安装simplejson by PIP安装simplejson并创建一个类

class Serialise(object):

    def _asdict(self):
        """
        Serialization logic for converting entities using flask's jsonify

        :return: An ordered dictionary
        :rtype: :class:`collections.OrderedDict`
        """

        result = OrderedDict()
        # Get the columns
        for key in self.__mapper__.c.keys():
            if isinstance(getattr(self, key), datetime):
                result["x"] = getattr(self, key).timestamp() * 1000
                result["timestamp"] = result["x"]
            else:
                result[key] = getattr(self, key)

        return result

并将这个类继承到每个orm类，这样这个_asdict函数就会注册到每个orm类，然后。 并在任何地方使用jsonify

你可以像这样使用SqlAlchemy的自省:

mysql = SQLAlchemy()
from sqlalchemy import inspect

class Contacts(mysql.Model):  
    __tablename__ = 'CONTACTS'
    id = mysql.Column(mysql.Integer, primary_key=True)
    first_name = mysql.Column(mysql.String(128), nullable=False)
    last_name = mysql.Column(mysql.String(128), nullable=False)
    phone = mysql.Column(mysql.String(128), nullable=False)
    email = mysql.Column(mysql.String(128), nullable=False)
    street = mysql.Column(mysql.String(128), nullable=False)
    zip_code = mysql.Column(mysql.String(128), nullable=False)
    city = mysql.Column(mysql.String(128), nullable=False)
    def toDict(self):
        return { c.key: getattr(self, c.key) for c in inspect(self).mapper.column_attrs }

@app.route('/contacts',methods=['GET'])
def getContacts():
    contacts = Contacts.query.all()
    contactsArr = []
    for contact in contacts:
        contactsArr.append(contact.toDict()) 
    return jsonify(contactsArr)

@app.route('/contacts/<int:id>',methods=['GET'])
def getContact(id):
    contact = Contacts.query.get(id)
    return jsonify(contact.toDict())

从下面的答案中得到启发: 将sqlalchemy行对象转换为python dict

AlchemyEncoder是很棒的，但有时会失败的十进制值。这是一个改进的编码器，解决十进制问题-

class AlchemyEncoder(json.JSONEncoder):
# To serialize SQLalchemy objects 
def default(self, obj):
    if isinstance(obj.__class__, DeclarativeMeta):
        model_fields = {}
        for field in [x for x in dir(obj) if not x.startswith('_') and x != 'metadata']:
            data = obj.__getattribute__(field)
            print data
            try:
                json.dumps(data)  # this will fail on non-encodable values, like other classes
                model_fields[field] = data
            except TypeError:
                model_fields[field] = None
        return model_fields
    if isinstance(obj, Decimal):
        return float(obj)
    return json.JSONEncoder.default(self, obj)

扁平化实现

你可以使用这样的代码:

from sqlalchemy.ext.declarative import DeclarativeMeta

class AlchemyEncoder(json.JSONEncoder):

    def default(self, obj):
        if isinstance(obj.__class__, DeclarativeMeta):
            # an SQLAlchemy class
            fields = {}
            for field in [x for x in dir(obj) if not x.startswith('_') and x != 'metadata']:
                data = obj.__getattribute__(field)
                try:
                    json.dumps(data) # this will fail on non-encodable values, like other classes
                    fields[field] = data
                except TypeError:
                    fields[field] = None
            # a json-encodable dict
            return fields

        return json.JSONEncoder.default(self, obj)

然后转换为JSON使用:

c = YourAlchemyClass()
print json.dumps(c, cls=AlchemyEncoder)

它将忽略不可编码的字段(将它们设置为“None”)。

它不会自动展开关系(因为这可能导致自引用，并永远循环)。

递归的非循环实现

然而，如果你宁愿永远循环，你可以使用:

from sqlalchemy.ext.declarative import DeclarativeMeta

def new_alchemy_encoder():
    _visited_objs = []

    class AlchemyEncoder(json.JSONEncoder):
        def default(self, obj):
            if isinstance(obj.__class__, DeclarativeMeta):
                # don't re-visit self
                if obj in _visited_objs:
                    return None
                _visited_objs.append(obj)

                # an SQLAlchemy class
                fields = {}
                for field in [x for x in dir(obj) if not x.startswith('_') and x != 'metadata']:
                    fields[field] = obj.__getattribute__(field)
                # a json-encodable dict
                return fields

            return json.JSONEncoder.default(self, obj)

    return AlchemyEncoder

然后对对象进行编码，使用:

print json.dumps(e, cls=new_alchemy_encoder(), check_circular=False)

这将编码所有的子代、子代、子代……基本上可以编码你的整个数据库。当它到达之前编码过的东西时，它会将其编码为“None”。

递归的、可能是循环的、有选择的实现

另一种选择，可能更好，是能够指定你想要展开的字段:

def new_alchemy_encoder(revisit_self = False, fields_to_expand = []):
    _visited_objs = []

    class AlchemyEncoder(json.JSONEncoder):
        def default(self, obj):
            if isinstance(obj.__class__, DeclarativeMeta):
                # don't re-visit self
                if revisit_self:
                    if obj in _visited_objs:
                        return None
                    _visited_objs.append(obj)

                # go through each field in this SQLalchemy class
                fields = {}
                for field in [x for x in dir(obj) if not x.startswith('_') and x != 'metadata']:
                    val = obj.__getattribute__(field)

                    # is this field another SQLalchemy object, or a list of SQLalchemy objects?
                    if isinstance(val.__class__, DeclarativeMeta) or (isinstance(val, list) and len(val) > 0 and isinstance(val[0].__class__, DeclarativeMeta)):
                        # unless we're expanding this field, stop here
                        if field not in fields_to_expand:
                            # not expanding this field: set it to None and continue
                            fields[field] = None
                            continue

                    fields[field] = val
                # a json-encodable dict
                return fields

            return json.JSONEncoder.default(self, obj)

    return AlchemyEncoder

你现在可以调用它:

print json.dumps(e, cls=new_alchemy_encoder(False, ['parents']), check_circular=False)

例如，仅展开名为“parents”的SQLAlchemy字段。

你可以像这样将RowProxy转换为dict:

 d = dict(row.items())

然后将其序列化为JSON(必须为datetime值等指定编码器) 如果您只想要一条记录(而不是相关记录的完整层次结构)，这并不难。

json.dumps([(dict(row.items())) for row in rs])

更详细的解释。 在你的模型中，添加:

def as_dict(self):
       return {c.name: str(getattr(self, c.name)) for c in self.__table__.columns}

str()是针对python3的，所以如果使用python2则使用unicode()。它应该有助于反序列化日期。如果不处理这些，你可以删除它。

现在可以像这样查询数据库

some_result = User.query.filter_by(id=current_user.id).first().as_dict()

需要First()来避免奇怪的错误。As_dict()现在将反序列化结果。反序列化之后，就可以将其转换为json了

jsonify(some_result)