monte-carlo-sim / mcp_server /tests /test_prepare_data.py
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Setup Monte Carlo MCP Server with Git LFS
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import os
import pandas as pd
import pytest
from unittest.mock import patch, MagicMock
# Since the prepare_data script is not in a package, we need to add its directory to the path
import sys
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
from prepare_data import main as prepare_data_main
@pytest.fixture
def temp_data_dir(tmp_path):
"""Creates a temporary data directory structure for testing."""
mcp_server_dir = tmp_path / "mcp_server"
data_dir = mcp_server_dir / "data"
unzipped_dir = mcp_server_dir / "unzipped_data" / "barber-motorsports-park" / "barber"
unzipped_dir.mkdir(parents=True, exist_ok=True)
data_dir.mkdir(parents=True, exist_ok=True)
# Create a dummy analysis and telemetry file
analysis_data = {
'LAP_NUMBER': [1], 'LAP_TIME': ['1:30.5'], 'DRIVER_NUMBER': [1]
}
telemetry_data = {
'timestamp': [100], 'lap': [1], 'vehicle_id': [1],
'telemetry_name': ['speed'], 'telemetry_value': [150]
}
pd.DataFrame(analysis_data).to_csv(unzipped_dir / "Test_Analysis.csv", index=False, sep=';')
pd.DataFrame(telemetry_data).to_csv(unzipped_dir / "Test_Telemetry.csv", index=False)
return mcp_server_dir
@patch('prepare_data.download_and_move_files')
@patch('prepare_data.unzip_data')
@patch('prepare_data.parse_telemetry')
def test_prepare_data_main(mock_parse_telemetry, mock_unzip_data, mock_download_files, temp_data_dir):
"""Tests the main data preparation script."""
# Mock the functions that download and unzip data
mock_download_files.return_value = None
mock_unzip_data.return_value = None
# Mock the telemetry parser to return a simple DataFrame
mock_parsed_df = pd.DataFrame({'lap': [1], 'speed': [150]})
mock_parse_telemetry.return_value = mock_parsed_df
# We need to change the working directory so the script can find the data
original_cwd = os.getcwd()
os.chdir(temp_data_dir)
# Run the script
with patch('prepare_data.script_dir', '.'):
prepare_data_main()
# Check that the output CSV was created
output_csv_path = "unzipped_data/barber-motorsports-park/barber/data.csv"
assert os.path.exists(output_csv_path)
# Check the content of the CSV
result_df = pd.read_csv(output_csv_path)
pd.testing.assert_frame_equal(result_df, mock_parsed_df)
# Clean up
os.chdir(original_cwd)