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Executing stored procedures in SQL Server using Python client

I learned from a helpful post on StackOverflow about how to call stored procedures on SQL Server in python (pyodbc). After modifying my code to what is below, I am able to connect and run execute() from the db_engine that I created.
import pyodbc
import sqlalchemy as sal
from sqlalchemy import create_engine
import pandas as pd
import urllib
params = urllib.parse.quote_plus(
'DRIVER={ODBC Driver 17 for SQL Server};'
f'SERVER=myserver.com;'
f'DATABASE=mydb;'
f'UID=foo;'
f'PWD=bar')
cobnnection_string = f'mssql+pyodbc:///?odbc_connect={params}'
db_engine = create_engine(connection_string)
db_engine.execute("EXEC [dbo].[appDoThis] 'MYDB';")
<sqlalchemy.engine.result.ResultProxy at 0x1121f55e0>
db_engine.execute("EXEC [dbo].[appDoThat];")
<sqlalchemy.engine.result.ResultProxy at 0x1121f5610>
However, even though no errors are returned after running the above code in Python, when I check the database, I confirm that nothing has been executed (what is more telling is that the above commands take one or two seconds to complete whereas running these stored procedures successfully on the database admin tool takes about 5 minutes).
How should I understand what is not working correctly in the above setup in order to properly debug? I literally run the exact same code through my database admin tool with no issues - the stored procedures execute as expected. What could be preventing this from happening via Python? Does the executed SQL need to be committed? Is there a way to debug using the ResultProxy that is returned? Any advice here would be appreciated.

Calling .execute() directly on an Engine object is an outdated usage pattern and will emit deprecation warnings starting with SQLAlchemy version 1.4. These days the preferred approach is to use a context manager (with block) that uses engine.begin():
import sqlalchemy as sa
# …
with engine.begin() as conn: # transaction starts here
conn.execute(sa.text("EXEC [dbo].[appDoThis] 'MYDB';"))
# On exiting the `with` block the transaction will automatically be committed
# if no errors have occurred. If an error has occurred the transaction will
# automatically be rolled back.
Notes:
When passing an SQL command string it should be wrapped in a SQLAlchemy text() object.
SQL Server stored procedures (and anonymous code blocks) should begin with SET NOCOUNT ON; in the overwhelming majority of cases. Failure to do so can result in legitimate results or errors getting "stuck behind" any row counts that may have been emitted by DML statements like INSERT, UPDATE, or DELETE.

How to update a Postgres schema with flask-sqlalchemy?

I'm running a simple Flask app with Heroku, and I can run the following command to create all the tables:
db.create_all()
However, I ship new stuff frequently and I often need to add new columns to existing tables. Is there an easy way to do this?
If I need to manually create a new column with Postgres, how would I access the repl for Heroku's Postgres database?

You should be using migrations.
This is a great plugin for that: https://flask-migrate.readthedocs.io/en/latest/
and this is a good explanation about how to get going with that: https://realpython.com/flask-by-example-part-2-postgres-sqlalchemy-and-alembic/

How do you create a table with Sqlalchemy within a transaction in Postgres?

I'm using Sqlalchemy in a multitenant Flask application and need to create tables on the fly when a new tenant is added. I've been using Table.create to create individual tables within a new Postgres schema (along with search_path modifications) and this works quite well.
The limitation I've found is that the Table.create method blocks if there is anything pending in the current transaction. I have to commit the transaction right before the .create call or it will block. It doesn't appear to be blocked in Sqlalchemy because you can't Ctrl-C it. You have to kill the process. So, I'm assuming it's something further down in Postgres.
I've read in other answers that CREATE TABLE is transactional and can be rolled back, so I'm presuming this should be working. I've tried starting a new transaction with the current engine and using that for the table create (vs. the current Flask one) but that hasn't helped either.
Does anybody know how to get this to work without an early commit (and risking partial dangling data)?
This is Python 2.7, Postgres 9.1 and Sqlalchemy 0.8.0b2.

(Copy from comment)
Assuming sess is the session, you can do sess.execute(CreateTable(tenantX_tableY)) instead.
EDIT: CreateTable is only one of the things being done when calling table.create(). Use table.create(sess.connection()) instead.

How to disable SQLAlchemy caching?

I have a caching problem when I use sqlalchemy.
I use sqlalchemy to insert data into a MySQL database. Then, I have another application process this data, and update it directly.
But sqlalchemy always returns the old data rather than the updated data. I think sqlalchemy cached my request ... so ... how should I disable it?

The usual cause for people thinking there's a "cache" at play, besides the usual SQLAlchemy identity map which is local to a transaction, is that they are observing the effects of transaction isolation. SQLAlchemy's session works by default in a transactional mode, meaning it waits until session.commit() is called in order to persist data to the database. During this time, other transactions in progress elsewhere will not see this data.
However, due to the isolated nature of transactions, there's an extra twist. Those other transactions in progress will not only not see your transaction's data until it is committed, they also can't see it in some cases until they are committed or rolled back also (which is the same effect your close() is having here). A transaction with an average degree of isolation will hold onto the state that it has loaded thus far, and keep giving you that same state local to the transaction even though the real data has changed - this is called repeatable reads in transaction isolation parlance.
http://en.wikipedia.org/wiki/Isolation_%28database_systems%29

This issue has been really frustrating for me, but I have finally figured it out.
I have a Flask/SQLAlchemy Application running alongside an older PHP site. The PHP site would write to the database and SQLAlchemy would not be aware of any changes.
I tried the sessionmaker setting autoflush=True unsuccessfully
I tried db_session.flush(), db_session.expire_all(), and db_session.commit() before querying and NONE worked. Still showed stale data.
Finally I came across this section of the SQLAlchemy docs: http://docs.sqlalchemy.org/en/latest/dialects/postgresql.html#transaction-isolation-level
Setting the isolation_level worked great. Now my Flask app is "talking" to the PHP app. Here's the code:
engine = create_engine(
"postgresql+pg8000://scott:tiger#localhost/test",
isolation_level="READ UNCOMMITTED"
)
When the SQLAlchemy engine is started with the "READ UNCOMMITED" isolation_level it will perform "dirty reads" which means it will read uncommited changes directly from the database.
Hope this helps
Here is a possible solution courtesy of AaronD in the comments
from flask.ext.sqlalchemy import SQLAlchemy
class UnlockedAlchemy(SQLAlchemy):
def apply_driver_hacks(self, app, info, options):
if "isolation_level" not in options:
options["isolation_level"] = "READ COMMITTED"
return super(UnlockedAlchemy, self).apply_driver_hacks(app, info, options)

Additionally to zzzeek excellent answer,
I had a similar issue. I solved the problem by using short living sessions.
with closing(new_session()) as sess:
# do your stuff
I used a fresh session per task, task group or request (in case of web app). That solved the "caching" problem for me.
This material was very useful for me:
When do I construct a Session, when do I commit it, and when do I close it

This was happening in my Flask application, and my solution was to expire all objects in the session after every request.
from flask.signals import request_finished
def expire_session(sender, response, **extra):
app.db.session.expire_all()
request_finished.connect(expire_session, flask_app)
Worked like a charm.

I have tried session.commit(), session.flush() none worked for me.
After going through sqlalchemy source code, I found the solution to disable caching.
Setting query_cache_size=0 in create_engine worked.
create_engine(connection_string, convert_unicode=True, echo=True, query_cache_size=0)

First, there is no cache for SQLAlchemy.
Based on your method to fetch data from DB, you should do some test after database is updated by others, see whether you can get new data.
(1) use connection:
connection = engine.connect()
result = connection.execute("select username from users")
for row in result:
print "username:", row['username']
connection.close()
(2) use Engine ...
(3) use MegaData...
please folowing the step in : http://docs.sqlalchemy.org/en/latest/core/connections.html
Another possible reason is your MySQL DB is not updated permanently. Restart MySQL service and have a check.

As i know SQLAlchemy does not store caches, so you need to looking at logging output.

Execute sql query with Elixir

I'm using Elixir in a project that connects to a postgres database. I want to run the following query on the database I'm connected to, but I'm not sure how to do it as I'm rather new to Elixir and SQLAlchemy. Anyone know how?
VACUUM FULL ANALYZE table
Update
The error is: "UnboundExecutionError: Could not locate a bind configured on SQL expression or this Session". And the same result with session.close() issued before. I did try doing metadata.bind.execute() and that worked for a simple select. But for the VACUUM it said - "InternalError: (InternalError) VACUUM cannot run inside a transaction block", so now I'm trying to figure out how to turn that off.
Update 2
I can get the query to execute, but I'm still getting the same error - even when I create a new session and close the previous one.
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
# ... insert stuff
old_session.commit()
old_session.close()
new_sess = sessionmaker(autocommit=True)
new_sess.configure(bind=create_engine('postgres://user:pw#host/db', echo=True))
sess = new_sess()
sess.execute('VACUUM FULL ANALYZE table')
sess.close()
and the output I get is
2009-12-10 10:00:16,769 INFO sqlalchemy.engine.base.Engine.0x...05ac VACUUM FULL ANALYZE table
2009-12-10 10:00:16,770 INFO sqlalchemy.engine.base.Engine.0x...05ac {}
2009-12-10 10:00:16,770 INFO sqlalchemy.engine.base.Engine.0x...05ac ROLLBACK
finishing failed run, (InternalError) VACUUM cannot run inside a transaction block
'VACUUM FULL ANALYZE table' {}
Update 3
Thanks to everyone who responded. I wasn't able to find the solution I wanted, but I think I'm just going to go with the one described here PostgreSQL - how to run VACUUM from code outside transaction block?. It's not ideal, but it works.

Dammit. I knew the answer was going to be right under my nose. Assuming you setup your connection like I did.
metadata.bind = 'postgres://user:pw#host/db'
The solution to this was as simple as
conn = metadata.bind.engine.connect()
old_lvl = conn.connection.isolation_level
conn.connection.set_isolation_level(0)
conn.execute('vacuum analyze table')
conn.connection.set_isolation_level(old_lvl)
This is similar to what was suggested here PostgreSQL - how to run VACUUM from code outside transaction block?
because underneath it all, sqlalchemy uses psycopg to make the connection to postgres. Connection.connection is a proxy to the psycopg connection. Once I realized this, this problem came back to mind and I decided to take another whack at it.
Hopefully this helps someone.

You need to bind the session to an engine
session.bind = metadata.bind
session.execute('YOUR SQL STATEMENT')

UnboundExecutionError says that your session is not bound to an engine and there is no way to discover engine from query passed to execute(). You can either use engine.execute() directly or pass additional mapper parameter (either mapper or mapped model corresponding to table used in query) to session.execute() to help SQLAlchemy discover proper engine.
The InternalError says that you are trying to execute this statement inside explicitly (with BEGIN statement) started transaction. Have you issued some statements before it without calling commit()? If so, just call commit() or rollback() method to close transaction before doing VACUUM. Also note, that there are several parameter to sessionmaker() that tell SQLAlchemy when transaction should be started.

If you have access to SQLAlchemy session, you can execute arbitrary SQL statements via its execute method:
session.execute("VACUUM FULL ANALYZE table")

(Depending on the Postgres version) you most likely do not want to run "VACUUM FULL".