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This commit introduces the initial version of the FitTrack Report Generator, a FastAPI application for analyzing workout files. Key features include: - Parsing of FIT, TCX, and GPX workout files. - Analysis of power, heart rate, speed, and elevation data. - Generation of summary reports and charts. - REST API for single and batch workout analysis. The project structure has been set up with a `src` directory for core logic, an `api` directory for the FastAPI application, and a `tests` directory for unit, integration, and contract tests. The development workflow is configured to use Docker and modern Python tooling.
66 lines
3.2 KiB
Markdown
66 lines
3.2 KiB
Markdown
# Data Model
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## Entities
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### User
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- **Description**: Represents a user of the system, primarily for storing personalized settings.
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- **Fields**:
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- `id`: Unique identifier (e.g., UUID)
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- `ftp_value`: Configured Functional Threshold Power (float, nullable, default value if null)
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- **Relationships**: One-to-many with `WorkoutAnalysis` (a user can have multiple analyses).
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- **Validation Rules**: `ftp_value` must be a positive number if set.
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### WorkoutAnalysis
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- **Description**: Represents the result of analyzing a single workout file. This entity links a user to their analyzed workout data.
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- **Fields**:
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- `id`: Unique identifier (e.g., UUID)
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- `user_id`: Foreign key to `User.id`
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- `file_name`: Original name of the workout file (string)
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- `analysis_date`: Timestamp of when the analysis was performed (datetime)
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- `status`: Status of the analysis (e.g., 'completed', 'failed', 'processing')
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- `summary_metrics`: JSONB field for storing overall workout summary metrics (e.g., total distance, duration, average speed, etc.)
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- `report_path`: Path to the generated report (string)
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- `chart_paths`: JSONB field for storing paths to generated charts (e.g., `{'power_curve': '/path/to/chart.png'}`)
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- **Relationships**: Many-to-one with `User`.
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### WorkoutData (Conceptual/In-Memory Structure)
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- **Description**: Represents the complete raw and processed data for a single workout session. This is primarily an in-memory object during analysis and its key components are persisted in `WorkoutAnalysis`.
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- **Fields**:
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- `metadata`: `WorkoutMetadata` object
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- `time_series_data`: Pandas DataFrame containing raw time-series data (e.g., timestamp, power, heart rate, speed, elevation)
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- `power_data`: `PowerData` object
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- `heart_rate_data`: `HeartRateData` object
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- `speed_data`: `SpeedData` object (derived from time-series)
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- `elevation_data`: `ElevationData` object (derived from time-series)
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### WorkoutMetadata
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- **Description**: Metadata extracted from the workout file.
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- **Fields**:
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- `start_time`: Datetime of workout start
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- `duration`: Total duration (timedelta or seconds)
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- `device`: Device used for recording (string)
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- `file_type`: Original file type (e.g., 'FIT', 'TCX', 'GPX')
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### PowerData
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- **Description**: Contains all power-related analysis results.
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- **Fields**:
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- `raw_power_stream`: List of power values
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- `average_power`: Float
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- `normalized_power`: Float
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- `intensity_factor`: Float
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- `training_stress_score`: Float
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- `zone_distribution`: Dictionary/JSONB of time spent in each power zone
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### HeartRateData
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- **Description**: Contains all heart-rate-related analysis results.
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- **Fields**:
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- `raw_hr_stream`: List of heart rate values
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- `average_hr`: Float
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- `max_hr`: Integer
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- `zone_distribution`: Dictionary/JSONB of time spent in each heart rate zone
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### ZoneCalculator (Utility)
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- **Description**: A utility class/module for defining and calculating training zones based on user-specific thresholds (like FTP) or default values.
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- **Fields**: (Methods for calculation, not data fields)
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- `calculate_power_zones(ftp, max_power)`
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- `calculate_heart_rate_zones(max_hr)` |