{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "11b8593d-dea7-44e0-beee-c0c6ffea7d1a", "metadata": {}, "outputs": [], "source": [ "from pathlib import Path" ] }, { "cell_type": "code", "execution_count": 6, "id": "2b9388f3-c7e0-401d-8d0b-9ef43b78bd73", "metadata": {}, "outputs": [], "source": [ "work_dir = Path(__name__).resolve().parent.parent / \"src\"" ] }, { "cell_type": "code", "execution_count": 7, "id": "c0625c16-9e78-4525-aa84-2194480aaf0c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "WindowsPath('C:/dev/python/interview_eval_project/highmark_agentic_ai/src')" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "work_dir" ] }, { "cell_type": "code", "execution_count": 8, "id": "481c534a-5120-457c-8f5e-3dbb2a5f1c3d", "metadata": {}, "outputs": [], "source": [ "backend = work_dir / \"backend\"" ] }, { "cell_type": "code", "execution_count": 13, "id": "69c64859-7ad8-4e04-b974-ad54c8647bbf", "metadata": {}, "outputs": [], "source": [ "if backend.exists():\n", " for folder in (\"core\", \"db\", \"server\", \"settings\", \"site\"):\n", " directory = backend / folder\n", " if not directory.exists():\n", " directory.mkdir(exist_ok=True)\n", " for file in (\"__init__\", \"core\", \"main\", \"utils\", \"consts\"):\n", " file_path = directory / file\n", " # file_path.touch(exist_ok=True)\n", " file_path.unlink(missing_ok=True)" ] }, { "cell_type": "code", "execution_count": null, "id": "50e9ff3d-f23a-402d-8bad-5f7f821d6b84", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Pydantic Agent AI", "language": "python", "name": "agentic_ai" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.8" } }, "nbformat": 4, "nbformat_minor": 5 }