Dynamically setting __tablename__ for sharding in SQLAlchemy?

Question

In order to handle a growing database table, we are sharding on table name. So we could have database tables that are named like this:

table_md5one
table_md5         


        

Answer 1

Because I insist to use declarative classes with their __tablename__ dynamically specified by given parameter, after days of failing with other solutions and hours of studying SQLAlchemy internals, I come up with the following solution that I believe is simple, elegant and race-condition free.

def get_model(suffix):
    DynamicBase = declarative_base(class_registry=dict())

    class MyModel(DynamicBase):
        __tablename__ = 'table_{suffix}'.format(suffix=suffix)

        id = Column(Integer, primary_key=True)
        name = Column(String)
        ...

    return MyModel

Since they have their own class_registry, you will not get that warning saying:

This declarative base already contains a class with the same class name and module name as mypackage.models.MyModel, and will be replaced in the string-lookup table.

Hence, you will not be able to reference them from other models with string lookup. However, it works perfectly fine to use these on-the-fly declared models for foreign keys as well:

ParentModel1 = get_model(123)
ParentModel2 = get_model(456)

class MyChildModel(BaseModel):
    __tablename__ = 'table_child'

    id = Column(Integer, primary_key=True)
    name = Column(String)
    parent_1_id = Column(Integer, ForeignKey(ParentModel1.id))
    parent_2_id = Column(Integer, ForeignKey(ParentModel2.id))
    parent_1 = relationship(ParentModel1)
    parent_2 = relationship(ParentModel2)

If you only use them to query/insert/update/delete without any reference left such as foreign key reference from another table, they, their base classes and also their class_registry will be garbage collected, so no trace will be left.

Answer 2

OK, we went with the custom SQLAlchemy declaration rather than the declarative one.

So we create a dynamic table object like this:

from sqlalchemy import MetaData, Table, Column

def get_table_object(self, md5hash):
    metadata = MetaData()
    table_name = 'table_' + md5hash
    table_object = Table(table_name, metadata,
        Column('Column1', DATE, nullable=False),
        Column('Column2', DATE, nullable=False)
    )
    clear_mappers()
    mapper(ActualTableObject, table_object)
    return ActualTableObject

Where ActualTableObject is the class mapping to the table.

Answer 3

you can write a function with tablename parameter and send back the class with setting appropriate attributes.

def get_class(table_name):

   class GenericTable(Base):

       __tablename__ = table_name

       ID= Column(types.Integer, primary_key=True)
       def funcation(self):
        ......
   return GenericTable

Then you can create a table using:

get_class("test").__table__.create(bind=engine)  # See sqlachemy.engine

Answer 4

Try this

import zlib

from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, BigInteger, DateTime, String

from datetime import datetime

BASE = declarative_base()
ENTITY_CLASS_DICT = {}


class AbsShardingClass(BASE):

    __abstract__ = True

def get_class_name_and_table_name(hashid):
    return 'ShardingClass%s' % hashid, 'sharding_class_%s' % hashid

def get_sharding_entity_class(hashid):
    """
    @param hashid: hashid
    @type hashid: int
    @rtype AbsClientUserAuth
    """

    if hashid not in ENTITY_CLASS_DICT:
        class_name, table_name = get_class_name_and_table_name(hashid)
        cls = type(class_name, (AbsShardingClass,),
                   {'__tablename__': table_name})
        ENTITY_CLASS_DICT[hashid] = cls

    return ENTITY_CLASS_DICT[hashid]

cls = get_sharding_entity_class(1)
print session.query(cls).get(100)

Answer 5

Instead of using imperative creating Table object, you can use usual declarative_base and make a closure to set a table name as the following:

def make_class(Base, table_name):
    class User(Base):
        __tablename__ = table_name
        id = Column(Integer, primary_key=True)
        name= Column(String)

    return User

Base = declarative_base()
engine = make_engine()
custom_named_usertable = make_class(Base, 'custom_name')
Base.metadata.create_all(engine)

session = make_session(engine)
new_user = custom_named_usertable(name='Adam')
session.add(new_user)
session.commit()
session.close()
engine.dispose()

Answer 6

In Augmenting the Base you find a way of using a custom Base class that can, for example, calculate the __tablename__ attribure dynamically:

class Base(object):
    @declared_attr
    def __tablename__(cls):
        return cls.__name__.lower()

The only problem here is that I don't know where your hash comes from, but this should give a good starting point.

If you require this algorithm not for all your tables but only for one you could just use the declared_attr on the table you are interested in sharding.