATTS = 10.0 # Baseline power for indoor when stationary
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POWER_ESTIMATE_SMOOTHING_WINDOW_SAMPLES = 3 # Smoothing window for power estimates
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MAX_POWER_WATTS = 1500 # Maximum allowed power estimate to cap spikes
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# Legacy constants (kept for compatibility)
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AERO_CDA_BASE = 0.324 # Base aerodynamic drag coefficient * frontal area (m²)
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ROLLING_RESISTANCE_BASE = 0.0063 # Base rolling resistance coefficient
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EFFICIENCY = 0.97 # Drive train efficiency
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MECHANICAL_LOSS_COEFF = 5.0 # Mechanical losses in watts
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INDOOR_BASE_RESISTANCE = 0.02 # Base grade equivalent for indoor bikes
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INDOOR_CADENCE_THRESHOLD = 80 # RPM threshold for increased indoor resistance
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# Gear ratios
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GEAR_RATIOS = {
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38: {
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14: 38/14,
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16: 38/16,
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18: 38/18,
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20: 38/20
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},
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46: {
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16: 46/16
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}
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}
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# Indoor activity detection
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INDOOR_KEYWORDS = [
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'indoor_cycling', 'indoor cycling', 'indoor bike',
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'trainer', 'zwift', 'virtual'
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]
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# File type detection
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SUPPORTED_FORMATS = ['.fit', '.tcx', '.gpx']
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# Logging configuration
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LOG_LEVEL = os.getenv("LOG_LEVEL", "INFO")
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LOG_FORMAT = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
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# Report generation
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REPORT_TEMPLATE_DIR = BASE_DIR / "reports" / "templates"
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DEFAULT_REPORT_FORMAT = "markdown"
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CHART_DPI = 300
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CHART_FORMAT = "png"
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# Data processing
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SMOOTHING_WINDOW = 10 # meters for gradient smoothing
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MIN_WORKOUT_DURATION = 300 # seconds (5 minutes)
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MAX_POWER_ESTIMATE = 1000 # watts
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# User-specific settings (can be overridden via CLI or environment)
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FTP = int(os.getenv("FTP", "250")) # Functional Threshold Power in watts
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MAX_HEART_RATE = int(os.getenv("MAX_HEART_RATE", "185")) # Maximum heart rate in bpm
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COG_SIZE = int(os.getenv("COG_SIZE", str(BikeConfig.DEFAULT_CHAINRING_TEETH))) # Chainring teeth
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# Zones configuration
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ZONES_FILE = BASE_DIR / "config" / "zones.json"
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