自定义序列化和反序列化。

"from_json"(类方法)基于json数据构建一个Model对象。

“反序列化”只能在实例上调用，并将json中的所有数据合并到Model实例中。

"serialize" -递归序列化

需要__write_only__属性来定义只写属性(例如“password_hash”)。

class Serializable(object):
    __exclude__ = ('id',)
    __include__ = ()
    __write_only__ = ()

    @classmethod
    def from_json(cls, json, selfObj=None):
        if selfObj is None:
            self = cls()
        else:
            self = selfObj
        exclude = (cls.__exclude__ or ()) + Serializable.__exclude__
        include = cls.__include__ or ()
        if json:
            for prop, value in json.iteritems():
                # ignore all non user data, e.g. only
                if (not (prop in exclude) | (prop in include)) and isinstance(
                        getattr(cls, prop, None), QueryableAttribute):
                    setattr(self, prop, value)
        return self

    def deserialize(self, json):
        if not json:
            return None
        return self.__class__.from_json(json, selfObj=self)

    @classmethod
    def serialize_list(cls, object_list=[]):
        output = []
        for li in object_list:
            if isinstance(li, Serializable):
                output.append(li.serialize())
            else:
                output.append(li)
        return output

    def serialize(self, **kwargs):

        # init write only props
        if len(getattr(self.__class__, '__write_only__', ())) == 0:
            self.__class__.__write_only__ = ()
        dictionary = {}
        expand = kwargs.get('expand', ()) or ()
        prop = 'props'
        if expand:
            # expand all the fields
            for key in expand:
                getattr(self, key)
        iterable = self.__dict__.items()
        is_custom_property_set = False
        # include only properties passed as parameter
        if (prop in kwargs) and (kwargs.get(prop, None) is not None):
            is_custom_property_set = True
            iterable = kwargs.get(prop, None)
        # loop trough all accessible properties
        for key in iterable:
            accessor = key
            if isinstance(key, tuple):
                accessor = key[0]
            if not (accessor in self.__class__.__write_only__) and not accessor.startswith('_'):
                # force select from db to be able get relationships
                if is_custom_property_set:
                    getattr(self, accessor, None)
                if isinstance(self.__dict__.get(accessor), list):
                    dictionary[accessor] = self.__class__.serialize_list(object_list=self.__dict__.get(accessor))
                # check if those properties are read only
                elif isinstance(self.__dict__.get(accessor), Serializable):
                    dictionary[accessor] = self.__dict__.get(accessor).serialize()
                else:
                    dictionary[accessor] = self.__dict__.get(accessor)
        return dictionary

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])

class SqlToDict:
    def __init__(self, data) -> None:
        self.data = data

    def to_timestamp(self, date):
        if isinstance(date, datetime):
            return int(datetime.timestamp(date))
        else:
            return date

    def to_dict(self) -> List:
        arr = []
        for i in self.data:
            keys = [*i.keys()]
            values = [*i]
            values = [self.to_timestamp(d) for d in values]
            arr.append(dict(zip(keys, values)))
        return arr

例如:

SqlToDict(data).to_dict()

你可以把你的对象输出为一个字典:

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

然后使用User.as_dict()序列化对象。

如将sqlalchemy行对象转换为python dict中所述

当使用sqlalchemy连接到db I时，这是一个高度可配置的简单解决方案。使用熊猫。

import pandas as pd
import sqlalchemy

#sqlalchemy engine configuration
engine = sqlalchemy.create_engine....

def my_function():
  #read in from sql directly into a pandas dataframe
  #check the pandas documentation for additional config options
  sql_DF = pd.read_sql_table("table_name", con=engine)

  # "orient" is optional here but allows you to specify the json formatting you require
  sql_json = sql_DF.to_json(orient="index")

  return sql_json

虽然使用一些原始sql和未定义的对象，使用cursor.description似乎得到了我正在寻找的东西:

with connection.cursor() as cur:
    print(query)
    cur.execute(query)
    for item in cur.fetchall():
        row = {column.name: item[i] for i, column in enumerate(cur.description)}
        print(row)