feat: Initial implementation of FitTrack Report Generator

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.

tests/unit/test_chart_generator.py

@@ -0,0 +1,103 @@
+import pytest
+import pandas as pd
+from datetime import datetime, timedelta
+from src.core.workout_data import WorkoutData, WorkoutMetadata, PowerData, HeartRateData, SpeedData, ElevationData
+from src.core.chart_generator import ChartGenerator
+
+@pytest.fixture
+def sample_workout_data():
+    # Create dummy time-series data
+    timestamps = pd.to_datetime([datetime(2025, 1, 1, 10, 0, 0) + timedelta(seconds=i) for i in range(600)])
+    power = pd.Series([150 + 50 * (i % 10) for i in range(600)], index=timestamps)
+    heart_rate = pd.Series([120 + 10 * (i % 5) for i in range(600)], index=timestamps)
+    speed = pd.Series([5 + 2 * (i % 7) for i in range(600)], index=timestamps)
+    altitude = pd.Series([100 + 10 * (i % 12) for i in range(600)], index=timestamps)
+
+    time_series_data = pd.DataFrame({
+        "power": power,
+        "heart_rate": heart_rate,
+        "speed": speed,
+        "altitude": altitude
+    })
+
+    metadata = WorkoutMetadata(
+        start_time=datetime(2025, 1, 1, 10, 0, 0),
+        duration=timedelta(minutes=10),
+        device="Garmin",
+        file_type="FIT"
+    )
+
+    power_data = PowerData(
+        raw_power_stream=power.tolist(),
+        average_power=power.mean(),
+        normalized_power=power.mean() * 1.05, # Dummy value
+        intensity_factor=0.8,
+        training_stress_score=50,
+        zone_distribution={'Z1': 100, 'Z2': 200, 'Z3': 300}
+    )
+
+    heart_rate_data = HeartRateData(
+        raw_hr_stream=heart_rate.tolist(),
+        average_hr=heart_rate.mean(),
+        max_hr=heart_rate.max(),
+        zone_distribution={'Z1': 150, 'Z2': 250, 'Z3': 200}
+    )
+
+    speed_data = SpeedData(
+        raw_speed_stream=speed.tolist(),
+        average_speed=speed.mean(),
+        max_speed=speed.max(),
+        zone_distribution={'S1': 100, 'S2': 200, 'S3': 300}
+    )
+
+    elevation_data = ElevationData(
+        raw_elevation_stream=altitude.tolist(),
+        total_ascent=100,
+        total_descent=50,
+        max_elevation=200,
+        min_elevation=50
+    )
+
+    return WorkoutData(
+        metadata=metadata,
+        time_series_data=time_series_data,
+        power_data=power_data,
+        heart_rate_data=heart_rate_data,
+        speed_data=speed_data,
+        elevation_data=elevation_data
+    )
+
+def test_generate_power_curve_chart(sample_workout_data, tmp_path):
+    chart_generator = ChartGenerator(sample_workout_data)
+    output_file = tmp_path / "power_curve.png"
+    chart_generator.generate_power_curve_chart(output_file)
+    assert output_file.exists()
+    assert output_file.stat().st_size > 0
+
+def test_generate_elevation_profile_chart(sample_workout_data, tmp_path):
+    chart_generator = ChartGenerator(sample_workout_data)
+    output_file = tmp_path / "elevation_profile.png"
+    chart_generator.generate_elevation_profile_chart(output_file)
+    assert output_file.exists()
+    assert output_file.stat().st_size > 0
+
+def test_generate_power_zone_distribution_chart(sample_workout_data, tmp_path):
+    chart_generator = ChartGenerator(sample_workout_data)
+    output_file = tmp_path / "power_zone_distribution.png"
+    chart_generator.generate_zone_distribution_chart("power", output_file)
+    assert output_file.exists()
+    assert output_file.stat().st_size > 0
+
+def test_generate_hr_zone_distribution_chart(sample_workout_data, tmp_path):
+    chart_generator = ChartGenerator(sample_workout_data)
+    output_file = tmp_path / "hr_zone_distribution.png"
+    chart_generator.generate_zone_distribution_chart("heart_rate", output_file)
+    assert output_file.exists()
+    assert output_file.stat().st_size > 0
+
+def test_generate_speed_zone_distribution_chart(sample_workout_data, tmp_path):
+    chart_generator = ChartGenerator(sample_workout_data)
+    output_file = tmp_path / "speed_zone_distribution.png"
+    chart_generator.generate_zone_distribution_chart("speed", output_file)
+    assert output_file.exists()
+    assert output_file.stat().st_size > 0