mysql-5.7安装
https://blog.csdn.net/since_1904/article/details/70233403
flask-sqlalchemy教程
http://www.pythondoc.com/flask-sqlalchemy/
sqlalchemy文档
https://docs.sqlalchemy.org/en/rel_0_9/orm/tutorial.html
中文翻译版
https://www.jianshu.com/p/8d085e2f2657
sqlalchemy查询使用
https://www.cnblogs.com/jingqi/p/8059673.html
MySQL外键与外键关系说明(简单易懂)
https://www.cnblogs.com/programmer-tlh/p/5782451.html
relationship和ForeignKey这个两个属性决定了表之间关系的属性,ForeignKey是mysql的本身的属性,relationship是orm的属性,relationship存在的用途感觉是为了方便类表的控制,可以像控制类的属性一样改变
具体参考:
http://docs.sqlalchemy.org/en/latest/orm/backref.html#relationships-backref
http://docs.sqlalchemy.org/en/latest/orm/relationship_api.html
relationship是为了简化联合查询join等,创建的两个表之间的虚拟关系,这种关系与标的结构时无关的。他与外键十分相似,确实,他必须在外键的基础上才允许使用,使两个表之间产生管理,类似于合成一张表,可以直接取出关联的表,进行获取数据,而不需要join操作
https://www.cnblogs.com/ssyfj/p/8568013.html
from sqlalchemy import create_engine # 创建一个和mysql数据库之间的连接引擎对象
from datetime import datetime
from sqlalchemy import ForeignKey
from sqlalchemy import Column, String, Integer
from sqlalchemy.orm import relationship, backref # 引入需要的模块
from sqlalchemy.ext.declarative import declarative_base # 创建基础类
from sqlalchemy.orm.exc import MultipleResultsFound
from sqlalchemy.orm.exc import NoResultFound
BaseModel = declarative_base()
engine = create_engine("mysql+pymysql://root:lgj123@localhost/myschool2", encoding="utf8", echo=True)
# 创建用户类型
class User(BaseModel):
# 定义和指定数据库表之间的关联
__tablename__ = 'user'
# 创建字段类型
id = Column(Integer, primary_key=True)
name = Column(String(50))
fullname = Column(String(50))
password = Column(String(50))
#addresses = relationship("Address", order_by="Address.id", backref="user")
def __repr__(self):
return '< User-->id:%s,name:%s,fullname:%s,password:%s >' % (self.id,self.name,self.fullname,self.password)
#建立联系(外键)
class Address(BaseModel):
__tablename__ = 'addresses'
id= Column(Integer, primary_key=True)
email_address = Column(String(50), nullable=False)
user_id = Column(Integer, ForeignKey('user.id'))
user = relationship("User", backref=backref('addresses',order_by=id))
def __repr__(self):
return"< Address -->id:%s,email_address:%s,user_id:%s,user:%s>" % (self.id,self.email_address,self.user_id,self.user)
BaseModel.metadata.create_all(engine)# 创建表
from sqlalchemy.orm import sessionmaker
Session = sessionmaker(bind=engine)
session = Session()
# ed_user1 = User(name='ed1', fullname='Ed Jones', password='edspassword')
# ed_user2 = User(name='ed2', fullname='Ed Jones', password='edspassword')
# ed_user3 = User(name='ed3', fullname='Ed Jones', password='edspassword')
# session.add(ed_user1)
# session.add(ed_user2)
# session.add(ed_user3) # 这三条就算未commit到数据库中,但还是能被下面的查询语句查到,这里需要注意!
#
# session.commit()
print("-------------1")
for instance in session.query(User).order_by(User.id):
print (instance.name,instance.fullname,instance.password)
print("-------------2")
for name, fullname in session.query(User.name,User.fullname):
print (name, fullname)
print("-------------3")
query = session.query(User).filter(User.name.like('%ed%')).order_by(User.id)
user_all = query.all()
print("-------------4")
print("user_all:",user_all)
print("first:",query.first())
try:
user1 = query.one()
print ("user1:",user1)
except Exception as e:
print("e:",e)
print("-------------5")
try:
user2 = query.filter(User.id == 20).one()
print ("user2:",user2)
except Exception as e:
print("e:",e)
print("-------------6")
from sqlalchemy import text
for user in session.query(User).filter(text("id<25")).order_by(text("id")).all():
print("user:",user)
print("-------------7")
user_text=session.query(User).filter(text("id<:value and name=:name")).params(value=50, name='ed3').order_by(User.id).one()
print("user_text:",user_text)
print("-------------8")
print("count:",session.query(User).filter(User.name.like('%ed%')).count())
print("-------------9")
# jack = User(name='jack', fullname='Jack Bean', password='gjffdd')
# print ("jack.addresses:",jack.addresses)
# jack.addresses = [Address(email_address='jack@google.com'),Address(email_address='j25@yahoo.com')]
# session.add(jack)
# session.commit()
print("-------------10")
for u,a in session.query(User, Address).filter(User.id==Address.user_id).filter(Address.email_address=='jack@google.com').all():
print ("user:",u)
print ("address:",a)
print("-------------11")
for u,a in session.query(User, Address).join(Address).filter(Address.email_address=='jack@google.com').all():
print("user:", u)
print("address:", a)
print("-------------12")
ad1=Address(email_address='123@qq.com',user_id=1)
#ad1.user=1
ad2=Address(email_address='123@qq.com',user_id=1)
#ad2.user=1
session.add(ad1)
session.add(ad2)
session.commit()
print("-------------13")
返回列表(List)和单项(Scalar)
很多Query的方法执行了SQL命令并返回了取出的数据库结果。
all()返回一个列表:
>>> query = session.query(User).filter(User.name.like('%ed')).order_by(User.id)
SQL>>> query.all()
[<User(name='ed', fullname='Ed Jones', password='f8s7ccs')>,
<User(name='fred', fullname='Fred Flinstone', password='blah')>]
first()返回至多一个结果,而且以单项形式,而不是只有一个元素的tuple形式返回这个结果.
>>> query.first()
<User(name='ed', fullname='Ed Jones', password='f8s7ccs')>
one()返回且仅返回一个查询结果。当结果的数量不足一个或者多于一个时会报错。
>>> user = query.one()
Traceback (most recent call last):
...
MultipleResultsFound: Multiple rows were found for one()
没有查找到结果时:
>>> user = query.filter(User.id == 99).one()
Traceback (most recent call last):
...
NoResultFound: No row was found for one()
one_or_none():从名称可以看出,当结果数量为0时返回None, 多于1个时报错
scalar()和one()类似,但是返回单项而不是tuple
使用关键字变量过滤查询结果,filter 和 filter_by都适用,下面列出几个常用的操作:
query.filter(User.name =='ed') #equals
query.filter(User.name !='ed') #not equals
query.filter(User.name.like('%ed%')) #LIKE
uery.filter(User.name.in_(['ed','wendy', 'jack'])) #IN
query.filter(User.name.in_(session.query(User.name).filter(User.name.like('%ed%'))#IN
query.filter(~User.name.in_(['ed','wendy', 'jack']))#not IN
query.filter(User.name ==None)#is None
query.filter(User.name !=None)#not None
from sqlalchemy import and_
query.filter(and_(User.name =='ed',User.fullname =='Ed Jones')) # and
query.filter(User.name =='ed',User.fullname =='Ed Jones') # and
query.filter(User.name =='ed').filter(User.fullname =='Ed Jones')# and
from sqlalchemy import or_
query.filter(or_(User.name =='ed', User.name =='wendy')) #or
query.filter(User.name.match('wendy')) #match
使用字符串SQL
字符串能使Query更加灵活,通过text()构造指定字符串的使用,这种方法可以用在很多方法中,像filter()和order_by()。
from sqlalchemy import text
for user in session.query(User).filter(text("id<224")).order_by(text("id")).all()
绑定参数可以指定字符串,用params()方法指定数值。
session.query(User).filter(text("id<:value and name=:name")).params(value=224, name='fred').order_by(User.id).one()
如果要用一个完整的SQL语句,可以使用from_statement()。
session.query(User).from_statement(text("SELECT* FROM users where name=:name")).params(name='ed').all()
通过text的存在可以灵活的构造查询请求,就像拼凑字符串一样简单,根据查询的条件不同拼凑出合适的字符串
def table_search(page, per_page, name, status, trans_type, start_port, end_port):
statement = "1=1"
if name:
statement += " and name like '%s%s%s' " % ('%', name, '%')
if status:
statement += " and status = '%s' " % status
if trans_type:
statement += " and trans_type = '%s' " % trans_type
if start_port:
statement += " and start_port_name like '%s%s%s' " % ('%', start_port, '%')
if end_port:
statement += " and end_port_name like '%s%s%s' " % ('%', end_port, '%')
lines = mytable.query.filter(statement).order_by(mytable.update_at.desc(),
mytable.create_at.desc()).paginate(int(page), int(per_page), False)
count = mytable.query.filter(statement).count()
lines_list = []
for item in lines.items:
line = item.to_dict()
if line['create_at']:
line['create_at'] = datetime.datetime.strftime(line['create_at'], '%Y-%m-%d %H:%M')
if line['update_at']:
line['update_at'] = datetime.datetime.strftime(line['update_at'], '%Y-%m-%d %H:%M')
lines_list.append(line)
result = {"count": count, "lines": lines_list}
db.session.remove()
return None, result
在看项目中看到 session.query(User).filter("id<224")) 在字符串外并未构造成text("id<224")也是可以的,心存疑惑,需要验证一下。
已验证--->目前使用的Flask-1.0.2版本中是支持不加text的,但会在不加的时候报出warning,具体的代码实现如下:
@_generative(_no_statement_condition, _no_limit_offset)
def filter(self, *criterion):
"""
session.query(MyClass).filter(MyClass.name == 'some name')
session.query(MyClass).\
filter(MyClass.name == 'some name', MyClass.id > 5)
The criterion is any SQL expression object applicable to the
WHERE clause of a select.
String expressions are coerced into SQL expression constructs via the :func:`.text` construct.(字符串表达式通过:func:`。text`结构强制转换为SQL表达式构造。)
"""
for criterion in list(criterion):
criterion = expression._expression_literal_as_text(criterion)
criterion = self._adapt_clause(criterion, True, True)
if self._criterion is not None:
self._criterion = self._criterion & criterion
else:
self._criterion = criterion
def _expression_literal_as_text(element):
return _literal_as_text(element, warn=True)
def _literal_as_text(element, warn=False):
if isinstance(element, Visitable):
return element
elif hasattr(element, '__clause_element__'):
return element.__clause_element__()
elif isinstance(element, util.string_types):
if warn:
util.warn_limited(
"Textual SQL expression %(expr)r should be "
"explicitly declared as text(%(expr)r)",
{"expr": util.ellipses_string(element)})
return TextClause(util.text_type(element))
elif isinstance(element, (util.NoneType, bool)):
return _const_expr(element)
else:
raise exc.ArgumentError(
"SQL expression object or string expected, got object of type %r "
"instead" % type(element)
)
text 方法就是通过sqlalchemy.sql.elements.TextClause#_create_text构造的,这里殊途同归了。总结就是:不使用text(str)也是可以的,就是会报个warning。
2018-7-24号 遇到的问题--已解决
https://stackoverflow.com/questions/28047027/sqlalchemy-not-find-table-for-creating-foreign-key
https://segmentfault.com/q/1010000003983231/revision
https://segmentfault.com/q/1010000002361279
sqlalchemy.exc.NoReferencedTableError: Foreign key associated with column 'Address.fk_province_code' could not find table 'Geo_Code' with which to generate a foreign key to target column 'ad_code'
sqlalchemy.exc.NoReferencedTableError:与列'Address.fk_province_code'关联的外键无法找到用于生成目标列'ad_code'的外键的表'Geo_Code'
python manage.py db init
python manage.py db migrate
python mmanage.py shell
db.create_all()
再执行上述命令前 要把所有可能报错的model中的表文件导入到 manage.py中,显式的告诉migrate时需要创建哪些表,隐式依赖的表不这样做就会报错。
relationship是为了简化联合查询join等,创建的两个表之间的虚拟关系,这种关系与标的结构时无关的。他与外键十分相似,确实,他必须在外键的基础上才允许使用
不然会报错:
sqlalchemy.exc.NoForeignKeysError: Could not determine join condition between parent/child tables on relationship Father.son - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression
详细的relationship可以点击这里进行查看
relationship的使用:
使两个表之间产生管理,类似于合成一张表,可以直接取出关联的表,进行获取数据,而不需要join操作
#简单查询
print(session.query(User).all())
print(session.query(User.name, User.fullname).all())
print(session.query(User, User.name).all())
#带条件查询
print(session.query(User).filter_by(name='user1').all())
print(session.query(User).filter(User.name == "user").all())
print(session.query(User).filter(User.name.like("user%")).all())
#多条件查询
print(session.query(User).filter(and_(User.name.like("user%"), User.fullname.like("first%"))).all())
print(session.query(User).filter(or_(User.name.like("user%"), User.password != None)).all())
#sql过滤
print(session.query(User).filter("id>:id").params(id=1).all())
#关联查询
print(session.query(User, Address).filter(User.id == Address.user_id).all())
print(session.query(User).join(User.addresses).all())
print(session.query(User).outerjoin(User.addresses).all())
#聚合查询
print(session.query(User.name, func.count('*').label("user_count")).group_by(User.name).all())
print(session.query(User.name, func.sum(User.id).label("user_id_sum")).group_by(User.name).all())
#子查询
stmt = session.query(Address.user_id, func.count('*').label("address_count")).group_by(Address.user_id).subquery()
print(session.query(User, stmt.c.address_count).outerjoin((stmt, User.id == stmt.c.user_id)).order_by(User.id).all())
#exists
print(session.query(User).filter(exists().where(Address.user_id == User.id)))
print(session.query(User).filter(User.addresses.any()))
#限制返回字段查询
person = session.query(Person.name, Person.created_at,
Person.updated_at).filter_by(name="zhongwei").order_by(
Person.created_at).first()
#记录总数查询的几种姿势
from sqlalchemy import func
# count User records, without
# using a subquery.
session.query(func.count(User.id))
# return count of user "id" grouped
# by "name"
session.query(func.count(User.id)).
group_by(User.name)
from sqlalchemy import distinct
# count distinct "name" values
session.query(func.count(distinct(User.name)))