I'm using fixtures with SQLAlchemy to create some integration tests.
I'd like to put SQLAlchemy into a "never commit" mode to prevent changes ever being written to the database, so that my tests are completely isolated from each other. Is there a way to do this?
My initial thoughts are that perhaps I could replace Session.commit with a mock object; however I'm not sure if there are other things that might have the same effect that I also need to mock if I'm going to go down that route.
The scoped session manager will by default return the same session object for each connection. Accordingly, one can replace .commit with .flush, and have that change persist across invocations to the session manager.
That will prevent commits.
To then rollback all changes, one should use session.transaction.rollback().
Related
In the case of sqlite, it is not clear whether we can easily commit right after each dataframe insert. (Assuming that auto-commit is off by default, following the python database wrapping convention).
Using the simplest sqlalchemy api flow ―
db_engine = db.create_engine()
for .....
# slowly compute some_df, takes a lot of time
some_df.to_sql(con = db_engine)
How can we make sure that every .to_sql is committed?
For motivation, imagine the particular use case being that each write reflects the result of a potentially very long computation and we do not want to lose a huge batch of such computations nor any single one of them, in case a machine goes down or in case the python sqlalchemy engine object is garbage collected before all its writes have actually drained in the database.
I believe auto-commit is off by default, and for sqlite, there is no way of changing that in the create_engine command. What might be the simplest, safest way for adding auto-commit behavior ― or explicitly committing after every dataframe write ― when using the simplistic .to_sql api?
Or must the code be refactored to use a different api flow to accomplish that?
You can set the connection to autocommit by:
db_engine = db_engine.execution_options(autocommit=True)
From https://docs.sqlalchemy.org/en/13/core/connections.html#understanding-autocommit:
The “autocommit” feature is only in effect when no Transaction has otherwise been declared. This means the feature is not generally used with the ORM, as the Session object by default always maintains an ongoing Transaction.
In your code you have not presented any explicit transactions, and so the engine used as the con is in autocommit mode (as implemented by SQLA).
Note that SQLAlchemy implements its own autocommit that is independent from the DB-API driver's possible autocommit / non-transactional features.
Hence the "the simplest, safest way for adding auto-commit behavior ― or explicitly committing after every dataframe write" is what you already had, unless to_sql() emits some funky statements that SQLA does not recognize as data changing operations, which it has not, at least of late.
It might be that the SQLA autocommit feature is on the way out in the next major release, but we'll have to wait and see.
I'm trying to use pyramid's transaction manager to commit the changes. Unfortunately every time, they're rolled back regardless of what I do.
I tried the simple:
def handle(conn):
conn.execute('''ALTER TABLE ....''')
with bootstrap(sys.argv[1]) as env:
with env['request'].tm:
handle(env['request'].dbsession)
As well as dropping down to connection and creating explicit transaction:
def handle(conn):
with conn.begin() as tran:
conn.execute('''ALTER TABLE ....''')
tran.commit()
with bootstrap(sys.argv[1]) as env:
with env['request'].tm:
handle(env['request'].dbsession.connection())
and a few other ways, but every time, I'm getting a ROLLBACK instead of a COMMIT.
Doing a simple commit at the end of the first case results in:
Error: Transaction must be committed using the transaction manager
I'm quite lost at what what is sqlalchemy actually doing in this case - why do I get a "success" with a rollback? What should I do to commit? What would it look like in case of a nested, explicit transaction inside handle?
As ilja said in the comments, the right answer is that when you're operating on the connection directly and not on the ORM session via ORM operations, it's not possible for zope.sqlalchemy to know whether you changed things or not. By default, zope.sqlalchemy requires you to either use the ORM or to mark the session changed manually.
from zope.sqlalchemy import mark_changed
mark_changed(env['request'].dbsession)
Alternatively, if this is a common pattern for you then you can configure zope.sqlalchemy to just always assume the session was changed and thus issue commits instead of rollbacks by default.
zope.sqlalchemy.register(..., initial_state='changed')
You already have a call like this somewhere in your code and you just need to add the initial_state attribute.
I have an endpoint to delete an object from my database. I delete it with the following code:
my_object = Object.query.get(id)
db.session.delete(my_object)
db.session.commit()
return json.dumps({'success': True}
I have an API test to test the endpoint where I create an object and then use the endpoint to delete it. I am trying to assert after the deletion happens it isn't in the database.
my_object = MyObject()
db.session.add(my_object)
db.session.commit()
response = requests.delete('{}/my-object/{}'.format(
os.environ.get('MY_URL'),
my_object.id
))
self.assertTrue(response.json()['success']) // this passes
self.assertEqual(200, response.status_code) // this passes
result = db.session.query(MyObject).get(my_object.id)
print(result.id) // prints the id of the job even though it is deleted from the database
I think this is related to some SQLAlchemy session caching. I have tried db.session.flush(), db.session.expire_all() to no avail. The object is actually being deleted from the database. So I would expect the query result to be None.
I see this in the docs but haven't full wrapped my head around it. when to commit and close a session
Thanks for any help.
So in your test code, you add the object to a session and commit it. It gets saved to the db, and is your session's identity map.
Then you hit your app, it has it's own session. It deletes the object and commits, now it's gone from the db. But...
Your previous session doesn't know anything about this, and when you use a .get(), it will give back what's in its identity map: a Python object with an ID. It won't refetch unless you close the session or force a refresh from the DB (I can't remember OTOH how to do this, but you can, it's in the docs somewhere). If you used a clean third session, it would have a fresh identity map and would not be holding onto a reference to the python object so you'd get what you expect, ie. no result. This is by design because the Identity Map allows SQLAlchemy to chain a bunch of changes together into one optimal SQL query that is only fired when you commit.
So yeah, you're seeing the fetch from the Identity Map which is still alive. (You can even pop it open in the interactive interpreter and poke around) And it makes sense, because say you have two threads of different web requests and one is part way doing some longer lived stuff with an object when another request deletes the object. The first thread shouldn't barf on the Python code working with the object, because that would just trigger random exceptions wherever you were in the code. It should just think that it can do its thing, and then fail on commit, triggering a rollback.
HTH
db.session.expunge_all()
"Remove all object instances from this Session..."
http://docs.sqlalchemy.org/en/latest/orm/session_api.html#sqlalchemy.orm.session.Session.expunge_all
Or simple trigger after each request db.session.remove()
For example in Flask with SQLAlchemy scoped_session:
#app.teardown_appcontext
def shutdown_session(exception=None):
db.session.remove()
"The scoped_session.remove() method, as always, removes the current Session associated with the thread, if any. However, one advantage of the threading.local() object is that if the application thread itself ends, the “storage” for that thread is also garbage collected. So it is in fact “safe” to use thread local scope with an application that spawns and tears down threads, without the need to call scoped_session.remove(). However, the scope of transactions themselves, i.e. ending them via Session.commit() or Session.rollback(), will usually still be something that must be explicitly arranged for at the appropriate time, unless the application actually ties the lifespan of a thread to the lifespan of a transaction."
http://docs.sqlalchemy.org/en/latest/orm/contextual.html#thread-local-scope
http://docs.sqlalchemy.org/en/latest/orm/contextual.html#using-thread-local-scope-with-web-applications
After a fair amount of reading and testing I found creating a new session to be the easiest solution. I wasn't able to figure out how to refresh the record from the database even though the record was stale.
Here is some reading I did:
when to commit and close a session
is the session a cache
is the session thread safe
understanding sqlalchemy session
Here is how I solved the problem by creating a new db connection and session using Flask-SQLAlchemy:
[my other imports...]
from flask.ext.sqlalchemy import SQLAlchemy
[my other code...]
def test_it_should_delete_my_object(self):
my_object = MyObject()
db.session.add(my_object)
db.session.commit()
response = requests.delete('{}/my-object/{}'.format(
os.environ.get('MY_URL'),
my_object.id
))
self.assertTrue(response.json()['success'])
self.assertEqual(200, response.status_code)
new_db = SQLAlchemy(app) // establishing a new connection
result = new_db.session.query(MyObject).get(my_object.id) // by using a new
self.assertIsNone(result)
Thank you all for the help. Gonna be doing more research on this.
I need to test Django application behavior for concurrent requests. I need to test is database data correct after that. As a cnclusion, I need to test and transactions mechanism. So let's use TransactionTestCase for that.
I spawned requests to database using threading and got 'DatabaseError: no such table: app_modelname exception' in threads because of automatic switching to in-memory database type (for SQLite by Django when running test).
Of course, I can specify 'TEST_NAME' for 'default' key in settings.DATABASES, and test will pass as expected. But this also used for all tests too, so tests running takes a much more time.
I thought about custom database router, but it seems to be very
hackish way to do that since I need to patch / mock a lot of
attributes in models to define is this executed in
TransactionTestCase or not.
There was also idea to use
override_settings but unfortunately it does not work (see
issue for details)
How I can specify (or create) not in-memory database (on hard drive) for just a few test cases (TransactionTestCase) and left others to run with in-memory database?
Any thoughts, ideas or code samples will be appreciated.
Thanks!
I am dealing with a doubt about sqlalchemy and objects refreshing!
I am in the situation in what I have 2 sessions, and the same object has been queried in both sessions! For some particular thing I cannot to close one of the sessions.
I have modified the object and commited the changes in session A, but in session B, the attributes are the initial ones! without modifications!
Shall I implement a notification system to communicate changes or there is a built-in way to do this in sqlalchemy?
Sessions are designed to work like this. The attributes of the object in Session B WILL keep what it had when first queried in Session B. Additionally, SQLAlchemy will not attempt to automatically refresh objects in other sessions when they change, nor do I think it would be wise to try to create something like this.
You should be actively thinking of the lifespan of each session as a single transaction in the database. How and when sessions need to deal with the fact that their objects might be stale is not a technical problem that can be solved by an algorithm built into SQLAlchemy (or any extension for SQLAlchemy): it is a "business" problem whose solution you must determine and code yourself. The "correct" response might be to say that this isn't a problem: the logic that occurs with Session B could be valid if it used the data at the time that Session B started. Your "problem" might not actually be a problem. The docs actually have an entire section on when to use sessions, but it gives a pretty grim response if you are hoping for a one-size-fits-all solution...
A Session is typically constructed at the beginning of a logical
operation where database access is potentially anticipated.
The Session, whenever it is used to talk to the database, begins a
database transaction as soon as it starts communicating. Assuming the
autocommit flag is left at its recommended default of False, this
transaction remains in progress until the Session is rolled back,
committed, or closed. The Session will begin a new transaction if it
is used again, subsequent to the previous transaction ending; from
this it follows that the Session is capable of having a lifespan
across many transactions, though only one at a time. We refer to these
two concepts as transaction scope and session scope.
The implication here is that the SQLAlchemy ORM is encouraging the
developer to establish these two scopes in his or her application,
including not only when the scopes begin and end, but also the expanse
of those scopes, for example should a single Session instance be local
to the execution flow within a function or method, should it be a
global object used by the entire application, or somewhere in between
these two.
The burden placed on the developer to determine this scope is one area
where the SQLAlchemy ORM necessarily has a strong opinion about how
the database should be used. The unit of work pattern is specifically
one of accumulating changes over time and flushing them periodically,
keeping in-memory state in sync with what’s known to be present in a
local transaction. This pattern is only effective when meaningful
transaction scopes are in place.
That said, there are a few things you can do to change how the situation works:
First, you can reduce how long your session stays open. Session B is querying the object, then later you are doing something with that object (in the same session) that you want to have the attributes be up to date. One solution is to have this second operation done in a separate session.
Another is to use the expire/refresh methods, as the docs show...
# immediately re-load attributes on obj1, obj2
session.refresh(obj1)
session.refresh(obj2)
# expire objects obj1, obj2, attributes will be reloaded
# on the next access:
session.expire(obj1)
session.expire(obj2)
You can use session.refresh() to immediately get an up-to-date version of the object, even if the session already queried the object earlier.
Run this, to force session to update latest value from your database of choice:
session.expire_all()
Excellent DOC about default behavior and lifespan of session
I just had this issue and the existing solutions didn't work for me for some reason. What did work was to call session.commit(). After calling that, the object had the updated values from the database.
TL;DR Rather than working on Session synchronization, see if your task can be reasonably easily coded with SQLAlchemy Core syntax, directly on the Engine, without the use of (multiple) Sessions
For someone coming from SQL and JDBC experience, one critical thing to learn about SQLAlchemy, which, unfortunately, I didn't clearly come across reading through the multiple documents for months is that SQLAlchemy consists of two fundamentally different parts: the Core and the ORM. As the ORM documentation is listed first on the website and most examples use the ORM-like syntax, one gets thrown into working with it and sets them-self up for errors and confusion - if thinking about ORM in terms of SQL/JDBC. ORM uses its own abstraction layer that takes a complete control over how and when actual SQL statements are executed. The rule of thumb is that a Session is cheap to create and kill, and it should never be re-used for anything in the program's flow and logic that may cause re-querying, synchronization or multi-threading. On the other hand, the Core is the direct no-thrills SQL, very much like a JDBC Driver. There is one place in the docs I found that "suggests" using Core over ORM:
it is encouraged that simple SQL operations take place here, directly on the Connection, such as incrementing counters or inserting extra rows within log
tables. When dealing with the Connection, it is expected that Core-level SQL
operations will be used; e.g. those described in SQL Expression Language Tutorial.
Although, it appears that using a Connection causes the same side effect as using a Session: re-query of a specific record returns the same result as the first query, even if the record's content in the DB was changed. So, apparently Connections are as "unreliable" as Sessions to read DB content in "real time", but a direct Engine execution seems to be working fine as it picks a Connection object from the pool (assuming that the retrieved Connection would never be in the same "reuse" state relatively to the query as the specific open Connection). The Result object should be closed explicitly, as per SA docs
What is your isolation level is set to?
SHOW GLOBAL VARIABLES LIKE 'transaction_isolation';
By default mysql innodb transaction_isolation is set to REPEATABLE-READ.
+-----------------------+-----------------+
| Variable_name | Value |
+-----------------------+-----------------+
| transaction_isolation | REPEATABLE-READ |
+-----------------------+-----------------+
Consider setting it to READ-COMMITTED.
You can set this for your sqlalchemy engine only via:
create_engine("mysql://<connection_string>", isolation_level="READ COMMITTED")
I think another option is:
engine = create_engine("mysql://<connection_string>")
engine.execution_options(isolation_level="READ COMMITTED")
Or set it globally in the DB via:
SET GLOBAL TRANSACTION ISOLATION LEVEL READ COMMITTED;
https://dev.mysql.com/doc/refman/8.0/en/innodb-transaction-isolation-levels.html
and
https://docs.sqlalchemy.org/en/14/orm/session_transaction.html#setting-transaction-isolation-levels-dbapi-autocommit
If u had added the incorrect model to the session, u can do:
db.session.rollback()