I have this class in one file and item class in another file in the same module. If they are in different modules or files when I define a new Channel, I got an error because Item is not in the same file. How can I solve this problem? If both classes are in the same file, I don't get any error.
ChannelTest.py
from ItemTest import Item
metadata = rdb.MetaData()
channel_items = Table(
"channel_items",
metadata,
Column("channel_id", Integer,
ForeignKey("channels.id")),
Column("item_id", Integer,
ForeignKey("items.id"))
)
class Channel(rdb.Model):
""" Set up channels table in the database """
rdb.metadata(metadata)
rdb.tablename("channels")
id = Column("id", Integer, primary_key=True)
title = Column("title", String(100))
items = relation("Item",
secondary=channel_items, backref="channels")
Item.py Different file, but in the same module
class Item(rdb.Model):
""" Set up items table in the database """
rdb.metadata(metadata)
rdb.tablename("items")
id = Column("id", Integer, primary_key=True)
title = Column("title", String(100))
Thanks in advance!
"NoReferencedTableError: Could not find table 'items' with which to generate a foreign key"
All your table definitions should share metadata object.
So you should do metadata = rdb.MetaData() in some separate module, and then use this metadata instance in ALL Table()'s.
The string method should work, but if it doesn't than there is also the option of simply importing the module.
And if that gives you import loops than you can still add the property after instantiating the class like this:
import item
Channel.items = relation(item.Item,
secondary=item.channel_items,
backref='channels')
Related
In my postgres server we have a database database with 2 schemas: public and api.
public has several tables, and I need to create a table in api with a foreign key to a table in public called model.
So it's:
-Schemas
--public
---tables
----models
--api
---tables
Using SQLAlchemy I have the following class:
from sqlalchemy import create_engine, MetaData, Table, Column
class __PostgresService:
def __init__(self):
self.__client = create_engine("postgresql://postgres#localhost:5432/database")
metadata = MetaData(self.__client, schema="public")
self.__table = Table("training", metadata,
Column("id", String, primary_key=True, nullable=False),
Column("model_id", ForeignKey("model.id"), nullable=False),
schema="api")
metadata.create_all()
postgres_service = __PostgresService()
However upon launch I receive the following error:
sqlalchemy.exc.NoReferencedTableError: Foreign key associated with column 'training.model_id' could not find table 'public.model' with which to generate a foreign key to target column 'id'
It seems it does look for the correct thing but can't find it? I'm very confused as to why this is happening, especially because the error refers to not finding "public", which is created by default by postgres, rather than "api" which I created myself in pgAdmin.
Am I missing some cruicial config?
The error you are getting means that you are trying to create a foreign key referencing a table that SQLAlchemy does not know about. You can tell sqlalchemy about it by creating a Table associated with the same MetaData describing the referenced table. You can also do this using sqlalchemy's reflection capabilities. For example:
from sqlalchemy import create_engine, MetaData, Table, Column
class __PostgresService:
def __init__(self):
self.__client = create_engine("postgresql://postgres#localhost:5432/database")
metadata = MetaData(self.__client, schema="public")
metadata.reflect(schema="public", only=["model"])
self.__table = Table("training", metadata,
Column("id", String, primary_key=True, nullable=False),
Column("model_id", ForeignKey("model.id"), nullable=False),
schema="api")
metadata.create_all()
postgres_service = __PostgresService()
By default, MetaData.create_all() will check for the existence of tables first, before creating them, but you can also specify the exact tables to create: metadata.create_all(tables=[self.__table])
Running into something guys and was hoping to get some ideas/help.
I have a database with the tree structure where leaf can participate in the several parents as a foreign key. The typical example is a city, which belongs to the country and to the continent. Needless to say that countries and continents should not be repeatable, hence before adding another city I need to find an object in the DB. If it doesn't exist I have to create it, but if for instance country doesn't exist yet, then I have to check for the continent and if this one doesn't exist then I have to have creation process for it.
So far I got around with the creation of a whole bunch of items if I run it from the single file, but if I push the SQL alchemy code into module the story becomes different. For some reason meta scope becomes limited and if the table doesn't exist yet, then the code start throwing ProgrammingError exceptions if I query for the foreign key presence (from the city for the country). I have intercepted it and in the __init__ class constructor of the class I am looking for (country) I am checking if the table exists and creating it if doesn't. Two things I have a problem with and need an advice on:
1) Verification of the table is inefficient - I am working with the Base.metadata.sorted_tables array through which I have to look through and figure out if the table structure is the one that matches my class __tablename__. Such as:
for table in Base.metadata.sorted_tables:
# Find a right table in the list of tables
if table.name == self.__tablename__:
if __DEBUG__:
print 'DEBUG: Found table {} that equal to the class table {}'.format(table.name, self.__tablename__)
if not table.exists():
session.get_bind().execute(table.create())
Needless to say, this takes time I am looking for more efficient way to do the same.
2) The second issue is with the inheritance of the declarative base (declarative_base()) with respect to the OOP in Python. I want to take some of the code repetitions away and pull them into one class from which the other classes will be derived from. For instance code above can be taken out into the separate function and have something like this:
Base = declarative_base()
class OnDemandTables(Base):
__tablename__ = 'no_table'
# id = Column(Integer, Sequence('id'), nullable=False, unique=True, primary_key=True, autoincrement=True)
def create_my_table(self, session):
if __DEBUG__:
print 'DEBUG: Creating tables for the class {}'.format(self.__class__)
print 'DEBUG: Base.metadata.sorted_tables exists returns {}'.format(Base.metadata.sorted_tables)
for table in Base.metadata.sorted_tables:
# Find a right table in the list of tables
if table.name == self.__tablename__:
if __DEBUG__:
print 'DEBUG: Found table {} that equal to the class table {}'.format(table.name, self.__tablename__)
if not table.exists():
session.get_bind().execute(table.create())
class Continent(OnDemandTables):
__tablename__ = 'continent'
id = Column(Integer, Sequence('id'), nullable=False, unique=True, primary_key=True, autoincrement=True)
name = Column(String(64), unique=True, nullable=False)
def __init__(self, session, continent_description):
if type(continent_description) != dict:
raise AttributeError('Continent should be described by the dictionary!')
else:
self.create_my_table(session)
if 'continent' not in continent_description:
raise ReferenceError('No continent can be created without a name!. Dictionary is {}'.
format(continent_description))
else:
self.name = continent_description['continent']
print 'DEBUG: Continent name is {} '.format(self.name)
The problem here is that the metadata is trying to link unrelated classes together and requires __tablename__ and some index column to be present in the parent OnDemandTables class, which doesn't make any sense to me.
Any ideas?
Cheers
Wanted to post the solution here for the rest of the gang to keep it in mind. Apparently, SQLAlchemy doesn't see the classes in the module if they are not being used, so to say. After couple days of trying to work around things, the simplest solution that I found was to do it in a semi-manual way - not rely on the ORM to construct and build-up the database for you, but rather do this part in a sort of manual approach using class methods. The code is:
__DEBUG__ = True
from sqlalchemy import String, Integer, Column, ForeignKey, BigInteger, Float, Boolean, Sequence
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import relationship
from sqlalchemy.orm.exc import MultipleResultsFound, NoResultFound
from sqlalchemy.exc import ProgrammingError
from sqlalchemy import create_engine, schema
from sqlalchemy.orm import sessionmaker
Base = declarative_base()
engine = create_engine("mysql://test:test123#localhost/test", echo=True)
Session = sessionmaker(bind=engine, autoflush=False)
session = Session()
schema.MetaData.bind = engine
class TemplateBase(object):
__tablename__ = None
#classmethod
def create_table(cls, session):
if __DEBUG__:
print 'DEBUG: Creating tables for the class {}'.format(cls.__class__)
print 'DEBUG: Base.metadata.sorted_tables exists returns {}'.format(Base.metadata.sorted_tables)
for table in Base.metadata.sorted_tables:
# Find a right table in the list of tables
if table.name == cls.__tablename__:
if __DEBUG__:
print 'DEBUG: Found table {} that equal to the class table {}'.format(table.name, cls.__tablename__)
if not table.exists():
if __DEBUG__:
print 'DEBUG: Session is {}, engine is {}, table is {}'.format(session, session.get_bind(), dir(table))
table.create()
#classmethod
def is_provisioned(cls):
for table in Base.metadata.sorted_tables:
# Find a right table in the list of tables
if table.name == cls.__tablename__:
if __DEBUG__:
print 'DEBUG: Found table {} that equal to the class table {}'.format(table.name, cls.__tablename__)
return table.exists()
class Continent(Base, TemplateBase):
__tablename__ = 'continent'
id = Column(Integer, Sequence('id'), nullable=False, unique=True, primary_key=True, autoincrement=True)
name = Column(String(64), unique=True, nullable=False)
def __init__(self, session, provision, continent_description):
if type(continent_description) != dict:
raise AttributeError('Continent should be described by the dictionary!')
else:
if 'continent' not in continent_description:
raise ReferenceError('No continent can be created without a name!. Dictionary is {}'.
format(continent_description))
else:
self.name = continent_description['continent']
if __DEBUG__:
print 'DEBUG: Continent name is {} '.format(self.name)
It gives the following:
1. Class methods is_provisioned and create_table can be called during initial code start and will reflect the database state
2. Class inheritance is done from the second class where these methods are being kept and which is not interfering with the ORM classes, hence is not being linked.
As the result of the Base.metadata.sorted_tables loop is just a class table, the code can be optimized even further removing the loop. The following action would be to organize classes to have their tables checked and possibly created in a form of a list with keeping in mind their linkages and then loop through them using is_provisioned and, if necessary, create table methods.
Hope it helps the others.
Regards
I'm using SQL Alchemy and have some schema's that are account specific. The name of the schema is derived using the account ID, so I don't have the name of the schema until I hit my application service or repository layer. I'm wondering if it's possible to run a query against an entity that has it's schema dynamically set at runtime?
I know I need to set the __table_args__['schema'] and have tried doing that using the type() built-in, but I always get the following error:
could not assemble any primary key columns for mapped table
I'm ready to give up and just write straight sql, but I really hate to do that. Any idea how this can be done? I'm using SA 0.99 and I do have a PK mapped.
Thanks
from sqlalchemy 1.1,
this can be done easily using using schema_translation_map.
https://docs.sqlalchemy.org/en/11/changelog/migration_11.html#multi-tenancy-schema-translation-for-table-objects
One option would be to reflect the particular account-dependent tables. Here is the SqlAlchemy Documentation on the matter.
Alternatively, You can create the table with a static schema attribute and update it as needed at runtime and run the queries you need to. I can't think of a non-messy way to do this. So here's the messy option
Use a loop to update the schema property in each table definition whenever the account is switched.
add all the tables that are account-specific to a list.
if the tables are expressed in the declarative syntax, then you have to modify the DeclarativeName.__table__.schema attribute. I'm not sure if you need to also modify DeclarativeName.__table_args__['schema'], but I guess it won't hurt.
If the tables are expressed in the old style Table syntax, then you have to modify the Table.schema attribute.
If you're using text for any relationships or foreign keys, then that will break, and you have to inspect each table for such hard coded usage and change them
example
user_id = Column(ForeignKey('my_schema.user.id')) needs to be written as user_id = Column(ForeignKey(User.id)). Then you can change the schema of User to my_new_schema. Otherwise, at query time sqlalchemy will be confused because the foreign key will point to my_schema.user.id while the query would point to my_new_schema.user.
I'm not sure if more complicated relationships can be expressed without the use of plain text, so I guess that's the limit to my proposed solution.
Here's an example I wrote up in the terminal:
>>> from sqlalchemy import Column, Table, Integer, String, select, ForeignKey
>>> from sqlalchemy.orm import relationship, backref
>>> from sqlalchemy.ext.declarative import declarative_base
>>> B = declarative_base()
>>>
>>> class User(B):
... __tablename__ = 'user'
... __table_args__ = {'schema': 'first_schema'}
... id = Column(Integer, primary_key=True)
... name = Column(String)
... email = Column(String)
...
>>> class Posts(B):
... __tablename__ = 'posts'
... __table_args__ = {'schema':'first_schema'}
... id = Column(Integer, primary_key=True)
... user_id = Column(ForeignKey(User.id))
... text = Column(String)
...
>>> str(select([User.id, Posts.text]).select_from(User.__table__.join(Posts)))
'SELECT first_schema."user".id, first_schema.posts.text \nFROM first_schema."user" JOIN first_schema.posts ON first_schema."user".id = first_schema.posts.user_id'
>>> account_specific = [User, Posts]
>>> for Tbl in account_specific:
... Tbl.__table__.schema = 'second_schema'
...
>>> str(select([User.id, Posts.text]).select_from(User.__table__.join(Posts)))
'SELECT second_schema."user".id, second_schema.posts.text \nFROM second_schema."user" JOIN second_schema.posts ON second_schema."user".id = second_schema.posts.user_id'
As you see the same query refers to the second_schema after I update the table's schema attribute.
edit: Although you can do what I did here, using the schema translation map as shown in the the answer below is the proper way to do it.
They are set statically. Foreign keys needs the same treatment, and I have an additional issue, in that I have multiple schemas that contain multiple tables so I did this:
from sqlalchemy.ext.declarative import declarative_base
staging_dbase = declarative_base()
model_dbase = declarative_base()
def adjust_schemas(staging, model):
for vv in staging_dbase.metadata.tables.values():
vv.schema = staging
for vv in model_dbase.metadata.tables.values():
vv.schema = model
def all_tables():
return staging_dbase.metadata.tables.union(model_dbase.metadata.tables)
Then in my startup code:
adjust_schemas(staging=staging_name, model=model_name)
You can mod this for a single declarative base.
I'm working on a project in which I have to create postgres schemas and tables dynamically and then insert data in proper schema. Here is something I have done maybe it will help someone:
import sqlalchemy
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from app.models.user import User
engine_uri = "postgres://someusername:somepassword#localhost:5432/users"
engine = create_engine(engine_uri, pool_pre_ping=True)
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
def create_schema(schema_name: str):
"""
Creates a new postgres schema
- **schema_name**: name of the new schema to create
"""
if not engine.dialect.has_schema(engine, schema_name):
engine.execute(sqlalchemy.schema.CreateSchema(schema_name))
def create_tables(schema_name: str):
"""
Create new tables for postgres schema
- **schema_name**: schema in which tables are to be created
"""
if (
engine.dialect.has_schema(engine, schema_name) and
not engine.dialect.has_table(engine, str(User.__table__.name))
):
User.__table__.schema = schema_name
User.__table__.create(engine)
def add_data(schema_name: str):
"""
Add data to a particular postgres schema
- **schema_name**: schema in which data is to be added
"""
if engine.dialect.has_table(engine, str(User.__table__.name)):
db = SessionLocal()
db.connection(execution_options={
"schema_translate_map": {None: schema_name}},
)
user = User()
user.name = "Moin"
user.salary = 10000
db.add(user)
db.commit()
I have Table
# File : MyRelations.py
ACC_ADD_TABLE = Table('acc_add_rel', METADATA,
Column('acc_id', ForeignKey('acc.id'),
nullable=False),
Column('add_id', ForeignKey('address.id'),
nullable=False),
PrimaryKeyConstraint('add_id', 'acc_id'),
)
# File : Address.py
class Address(Base):
id = Column(Integer, primary_key=True,)
type = Column(String(length=10), nullable=False)
# File : Account.py
class Account(Base):
id = Column(Integer, primary_key=True,)
addresses = relationship('Address',
secondary=ACC_ADD_TABLE
)
# default_address = relationship('Address',
# secondary=ACC_ADD_TABLE,
# primaryjoin=and_("ACC_ADD_TABLE.add_id==Address.id",
# "ACC_ADD_TABLE.acc_id==Account.id",
# "Address.type='default'")
# )
As per the example I want to access the all default addresses in account. I can use declared_attr or can write the function but is there any way to combine Table and Class attribute in single and_ operation?
Note: Address.py and Account.py both are different files and due to cycle dependency I cant import any model in other model
Thx for you help.
This works without requiring an import:
default_address = relationship('Address',
secondary=ACC_ADD_TABLE,
primaryjoin="acc.c.id==acc_add_rel.c.acc_id",
secondaryjoin="and_(address.c.id==acc_add_rel.c.add_id, address.c.type=='default')",
#uselist = True,
)
If you are certain that there is only one default address, you might use uselist=True for convenience.
Sometimes I prefer the other structure for such situations though: add a column to the Account table: default_address_id and build 1-[0..1] relationship based on this column, still checking that the referenced Address is also part of Account.addresses M-N relationship.
On the side note, a typo: in your (commented) code you should use == instead of = in "Address.type='default'". This does not solve the problem though.
I've got a sqlalchemy model that is set up like this:
class Entry(Base):
__tablename__ = 'entries'
__table__ = Table('entries', Base.metadata,
Column('id', Integer, primary_key=True, unique=True),
Column('user_id', Integer, ForeignKey('users.id', onupdate="CASCADE", ondelete="RESTRICT")),
Column('title', String(128)),
Column('slug', String(128), index=True),
Column('url', String(256), index=True),
Column('entry', Text),
Column('cached_entry', Text),
Column('created', DateTime, server_default=text('current_timestamp')),
Column('modified', DateTime, server_onupdate=text('current_timestamp')),
Column('pubdate', DateTime),
)
What I would like is that when I update entry that cached_entry gets re-generated, cached_entry is the markdown parsed version of entry. Basically I am caching the output of the markdown parsing so that I don't have to do it on each showing of the entry. I've ttried using #hybrid_method however that didn't seem to work as that is not stored in the database at all. I've got it working on Google AppEngine, but I can't seem to figure out how to do the same thing using SQLAlchemy.
I really would prefer not to have to add a function to the class that is used instead of the names in the model because it is harder to enforce it from an application standpoint, I don't want to accidentally miss something.
#hybrid_descriptor certainly does it using the form described at http://www.sqlalchemy.org/docs/orm/mapper_config.html#using-descriptors . You assign to the database-mapped attribute, which you can map under a different name - since you're using the __table__, you can use a form like:
class Entry(Base):
__table__ = ...
_entry = __table__.c.entry
#hybrid_property
def entry(self):
return self._entry
#entry.setter
def entry(self, value):
self._entry = value
self.cached_entry = markdown(value)
Another is to use the before_insert and before_update events to populate the column at flush time - this is a simple approach but has the disadvantage that you have to wait for a flush() for it to happen.
I think the quickest way for an "on-set" is to use #validates:
from sqlalchemy.orm import validates
class Entry(Base):
__table__ = ...
#validates('entry')
def _set_entry(self, key, value):
self.cached_entry = markdown(value)
return value