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hse-python-assistant
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v6

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Oleg Zakharov 2024-10-18 00:08:45 +03:00
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commit 32ae109f66
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{
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{
"cell_type": "code",
"execution_count": 3,
"id": "58e6167e-1e30-4bbf-93a1-af6ab5cb4673",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"\n",
"def preprocess_test(test_solutions_path: str, test_tasks_path: str, test_tests_path: str, save_path: str) -> None:\n",
" def read_files(*paths):\n",
" return (pd.read_excel(path) for path in paths)\n",
"\n",
" solutions_df, tasks_df, tests_df = read_files(test_solutions_path, test_tasks_path, test_tests_path)\n",
"\n",
" test_dataset = pd.merge(pd.merge(solutions_df, tasks_df, left_on='task_id', right_on='id', how='inner'), \n",
" tests_df, on='task_id', how='inner')\n",
"\n",
" test_dataset['input_output'] = test_dataset.apply(\n",
" lambda row: f\"{row['input']}->{row['output']}\" if pd.notna(row['input']) or pd.notna(row['output']) else \"\", \n",
" axis=1\n",
" )\n",
"\n",
" test_dataset = test_dataset[['id', 'student_solution', 'description', 'author_solution', 'input_output']]\n",
" test_dataset.to_excel(save_path, index=False)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "e561a852-007c-4b78-a7e1-697f80272169",
"metadata": {},
"outputs": [],
"source": [
"base = 'data/raw/test/{}'\n",
"\n",
"preprocess_test(base.format('solutions.xlsx'), base.format('tasks.xlsx'), base.format('tests.xlsx'), './test.xlsx')"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "2c15dbb7-1034-41a7-96be-69e2418bf98e",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 19,
"id": "d923d6c4-f962-4646-a041-999862bb3950",
"metadata": {},
"outputs": [],
"source": [
"preprocess_test(base.format('solutions.xlsx'), base.format('tasks.xlsx'), base.format('tests.xlsx'), './test2.xlsx')"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python [conda env:.conda-poetry]",
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"name": "conda-env-.conda-poetry-py"
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