feat: 新增技能扩展N10一章相关示例源码

This commit is contained in:
100gle
2022-12-22 11:51:01 +08:00
parent 7686cabcd2
commit d8b4c8e33a
3 changed files with 1273 additions and 0 deletions

View File

@@ -0,0 +1,487 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 定义数据类"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"User(username='100gle', password='password', email='email@example.com', is_vip=False)"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import attrs\n",
"\n",
"\n",
"@attrs.define\n",
"class User:\n",
" username: str\n",
" password: str\n",
" email: str\n",
" is_vip: bool = False\n",
"\n",
"User(\"100gle\", \"password\", email=\"email@example.com\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"User(username='100gle', password=***, email='email@example.com')"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@attrs.define\n",
"class User:\n",
" username: str\n",
" password: str = attrs.field(repr=lambda v: \"***\")\n",
" email: str\n",
" is_vip: bool = attrs.field(default=False, repr=False)\n",
"\n",
"User(\"100gle\", \"password\", email=\"email@example.com\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"from datetime import datetime\n",
"\n",
"import attrs\n",
"\n",
"\n",
"@attrs.define\n",
"class User:\n",
" username: str\n",
" email: str\n",
" _password: str = attrs.field(repr=lambda v: \"***\")\n",
" _is_vip: bool = attrs.field(init=False, default=False, repr=False)\n",
" _recent_login_at: datetime = attrs.field(init=False, default=datetime.now())"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"User(username='100gle', email='email@example.com', _password=***, _recent_login_at=datetime.datetime(2022, 11, 19, 10, 44, 48, 848285))"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"User(\"100gle\", email=\"email@example.com\", password=\"password\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"from datetime import datetime\n",
"\n",
"import attr\n",
"\n",
"\n",
"@attr.s\n",
"class User:\n",
" username = attr.ib(type=str)\n",
" email = attr.ib(type=str)\n",
" _password = attr.ib(repr=lambda v: \"***\")\n",
" _is_vip = attr.ib(default=False, repr=False)\n",
" _recent_login_at = attr.ib(init=False, default=datetime.now())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 自定义字段校验逻辑"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"class LimitError(Exception):\n",
" pass\n",
"\n",
"\n",
"@attrs.define\n",
"class User:\n",
" username: str\n",
" email: str = attrs.field()\n",
" _password: str = attrs.field(repr=lambda v: \"***\")\n",
" _is_vip: bool = attrs.field(default=False, repr=False)\n",
" _recent_login_at: datetime = attrs.field(init=False, default=datetime.now())\n",
"\n",
" @email.validator\n",
" def _check_email(self, attribute, value: str):\n",
" if not \"@\" in value:\n",
" raise ValueError(\"invalid email that doesn't contains an '@' symbol\")\n",
"\n",
" if len(value) >= 15:\n",
" raise LimitError(\"email out of the max length of 15 chars\")\n",
"\n",
" return value"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"# User(\"100gle\", email=\"email#example.com\", password=\"password\") # raise ValueError here!"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"import attrs\n",
"\n",
"class LimitError(Exception):\n",
" pass\n",
"\n",
"def check_email_validation(instance, attribute, value: str):\n",
" if not \"@\" in value:\n",
" raise ValueError(\"invalid email that doesn't contains an '@' symbol\")\n",
"\n",
"\n",
"def check_email_length(instance, attribute, value: str):\n",
" if len(value) >= 15:\n",
" raise LimitError(\"email out of the max length of 15 chars\")\n",
"\n",
"@attrs.define\n",
"class User:\n",
" username: str\n",
" email: str = attrs.field(\n",
" validator=[\n",
" check_email_validation,\n",
" check_email_length,\n",
" ]\n",
" )\n",
" _password: str = attrs.field(repr=lambda v: \"***\")\n",
" _is_vip: bool = attrs.field(default=False, repr=False)\n",
" _recent_login_at: datetime = attrs.field(init=False, default=datetime.now())\n",
"\n",
" @email.validator\n",
" def _check_email_suffix(self, attribute, value: str):\n",
" if not value.endswith(\"com\"):\n",
" raise ValueError(\"invalid domain\")\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"# User(\"100gle\", email=\"email#example.com\", password=\"password\") # raise ValueError here!"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 自定义转换器"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"@attrs.define\n",
"class C:\n",
" x: int = attrs.field(converter=int)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"o = C(\"1\")\n",
"o.x\n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"int"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"type(o.x)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"from datetime import datetime\n",
"\n",
"import attrs\n",
"\n",
"\n",
"class LimitError(Exception):\n",
" pass\n",
"\n",
"\n",
"def fix_invalid_email(value: str) -> str:\n",
" if not \"@\" in value and \"#\" in value:\n",
" return value.replace(\"#\", \"@\")\n",
" return value\n",
"\n",
"@attrs.define\n",
"class User:\n",
" username: str\n",
" email: str = attrs.field(converter=fix_invalid_email)\n",
" _password: str = attrs.field(repr=lambda v: \"***\")\n",
" _is_vip: bool = attrs.field(default=False, repr=False)\n",
" _recent_login_at: datetime = attrs.field(init=False, default=datetime.now())\n",
"\n",
" @email.validator\n",
" def _check_email_suffix(self, attribute, value: str):\n",
" if not value.endswith(\"com\"):\n",
" raise ValueError(\"invalid domain\")"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"User(username='100gle', email='email@example.com', _password=***, _recent_login_at=datetime.datetime(2022, 11, 19, 10, 44, 49, 229669))"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"User(\"100gle\", email=\"email#example.com\", password=\"password\")"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"# User(\"100gle\", email=\"email@example.net\", password=\"password\") # raise ValueError here!"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 导出数据类"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'username': '100gle',\n",
" 'email': 'email@example.com',\n",
" '_password': 'password',\n",
" '_is_vip': False,\n",
" '_recent_login_at': datetime.datetime(2022, 11, 19, 10, 44, 49, 229669)}"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"user = User(\"100gle\", email=\"email#example.com\", password=\"password\")\n",
"attrs.asdict(user)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'username': '100gle', 'email': 'email@example.com'}"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"attrs.asdict(\n",
" user,\n",
" filter=lambda attr, value: not attr.name.startswith(\"_\"),\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'username': '100gle', 'email': 'email@example.com'}"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from attrs import fields, filters\n",
"\n",
"attrs.asdict(\n",
" user,\n",
" filter=filters.include(\n",
" fields(User).username,\n",
" fields(User).email,\n",
" ),\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'username': '100gle', 'email': 'email@example.com'}"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"attrs.asdict(\n",
" user,\n",
" filter=filters.exclude(\n",
" fields(User)._password,\n",
" fields(User)._is_vip,\n",
" datetime,\n",
" ),\n",
")"
]
},
{
"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
}

View File

@@ -0,0 +1,270 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import typing as t\n",
"from dataclasses import dataclass\n",
"\n",
"@dataclass\n",
"class Item:\n",
" name: str\n",
" price: t.Union[int, float]\n",
" number: int"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import typing as t\n",
"from dataclasses import dataclass\n",
"\n",
"@dataclass(repr=False, eq=True, order=False)\n",
"class Item:\n",
" name: str\n",
" price: t.Union[int, float]\n",
" number: int"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"import typing as t\n",
"from dataclasses import dataclass\n",
"\n",
"@dataclass\n",
"class Item:\n",
" name: str\n",
" price: t.Union[int, float] = 0\n",
" number: int = 0"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"import typing as t\n",
"from dataclasses import dataclass, field\n",
"\n",
"@dataclass\n",
"class Item:\n",
" name: str\n",
" price: t.Union[int, float] = 0\n",
" number: int = 0\n",
" categories: t.List[str] = field(default_factory=list)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"import typing as t\n",
"from dataclasses import dataclass, field\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[str] = field(default_factory=list)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Item(name='iPhone 14', price=6999, number=1000, categories=[Category(level=1, name='')])"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import typing as t\n",
"from dataclasses import dataclass, field\n",
"\n",
"\n",
"@dataclass\n",
"class Category:\n",
" level: int = 1\n",
" name: str = \"\"\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",
"\n",
"Item(\"iPhone 14\", price=6999, number=1000)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"\n",
"if sys.version_info >= (3, 10):\n",
" from dataclasses import KW_ONLY\n",
"\n",
" import typing as t\n",
" from dataclasses import KW_ONLY, dataclass, field\n",
"\n",
"\n",
" @dataclass\n",
" class Category:\n",
" level: int = 1\n",
" name: str = \"\"\n",
"\n",
"\n",
" def default_categories():\n",
" return [Category()]\n",
"\n",
"\n",
" @dataclass\n",
" class Item:\n",
" name: str\n",
" _: KW_ONLY\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)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"import typing as t\n",
"from dataclasses import asdict, astuple, dataclass, field\n",
"\n",
"\n",
"@dataclass\n",
"class Category:\n",
" level: int = 1\n",
" name: str = \"\"\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",
"\n",
"item = Item(\"iPhone 14\", price=6999, number=1000)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"('iPhone 14', 6999, 1000, [(1, '')])"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"astuple(item)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'name': 'iPhone 14',\n",
" 'price': 6999,\n",
" 'number': 1000,\n",
" 'categories': [{'level': 1, 'name': ''}]}"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"asdict(item)"
]
},
{
"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
}

View File

@@ -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
}