搭建一个利用docker启动服务的Flask的小demo

定义数据库

# -*- coding: utf-8 -*-from sqlalchemy import *
from sqlalchemy.orm import (scoped_session, sessionmaker, relationship, backref
)
from sqlalchemy.ext.declarative import declarative_base# mysql+mysqlconnector://<user>:<password>@<host>[:<port>]/<dbname>
engine = create_engine("mysql+mysqlconnector://root:@localhost:3306/demo", convert_unicode=True)
session = scoped_session(sessionmaker(autocommit=False, autoflush=False, bind=engine
))Base = declarative_base()
Base.query = session.query_property()class Department(Base):__tablename__ = "department"id = Column(Integer, primary_key=True)name = Column(String(50))class Employee(Base):__tablename__ = "employee"id = Column(Integer, primary_key=True)name = Column(String(50))hired_on = Column(DateTime, default=func.now())department_id = Column(Integer, ForeignKey("department.id"))department = relationship(Department,backref=backref("employee",uselist=True,cascade="delete,all"))

利用SQLAlchemy定义了两个表，其中Department通过relationship可以关联多个Employee，然后通过python console创建表和数据：

>>> from models import *
>>>
>>>
>>> Base.metadata.create_all(bind=engine)
>>>
>>>
>>> engineering = Department(name="Engineering")
>>> session.add(engineering)
>>> hr = Department(name="Human")
>>> session.add(hr)
>>>
>>>
>>> peter = Employee(name="Peter", department=engine)
engine              engine_from_config( engineering
>>> peter = Employee(name="Peter", department=engineering)
>>>
>>> session.add(peter)
>>>
>>>
>>>
>>> roy = Employee(name="Roy", department=engineering)
>>>
>>> session.add(roy)
>>>
>>>
>>> tracy = Employee(name="Tracy", department=hr)
>>>
>>> session.add(tracy)

定义graphql的的Query

# -*- coding: utf-8 -*-from graphene import relay, ObjectType, Schema
from graphene_sqlalchemy import (SQLAlchemyConnectionField, SQLAlchemyObjectType
)from models import (Department as DepartmentModel,Employee as EmployeeModel
)class Department(SQLAlchemyObjectType):class Meta:model = DepartmentModelinterfaces = (relay.Node, )class DepartmentConnections(relay.Connection):class Meta:node = Departmentclass Employee(SQLAlchemyObjectType):class Meta:model = EmployeeModelinterfaces = (relay.Node, )class EmployeeConnections(relay.Connection):class Meta:node = Employeeclass Query(ObjectType):node = relay.Node.Field()all_employees = SQLAlchemyConnectionField(EmployeeConnections)all_departments = SQLAlchemyConnectionField(DepartmentConnections, sort=None)schema = Schema(query=Query)

首先通过继承SQLAlchemyObjectType类来定义新的查询的类，然后通过relay.Connection来连接所定义的查询类，并且在Query中进行申明，其中我在Connection后面加了一个s是因为在github上看issue的时候发现在构造类的过程中会出现重名的情况导致申明Query的时候会报错，所以加一个s用来避免这个错误。
其中有关graphene的部分我自己也还不是特别熟悉，所以只能是大概说一下自己的思路，如果有错误的地方会在后续中及时的进行修改，避免误人子弟。
最终达到的效果是指定来一个schema，其中包含了我所定义的查询。

本地启动

# -*- coding: utf-8 -*-from flask import Flask
from flask_graphql import GraphQLViewfrom models import session
from schema import schemaapp = Flask(__name__)
app.debug = Trueapp.add_url_rule("/graphql",view_func=GraphQLView.as_view("graphql",schema=schema,graphiql=True)
)@app.teardown_appcontext
def shutdown_session(exception=None):session.remove()if __name__ == "__main__":app.run()

通过Flask的add_url_rule将graph的视图定义成通过路由可访问，然后启动就可以进行访问了,点击http://127.0.0.1:5000/graphql就可以本地访问了。

通过docker启动

• 建立镜像

# run.docker
FROM python:3.6COPY . /appWORKDIR /appRUN pip install -r requirements.txtCMD ["python", "app.py"]

这个是我的Dockerfile，通过Dockerfile，我指定了这个镜像是来自于python:3.6这个镜像，然后把我当前目录下的所有内容通过COPY . /app复制到了docker镜像中的/app目录下，接着我指定了WORKDIR为/app,这样我就可以在/app目录下进行操作了，首先是安装所有需要的依赖包，因为我是从python3.6拉的镜像，所以可以不用再去安装pip，直接就可以安装了，如果是其他镜像可能还要同构apt去安装pip再进行依赖包的安装，最后就是用CMD来运行文件了。

docker build -t flask_sqlalchemy:core -f run.docker .
# 其中的.是为了指明上下文路径，其实Dockerfile中的命令并不是对本地文件进行操作，而是通过指定上下文路径将这些文件传到docker搭建镜像的环境中再进行操作。

镜像建立之后就可以run了

docker run -d -p 5000:5000 --name flask-core flask_sqlalchemy:lastest

然后就启动了。