How to convert SQLAlchemy row object to a Python dict?

Viewed 384489

Is there a simple way to iterate over column name and value pairs?

My version of SQLAlchemy is 0.5.6

Here is the sample code where I tried using dict(row):

import sqlalchemy
from sqlalchemy import *
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker

print "sqlalchemy version:",sqlalchemy.__version__ 

engine = create_engine('sqlite:///:memory:', echo=False)
metadata = MetaData()
users_table = Table('users', metadata,
     Column('id', Integer, primary_key=True),
     Column('name', String),
)
metadata.create_all(engine) 

class User(declarative_base()):
    __tablename__ = 'users'
    
    id = Column(Integer, primary_key=True)
    name = Column(String)
    
    def __init__(self, name):
        self.name = name

Session = sessionmaker(bind=engine)
session = Session()

user1 = User("anurag")
session.add(user1)
session.commit()

# uncommenting next line throws exception 'TypeError: 'User' object is not iterable'
#print dict(user1)
# this one also throws 'TypeError: 'User' object is not iterable'
for u in session.query(User).all():
    print dict(u)

Running this code on my system outputs:

Traceback (most recent call last):
  File "untitled-1.py", line 37, in <module>
    print dict(u)
TypeError: 'User' object is not iterable
43 Answers

I couldn't get a good answer so I use this:

def row2dict(row):
    d = {}
    for column in row.__table__.columns:
        d[column.name] = str(getattr(row, column.name))

    return d

Edit: if above function is too long and not suited for some tastes here is a one liner (python 2.7+)

row2dict = lambda r: {c.name: str(getattr(r, c.name)) for c in r.__table__.columns}
from sqlalchemy.orm import class_mapper

def asdict(obj):
    return dict((col.name, getattr(obj, col.name))
                for col in class_mapper(obj.__class__).mapped_table.c)

with sqlalchemy 1.4

session.execute(select(User.id, User.username)).mappings().all()
>> [{'id': 1, 'username': 'Bob'}, {'id': 2, 'username': 'Alice'}]

With python 3.8+, we can do this with dataclass, and the asdict method that comes with it:

from dataclasses import dataclass, asdict

from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
from sqlalchemy import Column, String, Integer, create_engine

Base = declarative_base()
engine = create_engine('sqlite:///:memory:', echo=False)


@dataclass
class User(Base):
    __tablename__ = 'users'

    id: int = Column(Integer, primary_key=True)
    name: str = Column(String)
    email = Column(String)

    def __init__(self, name):
        self.name = name
        self.email = 'hello@example.com'


Base.metadata.create_all(engine)

SessionMaker = sessionmaker(bind=engine)
session = SessionMaker()

user1 = User("anurag")
session.add(user1)
session.commit()

query_result = session.query(User).one()  # type: User
print(f'{query_result.id=:}, {query_result.name=:}, {query_result.email=:}')
# query_result.id=1, query_result.name=anurag, query_result.email=hello@example.com

query_result_dict = asdict(query_result)
print(query_result_dict)
# {'id': 1, 'name': 'anurag'}

The key is to use the @dataclass decorator, and annotate each column with its type (the : str part of the name: str = Column(String) line).

Also note that since the email is not annotated, it is not included in query_result_dict.

The expression you are iterating through evaluates to list of model objects, not rows. So the following is correct usage of them:

for u in session.query(User).all():
    print u.id, u.name

Do you realy need to convert them to dicts? Sure, there is a lot of ways, but then you don't need ORM part of SQLAlchemy:

result = session.execute(User.__table__.select())
for row in result:
    print dict(row)

Update: Take a look at sqlalchemy.orm.attributes module. It has a set of functions to work with object state, that might be useful for you, especially instance_dict().

I've just been dealing with this issue for a few minutes. The answer marked as correct doesn't respect the type of the fields. Solution comes from dictalchemy adding some interesting fetures. https://pythonhosted.org/dictalchemy/ I've just tested it and works fine.

Base = declarative_base(cls=DictableModel)

session.query(User).asdict()
{'id': 1, 'username': 'Gerald'}

session.query(User).asdict(exclude=['id'])
{'username': 'Gerald'}
class User(object):
    def to_dict(self):
        return dict([(k, getattr(self, k)) for k in self.__dict__.keys() if not k.startswith("_")])

That should work.

You can convert sqlalchemy object to dictionary like this and return it as json/dictionary.

Helper functions:

import json
from collections import OrderedDict


def asdict(self):
    result = OrderedDict()
    for key in self.__mapper__.c.keys():
        if getattr(self, key) is not None:
            result[key] = str(getattr(self, key))
        else:
            result[key] = getattr(self, key)
    return result


def to_array(all_vendors):
    v = [ ven.asdict() for ven in all_vendors ]
    return json.dumps(v) 

Driver Function:

def all_products():
    all_products = Products.query.all()
    return to_array(all_products)

Two ways:

1.

for row in session.execute(session.query(User).statement):
    print(dict(row))

2.

selected_columns = User.__table__.columns
rows = session.query(User).with_entities(*selected_columns).all()
for row in rows :
    print(row._asdict())

Here is how Elixir does it. The value of this solution is that it allows recursively including the dictionary representation of relations.

def to_dict(self, deep={}, exclude=[]):
    """Generate a JSON-style nested dict/list structure from an object."""
    col_prop_names = [p.key for p in self.mapper.iterate_properties \
                                  if isinstance(p, ColumnProperty)]
    data = dict([(name, getattr(self, name))
                 for name in col_prop_names if name not in exclude])
    for rname, rdeep in deep.iteritems():
        dbdata = getattr(self, rname)
        #FIXME: use attribute names (ie coltoprop) instead of column names
        fks = self.mapper.get_property(rname).remote_side
        exclude = [c.name for c in fks]
        if dbdata is None:
            data[rname] = None
        elif isinstance(dbdata, list):
            data[rname] = [o.to_dict(rdeep, exclude) for o in dbdata]
        else:
            data[rname] = dbdata.to_dict(rdeep, exclude)
    return data

With this code you can also to add to your query "filter" or "join" and this work!

query = session.query(User)
def query_to_dict(query):
        def _create_dict(r):
            return {c.get('name'): getattr(r, c.get('name')) for c in query.column_descriptions}

    return [_create_dict(r) for r in query]

For the sake of everyone and myself, here is how I use it:

def run_sql(conn_String):
  output_connection = engine.create_engine(conn_string, poolclass=NullPool).connect()
  rows = output_connection.execute('select * from db1.t1').fetchall()  
  return [dict(row) for row in rows]

As OP stated, calling the dict initializer raises an exception with the message "User" object is not iterable. So the real question is how to make a SQLAlchemy Model iterable?

We'll have to implement the special methods __iter__ and __next__, but if we inherit directly from the declarative_base model, we would still run into the undesirable "_sa_instance_state" key. What's worse, is we would have to loop through __dict__.keys() for every call to __next__ because the keys() method returns a View -- an iterable that is not indexed. This would increase the time complexity by a factor of N, where N is the number of keys in __dict__. Generating the dict would cost O(N^2). We can do better.

We can implement our own Base class that implements the required special methods and stores a list of of the column names that can be accessed by index, reducing the time complexity of generating the dict to O(N). This has the added benefit that we can define the logic once and inherit from our Base class anytime we want our model class to be iterable.

class IterableBase(declarative_base()):
    __abstract__ = True

    def _init_keys(self):
        self._keys = [c.name for c in self.__table__.columns]
        self._dict = {c.name: getattr(self, c.name) for c in self.__table__.columns}

    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self._init_keys()

    def __setattr__(self, name, value):
        super().__setattr__(name, value)
        if name not in ('_dict', '_keys', '_n') and '_dict' in self.__dict__:
            self._dict[name] = value

    def __iter__(self):
        self._n = 0
        return self

    def __next__(self):
        if self._n >= len(self._keys):
            raise StopIteration
        self._n += 1
        key = self._keys[self._n-1]
        return (key, self._dict[key])

Now the User class can inherit directly from our IterableBase class.

class User(IterableBase):
    __tablename__ = 'users'
    id = Column(Integer, primary_key=True)
    name = Column(String)

You can confirm that calling the dict function with a User instance as an argument returns the desired dictionary, sans "_sa_instance_state". You may have noticed the __setattr__ method that was declared in the IterableBase class. This ensures the _dict is updated when attributes are mutated or set after initialization.

def main():
    user1 = User('Bob')
    print(dict(user1))
    # outputs {'id': None, 'name': 'Bob'}
    user1.id = 42
    print(dict(user1))
    # outputs {'id': 42, 'name': 'Bob'}

if __name__ == '__main__':
    main()

To complete @Anurag Uniyal 's answer, here is a method that will recursively follow relationships:

from sqlalchemy.inspection import inspect

def to_dict(obj, with_relationships=True):
    d = {}
    for column in obj.__table__.columns:
        if with_relationships and len(column.foreign_keys) > 0:
             # Skip foreign keys
            continue
        d[column.name] = getattr(obj, column.name)

    if with_relationships:
        for relationship in inspect(type(obj)).relationships:
            val = getattr(obj, relationship.key)
            d[relationship.key] = to_dict(val) if val else None
    return d

class User(Base):
    __tablename__ = 'users'
    id = Column(Integer, primary_key=True)
    first_name = Column(TEXT)
    address_id = Column(Integer, ForeignKey('addresses.id')
    address = relationship('Address')

class Address(Base):
    __tablename__ = 'addresses'
    id = Column(Integer, primary_key=True)
    city = Column(TEXT)


user = User(first_name='Nathan', address=Address(city='Lyon'))
# Add and commit user to session to create ids

to_dict(user)
# {'id': 1, 'first_name': 'Nathan', 'address': {'city': 'Lyon'}}
to_dict(user, with_relationship=False)
# {'id': 1, 'first_name': 'Nathan', 'address_id': 1}

We can get a list of object in dict:

def queryset_to_dict(query_result):
   query_columns = query_result[0].keys()
   res = [list(ele) for ele in query_result]
   dict_list = [dict(zip(query_columns, l)) for l in res]
   return dict_list

query_result = db.session.query(LanguageMaster).all()
dictvalue=queryset_to_dict(query_result)
from copy import copy

def to_record(row):
    record = copy(row.__dict__)
    del record["_sa_instance_state"]
    return record

If not using copy, you might run into errors.

An improved version of Anurag Uniyal's version, which takes into account types:

def sa_vars(row):
    return {
        column.name: column.type.python_type(getattr(row, column.name))
        for column in row.__table__.columns
    }

if your models table column is not equie mysql column.

such as :

class People:
    id: int = Column(name='id', type_=Integer, primary_key=True)
    createdTime: datetime = Column(name='create_time', type_=TIMESTAMP,
                               nullable=False,
                               server_default=text("CURRENT_TIMESTAMP"),
                               default=func.now())
    modifiedTime: datetime = Column(name='modify_time', type_=TIMESTAMP,
                                server_default=text("CURRENT_TIMESTAMP"),
                                default=func.now())

Need to use:

 from sqlalchemy.orm import class_mapper 
 def asDict(self):
        return {x.key: getattr(self, x.key, None) for x in
            class_mapper(Application).iterate_properties}

if you use this way you can get modify_time and create_time both are None

{'id': 1, 'create_time': None, 'modify_time': None}


    def to_dict(self):
        return {c.name: getattr(self, c.name, None)
         for c in self.__table__.columns}

Because Class Attributes name not equal with column store in mysql

Return the contents of this :class:.KeyedTuple as a dictionary

In [46]: result = aggregate_events[0]

In [47]: type(result)
Out[47]: sqlalchemy.util._collections.result

In [48]: def to_dict(query_result=None):
    ...:     cover_dict = {key: getattr(query_result, key) for key in query_result.keys()}
    ...:     return cover_dict
    ...: 
    ...:     

In [49]: to_dict(result)
Out[49]: 
{'calculate_avg': None,
 'calculate_max': None,
 'calculate_min': None,
 'calculate_sum': None,
 'dataPointIntID': 6,
 'data_avg': 10.0,
 'data_max': 10.0,
 'data_min': 10.0,
 'data_sum': 60.0,
 'deviceID': u'asas',
 'productID': u'U7qUDa',
 'tenantID': u'CvdQcYzUM'}
def to_dict(row):
    return {column.name: getattr(row, row.__mapper__.get_property_by_column(column).key) for column in row.__table__.columns}


for u in session.query(User).all():
    print(to_dict(u))

This function might help. I can't find better solution to solve problem when attribute name is different then column names.

You'll need it everywhere in your project, I apriciate @anurag answered it works fine. till this point I was using it, but it'll mess all your code and also wont work with entity change.

Rather try this, inherit your base query class in SQLAlchemy

from flask_sqlalchemy import SQLAlchemy, BaseQuery


class Query(BaseQuery):
    def as_dict(self):
        context = self._compile_context()
        context.statement.use_labels = False
        columns = [column.name for column in context.statement.columns]

        return list(map(lambda row: dict(zip(columns, row)), self.all()))


db = SQLAlchemy(query_class=Query)

after that wherever you'll define your object "as_dict" method will be there.

use dict Comprehensions

for u in session.query(User).all():
    print ({column.name: str(getattr(row, column.name)) for column in row.__table__.columns})

After querying the database using following SQLAlchemy code:

from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker


SQLALCHEMY_DATABASE_URL = 'sqlite:///./examples/sql_app.db'
engine = create_engine(SQLALCHEMY_DATABASE_URL, echo=True)
query = sqlalchemy.select(TABLE)
result = engine.execute(query).fetchall()

You can use this one-liner:

query_dict = [record._mapping for record in results]

Python 3.6.8+

The builtin str() method automatically converts datetime.datetime objects to iso-8806-1.

print(json.dumps([dict(row.items()) for row in rows], default=str, indent="  "))

NOTE: The default func will only be applied to a value if there's an error so int and float values won't be converted... unless there's an error :).

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