{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 工具类\n",
    "## 生成随机数，用于图片文件名"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "G8hjNFEt.png\n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "import string\n",
    "\n",
    "def generate_random_filename(extension=\"png\", length=8):\n",
    "    characters = string.ascii_letters + string.digits\n",
    "    random_string = ''.join(random.choices(characters, k=length))\n",
    "    return f\"{random_string}.{extension}\"\n",
    "\n",
    "# 示例使用\n",
    "print(generate_random_filename())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 生成 argon2 密码"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hashed password: $argon2id$v=19$m=65536,t=3,p=4$lFZ6NGOPLXGAjO7u3B+6kw$wvkNArNX7DGsmqHANJ+ah1ggPm/F8tdKURSYx3vaDwg\n",
      "Password is valid: True\n"
     ]
    }
   ],
   "source": [
    "# 安装 argon2-cffi 库\n",
    "# 在终端中运行以下命令\n",
    "# pip install argon2-cffi\n",
    "\n",
    "from argon2 import PasswordHasher\n",
    "\n",
    "# 创建一个 PasswordHasher 实例\n",
    "ph = PasswordHasher()\n",
    "\n",
    "def hash_password(password):\n",
    "    \"\"\"\n",
    "    使用 argon2 哈希密码\n",
    "    :param password: 原始密码\n",
    "    :return: 哈希后的密码\n",
    "    \"\"\"\n",
    "    return ph.hash(password)\n",
    "\n",
    "def verify_password(hashed_password, password):\n",
    "    \"\"\"\n",
    "    验证密码是否匹配\n",
    "    :param hashed_password: 哈希后的密码\n",
    "    :param password: 原始密码\n",
    "    :return: 是否匹配\n",
    "    \"\"\"\n",
    "    try:\n",
    "        ph.verify(hashed_password, password)\n",
    "        return True\n",
    "    except:\n",
    "        return False\n",
    "\n",
    "# 示例用法\n",
    "if __name__ == \"__main__\":\n",
    "    original_password = \"my_secure_password\"\n",
    "    hashed = hash_password(original_password)\n",
    "    print(f\"Hashed password: {hashed}\")\n",
    "\n",
    "    is_valid = verify_password(hashed, original_password)\n",
    "    print(f\"Password is valid: {is_valid}\")    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 将Word文字提取为Txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'docx'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[2], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mdocx\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Document\n\u001b[0;32m      3\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mextract_text_from_docx\u001b[39m(docx_path, txt_path):\n\u001b[0;32m      4\u001b[0m     \u001b[38;5;66;03m# 打开Word文档\u001b[39;00m\n\u001b[0;32m      6\u001b[0m     doc \u001b[38;5;241m=\u001b[39m Document(docx_path)\n",
      "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'docx'"
     ]
    }
   ],
   "source": [
    "from docx import Document\n",
    "\n",
    "def extract_text_from_docx(docx_path, txt_path):\n",
    "    # 打开Word文档\n",
    "    \n",
    "    doc = Document(docx_path)\n",
    "    \n",
    "    # 提取所有段落的文字\n",
    "    full_text = []\n",
    "    for para in doc.paragraphs:\n",
    "        full_text.append(para.text)\n",
    "    \n",
    "    # 将文字写入txt文件\n",
    "    with open(txt_path, 'w', encoding='utf-8') as txt_file:\n",
    "        txt_file.write('\\n'.join(full_text))\n",
    "\n",
    "# 示例用法\n",
    "docx_path = 'example.docx'  # 替换为你的Word文档路径\n",
    "txt_path = 'output.txt'     # 替换为你想要保存的txt文件路径\n",
    "extract_text_from_docx(docx_path, txt_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 将 Markdown 转为 Word"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pypandoc in c:\\users\\wangq\\miniconda3\\envs\\local_p312\\lib\\site-packages (1.13)\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "转换成功: C:\\Users\\wangq\\OneDrive\\Wantsong.Life\\Work\\生产管理系统\\数字化转型下的智慧电厂建设.docx\n"
     ]
    }
   ],
   "source": [
    "%pip install pypandoc\n",
    "import pypandoc\n",
    "\n",
    "def convert_md_to_docx(md_file, output_file, css_file=None):\n",
    "    extra_args = []\n",
    "    if css_file:\n",
    "        extra_args = ['--css', css_file]\n",
    "    output = pypandoc.convert_file(md_file, 'docx', outputfile=output_file, extra_args=extra_args)\n",
    "    assert output == \"\"\n",
    "    print(f\"转换成功: {output_file}\")\n",
    "\n",
    "# 示例使用\n",
    "#convert_md_to_docx(r'C:\\Users\\wangq\\OneDrive\\Wantsong.Life\\Work\\生产管理系统\\数字化转型下的智慧电厂建设.md', r'C:\\Users\\wangq\\OneDrive\\Wantsong.Life\\Work\\生产管理系统\\数字化转型下的智慧电厂建设.docx')\n",
    "\n",
    "# 示例使用\n",
    "convert_md_to_docx(\n",
    "    r'C:\\Users\\wangq\\OneDrive\\Wantsong.Life\\Work\\生产管理系统\\数字化转型下的智慧电厂建设.md',\n",
    "    r'C:\\Users\\wangq\\OneDrive\\Wantsong.Life\\Work\\生产管理系统\\数字化转型下的智慧电厂建设.docx',\n",
    "    r'C:\\Users\\wangq\\OneDrive\\Wantsong.Life\\Work\\md2word.css'\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Markdown 转为 PDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "转换成功: C:\\Users\\wangq\\OneDrive\\Wantsong.Life\\Work\\生产管理系统\\数字化转型下的智慧电厂建设.pdf\n"
     ]
    }
   ],
   "source": [
    "import pypandoc\n",
    "\n",
    "def convert_md_to_pdf(md_file, output_file):\n",
    "    output = pypandoc.convert_file(md_file, 'pdf', outputfile=output_file, extra_args=['--pdf-engine=xelatex'])\n",
    "    assert output == \"\"\n",
    "    print(f\"转换成功: {output_file}\")\n",
    "\n",
    "# 示例使用\n",
    "convert_md_to_pdf(r'C:\\Users\\wangq\\OneDrive\\Wantsong.Life\\Work\\生产管理系统\\数字化转型下的智慧电厂建设.md', r'C:\\Users\\wangq\\OneDrive\\Wantsong.Life\\Work\\生产管理系统\\数字化转型下的智慧电厂建设.pdf')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## SVG 转为 PNG"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cairosvg\n",
    "\n",
    "def convert_svg_to_png(input_svg_path, output_png_path):\n",
    "    cairosvg.svg2png(url=input_svg_path, write_to=output_png_path)\n",
    "\n",
    "# 示例调用\n",
    "convert_svg_to_png(r'C:\\Users\\wangq\\OneDrive\\Wantsong.Life\\Note\\Prompts\\汉语新解\\教师.svg', r'C:\\Users\\wangq\\OneDrive\\Wantsong.Life\\Note\\Prompts\\汉语新解\\教师.png')\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "local_p312",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}