mirror of
https://github.com/sstent/FitTrack_ReportGenerator.git
synced 2026-01-26 00:52:03 +00:00
sstent
9e0bd322d3
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.
51 lines
2.0 KiB
Python
51 lines
2.0 KiB
Python
import pytest
|
|
from unittest.mock import MagicMock, patch
|
|
from src.core.file_parser import FitParser, WorkoutData, WorkoutMetadata, PowerData, HeartRateData, SpeedData, ElevationData
|
|
from datetime import datetime, timedelta
|
|
import pandas as pd
|
|
|
|
@pytest.fixture
|
|
def mock_fit_file():
|
|
with patch('fitparse.FitFile') as mock_fit_file_class:
|
|
mock_fit_file_instance = MagicMock()
|
|
mock_fit_file_class.return_value = mock_fit_file_instance
|
|
|
|
# Mocking get_messages to return some dummy records
|
|
mock_record1 = MagicMock()
|
|
mock_record1.as_dict.return_value = {
|
|
'timestamp': datetime(2023, 1, 1, 10, 0, 0),
|
|
'power': 150,
|
|
'heart_rate': 130,
|
|
'speed': 5.0,
|
|
'altitude': 100.0
|
|
}
|
|
mock_record2 = MagicMock()
|
|
mock_record2.as_dict.return_value = {
|
|
'timestamp': datetime(2023, 1, 1, 10, 1, 0),
|
|
'power': 160,
|
|
'heart_rate': 135,
|
|
'speed': 5.5,
|
|
'altitude': 105.0
|
|
}
|
|
mock_fit_file_instance.get_messages.return_value = [mock_record1, mock_record2]
|
|
yield mock_fit_file_class
|
|
|
|
def test_fit_parser_initialization():
|
|
parser = FitParser("dummy.fit")
|
|
assert parser.file_path == "dummy.fit"
|
|
|
|
def test_fit_parser_parse_method_returns_workout_data(mock_fit_file):
|
|
parser = FitParser("dummy.fit")
|
|
workout_data = parser.parse()
|
|
|
|
assert isinstance(workout_data, WorkoutData)
|
|
assert isinstance(workout_data.metadata, WorkoutMetadata)
|
|
assert workout_data.metadata.file_type == "FIT"
|
|
assert isinstance(workout_data.time_series_data, pd.DataFrame)
|
|
assert not workout_data.time_series_data.empty
|
|
assert "power" in workout_data.time_series_data.columns
|
|
assert "heart_rate" in workout_data.time_series_data.columns
|
|
assert "speed" in workout_data.time_series_data.columns
|
|
assert "altitude" in workout_data.time_series_data.columns
|
|
assert workout_data.metadata.start_time == datetime(2023, 1, 1, 10, 0, 0)
|
|
assert workout_data.metadata.duration == timedelta(minutes=1) |