feat: 新增技能扩展N10一章相关示例源码

code/newsletter/N10/pydantic.ipynb

@@ -0,0 +1,516 @@
+{
+ "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": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.9.0 ('pandas-startup')",
+   "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": "3.9.0"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "13977d4cc82dee5f9d9535ceb495bd0ab12a43c33c664e5f0d53c24cf634b67f"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}