{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Item(name='iPhone', price=0, number=0, categories=[Category(name='', level=1)])"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import typing as t\n",
    "\n",
    "from pydantic import BaseModel\n",
    "\n",
    "\n",
    "class Category(BaseModel):\n",
    "    name: str = \"\"\n",
    "    level: int = 1\n",
    "\n",
    "\n",
    "class Item(BaseModel):\n",
    "    name: str\n",
    "    price: t.Union[int, float] = 0\n",
    "    number: int = 0\n",
    "    categories: t.List[Category] = [Category()]\n",
    "\n",
    "\n",
    "Item(name=\"iPhone\")\n",
    "Item(name='iPhone', price=0, number=0, categories=[Category(name='', level=1)])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 额外的类型注解"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pydantic import BaseModel, FilePath, HttpUrl, IPvAnyAddress, PostgresDsn\n",
    "from pydantic.color import Color\n",
    "\n",
    "class FileSystem(BaseModel):\n",
    "    path: FilePath\n",
    "\n",
    "\n",
    "class Link(BaseModel):\n",
    "    url: HttpUrl\n",
    "\n",
    "\n",
    "class Network(BaseModel):\n",
    "    ip: IPvAnyAddress\n",
    "\n",
    "\n",
    "class PostgreDatabase(BaseModel):\n",
    "    dsn: PostgresDsn\n",
    "\n",
    "\n",
    "class WebColor(BaseModel):\n",
    "    value: Color"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Item(name='iphone', number=0)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pydantic import constr, conint\n",
    "\n",
    "class Item(BaseModel):\n",
    "    name: constr(strip_whitespace=True, min_length=2, max_length=10)\n",
    "    number: conint(ge=0) = 0\n",
    "\n",
    "\n",
    "Item(name=\" iphone             \")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Item(name=\"iPhone\", number=-1)  # raise ValidationError here!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据校验"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import typing as t\n",
    "from dataclasses import dataclass\n",
    "from pydantic import BaseModel, validator\n",
    "\n",
    "@dataclass\n",
    "class Category:\n",
    "    level: int = 1\n",
    "    name: str = \"\"\n",
    "\n",
    "class Item(BaseModel):\n",
    "    name: str\n",
    "    price: t.Union[int, float] = 0\n",
    "    number: int = 0\n",
    "    categories: t.List[Category] = [Category()]\n",
    "\n",
    "\n",
    "    @validator(\"price\", \"number\")\n",
    "    def prevent_negative_number(cls, v):\n",
    "        if v < 0:\n",
    "            raise ValueError(\"can't set a negative number\")\n",
    "        return v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Item(name=\"iPhone\", price=-1)  # raise ValidationError here!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import typing as t\n",
    "from dataclasses import field\n",
    "\n",
    "from pydantic import validator\n",
    "from pydantic.dataclasses import dataclass  # <-- use pydantic.dataclasses.dataclass\n",
    "\n",
    "\n",
    "@dataclass\n",
    "class Category:\n",
    "    name: str = \"\"\n",
    "    level: int = 1\n",
    "\n",
    "\n",
    "def default_categories():\n",
    "    return [Category()]\n",
    "\n",
    "\n",
    "@dataclass\n",
    "class Item:\n",
    "    name: str\n",
    "    price: t.Union[int, float] = field(default=0)\n",
    "    number: int = field(default=0)\n",
    "    categories: t.List[Category] = field(default_factory=default_categories)\n",
    "\n",
    "    @validator(\"price\", \"number\")\n",
    "    def prevent_negative_number(cls, v):\n",
    "        if v < 0:\n",
    "            raise ValueError(\"can't set a negative number\")\n",
    "        return v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import typing as t\n",
    "\n",
    "from pydantic import BaseModel, validator\n",
    "from pydantic.dataclasses import dataclass\n",
    "\n",
    "\n",
    "@dataclass\n",
    "class Category:\n",
    "    name: str = \"\"\n",
    "    level: int = 1\n",
    "\n",
    "\n",
    "\n",
    "class ItemCode(str):\n",
    "    @classmethod\n",
    "    def __get_validators__(cls):\n",
    "        yield cls.validate\n",
    "\n",
    "    @classmethod\n",
    "    def validate(cls, v):\n",
    "        if not v.startswith(\"ITEM\"):\n",
    "            raise ValueError(\"invalid item code format\")\n",
    "        return v\n",
    "\n",
    "\n",
    "class Item(BaseModel):\n",
    "    name: str\n",
    "    itemcode: ItemCode\n",
    "    price: t.Union[int, float] = 0\n",
    "    number: int = 0\n",
    "    categories: t.List[Category] = [Category()]\n",
    "\n",
    "    @validator(\"price\", \"number\")\n",
    "    def prevent_negative_number(cls, v):\n",
    "        if v < 0:\n",
    "            raise ValueError(\"can't set a negative number\")\n",
    "        return v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Item(name='iPhone', itemcode='ITEM31415926', price=0, number=0, categories=[Category(name='', level=1)])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Item(name=\"iPhone\", itemcode=\"ITEM31415926\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Item(name=\"iPhone\", itemcode=\"aabbcc\")  # raise ValidationError here!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import typing as t\n",
    "\n",
    "from pydantic import BaseModel, validator\n",
    "from pydantic.dataclasses import dataclass\n",
    "\n",
    "\n",
    "class ItemValidator:\n",
    "    @classmethod\n",
    "    def prevent_negative_number(cls, v):\n",
    "        if v < 0:\n",
    "            raise ValueError(\"can't set a negative number\")\n",
    "        return v\n",
    "\n",
    "    @classmethod\n",
    "    def has_itemcode_preffix(cls, v: str):\n",
    "        if not v.startswith(\"ITEM\"):\n",
    "            raise ValueError(\"invalid item code format\")\n",
    "        return v\n",
    "\n",
    "\n",
    "@dataclass\n",
    "class Category:\n",
    "    name: str = \"\"\n",
    "    level: int = 1\n",
    "\n",
    "\n",
    "\n",
    "class Item(BaseModel):\n",
    "    name: str\n",
    "    itemcode: str\n",
    "    price: t.Union[int, float] = 0\n",
    "    number: int = 0\n",
    "    categories: t.List[Category] = [Category()]\n",
    "\n",
    "    check_number = validator(\"price\", \"number\")(ItemValidator.prevent_negative_number)\n",
    "    check_itemcode = validator(\"itemcode\")(ItemValidator.has_itemcode_preffix)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 导出数据类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import typing as t\n",
    "\n",
    "from pydantic import BaseModel\n",
    "\n",
    "\n",
    "class Category(BaseModel):\n",
    "    name: str = \"\"\n",
    "    level: int = 1\n",
    "\n",
    "\n",
    "class Item(BaseModel):\n",
    "    name: str\n",
    "    price: t.Union[int, float] = 0\n",
    "    number: int = 0\n",
    "    categories: t.List[Category] = [Category()]\n",
    "\n",
    "\n",
    "item = Item(\n",
    "    name=\"iPhone\",\n",
    "    price=6999,\n",
    "    number=1000,\n",
    "    categories=[Category(name=\"Phone\")],\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'name': 'iPhone',\n",
       " 'price': 6999,\n",
       " 'number': 1000,\n",
       " 'categories': [{'name': 'Phone', 'level': 1}]}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "item.dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'{\"name\": \"iPhone\", \"price\": 6999, \"number\": 1000, \"categories\": [{\"name\": \"Phone\", \"level\": 1}]}'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "item.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'name': 'iPhone',\n",
       " 'price': 6999,\n",
       " 'categories': [{'name': 'Phone', 'level': 1}]}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "item.dict(exclude={\"number\": True})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 从 ORM 中进行转换"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "import typing as t\n",
    "from datetime import datetime\n",
    "\n",
    "import peewee as pw\n",
    "from pydantic import BaseModel, Field\n",
    "\n",
    "db = pw.SqliteDatabase(\":memory:\")\n",
    "\n",
    "\n",
    "class NoteORM(pw.Model):\n",
    "    id = pw.AutoField()\n",
    "    title = pw.CharField()\n",
    "    content = pw.TextField()\n",
    "    tags = pw.CharField()\n",
    "    create_at = pw.DateTimeField(default=datetime.now())\n",
    "\n",
    "    class Meta:\n",
    "        database = db\n",
    "\n",
    "\n",
    "class NoteModel(BaseModel):\n",
    "    id: t.Optional[int] = Field(example=\"null\")\n",
    "    title: str\n",
    "    content: str\n",
    "    tags: t.Optional[t.List[str]] = Field(example=\"null\")\n",
    "\n",
    "    class Config:\n",
    "        orm_mode = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'id': None, 'title': '测试', 'content': '# Hello, world\\n', 'tags': ['技术分享']}"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "note_db = NoteORM(title=\"测试\", content=\"# Hello, world\\n\", tags=[\"技术分享\"])\n",
    "note = NoteModel.from_orm(note_db)\n",
    "note.dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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