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We host a multitenant app with SQLAlchemy and postgres. I am looking at moving from having separate databases for each tenant to a single database with multiple schemas. Does SQLAlchemy support this natively? I basically just want every query that comes out to be prefixed with a predetermined schema... e.g
select * from client1.users
instead of just
select * from users
Note that I want to switch the schema for all tables in a particular request/set of requests, not just a single table here and there.
I imagine that this could be accomplished with a custom query class as well but I can't imagine that something hasn't been done in this vein already.
well there's a few ways to go at this and it depends on how your app is structured. Here is the most basic way:
meta = MetaData(schema="client1")
If the way your app runs is one "client" at a time within the whole application, you're done.
But what may be wrong with that here is, every Table from that MetaData is on that schema. If you want one application to support multiple clients simultaneously (usually what "multitenant" means), this would be unwieldy since you'd need to create a copy of the MetaData and dupe out all the mappings for each client. This approach can be done, if you really want to, the way it works is you'd access each client with a particular mapped class like:
client1_foo = Client1Foo()
and in that case you'd be working with the "entity name" recipe at http://www.sqlalchemy.org/trac/wiki/UsageRecipes/EntityName in conjunction with sometable.tometadata() (see http://docs.sqlalchemy.org/en/latest/core/metadata.html#sqlalchemy.schema.Table.tometadata).
So let's say the way it really works is multiple clients within the app, but only one at a time per thread. Well actually, the easiest way to do that in Postgresql would be to set the search path when you start working with a connection:
# start request
# new session
sess = Session()
# set the search path
sess.execute("SET search_path TO client1")
# do stuff with session
# close it. if you're using connection pooling, the
# search path is still set up there, so you might want to
# revert it first
sess.close()
The final approach would be to override the compiler using the #compiles extension to stick the "schema" name in within statements. This is doable, but would be tricky as there's not a consistent hook for everywhere "Table" is generated. Your best bet is probably setting the search path on each request.
If you want to do this at the connection string level then use the following:
dbschema='schema1,schema2,public' # Searches left-to-right
engine = create_engine(
'postgresql+psycopg2://dbuser#dbhost:5432/dbname',
connect_args={'options': '-csearch_path={}'.format(dbschema)})
But, a better solution for a multi-client (multi-tenant) application is to configure a different db user for each client, and configure the relevant search_path for each user:
alter role user1 set search_path = "$user", public
It can now be done using schema translation map in Sqlalchemy 1.1.
class User(Base):
__tablename__ = 'user'
id = Column(Integer, primary_key=True)
__table_args__ = {'schema': 'per_user'}
On each request, the Session can be set up to refer to a different schema each time:
session = Session()
session.connection(execution_options={
"schema_translate_map": {"per_user": "account_one"}})
# will query from the ``account_one.user`` table
session.query(User).get(5)
Referred it from the SO answer here.
Link to the Sqlalchemy docs.
You may be able to manage this using the sqlalchemy event interface. So before you create the first connection, set up a listener along the lines of
from sqlalchemy import event
from sqlalchemy.pool import Pool
def set_search_path( db_conn, conn_proxy ):
print "Setting search path..."
db_conn.cursor().execute('set search_path=client9, public')
event.listen(Pool,'connect', set_search_path )
Obviously this needs to be executed before the first connection is created (eg in the application initiallization)
The problem I see with the session.execute(...) solution is that this executes on a specific connection used by the session. However I cannot see anything in sqlalchemy that guarantees that the session will continue to use the same connection indefinitely. If it picks up a new connection from the connection pool, then it will lose the search path setting.
I am needing an approach like this in order to set the application search_path, which is different to the database or user search path. I'd like to be able to set this in the engine configuration, but cannot see a way to do this. Using the connect event does work. I'd be interested in a simpler solution if anyone has one.
On the other hand, if you are wanting to handle multiple clients within an application, then this won't work - and I guess the session.execute(...) approach may be the best approach.
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
connection = engine.connect().execution_options(
schema_translate_map={None: "user_schema_one"})
result = connection.execute(user_table.select())
Here is a detailed reviews of all options available:
https://github.com/sqlalchemy/sqlalchemy/issues/4081
It's possible to solve this on DB level. I suppose you have a dedicated user for your application who is granted some privileges on the schema. Just set search_path for him to this schema:
ALTER ROLE your_user IN DATABASE your_db SET search_path TO your_schema;
There is a schema property in Table definitions
I'm not sure if it works but you can try:
Table(CP.get('users', metadata, schema='client1',....)
I tried:
con.execute('SET search_path TO {schema}'.format(schema='myschema'))
and that didn't work for me. I then used the schema= parameter in the init function:
# We then bind the connection to MetaData()
meta = sqlalchemy.MetaData(bind=con, reflect=True, schema='myschema')
Then I qualified the table with the schema name
house_table = meta.tables['myschema.houses']
and everything worked.
You can just change your search_path. Issue
set search_path=client9;
at the start of your session and then just keep your tables unqualified.
You can also set a default search_path at a per-database or per-user level. I'd be tempted to set it to an empty schema by default so you can easily catch any failure to set it.
http://www.postgresql.org/docs/current/static/ddl-schemas.html#DDL-SCHEMAS-PATH
I found none of the above answers worked with SqlAlchmeny 1.2.4. This is the solution that worked for me.
from sqlalchemy import MetaData, Table
from sqlalchemy import create_engine
def table_schemato_psql(schema_name, table_name):
conn_str = 'postgresql://{username}:{password}#localhost:5432/{database}'.format(
username='<username>',
password='<password>',
database='<database name>'
)
engine = create_engine(conn_str)
with engine.connect() as conn:
conn.execute('SET search_path TO {schema}'.format(schema=schema_name))
meta = MetaData()
table_data = Table(table_name, meta,
autoload=True,
autoload_with=conn,
postgresql_ignore_search_path=True)
for column in table_data.columns:
print column.name
I use the following pattern.
engine = sqlalchemy.create_engine("postgresql://postgres:mypass#172.17.0.2/mydb")
for schema in ['schema1', 'schema2']:
engine.execute(CreateSchema(schema))
tmp_engine = engine.execution_options(schema_translate_map = { None: schema } )
Base.metadata.create_all(tmp_engine)
For anyone who is coming here, for a more general solution that can support MYSQL or Oracle, please refer to this guide.
So basically it set the schemas for the engine when the first connection to the database is made.
engine = create_engine("engine_url")
#event.listens_for(engine, "connect", insert=True)
def set_current_schema(dbapi_connection, connection_record):
cursor_obj = dbapi_connection.cursor()
cursor_obj.execute(f"USE {self.schemas_name}")
cursor_obj.close()
the query to execute depends is specific to the database you are using, so for PSQL you will have a different query, for ORACLE, you will have a different, etc.
The Flask tutorial (and many other tutorials out there) suggests that the engine, the db_session and the Base (an instance of declarative_metadata) are all created at import-time.
This creates some problems, one being, that the URI of the DB is hardcoded in the code and evaluated only once.
One solution is to wrap these calls in functions that accept the app as a parameter, which is what I've done. Mind you - each call caches the result in app.config:
def get_engine(app):
"""Return the engine connected to the database URI in the config file.
Store it in the config for later use.
"""
engine = app.config.setdefault(
'DB_ENGINE', create_engine(app.config['DATABASE_URI'](), echo=True))
return engine
def get_session(app):
"""Return the DB session for the database in use
Store it in the config for later use.
"""
engine = get_engine(app)
db_session = app.config.setdefault(
'DB_SESSION', scoped_session(sessionmaker(
autocommit=False, autoflush=False, bind=engine)))
return db_session
def get_base(app):
"""Return the declarative base to use in DB models.
Store it in the config for later use.
"""
Base = app.config.setdefault('DB_BASE', declarative_base())
Base.query = get_session(app).query_property()
return Base
In init_db, I call all those functions, but there's still code smell:
def init_db(app):
"""Initialise the database"""
create_db(app)
engine = get_engine(app)
db_session = get_session(app)
base = get_base(app)
if not app.config['TESTING']:
import flaskr.models
else:
if 'flaskr.models' not in sys.modules:
import flaskr.models
else:
import flaskr.models
importlib.reload(flaskr.models)
base.metadata.create_all(bind=engine)
The smell is of course the hoops I have to go through to import and create all models.
The reason for the code above is that, when unit testing, init_db is called once for each test (in setup(), as suggested in the same tutorial), but the import will only be performed the first time, and create_all will therefore work only that time.
Not only that, now with a session shared for the duration of the app, I have problems in parametrized negative unit tests (that is, parametrized unit tests that expect some sort of failures): the first instance of the test will trigger a failure (e.g. login failure, see test_login_validate_input in the tutorial) and exit correctly, while all subsequent will bail out early because the db_session should be rolled back first. Clearly there's something wrong with the DB initialization.
What is the Right Way(TM) to initialize the database?
I have eventually decided to refactor the app so that it uses Flask-SQLAlchemy.
In short, the app now does something like this:
from flask_sqlalchemy import SQLAlchemy
db = SQLAlchemy()
def create_app():
app = Flask(__name__)
db.init_app(app)
# ...
With the benefit of hindsight, it's definitely a cleaner approach.
What put me off at the start was this entry from the tutorial (bold is mine):
Because SQLAlchemy is a common database abstraction layer and object relational mapper that requires a little bit of configuration effort, there is a Flask extension that handles that for you. This is recommended if you want to get started quickly.
Which I somehow read as "Using the Flask-SQLAlchemy extension will allow you to cut some corners, which you'll probably end up paying for later".
It's very early stages, but so far no price to pay in terms of flexibility for using said extension.
I am writing an app in python flask-sqlalchemy with MySQL DB (https://flask-sqlalchemy.palletsprojects.com/en/2.x/) and I am wondering if I have to make "db.session.commit() or db.session.rollback()" after GET call, which only query DB .
For example:
#app.route('/getOrders')
def getOrders():
orders = Order.query.all()
# Do I have to put here "db.session.commit()" or "db.session.rollback" ?
return { 'orders': [order.serialize() for order in orders] }
orders = Order.query.all() is a SELECT query that could be extended to include additional filters (WHERE etc.). It doesn't alter the database, it simply reads values from it. You don't need to commit on a read for precisely that reason - what would you store other than "I just read this data"? Databases are concerned about this in other ways i.e. access permissions and logs.
Given the above, rollback doesn't make any sense because there are no changes to actually roll back.
Flask-SQLAlchemy does a bit of magic around sessions amongst other things. It's roughly equivalent to:
from sqlalchemy.orm import scoped_session, sessionmaker
Session = sessionmaker(bind=engine, autocommit=False, autoflush=False)
db_session = scoped_session(Session)
Followed with a method to close sessions:
def init_db(app):
app.teardown_appcontext(teardown_session)
def teardown_session(exception=None):
db_session.remove()
Bottom line being: no, you don't have to worry about commit or rollback here, even in SQL, and the session management (completely separate) is handled by Flask-SQLALchemy
We host a multitenant app with SQLAlchemy and postgres. I am looking at moving from having separate databases for each tenant to a single database with multiple schemas. Does SQLAlchemy support this natively? I basically just want every query that comes out to be prefixed with a predetermined schema... e.g
select * from client1.users
instead of just
select * from users
Note that I want to switch the schema for all tables in a particular request/set of requests, not just a single table here and there.
I imagine that this could be accomplished with a custom query class as well but I can't imagine that something hasn't been done in this vein already.
well there's a few ways to go at this and it depends on how your app is structured. Here is the most basic way:
meta = MetaData(schema="client1")
If the way your app runs is one "client" at a time within the whole application, you're done.
But what may be wrong with that here is, every Table from that MetaData is on that schema. If you want one application to support multiple clients simultaneously (usually what "multitenant" means), this would be unwieldy since you'd need to create a copy of the MetaData and dupe out all the mappings for each client. This approach can be done, if you really want to, the way it works is you'd access each client with a particular mapped class like:
client1_foo = Client1Foo()
and in that case you'd be working with the "entity name" recipe at http://www.sqlalchemy.org/trac/wiki/UsageRecipes/EntityName in conjunction with sometable.tometadata() (see http://docs.sqlalchemy.org/en/latest/core/metadata.html#sqlalchemy.schema.Table.tometadata).
So let's say the way it really works is multiple clients within the app, but only one at a time per thread. Well actually, the easiest way to do that in Postgresql would be to set the search path when you start working with a connection:
# start request
# new session
sess = Session()
# set the search path
sess.execute("SET search_path TO client1")
# do stuff with session
# close it. if you're using connection pooling, the
# search path is still set up there, so you might want to
# revert it first
sess.close()
The final approach would be to override the compiler using the #compiles extension to stick the "schema" name in within statements. This is doable, but would be tricky as there's not a consistent hook for everywhere "Table" is generated. Your best bet is probably setting the search path on each request.
If you want to do this at the connection string level then use the following:
dbschema='schema1,schema2,public' # Searches left-to-right
engine = create_engine(
'postgresql+psycopg2://dbuser#dbhost:5432/dbname',
connect_args={'options': '-csearch_path={}'.format(dbschema)})
But, a better solution for a multi-client (multi-tenant) application is to configure a different db user for each client, and configure the relevant search_path for each user:
alter role user1 set search_path = "$user", public
It can now be done using schema translation map in Sqlalchemy 1.1.
class User(Base):
__tablename__ = 'user'
id = Column(Integer, primary_key=True)
__table_args__ = {'schema': 'per_user'}
On each request, the Session can be set up to refer to a different schema each time:
session = Session()
session.connection(execution_options={
"schema_translate_map": {"per_user": "account_one"}})
# will query from the ``account_one.user`` table
session.query(User).get(5)
Referred it from the SO answer here.
Link to the Sqlalchemy docs.
You may be able to manage this using the sqlalchemy event interface. So before you create the first connection, set up a listener along the lines of
from sqlalchemy import event
from sqlalchemy.pool import Pool
def set_search_path( db_conn, conn_proxy ):
print "Setting search path..."
db_conn.cursor().execute('set search_path=client9, public')
event.listen(Pool,'connect', set_search_path )
Obviously this needs to be executed before the first connection is created (eg in the application initiallization)
The problem I see with the session.execute(...) solution is that this executes on a specific connection used by the session. However I cannot see anything in sqlalchemy that guarantees that the session will continue to use the same connection indefinitely. If it picks up a new connection from the connection pool, then it will lose the search path setting.
I am needing an approach like this in order to set the application search_path, which is different to the database or user search path. I'd like to be able to set this in the engine configuration, but cannot see a way to do this. Using the connect event does work. I'd be interested in a simpler solution if anyone has one.
On the other hand, if you are wanting to handle multiple clients within an application, then this won't work - and I guess the session.execute(...) approach may be the best approach.
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
connection = engine.connect().execution_options(
schema_translate_map={None: "user_schema_one"})
result = connection.execute(user_table.select())
Here is a detailed reviews of all options available:
https://github.com/sqlalchemy/sqlalchemy/issues/4081
It's possible to solve this on DB level. I suppose you have a dedicated user for your application who is granted some privileges on the schema. Just set search_path for him to this schema:
ALTER ROLE your_user IN DATABASE your_db SET search_path TO your_schema;
There is a schema property in Table definitions
I'm not sure if it works but you can try:
Table(CP.get('users', metadata, schema='client1',....)
I tried:
con.execute('SET search_path TO {schema}'.format(schema='myschema'))
and that didn't work for me. I then used the schema= parameter in the init function:
# We then bind the connection to MetaData()
meta = sqlalchemy.MetaData(bind=con, reflect=True, schema='myschema')
Then I qualified the table with the schema name
house_table = meta.tables['myschema.houses']
and everything worked.
You can just change your search_path. Issue
set search_path=client9;
at the start of your session and then just keep your tables unqualified.
You can also set a default search_path at a per-database or per-user level. I'd be tempted to set it to an empty schema by default so you can easily catch any failure to set it.
http://www.postgresql.org/docs/current/static/ddl-schemas.html#DDL-SCHEMAS-PATH
I found none of the above answers worked with SqlAlchmeny 1.2.4. This is the solution that worked for me.
from sqlalchemy import MetaData, Table
from sqlalchemy import create_engine
def table_schemato_psql(schema_name, table_name):
conn_str = 'postgresql://{username}:{password}#localhost:5432/{database}'.format(
username='<username>',
password='<password>',
database='<database name>'
)
engine = create_engine(conn_str)
with engine.connect() as conn:
conn.execute('SET search_path TO {schema}'.format(schema=schema_name))
meta = MetaData()
table_data = Table(table_name, meta,
autoload=True,
autoload_with=conn,
postgresql_ignore_search_path=True)
for column in table_data.columns:
print column.name
I use the following pattern.
engine = sqlalchemy.create_engine("postgresql://postgres:mypass#172.17.0.2/mydb")
for schema in ['schema1', 'schema2']:
engine.execute(CreateSchema(schema))
tmp_engine = engine.execution_options(schema_translate_map = { None: schema } )
Base.metadata.create_all(tmp_engine)
For anyone who is coming here, for a more general solution that can support MYSQL or Oracle, please refer to this guide.
So basically it set the schemas for the engine when the first connection to the database is made.
engine = create_engine("engine_url")
#event.listens_for(engine, "connect", insert=True)
def set_current_schema(dbapi_connection, connection_record):
cursor_obj = dbapi_connection.cursor()
cursor_obj.execute(f"USE {self.schemas_name}")
cursor_obj.close()
the query to execute depends is specific to the database you are using, so for PSQL you will have a different query, for ORACLE, you will have a different, etc.
I'm using SqlAlchemy to access multiple databases (on the same server). My current connection string is the following
connect_string = "mssql+pyodbc://{0}:{1}#{2}/{3}".format(USERNAME_R, PASSWORD_R, SERVER_R, DATABASE_R)
engine = create_engine(connect_string)
session = sessionmaker(bind=engine)()
Record = declarative_base(engine)
How do I modify this declaration to be able to connect to multiple databases on the same server (e.g. DATABASE1 & DATABASE2). It seems like this is pointing in the right direction, but it's not very clear and I'm not sure if it is specific to Flask:
https://pythonhosted.org/Flask-SQLAlchemy/binds.html
Hi you can achieve this using follwing .
engines = {
'drivers':create_engine('postgres://postgres:admin#localhost:5432/Drivers'),
'dispatch':create_engine('postgres://postgres:admin#localhost:5432/dispatch')
}
i have two databases in sever and two tables.After that you can using Routing class to route for specific database connection while making a query :
class RoutingSession(Session):
def get_bind(self, mapper=None, clause=None):
if mapper and issubclass(mapper.class_, drivers):
return engines['drivers']
elif self._flushing:
return engines['dispatch']
now you can fire queries accordingly for eg first you need to make a session using like this :
Session = sessionmaker(class_=RoutingSession)
session = Session()
driverssql = session.query(drivers).all()
this was you can use multiple database in sqlalchemy
Adding a bit more of insight, the official SQLAlchemy documentation now has a couple more strategies than the ones presented on the rest of the answers.
Just take a look at the following links:
Partitioning Strategies (e.g. multiple database backends per Session)
Session API - Session and sessionmaker() - 'binds' parameter
(A hand-wavy answer because of lack of time, sorry.)
Do not bind an engine to declarative_base. Inherit form just declarative_base().
Instead, pass a specific engine to sqlalchemy.orm.sessionmaker when creating a session. Create different transaction factories (that sessionmaker returns) for different engines. In your queries, use .with_session to bind to a specific session, and thus a specific engine.