Convert sqlalchemy row object to python dict

Question

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), but it throws exception , TypeError: 'User' object is not iterable

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:

sqlalchemy version: 0.5.6
Traceback (most recent call last):
  File "untitled-1.py", line 37, in <module>
    print dict(u)
TypeError: 'User' object is not iterable

Answer 1

You may access the internal __dict__ of a SQLAlchemy object, like the following::

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

Answer 2

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}

Answer 3

As per @zzzeek in comments:

note that this is the correct answer for modern versions of SQLAlchemy, assuming "row" is a core row object, not an ORM-mapped instance.

for row in resultproxy:
    row_as_dict = dict(row)

Answer 4

In SQLAlchemy v0.8 and newer, use the inspection system.

from sqlalchemy import inspect

def object_as_dict(obj):
    return {c.key: getattr(obj, c.key)
            for c in inspect(obj).mapper.column_attrs}

user = session.query(User).first()

d = object_as_dict(user)

Note that .key is the attribute name, which can be different from the column name, e.g. in the following case:

class_ = Column('class', Text)

This method also works for column_property.

Answer 5

rows have an _asdict() function which gives a dict

In [8]: r1 = db.session.query(Topic.name).first()

In [9]: r1
Out[9]: (u'blah')

In [10]: r1.name
Out[10]: u'blah'

In [11]: r1._asdict()
Out[11]: {'name': u'blah'}

Answer 6

as @balki mentioned:

The _asdict() method can be used if you're querying a specific field because it is returned as a KeyedTuple.

In [1]: foo = db.session.query(Topic.name).first()
In [2]: foo._asdict()
Out[2]: {'name': u'blah'}

Whereas, if you do not specify a column you can use one of the other proposed methods - such as the one provided by @charlax. Note that this method is only valid for 2.7+.

In [1]: foo = db.session.query(Topic).first()
In [2]: {x.name: getattr(foo, x.name) for x in foo.__table__.columns}
Out[2]: {'name': u'blah'}

Answer 7

Old question, but since this the first result for "sqlalchemy row to dict" in Google it deserves a better answer.

The RowProxy object that SqlAlchemy returns has the items() method: http://docs.sqlalchemy.org/en/latest/core/connections.html#sqlalchemy.engine.RowProxy.items

It simply returns a list of (key, value) tuples. So one can convert a row to dict using the following:

In Python <= 2.6:

rows = conn.execute(query)
list_of_dicts = [dict((key, value) for key, value in row.items()) for row in rows]

In Python >= 2.7:

rows = conn.execute(query)
list_of_dicts = [{key: value for (key, value) in row.items()} for row in rows]

Answer 8

Assuming the following functions will be added to the class User the following will return all key-value pairs of all columns:

def columns_to_dict(self):
    dict_ = {}
    for key in self.__mapper__.c.keys():
        dict_[key] = getattr(self, key)
    return dict_

unlike the other answers all but only those attributes of the object are returned which are Column attributes at class level of the object. Therefore no _sa_instance_state or any other attribute SQLalchemy or you add to the object are included. Reference

EDIT: Forget to say, that this also works on inherited Columns.

hybrid_property extention

If you also want to include hybrid_property attributes the following will work:

from sqlalchemy import inspect
from sqlalchemy.ext.hybrid import hybrid_property

def publics_to_dict(self) -> {}:
    dict_ = {}
    for key in self.__mapper__.c.keys():
        if not key.startswith('_'):
            dict_[key] = getattr(self, key)

    for key, prop in inspect(self.__class__).all_orm_descriptors.items():
        if isinstance(prop, hybrid_property):
            dict_[key] = getattr(self, key)
    return dict_

I assume here that you mark Columns with an beginning _ to indicate that you want to hide them, either because you access the attribute by an hybrid_property or you simply do not want to show them. Reference

Tipp all_orm_descriptors also returns hybrid_method and AssociationProxy if you also want to include them.

Remarks to other answers

Every answer (like 1, 2 ) which based on the __dict__ attribute simply returns all attributes of the object. This could be much more attributes then you want. Like I sad this includes _sa_instance_state or any other attribute you define on this object.

Every answer (like 1, 2 ) which is based on the dict() function only works on SQLalchemy row objects returned by session.execute() not on the classes you define to work with, like the class User from the question.

The solving answer which is based on row.__table__.columns will definitely not work. row.__table__.columns contains the column names of the SQL Database. These can only be equal to the attributes name of the python object. If not you get an AttributeError. For answers (like 1, 2 ) based on class_mapper(obj.__class__).mapped_table.c it is the same.

Answer 9

Following @balki answer, since SQLAlchemy 0.8 you can use _asdict(), available for KeyedTuple objects. This renders a pretty straightforward answer to the original question. Just, change in your example the last two lines (the for loop) for this one:

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

This works because in the above code u is an object of type class KeyedTuple, since .all() returns a list of KeyedTuple. Therefore it has the method _asdict(), which nicely returns u as a dictionary.

WRT the answer by @STB: AFAIK, anything that .all() returns is a list of KeypedTuple. Therefore, the above works either if you specify a column or not, as long as you are dealing with the result of .all() as applied to a Query object.

Answer 10

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)

Answer 11

Refer to Alex Brasetvik's Answer, you can use one line of code to solve the problem

row_as_dict = [dict(row) for row in resultproxy]

Under the comment section of Alex Brasetvik's Answer, zzzeek the creator of SQLAlchemy stated this is the "Correct Method" for the problem.

Answer 12

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().

Answer 13

You could try to do it in this way.

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

It use a built-in method in the query object that return a dictonary object of the query object.

references: https://docs.sqlalchemy.org/en/latest/orm/query.html

Answer 14

I've found this post because I was looking for a way to convert a SQLAlchemy row into a dict. I'm using SqlSoup... but the answer was built by myself, so, if it could helps someone here's my two cents:

a = db.execute('select * from acquisizioni_motes')
b = a.fetchall()
c = b[0]

# and now, finally...
dict(zip(c.keys(), c.values()))

Answer 15

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 = '[email protected]'


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, [email protected]

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.

Answer 16

The 1.3 docs offer a very simple solution: KeyedTuple._asdict()

def to_array(rows):
    return [r._asdict() for r in rows]

def query():
    data = session.query(Table).all()
    return to_array(data)

Answer 17

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.

Answer 18

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)

Answer 19

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())

Answer 20

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

Answer 21

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]

Answer 22

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'}

Answer 23

I have a variation on Marco Mariani's answer, expressed as a decorator. The main difference is that it'll handle lists of entities, as well as safely ignoring some other types of return values (which is very useful when writing tests using mocks):

@decorator
def to_dict(f, *args, **kwargs):
  result = f(*args, **kwargs)
  if is_iterable(result) and not is_dict(result):
    return map(asdict, result)

  return asdict(result)

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

def is_dict(obj):
  return isinstance(obj, dict)

def is_iterable(obj):
  return True if getattr(obj, '__iter__', False) else False

Answer 24

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]

Answer 25

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}

Answer 26

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)

Answer 27

I am a newly minted Python programmer and ran into problems getting to JSON with Joined tables. Using information from the answers here I built a function to return reasonable results to JSON where the table names are included avoiding having to alias, or have fields collide.

Simply pass the result of a session query:

test = Session().query(VMInfo, Customer).join(Customer).order_by(VMInfo.vm_name).limit(50).offset(10)

json = sqlAl2json(test)

def sqlAl2json(self, result):
    arr = []
    for rs in result.all():
        proc = []
        try:
            iterator = iter(rs)
        except TypeError:
            proc.append(rs)
        else:
            for t in rs:
                proc.append(t)

        dict = {}
        for p in proc:
            tname = type(p).__name__
            for d in dir(p):
                if d.startswith('_') | d.startswith('metadata'):
                    pass
                else:
                    key = '%s_%s' %(tname, d)
                    dict[key] = getattr(p, d)
        arr.append(dict)
    return json.dumps(arr)

Answer 28

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

Answer 29

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'}

Answer 30

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.