How to keep session active for long time in sqlalchemy? - python

I have a code that runs a query from a query list. These query are long and take quite a long time to execute. Since I am executing these query in a loop, the session seems to expire and I get a error telling me that the connection to the server was lost.
Then I created the session as well as engine inside the loop (I closed the session and disposed the engine at the end of the loop.) I have understood that creating new connection is an expensive operation.
How can I re-use the connection in this case so that I do not have to create the session and engine each time?
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
# an Engine, which the Session will use for connection
# resources
some_engine = create_engine('mysql://user:password#localhost/')
# create a configured "Session" class
Session = sessionmaker(bind=some_engine)
# create a Session
session = Session()
for long_query in long_query_list:
# work with sess
session.execute(long_query)
session.commit()

Related

SQLAlchemy not identifying Python pool threads as seperate process

I am trying to convert my single threaded application to multi threaded application which uses database using SQLAlchemy. And I found that SQLAlchemy session is not thread safe. So we need to use scoped_session factory for thread safe db access.
Below is my input dataset
input_list = [data1, data2, data3, data4, data5]
Single thread application
from sqlalchemy.orm import sessionmaker, scoped_session
Session = sessionmaker(bind=engine_url)
for data in input_list:
def myfunction(data):
db_session = Session()
print(db_session)
# use db_session to query/store the data
When I try to convert it to multithreaded application
from sqlalchemy.orm import sessionmaker, scoped_session
Session = scoped_session(sessionmaker(bind=engine_url))
def myfunction(data):
db_session = Session()
print(db_session)
# use db_session to query/store the data
def myfunction_parallel():
with ThreadPool(4) as pool:
output = pool.map(myfunction, input_list)
In multithread variant, I am getting db_session as same object, but my expectation is that there should be a new session object created for each thread and the session should be different?
The scoped session registry registers session for each thread that requests one. This enables code to call db_session = Session() and get the expected session for the thread.
However it's application's responsibility to inform the session registry when a session is no longer required. The application does this by calling Session.remove(), as documented here:
The scoped_session.remove() method first calls Session.close() on the current Session, which has the effect of releasing any connection/transactional resources owned by the Session first, then discarding the Session itself. “Releasing” here means that connections are returned to their connection pool and any transactional state is rolled back, ultimately using the rollback() method of the underlying DBAPI connection.
At this point, the scoped_session object is “empty”, and will create a new Session when called again.
This code should work as expected:
def myfunction(data):
db_session = Session()
print(db_session)
# use db_session to query/store the data
Session.remove()

Issue with Stale data Flask/SqlAlchemy

I have the following set up for which on session.query() SqlAlchemy returns stale data:
Web application running on Flask with Gunicorn + supervisor.
one of the services is composed in this way:
app.py:
#app.route('/api/generatepoinvoice', methods=["POST"])
#auth.login_required
def generate_po_invoice():
try:
po_id = request.json['po_id']
email = request.json['email']
return jsonify(response=POInvoiceGenerator.get_invoice(po_id, email))
except Exception as ex:
app.logger.error("generate_po_invoice(): " + ex.message)
in another folder i have the database related stuff:
DatabaseModels (folder)
|-->Model.py
|-->Connection.py
that's what is contained in the connection.py file:
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker, scoped_session
from sqlalchemy.ext.declarative import declarative_base
engine = create_engine(DB_BASE_URI, isolation_level="READ COMMITTED")
Session = scoped_session(sessionmaker(bind=engine))
session = Session()
Base = declarative_base()
and thats an extract of the model.py file:
from DatabaseModels.Connection import Base
from sqlalchemy import Column, String, etc...
class Po(Base):
__tablename__ = 'PLC_PO'
id = Column("POId", Integer, primary_key=True)
code = Column("POCode", String(50))
etc...
Then i have another file POInvoiceGenerator.py
that contains the call to the database for fetching some data:
import DatabaseModels.Connection as connection
import DatabaseModels.model as model
def get_invoice(po_code, email):
try:
po_code = po_code.strip()
PLCConnection.session.expire_all()
po = connection.session.query(model.Po).filter(model.Po.code == po_code).first()
except Exception as ex:
logger.error("get_invoice(): " + ex.message)
in subsequent users calls to this service sometimes i start to get errors like: could not find data in the db for that specific code and so on. Like if the data are stale and so on.
My first approach was to add isolation_level="READ COMMITTED" to the engine declaration and then to create a scoped session, but the stale data reading keeps appening.
Is there anyone that had any idea if my setup is wrong (the session and the model are reused among multiple methods and files)
Thanks in advance.
even if the solution pointed by #TonyMountax seems valid and made me discover something that i didn't know about SqlAlchemy, In the end i opted for something different.
I figured out that the connection established by SqlAlchemy was durable since it was created from a pool of connection everytime, this somehow was causing the data to be stale.
i added a NullPool to my code:
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker, scoped_session
from sqlalchemy.pool import NullPool
engine = create_engine(DB_URI, isolation_level="READ COMMITTED", poolclass=NullPool)
Session = scoped_session(sessionmaker(bind=engine))
session = Session()
and then i'm calling a session close for every query that i make:
session.query("some query..")
session.close()
this will cause SqlAlchemy to create a new connection every time and get fresh data from the db.
Hope that this is the correct way to use it and that might be useful to someone else.
The way you instantiate your database connections means that they are reused for the next request, and they have some state left from the previous request. SQLAlchemy uses a concept of sessions to interact with the database, so that your data does not abruptly change in a single request even if you happen to perform the same query twice. This makes sense when you are using the ORM query features. For instance, if you were to query len(User.friendlist) twice during the same session, but a friend request was accepted during the request, then it will still show the same number in both locations.
To fix this, you must set up the session on first request, then you must tear it down when the request is finished. To do so is not trivial, but there is a well-established project that does it already: Flask-SQLAlchemy. It's from Pallets, the people behind Flask itself and Jinja2.

How does Flask start a new SQLAlchemy transaction at the start of each request?

I tried to totally seperate Flask and SQLAlchemy using this method but Flask still seems to be able to detect my database and start a new transaction at the beginning of each request.
The db.py file creates a new session and defines a simple model of a table:
from sqlalchemy import create_engine
from sqlalchemy.orm import scoped_session, sessionmaker
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, String
engine = create_engine("mysql://web:kingtezdu#localhost/web_unique")
print("creating new session")
db_session = scoped_session(sessionmaker(bind=engine))
Base = declarative_base()
Base.query = db_session.query_property()
# define model of 'persons' table
class Person(Base):
__tablename__ = "persons"
name = Column(String(30), primary_key=True)
def __repr__(self):
return "Person(\"{0.name}\")".format(self)
# create table
Base.metadata.create_all(bind=engine)
And app.py, a simple Flask application using the SQLAlchemy session and model:
from flask import Flask, escape
app = Flask(__name__)
# importing new session
from db import db_session, Person
# registering for app teardown to remove session
#app.teardown_appcontext
def shutdown_session(exception=None):
db_session.remove()
#app.route("/query")
def query():
# query all persons in the database
all_persons = Person.query.all()
print all_persons
return "" # we use the console output
if __name__ == "__main__":
app.run(debug=True)
Let's run this:
$ python app.py
creating new session
* Running on http://127.0.0.1:5000/
* Restarting with reloader
creating new session
Weired enough it runs db.py two times but we just ignore this, let's access the webpage /query:
[]
127.0.0.1 - - [23/Dec/2015 18:20:14] "GET /query HTTP/1.1" 200 -
We can see that our request was answered, though we only use the console output. There is no Person in the database yet, let's add one:
mysql> INSERT INTO persons (name) VALUES ("Marie");
Query OK, 1 row affected (0.11 sec)
Marie is part of the database now so we reload the webpage:
[Person("Marie")]
127.0.0.1 - - [23/Dec/2015 18:24:48] "GET /query HTTP/1.1" 200 -
As you can see the session already knows about Marie. Flask didn't create a new session. That means that there was a new transaction started. Contrast this to the plan python example below to see the difference.
My question is how Flask is able to start a new transaction on the begin of each request. Flask shouldn't know about the database but seems to be able to change something about it's behaviour.
In case you don't know what a SQLAlchemy transaction is read this paragraph extracted from Managing Transactions:
When the transactional state is completed after a rollback or commit,
the Session releases all Transaction and Connection resources, and
goes back to the “begin” state, which will again invoke new Connection
and Transaction objects as new requests to emit SQL statements are
received.
So a transaction is ended by a commit and will cause a new connection to be set up which will then make the session read the database again. In reality this means that you have to commit when you want to see changes made to the database:
First in interactive python mode:
>>> from db import db_session, Person
creating new session
>>> Person.query.all()
[]
Switch over to MySQL and insert a new Person:
mysql> INSERT INTO persons (name) VALUES ("Paul");
Query OK, 1 row affected (0.03 sec)
Finally try to load Paul into our session:
>>> Person.query.all()
[]
>>> db_session.commit()
>>> Person.query.all()
[Person("Paul")]
I think the issue here is that scoped_session somewhat hides what happens to the actual sessions in use. When your teardown handler
# registering for app teardown to remove session
#app.teardown_appcontext
def shutdown_session(exception=None):
db_session.remove()
runs at the end of each request, you call db_session.remove() which disposes of the session used in that particular request along with any transaction context. See http://docs.sqlalchemy.org/en/latest/orm/contextual.html for the details, particularly
The scoped_session.remove() method first calls Session.close() on the
current Session, which has the effect of releasing any
connection/transactional resources owned by the Session first, then
discarding the Session itself. “Releasing” here means that connections
are returned to their connection pool and any transactional state is
rolled back, ultimately using the rollback() method of the underlying
DBAPI connection.

sqlAlchemy does not recognise changes to DB made outside of session

Something peculiar I've noticed is that any changes committed to the DB outside of the session (such as ones made in MySQL's Workbench) are not recognised in the sqlAlchemy session. I have to close and open a new session for sqlAlchemy to recognise it.
For example, a row I deleted manually is still fetched from sqlAlchemy.
This is how I initialise the session:
engine = create_engine('mysql://{}:{}#{}/{}'.format(username, password, host, schema), pool_recycle=3600)
Session = sessionmaker(bind=engine)
session = Session()
metadata = MetaData()
How can I get sqlAlchemy to recognise them?
My sqlAlchemy version is 0.9.4 and my MySQL version is 5.5.34. We use only sqlAlchemy's Core (no ORM).
To be able to read committed data from others transactions you'll need to set transaction isolation level to READ COMMITTED. For sqlalchemy and mysql:
To set isolation level using create_engine():
engine = create_engine(
"mysql://scott:tiger#localhost/test",
isolation_level="READ COMMITTED")
To set using per-connection execution options:
connection = engine.connect()
connection = connection.execution_options(
isolation_level="READ COMMITTED")
source

Zombie Connection in SQLAlchemy

DBSession = sessionmaker(bind=self.engine)
def add_person(name):
s = DBSession()
s.add(Person(name=name))
s.commit()
Everytime I run add_person() another connection is created with my postgreSQL DB.
Looking at:
SELECT count(*) FROM pg_stat_activity;
I see the count going up, until I get a Remaining connection slots are reserved for non-replication superuser connections error.
How do I kill those connections? Am I wrong in opening a new session everytime I want to add a Person record?
In general, you should keep your Session object (here DBSession) separate from any functions that make changes to the database. So in your case you might try something like this instead:
DBSession = sessionmaker(bind=self.engine)
session = DBSession() # create your session outside of functions that will modify database
def add_person(name):
session.add(Person(name=name))
session.commit()
Now you will not get new connections every time you add a person to the database.

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