day100:MoFang:用户模型类的创建&Marshmallow模块&使用基本构造器Schema完成数据的序列化转换和反序列化转换

目录

1.用户模型的创建

2.Marshmallow模块

3.MarshMallow基本构造器:Schema

　　1.基于Schema完成数据序列化转换

　　2.基于Schema完成数据反序列化转换

　　3.反序列化阶段对数据进行校验

1.用户模型的创建

我们当前开发的项目属于社交类型项目，所以关于用户的信息和功能直接贯穿了整个项目。所以此处实现用户模块功能，我们先把用户基本信息构建起来，并通过基本信息实现用户注册登录相关功能，后面遇到业务再继续扩展。

1.创建用户蓝图/注册用户蓝图/添加总路由

cd application/apps
python ../../manage.py blue -n users

application/settings/dev.py

# 注册蓝图
INSTALLED_APPS = [
        "application.apps.home",
        "application.apps.users",
    ]

application/urls.py

from application.utils import include
urlpatterns = [
    include("","home.urls"),
    include("/users","users.urls"), # ***
]

2.用户相关模型

1.公共模型:BaseModel

application/model/utils.py

from application import db
from datetime import datetime
class BaseModel(db.Model):
    """公共模型"""
    __abstract__ = True # 抽象模型
    id = db.Column(db.Integer, primary_key=True, comment="主键ID")
    name = db.Column(db.String(255), default="", comment="名称/标题")
    is_deleted = db.Column(db.Boolean, default=False, comment="逻辑删除")
    orders = db.Column(db.Integer, default=0, comment="排序")
    status = db.Column(db.Boolean, default=True, comment="状态(是否显示,是否激活)")
    created_time = db.Column(db.DateTime, default=datetime.now, comment="创建时间")
    updated_time = db.Column(db.DateTime, default=datetime.now, onupdate=datetime.now, comment="更新时间")

    def __repr__(self):
        return "<%s: %s>" % (self.__class__.__name__, self.name)

2.用户模型:User/UserProfile

application/apps/users/models.py

from application.utils.models import BaseModel,db
from werkzeug.security import generate_password_hash, check_password_hash

class User(BaseModel):
    """用户基本信息表"""
    __tablename__ = "mf_user"
    name = db.Column(db.String(255), index=True, comment="用户账户")
    nickname = db.Column(db.String(255), comment="用户昵称")
    _password = db.Column(db.String(255), comment="登录密码")
    age = db.Column(db.SmallInteger, comment="年龄")
    money = db.Column(db.Numeric(7,2), comment="账户余额")
    ip_address = db.Column(db.String(255), default="", index=True, comment="登录IP")
    intro = db.Column(db.String(500), default="", comment="个性签名")
    avatar = db.Column(db.String(255), default="", comment="头像url地址")
    sex = db.Column(db.SmallInteger, default=0, comment="性别" ) # 0表示未设置,保密, 1表示男,2表示女
    email = db.Column(db.String(32), index=True, default="", nullable=False, comment="邮箱地址")
    mobile = db.Column(db.String(32), index=True, nullable=False, comment="手机号码")
    unique_id = db.Column(db.String(255), index=True, default="", comment="客户端唯一标记符")
    province = db.Column(db.String(255), default="", comment="省份")
    city = db.Column(db.String(255), default="", comment="城市")
    area = db.Column(db.String(255), default="", comment="地区")
    info = db.relationship('UserProfile', backref='user', uselist=False)

    @property
    def password(self):
        return self._password

    @password.setter
    def password(self, rawpwd):
        """密码加密"""
        self._password = generate_password_hash(rawpwd)

    def check_password(self, rawpwd):
        """验证密码"""
        return check_password_hash(self.password, rawpwd)


class UserProfile(BaseModel):
    """用户详情信息表"""
    __tablename__ = "mf_user_profile"
    user_id = db.Column(db.Integer,db.ForeignKey('mf_user.id'), comment="用户ID")
    education = db.Column(db.Integer, comment="学历教育")
    middle_school = db.Column(db.String(255), default="", comment="初中/中专")
    high_school = db.Column(db.String(255), default="", comment="高中/高职")
    college_school = db.Column(db.String(255), default="", comment="大学/大专")
    profession_cate = db.Column(db.String(255), default="", comment="职业类型")
    profession_info = db.Column(db.String(255), default="", comment="职业名称")
    position = db.Column(db.SmallInteger, default=0, comment="职位/职称")
    emotion_status = db.Column(db.SmallInteger, default=0, comment="情感状态")
    birthday =db.Column(db.DateTime, default="", comment="生日")
    hometown_province = db.Column(db.String(255), default="", comment="家乡省份")
    hometown_city = db.Column(db.String(255), default="", comment="家乡城市")
    hometown_area = db.Column(db.String(255), default="", comment="家乡地区")
    hometown_address = db.Column(db.String(255), default="", comment="家乡地址")
    living_province = db.Column(db.String(255), default="", comment="现居住省份")
    living_city = db.Column(db.String(255), default="", comment="现居住城市")
    living_area = db.Column(db.String(255), default="", comment="现居住地区")
    living_address = db.Column(db.String(255), default="", comment="现居住地址")

执行数据库迁移命令

cd ../..  # 切换工作目录会到项目根目录，manage.py所在目录下
python manage.py db init
python manage.py db migrate -m "users table"
python manage.py db upgrade

3.注册功能的实现:手机号码唯一性验证接口

在开发中，针对客户端提交的数据进行验证或提供模型数据转换格式成字典给客户端。可以使用Marshmallow模块来进行。

下面我们来了解一下Marshmallow模块.

2.Marshmallow模块

1.Marshmallow介绍

官方文档：https://marshmallow.readthedocs.io/en/latest/

Marshmallow，中文译作：棉花糖。是一个轻量级的数据格式转换的模块，也叫序列化和反序列化模块，常用于将复杂的orm模型对象与python原生数据类型之间相互转换。marshmallow提供了丰富的api功能。如下：

1. Serializing

   序列化[可以把数据对象转化为可存储或可传输的数据类型，例如：objects/object->list/dict，dict/list->string]

2. Deserializing

   反序列化器[把可存储或可传输的数据类型转换成数据对象，例如：list/dict->objects/object，string->dict/list]

3. Validation

   数据校验，可以在反序列化阶段，针对要转换数据的内容进行类型验证或自定义验证。

Marshmallow本身是一个单独的库，基于我们当前项目使用框架是flask并且数据库ORM框架使用SQLAlchemy，所以我们可以通过安装flask-sqlalchemy和marshmallow-sqlalchemy集成到项目就可以了。

2.基本安装和配置

1.模块安装

pip install -U marshmallow-sqlalchemy
pip install -U flask-sqlalchemy
pip install -U flask-marshmallow

2.模块初始化

import os

from flask_marshmallow import Marshmallow
...
# 数据转换器的对象创建
ma = Marshmallow()

def init_app(config_path):
    ...
    # 数据转换器的初始化
    ma.init_app(app)

  

3.创建一个marsh蓝图模块

为了方便学习和使用Marshllow, 我们单独创建一个蓝图来验证这个模块的基本使用.

cd application/apps
python ../../manage.py blue -n marsh

    INSTALLED_APPS = [
        "application.apps.home",
        "application.apps.users",
        "application.apps.marsh",
    ]

from application.utils import include
urlpatterns = [
    include("","home.urls"),
    include("/users","users.urls"),
    include("/marsh","marsh.urls"),
]

3.MarshMallow基本构造器:Schema

marshmallow转换数据格式主要通过构造器类来完成，而Schema类提供了数据转换的基本功能：序列化，验证和反序列化。所以在使用marshmallow的过程中所有的构造器类必须直接或间接继承于Schema基类

1.基于Schema完成数据序列化转换

1.序列化单个数据对象

application/apps/marsh/urls.py

from . import views
from application.utils import path
urlpatterns = [
    path("", views.index),
]

application/apps/marsh/views.py

from marshmallow import Schema,fields
from application.apps.users.models import User,UserProfile
class UserSchema(Schema):
    name   = fields.String()
    age    = fields.Integer()
    email  = fields.Email()
    money  = fields.Number()
    class Meta:
        fields = ["name","age","money","email","info"]
        ordered = True # 转换成有序字典

def index():
    """序列化"""
    """单个模型数据的序列化处理"""
    user1 = User(name="xiaoming", password="123456", age=16, email="333@qq.com", money=31.50)
    
    data1 = UserSchema().dump(user1) # 将模型类对象序列化为字典dict格式
        
    data2 = UserSchema().dumps(user1) # 把模型对象转换成json字符串格式
    return "ok"

2.序列化多个数据对象

在前面进行的序列化操作属于序列化单个数据对象, MarshMallow中也可以进行多个数据对象的序列化.

application/apps/marsh/views.py

from marshmallow import Schema,fields
from application.apps.users.models import User,UserProfile

class UserSchema(Schema):
    name   = fields.String()
    age    = fields.Integer()
    email  = fields.Email()
    money  = fields.Number()
    class Meta:
        fields = ["name","age","money","email","info"]
        ordered = True # 转换成有序字典

def index():
    """序列化"""
    """多个模型数据的序列化"""
    user1 = User(name="xiaoming", password="123456", age=15, email="333@qq.com", money=31.50)
    user2 = User(name="xiaohong", password="123456", age=16, email="333@qq.com", money=31.50)
    user3 = User(name="xiaopang", password="123456", age=17, email="333@qq.com", money=31.50)
    data_list = [user1,user2,user3]
    data1 = UserSchema(many=True).dumps(data_list) # 注意:序列化多个数据对象要加many=True
    return "ok"

3.构造器嵌套使用

application/apps/marsh/views.py

from marshmallow import Schema,fields
from application.apps.users.models import User,UserProfile
class UserProfileSchema(Schema):
    education = fields.Integer()
    middle_school = fields.String()

class UserSchema(Schema):
    name   = fields.String()
    age    = fields.Integer()
    email  = fields.Email()
    money  = fields.Number()
    
    # only的含义是外层序列化器要内层序列化器的哪些字段
    info   = fields.Nested(UserProfileSchema,only=["middle_school"])
    class Meta:
        fields = ["name","age","money","email","info"]
        ordered = True # 转换成有序字典

def index():
    """序列化"""
    """序列化嵌套使用"""
    user1 = User(name="xiaoming", password="123456", age=15, email="333@qq.com", money=31.50)
    user1.info = UserProfile(
        education=3,
        middle_school="北京师范学院附属中学白沙路分校"
    )
    data = UserSchema().dump(user1)
    data = UserSchema().dumps(user1)
    print(data)
    return "ok"

2.基于Schema完成数据反序列化转换

1.反序列化时设置字段的默认值:missing

from marshmallow import Schema, fields, validate, ValidationError,post_load
class UserSchema2(Schema):
    name = fields.String()
    sex = fields.String()
    age = fields.Integer(missing=18) # 反序列化数据时，如果数据没有给age字段赋值，则age默认值为18
    email = fields.Email()
    mobile = fields.String()

    @post_load
    def post_load(self, data, **kwargs):
        return User(**data)

def index():
    user_data = {"mobile":"1331345635","name": "xiaoming", "email": "xiaoming@qq.com","sex":"abc"}
    us2 = UserSchema2()
    result = us2.load(user_data) # 将字典转化为模型类对象
    print(type(result),result)  # <class 'application.apps.users.models.User'> <User: xiaoming>
    return "ok"

将user_data数据反序列化后再序列化，可以看到结果多了age:18这一项，这就是因为在schema中的age字段中设置了missing=18

2.反序列化转换/忽略部分数据:required/partial

from marshmallow import Schema, fields, validate, ValidationError,post_load
class UserSchema2(Schema):
    name = fields.String()
    sex = fields.String()
    age = fields.Integer(missing=18)
    email = fields.Email()
    
    # 设置反序列化时必须要有mobile字段
    mobile = fields.String(required=True)

    @post_load
    def post_load(self, data, **kwargs):
        return User(**data)

def index():
    user_data = {"name": "xiaoming","sex":"abc"}
    us2 = UserSchema2()
    
    # 设置反序列化时可以忽略部分数据
    result = us2.load(user_data,partial=True)
    
    print(result)  # ==> <User xiaoming>
    return "ok"

3.设置字段只在序列化或反序列化阶段才启用:load_only/dump_only

from marshmallow import Schema, fields, validate, ValidationError,post_load
class UserSchema2(Schema):
    name = fields.String()
    sex = fields.Integer()
    age = fields.Integer(missing=18)
    email = fields.Email()
    mobile = fields.String()
    password = fields.String(load_only=True) # 设置当前字段为只写字段，只会在反序列化阶段启用

    @post_load
    def post_load(self, data, **kwargs):
        return User(**data)

def index():
    user_data = {"name": "xiaoming","password":"123456","sex":1}
    us2 = UserSchema2()
    # 反序列化
    result = us2.load(user_data)
    print(result)  # ==> <User xiaoming>
    # 序列化
    us3 = UserSchema2(only=["sex","name","age"]) # 限制处理的字段,也就是序列化出来只有这三个字段
    result2 = us3.dump(result)
    print(result2)
    return "ok"
'''
class UserSchema(Schema):
    name = fields.Str()
    # password is 
    password = fields.Str(load_only=True) # 相当于只写字段 "write-only"
    created_time = fields.DateTime(dump_only=True) # 相当于只读字段 "read-only"
'''

4.反序列化阶段的钩子方法

post_dump([fn，pass_many，pass_original]) 注册序列化对象后调用的方法，它会在对象序列化后被调用。

post_load([fn，pass_many，pass_original]) 注册反序列化对象后要调用的方法，它会在验证数据之后被调用。

pre_dump([fn，pass_many]) 注册序列化对象之前调用的方法，它会在序列化对象之前被调用。

pre_load([fn，pass_many]) 在反序列化对象之前，注册要调用的方法，它会在验证数据之前调用。

from marshmallow import Schema, fields, validate, ValidationError,post_load,post_dump
class UserSchema2(Schema):
    name = fields.String()
    sex = fields.Integer(validate=validate.OneOf([0,1,2]))
    age = fields.Integer(missing=18)
    email = fields.Email()
    mobile = fields.String()
    password = fields.String(load_only=True) # 设置当前字段为只写字段，只会在反序列化阶段启用

    
    @post_load
    def post_load(self, data, **kwargs):
        return User(**data)

    @post_dump
    def post_dump(self,data, **kwargs):
        data["mobile"] = data["mobile"][:3] +"*****"+ data["mobile"][-3:]
        return data

def index():
    user_data = {"name": "xiaoming","password":"123456","sex":1,"mobile":"133123454656"}
    us2 = UserSchema2()

    # 反序列化
    result = us2.load(user_data)
    print(result)  # ==> <User xiaoming>

    # 序列化
    us3 = UserSchema2(only=["sex","name","age","mobile"]) # 限制处理的字段
    result2 = us3.dump(result)
    print(result2)
    return "ok"

Tip：schema常用属性数据类型

类型	描述
fields.Dict(keys, type]] = None, values, …)	字典类型，常用于接收json类型数据
fields.List(cls_or_instance, type], **kwargs)	列表类型，常用于接收数组数据
fields.Tuple(tuple_fields, *args, **kwargs)	元组类型
fields.String(*, default, missing, data_key, …)	字符串类型
fields.UUID(*, default, missing, data_key, …)	UUID格式类型的字符串
fields.Number(*, as_string, **kwargs)	数值基本类型
fields.Integer(*, strict, **kwargs)	整型
fields.Decimal(places, rounding, *, allow_nan, …)	数值型
fields.Boolean(*, truthy, falsy, **kwargs)	布尔型
fields.Float(*, allow_nan, as_string, **kwargs)	浮点数类型
fields.DateTime(format, **kwargs)	日期时间类型
fields.Time(format, **kwargs)	时间类型
fields.Date(format, **kwargs)	日期类型
fields.Url(*, relative, schemes, Set[str]]] = None, …)	url网址字符串类型
fields.Email(*args, **kwargs)	邮箱字符串类型
fields.IP(*args[, exploded])	IP地址字符串类型
fields.IPv4(*args[, exploded])	IPv4地址字符串类型
fields.IPv6(*args[, exploded])	IPv6地址字符串类型
fields.Method(serialize, deserialize, **kwargs)	基于Schema类方法返回值的字段
fields.Function(serialize, Any], Callable[[Any, …)	基于函数返回值得字段
fields.Nested(nested, type, str, Callable[[], …)	外键类型

 

Tip：schema数据类型的常用属性

属性名	描述
default	序列化阶段中设置字段的默认值
missing	反序列化阶段中设置字段的默认值
validate	反序列化阶段调用的内置数据验证器或者内置验证集合
required	设置当前字段的必填字段
allow_none	是否允许为空
load_only	是否在反序列化阶段才使用到当前字段
dump_omly	是否在序列化阶段才使用到当前字段
error_messages	字典类型，可以用来替代默认的字段异常提示语，格式：<br>error_messages={“required”: “用户名为必填项。”}

 

3.反序列化阶段对数据进行校验

1.基于内置器对数据进行校验

内置验证器	描述
validate.Email(*, error)	邮箱验证
validate.Equal(comparable, *, error)	判断值是否相等
validate.Length(min, max, *, equal, error)	值长度/大小验证
validate.OneOf(choices, labels, *, error)	选项验证
validate.Range([min, max])	范围验证
validate.Regexp(regex, bytes, Pattern][, flags])	正则验证
validate.URL(*, relative, schemes, Set[str]]] = None, …)	验证是否为URL

 

 

Tip:Schema常用属性数据类型

 

 

 

 

 

 

 

from marshmallow import Schema, fields, validate, ValidationError,post_load
class UserSchema3(Schema):
    name = fields.String(required=True)
    sex = fields.String(required=True,error_messages={"required":"对不起，permission必须填写"})
    age = fields.Integer(missing=18,validate=validate.Range(min=18,max=40,error="年龄必须在18-40之间！")) # 限制数值范围
    email = fields.Email(error_messages={"invalid":"对不起，必须填写邮箱格式！"})
    mobile = fields.String(required=True, validate=validate.Regexp("^1[3-9]\d{9}$",error="手机号码格式不正确"),error_messages={"Regexp":"手机格式不正确"})

    @post_load
    def make_user_obj(self, data, **kwargs):
        return User(**data)

def index3():
    user_data = {"mobile":"1331345635","name": "xiaoming","age":40, "email": "xiaoming@qq.com","sex":"abc"}
    us2 = UserSchema3()
    result = us2.load(user_data)
    result2 = us2.dumps(result)
    print(result)
    print(result2)
    return "ok"

2.自定义验证方法

局部钩子和全局钩子，比如局部钩子对单个字段（用户名）的判断，以及全局钩子对密码，确认密码多个字段的判断

from marshmallow import Schema, fields, validate,validates, ValidationError,post_load,validates_schema

class UserSchema4(Schema):
    name = fields.String(required=True)
    sex = fields.String(required=True,error_messages={"required":"对不起，permission必须填写"})
    age = fields.Integer(missing=18,validate=validate.Range(min=18,max=40,error="年龄必须在18-40之间！")) # 限制数值范围
    email = fields.Email(error_messages={"invalid":"对不起，必须填写邮箱格式！"})
    mobile = fields.String(required=True, validate=validate.Regexp("^1[3-9]\d{9}$",error="手机号码格式不正确"),error_messages={"Regexp":"手机格式不正确"})
    password = fields.String(required=True, load_only=True)
    password2 = fields.String(required=True, allow_none=True)
    
    @post_load
    def make_user_obj(self, data, **kwargs):
        return User(**data)
    
    # 局部钩子 ***
    @validates("name")
    def validate_name(self,data,**kwargs):
        print("name=%s" % data)
        if data == "root":
            raise ValidationError({"对不起,root用户是超级用户!您没有权限注册！"})

        # 必须有返回值
        return data

    # 全局钩子 ***
    @validates_schema
    def validate(self,data,**kwargs):
        print(data)
        if data["password"] != data["password2"]:
            raise ValidationError("密码和确认密码必须一样！")

        data.pop("password2")
        return data

def index():
    user_data = {"password":"12345","password2":"123456","mobile":"13313345635","name": "root1","age":40, "email": "xiaoming@qq.com","sex":"abc"}
    us2 = UserSchema4()
    result = us2.load(user_data)
    print(result)
    return "ok"