| import subprocess | |
| import time | |
| import requests | |
| import unittest | |
| from app import find_top_differences_table | |
| class TestAppFunctions(unittest.TestCase): | |
| def setUp(self): | |
| # Assuming that you have a ResultDataProcessor class or equivalent that provides the data | |
| self.processor = ResultDataProcessor() | |
| self.data = self.processor.data # Assuming this gives you the DataFrame you need | |
| def test_find_top_differences_table_error(self): | |
| # replicating the error before fixing it | |
| filtered_data = self.data | |
| # Get the closest 5 models with unique indices | |
| closest_models_diffs = filtered_data['MMLU_average'].sub(filtered_data.loc[selected_model_name, 'MMLU_average']).abs() | |
| closest_models = closest_models_diffs.nsmallest(5, keep='first').index.drop_duplicates().tolist() | |
| exclude_columns=['Parameters'] | |
| # Run the problematic function without catching the TypeError | |
| top_differences_table, top_differences_tasks = find_top_differences_table( | |
| self.data, selected_model_name, closest_models, exclude_columns | |
| ) | |
| def test_streamlit_app_runs(): | |
| # Start the Streamlit app in a subprocess | |
| process = subprocess.Popen(["streamlit", "run", "app.py"], stdout=subprocess.PIPE, stderr=subprocess.PIPE) | |
| # Wait for a few seconds to give Streamlit time to start | |
| time.sleep(5) | |
| # Make a request to the Streamlit app's default URL to check that it's running | |
| response = requests.get('http://localhost:8501') | |
| # Terminate the process | |
| process.terminate() | |
| # Check that the response from the Streamlit app was successful | |
| assert response.status_code == 200, "Streamlit app did not start successfully" | |
| if __name__ == '__main__': | |
| unittest.main() | |